The diversity of rural livelihoods and their influence on soil fertility in agricultural systems of East Africa - A typology of smallholder farms

Technological interventions to address the problem of poor productivity of smallholder agricultural systems must be designed to target socially diverse and spatially heterogeneous farms and farming systems. This paper proposes a categorisation of household diversity based on a functional typology of livelihood strategies, and analyses the influence of such diversity on current soil fertility status and spatial variability on a sample of 250 randomly selected farms from six districts of Kenya and Uganda. In spite of the agro-ecological and socio-economic diversity observed across the region (e.g. 4 months year-1 of food self-sufficiency in Vihiga, Kenya vs. 10 in Tororo, Uganda) consistent patterns of variability were also observed. For example, all the households with less than 3 months year-1 of food self-sufficiency had a land:labour ratio (LLR) 1 produced enough food to cover their diet for at least 5 months. Households with LLR <1 were also those who generated more than 50% of their total income outside the farm. Dependence on off/non-farm income was one of the main factors associated with household diversity. Based on indicators of resource endowment and income strategies and using principal component analysis, farmers’ rankings and cluster analysis the 250 households surveyed were grouped into five farm types: (1) Farms that rely mainly on permanent off-farm employment (from 10 to 28% of the farmers interviewed, according to site); (2) larger, wealthier farms growing cash crops (8–20%); (3) medium resource endowment, food self-sufficient farms (20–38%); (4) medium to low resource endowment relying partly on non-farm activities (18–30%); and (5) poor households with family members employed locally as agricultural labourers by wealthier farmers (13–25%). Due to differential soil management over long periods of time, and to ample diversity in resource endowments (land, livestock, labour) and access to cash, the five farm types exhibited different soil carbon and nutrient stocks (e.g. Type 2 farms had average C, N, P and K stocks that were 2–3 times larger than for Types 4 or 5). In general, soil spatial variability was larger in farms (and sites) with poorer soils and smaller in farms owning livestock. The five farm types identified may be seen as domains to target technological innovations and/or development efforts

The diversity of rural livelihoods and their influence on soil fertility in agricultural systems of East Africa - A typology of smallholder farms

Technological interventions to address the problem of poor productivity of smallholder agricultural systems must be designed to target socially diverse and spatially heterogeneous farms and farming systems. This paper proposes a categorisation of household diversity based on a functional typology of livelihood strategies, and analyses the influence of such diversity on current soil fertility status and spatial variability on a sample of 250 randomly selected farms from six districts of Kenya and Uganda. In spite of the agro-ecological and socio-economic diversity observed across the region (e.g. 4 months year-1 of food self-sufficiency in Vihiga, Kenya vs. 10 in Tororo, Uganda) consistent patterns of variability were also observed. For example, all the households with less than 3 months year-1 of food self-sufficiency had a land:labour ratio (LLR)   1 produced enough food to cover their diet for at least 5 months. Households with LLR Sub-Saharan Africa Farming systems Integrated soil fertility management Wealth ranking Recommendation domains Near-infrared spectroscopy Carbon Nutrients

The diversity of rural livelihoods and their influence on soil fertility in agricultural systems of East Africa – A typology of smallholder farms

Technological interventions to address the problem of poor productivity of smallholder agricultural systems must be designed to target socially diverse and spatially heterogeneous farms and farming systems. This paper proposes a categorisation of household diversity based on a functional typology of livelihood strategies, and analyses the influence of such diversity on current soil fertility status and spatial variability on a sample of 250 randomly selected farms from six districts of Kenya and Uganda. In spite of the agro-ecological and socio-economic diversity observed across the region (e.g. 4 months year-1 of food self-sufficiency in Vihiga, Kenya vs. 10 in Tororo, Uganda) consistent patterns of variability were also observed. For example, all the households with less than 3 months year-1 of food self-sufficiency had a land:labour ratio (LLR) 1 produced enough food to cover their diet for at least 5 months. Households with LLR < 1 were also those who generated more than 50% of their total income outside the farm. Dependence on off/non-farm income was one of the main factors associated with household diversity. Based on indicators of resource endowment and income strategies and using principal component analysis, farmers’ rankings and cluster analysis the 250 households surveyed were grouped into five farm types: (1) Farms that rely mainly on permanent off-farm employment (from 10 to 28% of the farmers interviewed, according to site); (2) larger, wealthier farms growing cash crops (8–20%); (3) medium resource endowment, food self-sufficient farms (20–38%); (4) medium to low resource endowment relying partly on non-farm activities (18–30%); and (5) poor households with family members employed locally as agricultural labourers by wealthier farmers (13–25%). Due to differential soil management over long periods of time, and to ample diversity in resource endowments (land, livestock, labour) and access to cash, the five farm types exhibited different soil carbon and nutrient stocks (e.g. Type 2 farms had average C, N, P and K stocks that were 2–3 times larger than for Types 4 or 5). In general, soil spatial variability was larger in farms (and sites) with poorer soils and smaller in farms owning livestock. The five farm types identified may be seen as domains to target technological innovations and/or development efforts

Wheat nutrient response functions for the east Africa highlands

Published online: 24 Feb 2018Wheat (Triticum æstivum L.) is an important East Africa highland crop but yields are low. Information is scarce for optimization of fertilizer use. Research was conducted to determine yield response functions for N, P and K, and to diagnose Mg–S–Zn–B deficiencies. The average grain yield increase in Rwanda due to N application was 1.5 Mg ha−1 with a mean economically optimal rate (EOR) of 68 kg ha−1 N. In Kenya and Tanzania, yield was increased by 29% with EOR N for two SY but unaffected by N rate for four other SY which on average had 50% of the soil organic C (SOC) as the N-responsive SY. Yield was increased, on average, with application of P and K by 0.47 and 0.23 Mg ha−1, respectively, at EOR in Rwanda but effects were inconsistent for other SY where soil test K was higher than in Rwanda. Application of Mg–S–Zn–B resulted in 0.46 Mg ha−1 more yield in Rwanda but did not affect yield at other SY where the average soil test values for these nutrients was 35% higher than in Rwanda. If the financially constrained farmer opts to apply the affordable fertilizer to twice as much land at 50% EOR compared with 100% EOR, the mean yield increase is reduced by 27% but production and PCR are increased by 43 and 72%, respectively. Nutrient effects were relatively consistent and positive in Rwanda, but less and less inconsistent elsewhere with generally less SOC, more K–Mg–S–Zn–B availability, and often lower yields

Diagnosis of crop secondary and micro-nutrient deficiencies in sub-Saharan Africa

Published online: 10 Jan 2019Crop production in sub-Saharan Africa has numerous biotic and abiotic constraints, including nutrient deficiencies. Information on crop response to macronutrients is relatively abundant compared with secondary and micronutrients (SMN). Data from 1339 trial replicates of 280 field trials conducted from 2013 to 2016 in 11 countries were analyzed for the diagnosis of SMN deficiencies. The diagnostic data included relative yield response (RYR) and soil and foliar test results. The RYR to application of a combination of Mg, S, Zn, and B (Mg–S–Zn–B) relative to a comparable N–P–K treatment was a > 5% increase for 35% of the legume blocks and 60% of the non-legume blocks. The frequencies of soil test Zn, Cu, and B being below their critical level were 28, 2 and 10% for eastern and southern Africa, respectively, and 55, 58 and 89% for western Africa, while low levels for other SMN were less frequent. The frequency of foliar results indicating low availability were 58% for Zn, 16% for S and less for other SMN. The r2 values for relationships between soil test, foliar test and RYR results were < 0.035 with little complementarity except for soil test Zn and B with cassava (Manihot esculenta L. Crantz) RYR in Ghana, and foliar Zn with cereal RYR in Uganda. Positive RYR is powerful diagnostic information and indicative of good profit potential for well-targeted and well-specified SMN application. Geo-referenced RYR, soil analysis and foliar analysis results for diagnosis of SMN deficiencies in 11 countries of sub-Saharan Africa were generally not complementary