Search

Increased concentration of atmospheric nitrous oxide (N2O), a potent greenhouse gas (GHG), is of great concern due to its impact on ozone layer depletion leading to climate change. Ozone layer depletion allows penetration of ultraviolet radiations, which are hazardous to human health. Climate change culminates in reduced food productivity. Limited empirical studies have been conducted in Sub-Saharan Africa (SSA) to quantify and understand the dynamics of soil N2O fluxes from smallholder cropping systems. The available literature on soil N2O fluxes in SSA is limited; hence, there is a pressing need to consolidate it to ease mitigation targeting and policy formulation initiatives. We reviewed the state of N2O emissions from selected cropping systems, drivers that significantly influence N2O emissions, and probable soil N2O emissions mitigation options from 30 studies in SSA cropping systems have been elucidated here. The review outcome indicates that coffee, tea, maize, and vegetables emit N2O ranging from 1 to 1.9, 0.4 to 3.9, 0.1 to 4.26, and 48 to 113.4 kg N2O-N ha-1 yr−1, respectively. The yield-scaled and N2O emissions factors ranged between 0.08 and 67 g N2O-N kg−1 and 0.01 and 4.1%, respectively, across cropping systems. Soil characteristics, farm management practices, and climatic and environmental conditions were significant drivers influencing N2O emissions across SSA cropping systems. We found that site-specific soil N2O emissions mitigation measures are required due to high variations in N2O drivers across SSA. We conclude that appropriate fertilizer and organic input management combined with improved soil management practices are potential approaches in N2O emissions mitigation in SSA. We recommend that (i) while formulating soil N2O emissions mitigation approaches, in SSA, policymakers should consider site-specific targeting approaches, and (ii) more empirical studies need to be conducted in diverse agroecological zones of SSA to qualify various mitigation options on N2O emissions, yield-scaled N2O emissions, and N2O emission factors which are essential in improving national and regional GHG inventories.

Process-based biogeochemical models can be used to simulate soil nitrous oxide (N2O) fluxes and maize yields and draw insights on yields improvement and climate change mitigation options. We compared both observed and DeNitrification-DeComposition (DNDC) simulated soil N2O fluxes and maize yields. We used DNDC model to simulate soil N2O fluxes and maize yields under four soil fertility treatments (inorganic fertiliser, animal manure, animal manure + inorganic fertiliser and control,) replicated thrice for 1 year in Central Highlands of Kenya. We sampled soil N2O fluxes using static chambers installed in each plot. We analysed soil N2O using gas chromatography and calculated cumulative fluxes using trapezoidal rule linear interpolation between sampling dates. DNDC showed poor results in simulating daily N2O fluxes (157.16% ≤ normalised root mean square error (nRMSE) ≤ 324.01% and 0.90 ≤ modelling efficiency (NSE) ≤ 0.96), good to excellent performance in simulating cumulative annual soil N2O fluxes (6.16 ≤ nRMSE ≤12.86 and 0.63 ≤ NSE ≤ 0.86) and good to excellent performance in simulating maize yields (1.15% ≤ nRMSE ≤13.86% and 0.51 ≤ NSE ≤ 0.88) across all soil fertility treatments. The DNDC model had good to excellent performance in simulating cumulative soil N2O fluxes and crop yields across treatments. Though the model captured yield-scaled N2O fluxes and N2O emission factors across treatments, they were underestimated under manure treatment. There is a need to continue calibrating the DNDC model for improved capture of daily N2O fluxes and uptakes on Kenyan soils.

Farmer adoption of soil technologies has been commonly explored in the literature using binary models, which significantly simplifies the multi-dimensional nature of technology adoption by farmers. Therefore, it is necessary to fill this gap to improve soil technology adoption models to enhance small-scale farmers' soil fertility management practices. We investigated patterns of multiple soil technology adoption using multivariate analysis and regression modeling in Central Kenya. We used a cross-sectional survey design to sample 300 small-scale farmers in Tharaka-Nithi County and employed a multi-stage sampling design. We found that soil nutrient applications and soil fertility management patterns were linked to crop enterprises, driven by socioeconomic farm characteristics. Our findings showed that farmers applied higher N inputs and soil fertility management technologies on crops with high economic and staple use-values. Farmers in high potential agro-ecozones and those with higher incomes and TLU (Tropical Livestock Units) intensity applied higher fertilizer N intensities than farmers with lower incomes and TLU intensity. Farmers in high potential agro-ecozones applied higher fertilizer and manure rates than their counterparts in low potential agro-ecozones of Tharaka-Nithi County. Farm size was inversely related to nitrogen fertilizer application intensity, while farmers had a lower propensity to restore fields undergoing degradation. We obtained five significant sets of soil fertility management technologies that farmers practiced due to the complementary nature of their benefits. We found that farmer perceptions of soil fertility, income distribution, site, education qualifications, credit access, labor availability, and access to extension services influenced their technology adoption patterns. We recommend that farmer sensitization about the fertility of their soils is needed to enhance soil fertility management strategies in small-scale farming systems.

Few studies have quantified soil greenhouse gas (GHG) −CH4, CO2 N2O – annual fluxes directly from smallholder maize cropping systems under different soil fertility management technologies in Sub Saharan Africa. We quantified soil GHG annual fluxes from smallholder maize cropping systems under four different soil fertility management technologies in the Central Highlands of Kenya. We regularly sampled GHG from 2nd March 2018 to 1st March 2019 (1 year) in three maize farms using a static chamber technique. The fertility management technologies were: inorganic fertilizer, animal manure, animal manure combined with inorganic fertilizer, and a Control (No external input). The experimental design was a randomized complete block design replicated thrice. Cumulative annual soil fluxes ranged from -2.40 kg CH4-C ha−1 yr−1 from the control treatment to −1.62 kg CH4-C ha−1 yr−1 from the manure combined with inorganic fertilizer treatment, 4810 kg CO2-C ha−1 yr−1 from the control treatment to 6576 kg CO2-C ha−1 yr−1 from the inorganic fertilizer treatment, and 0.21 kg N2O-N ha−1 yr−1 from the control treatment to 0.38 kg N2O-N ha−1 yr−1 from the inorganic fertilizer treatment for CH4, CO2, and N2O fluxes, respectively. Fertilizer treatment produced the highest CO2 emissions (p

Most sub-Saharan Africa smallholder farming systems are highly heterogeneous. Direct quantification of greenhouse gas emissions from these farming systems is hampered by diversity at farm-level. Each farm contributes differently to greenhouse gas (GHG) emissions and consequently GHG inventories. Typologies can be used as a mechanism of addressing farming systems’ heterogeneity by grouping them into specific farm types. With the GHG quantification simplification initiatives in mind, we developed smallholder farm typologies based on soil fertility inputs. We assessed nitrogen application rate, soil fertility management technologies and the socio-economic factors diversity among the farm typologies in the central highlands of Kenya. We used data from a cross-sectional household survey with a sample size of 300 smallholder farmers. We characterized the farm types using principal component analysis (PCA). To develop farm typologies, we subjected the PCA-derived typologies related factors to cluster analysis (CA). The results showed six farm types: Type 1, comprising cash crop and hybrid cattle farmers; Type 2, comprising food crop farmers; Type 3, composed of coffee-maize farmers; Type 4, comprising millet-livestock farmers; Type 5, comprising highly diversified farmers, and Type 6, comprising tobacco farmers. Land size owned, total tropical livestock unit, the proportion of land and nitrogen applied to different cropping systems were significant in the construction of farm typologies. Univariate analysis showed the household head's level of education, hired labour, group membership, access to extension services, and proportion of income from cropping activities as critical factors influencing farm typologies in the study area. This study demonstrates the importance of smallholder farm typologies in identifying greenhouse gas emissions hotspots, designing quantification experiment and policy framing. We concluded that policies and intervention measures targeting climate-smart agriculture at smallholder farms should consider not only farm-level soil fertility management technologies but also socio-economic characteristics that influence their adoption.

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, and all those with 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.

Conservation agriculture (CA) offers an opportunity to reverse prevailing land degradation and consequent loss of productivity often occasioned by intensive soil tillage in cropping systems in most parts of sub-Saharan Africa (SSA). A long term experiment was established in Nyabeda Western Kenya in 2003 to evaluate the effect of tillage and crop residue application on maize and soybean yields, and on soil properties. The experiment was set up as a split-split-split plot design with four replicates and involved a factorial combination of tillage system (reduced and conventional tillage), cropping system (continuous cereal, soybean-maize rotation and intercropping), crop residue – maize stover – management (plus and minus crop residue) and nitrogen (N) application. Results showed that tillage influenced performance of maize although significant tillage effects were observed in only 5 out of the 15 seasons analyzed. Overall average maize grain yields were 2.9 ton ha−1 in reduced tillage and 3.6 ton ha−1 in conventional tillage systems. Application of crop residue increased seasonal maize grain yield in reduced tillage (340 kg ha−1) and in conventional tillage (240 kg ha−1), but the only significant crop residue (CR) effect was observed in season 10. Differences in maize yields between the two systems were attributed to phosphorus availability as it was demonstrated that application of crop residue in the reduced tillage resulted in better availability of P than without crop residue application.

The prevailing low food production in sub-Saharan Africa is an issue of great concern especially since Africa south of the Sahara is the only remaining region of the world where per capita food production has remained stagnant. This chapter reviews long-term experiments in Africa in the context of shifting paradigms related to tropical soil fertility management from first external input paradigm right through to the current Integrated Soil Fertility Management (ISFM) approach, which is a culmination of the participatory methods developed along the paradigm shift. Long term experiments (LTE) are an important source of evidence for soil fertility decline and provide crucial datasets for the development of sustainable management practices for tropical land-use systems and the amelioration of global climatic and environmental change impacts. A survey was undertaken to identify some ongoing long-term trials distributed across east, south and western Africa and in different agro-ecological zones. A long-term Experiment was defined as that extending over a period of over 5 years and more. Results from these trials are discussed in detail. Inference has been drawn from these findings and includes the following key findings: a) All long term trials showed yield decline, often with a relatively rapid fall to a low level equilibrium; b) At all sites, there were positive yield responses to one or more nutrients added as mineral fertilizers, which were consistent for the duration of the experiments highlighting the effectiveness of mine­ral fertilizers in increasing yield in arable farming systems in Africa; c) Soil organic matter (SOM) also declines significantly when land is cultivated; d) Prolonged treatments using only inputs of organic matter also showed yield declines, although the positive impact were sustained longer than for inorganic fertilizers alone in most cases; e) Rotational treatments, including sequences with legume crops and fallow periods had lower yield declines than monocultures; f) The best results invariably were those treatments that combined inorganic and organic inputs.

Preface.- Chapter 1: Agro-ecological distribution of legumes in farming systems and identification of biophysical niches for legumes growth, Nandwa SM (The late), Obanyi SN and Mafongoya PL.- Chapter 2: Socio- economic contribution of Legumes to Livelihoods in Sub-Saharan Africa Odendo M, Bationo A and Kimani S.- Chapter 3: Inter And Intra-Specific Variation Of Legumes And Mechanisms To Access And Adapt To Less Available Soil Phosphorus And Rock Phosphate, Nandwa SM (The late), Bationo A, Obanyi SN, Rao IM, Sanginga N and Vanlauwe B.- Chapter 4: Legume based cropping systems and soil biodiversity dynamics Karanja NK, Kimenju JM, Esilaba AO, Jefwa J and Ayuke F.- Chapter 5: Strategies to adapt, disseminate and scale out legume based technologies Mugendi DN, Waswa BS, Mucheru MW and Kimetu JM.- Chapter 6: Comparative Analysis of the Current and Potential Role of Legumes in Integrated Soil Fertility Management in West and Central Africa Bationo A, Kimetu J, Vanlauwe B, Bagayoko M, Koala S and Mokwunye AU.- Chapter 7: Comparative Analysis of the Current and Potential Role of Legumes in Integrated Soil Fertility Management in East Africa Mugendi DN, Waswa BS, Mucheru M, Kimetu JM and Palm C.- Chapter 8: Comparative Analysis of the Current and Potential Role of Legumes in Integrated Soil Fertility Management in Southern Africa Mapfumo P.- Chapter 9: Options for improving plant nutrition to increase common bean productivity in Africa Jansa J, Bationo A, Frossard E and Rao IM.- Conclusion and the way forward