Davies D. Onduru

Many sources indicate that smallholder tree-crop commodity farmers are poor, but there is a paucity of data on how many of them are poor and the depth of poverty. The living income concept establishes the net annual income required for a household in a place to afford a decent standard of living. Based on datasets on smallholder cocoa and tea farmers in Ghana, Ivory Coast and Kenya and literature, we conclude that a large proportion of such farmers do not have the potential to earn a living income based on their current situation. Because these farmers typically cultivate small farm sizes and have low capacity to invest and to diversify, there are no silver bullets to move them out of poverty. We present an assessment approach that results in insights into which interventions can be effective in improving the livelihoods of different types of farmers. While it is morally imperative that all households living in poverty are supported to earn a living income, the assessment approach and literature indicate that focussing on short- to medium-term interventions for households with a low likelihood of generating a living income could be: improving food security and health, finding off-farm and alternative employment, and social assistance programmes. In the long term, land governance policies could address land fragmentation and secure rights. Achieving living incomes based on smallholder commodity production requires more discussion and engagement with farmers and their household members and within their communities, coordination between all involved stakeholders, sharing lessons learnt and data.

Sustainability is socially constructed, and striving for a sustainable agricultural system requires addressing ecological, social and economic dimensions simultaneously. The objective of this study was to assess the sustainability of dryland farming systems of Eastern Kenya based on farmers' perceptions of their farming environment and the implications for rural livelihoods. Farmers' perceptions were elicited through semi-structured interviews in which questionnaires were administered, on single visits, to 30 selected farm households. The study showed that soil fertility and yields of staple food crops (maize) have declined in the past decade and that current farming systems are not able to produce adequate food and income to the dependent households. Thus, the farming system is showing symptoms of unsustainability. Improving farming system sustainability in this dryland area will ultimately require integration of technical and policy options that take cognisance of farmers' abilities, opportunities and socio-economic circumstances.

A study was carried out to investigate soil quality of dryland farming systems of Mbeere District, Eastern Kenya and its implications on agricultural sustainability. Soil sampling was done in years 2002 and 2004 from 30 study farms and same sampling sites and from paired adjacent land-use systems (bush fallow and cultivated fields). Physical, chemical and biological laboratory analyses were carried out. Factor analysis showed that the main soil quality indicators for evaluating sustainability of the dryland farming systems of the district were texture; organic matter, exchangeable bases (Ca, Mg, K, and Na); extractable nutrients (P and Zn); and acidity (pH). Cultivated soils were characterised by low pH, nutrient deficiencies (N, P, Cu, and Zn) and low organic matter and a decline in organic C, total N, exchangeable K and extractable P across time. They were also lower in exchangeable bases and microbial biomass C than adjacent bush fallow soils. We conclude that the soils are degraded and farming systems are partially unsustainable and may increasingly be so in the near future if declining soil quality is not addressed.

The farmer field school (FFS) approach was used in semi-arid eastern Kenya in the period 2002–2003 to explore technology options for addressing declining soil fertility and to institute learning processes on integrated nutrient management (INM). Participatory diagnosis of soil fertility constraints and experimental design workshops led to the formulation of the INM-FFS learning curriculum and choice of INM technologies for testing in the central learning plot. INM technologies jointly chosen for testing included farmyard manure (FYM = T₁), diammonium phosphate (DAP = T₂), combined application of FYM and DAP (T₃); and T₃ combined with Tithonia diversifolia applied as green manure (T₄). Maize was used as a test crop. The treatments were replicated twice using a pair-wise design and data collected, bi-weekly, using the agroecosystem analysis (AESA) framework to aid learning and data analysis with farmers. Farmers' evaluation of the trials was conducted at the end of the study period using matrix scoring and ranking. Treatments with combined application of organic and inorganic materials had better agro-economic performance than sole application of either FYM or DAP (T₄ > T₃ > T₂ and T₁) and they had a high value cost ratio (VCR > 2). The technologies of T₁ to T₃ did not have a positive impact on either nitrogen or phosphorus balances. However, T₄ resulted in a positive partial N balance. Farmers' evaluation corresponded well with the majority of the quantitative agro-economic analysis. The study showed that there is a potential to use FFS for INM technology development and testing by stimulating interactions, farmer learning and closer working relationships between farmers, research scientists, extension and the institutions that they represent.

A study was conducted in the semi‐arid Mbeere district, Eastern Kenya, to determine spatial and temporal variability of crop yields and climatic factors and their impacts on sustainability of semi‐arid agriculture. Spatial aspects were assessed by conducting a survey of on‐farm crop yields and using a computer model (QUEFTS) to predict maize yields from soil chemical indices. Temporal aspects were studied using time‐series data (rainfall, temperature and crop yields). The study did not find a significant correlation between farmers' actual yields and QUEFTS predictions, and soil nutrients were thus not the only factors influencing maize yields in the study area. Other yield‐reducing factors (climate and management) not accounted for in the QUEFTS model played a role. Grain yields of staple food crops were highly variable, fluctuating in time and space, and suboptimal. Particular aspects of rainfall (e.g. the short rains, for cowpeas and beans) were more important than mean annual rainfall in determining crop yields, and factors other than rainfall and soil fertility apparently played a role. The observed low grain yields, large yield gaps and high rainfall variability challenge the sustainability of these farming systems. Copyright © 2008 John Wiley & Sons, Ltd