Abstract:
The productivity of grain legumes (Phaseolus vulgaris, Arachis hypogaea L.,Glycine max L., and Llablab purpureus L.) is low in smallholder systems in sub-Saharan Africa (SSA). Low soil fertility, high pest and disease pressure, and high heterogeneity of biophysical and socioeconomic contexts, makes it hard to find a suitable legume specie to grow in the smallholder systems of western Kenya. These constraints have resulted in low productivity, leading to food and nutritional insecurity, and low household income. It is therefore necessary to apply geospatial technologies to visualize the distribution of the production constraints and opportunities, as well as show how they interact to influence legume productivity. This study assessed selected biophysical factors influencing productivity of bean, groundnut, soybean and lablab, the most important food legumes in the region, and established their spatial and temporal distribution in the smallholder systems of Nandi County, western Kenya. Experiments were set up in 66 farms during the short rains 2016, and the long rains 2017 growing seasons at Kapkerer, Kiptaruswo, and Koibem sites in Nandi County, western Kenya. Composite soil samples were taken from each of the farms for the determination of pH, organic carbon, texture, and micro-nutrients. Daily rainfall, temperature, incidences and severity of pests and diseases, and legume grain yield were scored at each farm. Results showed large spatial and temporal variations in the distribution of pests and diseases, creating possible hotspots that significantly decreased legume productivity. Rainfall was negatively correlated with pests and diseases, especially BF (r=-0.35**), BCMV (r=-0.31**) and RV (r=-0.16), while a positive correlation was observed between rainfall and RR (r=0.12*). The impact of pests and diseases on legume productivity exhibited a temporal variation. Of the soil factors assessed, pH, Fe, Mn, Mg, and Ca had the largest effect on legume productivity. The results of this study indicate that knowledge of the spatial and temporal distribution of legume production constraints, and their impact on legume productivity is critical for informed technology testing and dissemination of production options that match biophysical contexts to improve legume productivity in the heterogeneous smallholder systems. In general, this study can inform national policy formulation and the necessary reform of agricultural technology dissemination services to improve smallholder productivity.
