Crop performance and soil nutrient dynamics under different cropping systems and organic inputs in central Kenya.

Abstract

Most soils in Kenya have been degraded and depleted of essential nutrients rendering them unsuitable for crop production (Drinkwater et al., 1995). Prolonged application of inorganic fertilizers on the other hand has resulted in negative environmental impacts such as accumulation of heavy metals in soil, crop and water (Halberg et al., 2006). Intercropping systems are deliberately designed and manipulated to optimize the use of spatial, temporal, and physical resources both above and belowground, by maximizing positive interactions and minimizing negative ones among the components (Silwana and Lucas, 2002). Continuous mono-cropping minus application of fertilizers result in mining of plant nutrients and depletion soil organic matter (Lal, 2008). In the current agricultural production environment, conventional farming methods pose the greatest risks in terms of reduced crop yields (Keating, 2003). This coupled with the vagaries of weather that have made crop production unreliable, hence the need for alternative means of soil fertility management. Soil fertility depletion can be addressed through use of organic inputs and integration of legumes into cropping systems. This will ultimately lead to increased crop yields and marketability. In view of the ever changing weather patterns, discontent among farmers over long term field experiments and resources required for conducting the same there is need for decision support tools to aid farmers decision making in crop production. One such tool is APSIM model that has been tested and validated across a wide range of environments for simulation of nutrient dynamics and crop responses to different inputs and climate. It is thus hypothesized that, legume integration and application of organic inputs will improve soil fertility status and enhance crop productivity. This study, therefore, aims to determine and model crop performance and soil nutrient dynamics under different cropping systems and organic inputs using APSIM.