Modelling Nutrient Dynamics and Maize Yields under Different Cropping Systems and Organic Amendments Using APSIM in Central Kenya
O. H. Ndukhu *
University of Nairobi, Kenya
G. R. Wahome
University of Nairobi, Kenya
*Author to whom correspondence should be addressed.
Abstract
A simulation study was carried out using APSIM model to assess the maize yield and soil nutrients to changes in temperatures and rainfall in Kabete and Kiserian areas of central Kenya. To obtain data for model calibration and validation, on-station (Kabete) and on-farm experiments (Kiserian) were set out during the short rain season of 2013. The experimental design was a randomized complete block (RCBD) with a split-plot arrangement where the main plots were three cropping systems; monocropping, intercropping and crop rotation and the split plots were farmyard manure (FYM) and Minjingu Rock Phosphate (MRP), and a control. The effect of the changes in rainfall and temperature on maize yields was considered, i.e. current temperature combinations in accordance to the International Panel on Climate Change projections. The model performed better for Kabete (ME=0.6) than Kiserian (ME=0.9). Simulations of crop rotations correlated most (R2=0.48) with observed results at Kabete and Kiserian. Simulations of the intercrops correlated favourable with coefficient of determination (R2) values of >0.4 showing a reasonable relationship between observed and simulated values. However, mono-crop simulation varied highly from observed yields (R2<0.3). The APSIM simulated matched well with the observed data in the trial; root means standard error (RMSE) 2.07 for Kabete and 2.49 for Kiserian. Maize-chickpea cropping systems with application of FYM and MRP gave better yields as they resulted in higher predicted yields compared to the monocrop. The impacts of climate change and variability, i.e. reduced rainfall and increased temperatures that led to lower maize yields. These rainfall and temperature regimes call for the development of appropriate adaptation techniques.
Keywords: Organic cropping systems, APSIM, correlation coefficient, CCV