Development of a simple empirical model for predicting maize yields in a semi-arid area

Abstract

A yield prediction model is necessary, together with long-term climate data, to calculate the long-term yields needed for making a quantitative productivity evaluation of a crop ecotope in the form of a cumulative probability function (CPF). In this study the development of such a model for maize grown on two semi-arid ecotopes, i.e. the Glen/Hutton-Ventersdorp and Glen/Oakleaf-Dipene ecotopes, located in the Free State Province, is described. A fairly reliable empirical relationship was obtained between the total above ground biomass and a water stress index using the results of 22 field experiments on these ecotopes. The model consists of the regression equation which describes this relationship viz. Yb = 15238 ISI + 1067 (R = 0.69) where Yb is the predicted total above ground biomass in kg ha⁻¹ and ISI is an integrated stress index for a particular growing season. The stress index is based on the ET/Eo relationship during the growing season.