Logistic model application for prediction of maize yield under water and nitrogen management

Simulation of crop yield allows better planning and efficient management under different environmental inputs such as water and nitrogen application. However, most of the models are complicated and difficult to understand. Furthermore, input data are not readily available. The objectives of this investigation were to use logistic equation to quantify the influence of seasonal water and nitrogen application on maize biomass accumulation and grain yield and to develop empirical models for prediction of maize biomass and grain yield. Logistic equations were fitted to dray matter (DM) yield at different times in the growing season at different irrigation water and nitrogen levels. The parameters of the logistic equations were then fitted to irrigation water and nitrogen as empirical functions. Further, the harvest index (HI) was related to the applied water and nitrogen as another empirical model. The empirical logistic models were used to estimate the DM and grain yield based on data from another experiment in the same area. Results indicated that the empirical models predicted the DM yield during the growing season with an acceptable accuracy, but dry matter (DM) prediction at harvest was very good. The grain yield also was predicted with a very good accuracy. It is concluded that logistic equation along with the presented empirical models for prediction of constants in logistic equation and HI are appropriate for accurate prediction of DM and grain yield of maize at the study region.