Estimation of yield and dry matter of winter wheat using logistic model under different irrigation water regimes and nitrogen application rates

Abstract

Complex simulation models need considerable input data that may be unavailable. In this study, based on growing degree days, a simple and empirical logistic model was used to predict top dry matter (DM) and grain yield (GY) of winter wheat in a semiarid area. For calibration and validation of the model, winter wheat cv. Shiraz was cultivated for two growing seasons (2009–2010 and 2010–2011) under different levels of irrigation water and nitrogen application rates. The coefficients of the logistic model and the harvest index were related to the seasonal amount of applied water (I) plus rainfall (R) and applied nitrogen plus residual soil mineral nitrogen (N + Nr) with good accuracy in 2009–2010. The values of DM were estimated using the developed empirical logistic model during the growing season in 2010–2011. Results also indicated that there was a good agreement between the measured and predicted GY in 2010–2011 with fair accuracy. Therefore, it is concluded that the presented model is appropriate for prediction of DM and GY of winter wheat at the study region.