WheatPot: A simple model for spring wheat yield potential using monthly weather data

A simple, deterministic crop growth model was developed to predict the site-specific yield potential of wheat. The model simulates critical developmental stages and dry matter production as a function of temperature and solar radiation. Crop-related outputs of the model include development stages, dry matter production, and grain yield. The model requires inputs of site mean monthly weather data (minimum and maximum temperatures in °C), the photosynthetically active radiation (PAR in MJ m−2), and plant characteristics including sowing date, growing degree days (GDD) for the vegetative and reproductive phases, radiation-use efficiency (RUE in g MJ−1), and harvest index (HI). The model was verified using experiments that were carried out in several locations in Khuzestan province in Iran during the 2003–2004 and 2004–2005 growing seasons. Comparisons of the simulated and measured outputs under non-limiting conditions indicated satisfactory performance for predicting anthesis and maturity dates, and fair prediction of dry matter production and grain yield. The root-mean-square errors (RMSE) of yield were 3.5 d, 4 d, 0.65 t ha−1, and 1.69 t ha−1, respectively. The model also proved to be a useful tool for the rough estimation of wheat yield potential at the regional level where there is access only to monthly weather data.