A Corn Yield Model for Operational Planning and Management

ABSTRACT A simple model is proposed for predicting corn yields as a function of hybrid, planting timeliness, growing season temperatures, moisture stress and frost occur-rence. The model is used in conjunction with a daily soil moisture balance model. Required meterologic data are daily temperatures, precipitation, and pan evaporation rates. Additional yield data such as hybrid factor and timeliness penalty are obtained from state field trial in-formation. Moisture stress parameters for each of three stress periods are estimated by model calibration. The model was tested in a two-stage calibration and valida-tion application in New York. Comparison of model predictions with measured crop yields showed errors of 3 to 8 percent in predicted yields.