OFF-SEASON MAIZE YIELD FORECASTING FOR DIFFERENT SOWING DATES

Abstract

Brazil is the world's third-largest maize producer. Its yield is influenced by climate, soil conditions, management and their interactions. Identifying the most suitable sowing window and using yield forecasting systems allows for increased yields and better harvest management. Crop simulation models can be used to assess crop responses to various conditions. This study aimed to identify the most favorable planting date for off-season maize by using the DSSAT CSM-CERES-Maize model for Jataí, Goiás state. Using meteorological data from 1986 to 2015, eight productivity forecasting strategies were tested. The results of the model application at different sowing dates indicated that the dates in January tended to present a more favorable attainable yield (Ya), i.e., values closer to the potential yield (Yp) of the crop, whereas in February, Ya were affected by lower precipitation from April to June. The best date for maize sowing was January 25^th. The simulations indicated the possibility of predicting the off-season maize productivity in Jataí with high precision and accuracy up to 30 days prior to harvest (R² ≥ 0.81, d ≥ 0.90, and c ≥ 0.81).