Simulation models are tools utilized for optimization of managements practices as well as to estimate crop yield. The present study aimed to test the efficiency of the CERES-maize model to simulate corn yield related to the field spatial variability. The experimental area was located at Federal University of Lavras, where experimental plots were established according to the variable areas of base saturation (V%), a parameter regarded as decisive in the observed yields. Data of maximum and minimum temperatures, rainfall and solar radiation; soil data in the 0-27, 27-45, 45-68, 68-80 and 80-100 cm layers to each experimental plot, management information of corn crop and genetic parameters of the corn hybrid, were collected. The simulation presented better results when the genetic parameters, particular to each plot, were utilized. Observed yield simulations were higher in areas of elevated base saturation. Due to that, it follows that the simulation was capable to estimate a trend of the distinguished yields as related to the spatial variables of the soil attribute (V%), obtaining more precise simulations with the use of the values of the genetic parameters estimated in each plot.
Models; DSSAT; Zea mays L
