Evaluation of a New Sweet Corn Model.

Sweet corn is grown in 50 USA states for either fresh or processing markets. Its production for the fresh-market is highly seasonal and dependent on weather conditions, especially during spring. Accurate prediction of sweet corn fresh yield is of high interest for the industry and crop models can provide that information after judicious evaluation of their performance. A new model to simulate growth, development, yield, and yield quality for sweet corn has been developed as part of the Decision Support System for Agrotechnology Transfer (DSSAT). The objective of the study was to evaluate the sweet corn model for environmental conditions and management practices that are representative for Georgia and other southeastern states. The evaluation data sets consisted of planting date experiments that were conducted in 2005 and 2006 in Mitchell and Pike counties, GA. Weather data were obtained from automatic weather stations located near the experiments. The soil input data for the simulations were obtained from samples took at each experimental location. Growth, development, yield, and yield quality data from three sweet corn genotypes were obtained from measurements at each experimental location. The cultivar coefficients for the three sweet corn genotypes were determined using a systematic approach with experimental data from two 2005 planting dates. Subsequently, we evaluated these cultivar coefficients by applying them to simulate crop growth, development, yield, and yield quality for other experimental data including six planting dates. The model simulated accumulation of dry matter for the plant and its components as well as for fresh and dry matter yield in good agreement with observed data. However, the model showed low performance simulating the quality of ears. Further work will include a regional application of the model to determine the impact of climate variability on sweet corn growth and yield in the southeastern USA.