A multiple and ensembling approach for calibration and evaluation of genetic coefficients of CERES-Maize to simulate maize phenology and yield in Michigan

The phenological and growth parameters of CERES-Maize were estimated using data from field variety trials in 2017 2018 to simulate hybrid maize (Zea mays L.) grown Michigan. Multiple calibration methods used include GENCALC (Genotype Coefficient Calculator), GLUE (Generalized Likelihood Uncertainty Estimate), NMCGA (Noisy Monte Carlo Genetic Algorithm) ensembling approach. Three irrigated sites for while six rainfed evaluation. Better results obtained when multiple years than only a single year. Model evaluation also suggests that fixed soil root factor (SRGF) (irrigated condition) tended restrict dynamics under condition. This resulted substantial yield mismatch due poorly modeled yields, although phenology was better predicted. Adjusting SRGF condition model both years. Moreover, weighted averaging genetic coefficients predictions yields. • Ensembling improved predictions. Root needs adjustment water stressed conditions. Robust calibrated over seasons can help improve prediction yield.