Customize maize production technology in Central Thailand using crop model

AbstractThis study effectively utilized crop modeling to develop and validate post-rice maize production technologies for Thailand’s central region between 2022 and 2024. Calibrated models for the Pacific 789 and Dekalb 9898C varieties were used to simulate and identify optimal management practices for key maize-producing provinces. The results highlighted soil test–based fertilization, an ideal planting period from October to December, and plant population densities between 66,663 and 88,888 plants per hectare as the most effective approaches. The models showed strong predictive accuracy, and field trials confirmed their effectiveness, resulting in yield increases of 12.3%–18.72% and profit gains of 22.41%–42.34% compared to traditional practices. These findings demonstrate that crop modeling is a valuable tool for enhancing maize productivity and farmer profitability in post-rice maize production systems.