Crop Models: Important Tools in Decision Support System to Manage Wheat Production under Vulnerable Environments

Decision support systems are key for yield improvement in modern agriculture. Crop models are decision support tools for crop management to increase crop yield and reduce production risks. Decision Support System for Agrotechnology Transfer (DSSAT) and an Agricultural System simulator (APSIM), intercomparisons were done to evaluate their performance for wheat simulation. Two-year field experimental data were used for model parameterization. The first year was used for calibration and the second-year data were used for model evaluation and intercomparison. Calibrated models were then evaluated with 155 farmers' fields surveyed for data in rice-wheat cropping systems. Both models simulated crop phenology, leaf area index (LAI), total dry matter and yield with high goodness of fit to the measured data during both years of evaluation. DSSAT better predicted yield compared to APSIM with a goodness of fit of 64% and 37% during evaluation of 155 farmers' data. Comparison of individual farmer's yields showed that the model simulated wheat yield with percent differences (PDs) of -25% to 17% and -26% to 40%, Root Mean Square Errors (RMSEs) of 436 and 592 kg ha(-1) with reasonable d-statistics of 0.87 and 0.72 for DSSAT and APSIM, respectively. Both models were used successfully as decision support system tools for crop improvement under vulnerable environments.

Automated summary

Decision support systems are crucial for yield improvement in modern agriculture, with crop models like DSSAT and APSIM serving as important tools for crop management. Both models demonstrated high accuracy in simulating crop yield and development, as evaluated through field experimental data and farmer surveys. The successful use of these models in vulnerable environments highlights their potential as effective decision support system tools for crop improvement.