Shubham Pandey, S.R. Mishra, A.K. Singh, Badri Narayan Mishra, Baljeet Kaur, Sameer Kumar Singh, Kirti Vardhan Pandey, A.N. Mishra and Gaurav Chaturvedi
Abstract
Crop simulation models are significant decision-support tools used for simulating crop growth, development and yield under different environmental and management conditions. The present study was carried out to calibrate and validate DSSAT CROPGRO-Chickpea model in eastern Uttar Pradesh during rabi 2023-24, 2024-25 and 2025-26. The experiment consisted of three sowing dates (25 October, 09 November and 24 November) and three cultivars (Uday, Radhey and RVG-202) in Split Plot design (SPD) with four replications where experimental data of 2023-24 and 2024-25 was used for calibration, while 2025-26 was used for validation. The model performance was evaluated using the coefficient of determination (R2), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), and index of agreement (d-stat). The model showed satisfactory agreement between observed and simulated days to flowering, days to physiological maturity and grain yield. The R2 values for days to flowering, days to physiological maturity and grain yield were 0.58, 0.69 and 0.66, respectively. The deviation between observed and simulated grain yield was below 10% under all treatments. Delayed sowing significantly reduced crop duration and yield due to terminal heat stress. Among cultivars, RVG-202 showed comparatively better yield performance across sowing dates. This study showed that the model can efficiently simulate chickpea growth and yield under eastern Uttar Pradesh conditions and can be used for crop management, yield prediction and climate change impact studies.