Optimizing Soybean Cultivation in Uttarakhand's Tarai Region Using the DSSAT CROPGRO Modeling Approach

Abstract

Soybean (Glycine max) is a vital oilseed crop globally, but in India, its average grain yields remain relatively low despite the presence of high-yielding varieties. This study aimed to optimize soybean cultivation in the Tarai region of Uttarakhand, India, by exploring the impact of different sowing dates on crop growth and yield using the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO model. The experiment was conducted in 2022 and 2023 at Pantnagar, Uttarakhand, using a split-plot design with three replications. The model was calibrated and validated for different sowing dates, and key parameters such as emergence days, physiological maturity days, grain yield, harvest index, and leaf area index were compared between simulated and observed values. During validation RMSE and R2 was 48.44 and 0.90 for grain yield, 1.10 and 0.99 for physiological maturity, 0.042 and 0.99 for harvest index and 1.14 and 0.97 for LAI respectively. The results showed that adjusting sowing dates can significantly affect soybean growth and yield, with optimal sowing times resulting in higher yields and better crop performance. Specifically, sowing on July 22nd resulted in the highest grain yield, while sowing on August 21st led to the lowest. The DSSAT CROPGRO model proved to be a valuable tool for simulating soybean growth and predicting crop outcomes under varying environmental conditions.