Evaluating rice yield and resource efficiency: DSSAT analysis of conventional vs. AWD techniques in Coimbatore

Rice cultivation is a key activity of Indian agriculture, contributing significantly to global rice production and exports. Optimal yield is crucial and influenced by various agronomical and environmental factors. For the experiment, the decision support system for agrotechnology transfer (DSSAT) of the rice crop model is utilized to validate the grain and straw yield in addition to resource productivity metrics and leaf area index. The study was conducted during the Zaid season from January to May in both 2022 and 2023 at the Thensangampalayam village, Coimbatore district, Tamil Nadu. The CO-55 rice variety was used for 2 cultivation methods i.e., conventional and alternate wetting and drying (AWD), along with drone spray of nano urea. The model was calibrated and validated with the input of comprehensive datasets of soil profile, meteorological parameters, crop-specific cultivation methods, agronomic practices and genetic coefficients. AWD consistently outperformed the conventional method in both grain and straw yields. DSSAT simulations achieved a high accuracy of 99.78 % in grain yield and 91.67 % in straw yield between the 2 cultivation methods. The AWD also outperformed in water use efficiency with 2.3 kg/m3 compared to conventional at 1.8 kg/m3. Leaf Area Index was recorded high in the conventional method at heading stage with 6.96 and AWD at 6.46. The study provides valuable information on adaptive farming practices and climate-resilient crop management strategies.