Assessment of CSM–CERES–Rice as a Decision Support Tool in the Identification of High-Yielding Drought-Tolerant Upland Rice Genotypes

Drought is considered as one of the critical abiotic stresses affecting growth and productivity upland rice. Advanced rapid identification drought-tolerant high-yielding genotypes in comparison to conventional rice breeding trials assessments can play a decisive role tackling climate-change-associated drought events. This study has endeavored explore potential CERES–Rice model decision support tool (DST) genotypes. Two experiments mentioned experiment (1) for calibration under optimum conditions an yield assessment (2) with three irrigation treatments, (i) control (100% field capacity [FC]), (ii) moderate stress (70% FC), (iii) severe (50 % were conducted. The results from indicated that grain studied decreased by 24–62% 43–78% compared control. values susceptibility index (DSI) ranged 0.54–1.38 0.68–1.23 treatment. Based on DSI relative yield, Khao/Sai, Dawk Kham, Pa–yawm, Goo Meuang Luang, Mai Tahk Kha, Nual Hawm, Bow Leb Nahag among top five well accurately simulated different treatments normalized root mean square error < 10%. An inverse relationship between indices was observed regression analysis. Simulated water use efficiency (WUE) revealed identified had lower increasing trend their WUE indicating able aid identifying Simulating could assist predicting response genotype final at harvest. idea be used DST stressed non-stressed conditions, thus assisting genotypic selection process crop programs.