Agalya Jasmin, Karthika Rajendran
Context: High temperature during the flowering phase is a major constraint to stable rice productivity. Heat tolerance cannot be explained solely by yield, as yield is affected by several interacting traits. Therefore, an integrated multi-trait evaluation is essential to identify rice genotypes with superior performance under heat stress. Objective: The research was designed to identify high-yielding, heat-tolerant rice genotypes and the key traits contributing to yield maintenance under heat stress. Methods: A total of 80 rice accessions, comprising 45 landraces and 35 improved cultivars, were evaluated across four field environments using an alpha-lattice design across two cropping seasons under normal and heat-stress conditions during 2024-2025. Twenty morphological, physiological, and phenological traits were recorded. Pooled analysis of variance, correlation analysis, path coefficient analysis, principal component analysis, cluster analysis, and Multi-Trait Genotype-Ideotype Distance Index (MGIDI) analysis were performed, while a trait-wise heat tolerance index was applied to examine genotype performance under heat stress conditions. Results: Pooled ANOVA revealed evident impacts of genotype, environment, and genotype × environment interaction for all traits, indicating substantial genetic variability and contrasting responses to heat stress. High temperature during the reproductive stage adversely affected reproductive and yield-associated traits, with the largest reductions noticed in single plant yield, panicle weight, number of filled grains per panicle, spikelet fertility, and productive tillers. Trait-wise, HTI showed considerable diversity among genotypes, with TKM 9, TRY 1, PR 128, TPS 5, and TRY 5 recording superior performance in single-plant yield. Correlation and path coefficient analyses highlighted harvest index, panicle weight, productive tillers, number of grains per panicle, and filled grains per panicle as major contributors for yield maintenance under stress, whereas delayed flowering and high leaf temperature were unfavorable. Principal component analysis revealed that reproductive efficiency and grain formation explained more variation in heat tolerance than vegetative vigor, while cluster analysis identified Cluster III as the most promising group with superior genotypes under heat stress. MGIDI-based ranking further recognized TRY 1, RNR 15048, TPS 5, Indhurani, and Anna R 4 as promising multi-trait genotypes. Conclusions: Heat tolerance in rice is governed by multiple interacting traits rather than yield alone. Integrating trait-based analysis with trait-wise HTI and MGIDI improves the identification of superior genotypes under field conditions. The identified genotypes and key traits offer valuable resources for breeding heat-tolerant rice under increasing temperature stress.