Multi-Trait Index-Based Characterization of Putative Drought-Heat Tolerant Gamma-Irradiated Rice Mutants Through Artificial Screening at the Seedling Stage

Abstract

Rice is highly vulnerable to concurrent drought-heat stress, which intensifies the disruption of plant growth and can cause high seedling mortality. Limited genetic diversity further constrains breeding for combined stress adaptation. Thus, mutation breeding has emerged as a solution for inducing beneficial variability in rice genomes. Based on this solution, this study aimed to identify rice mutants tolerant to drought and heat through artificial screening combined with multi-trait index analysis. Experiments were conducted from April to August 2025 at Hasanuddin University in two sequential phases: seedling screening in a controlled stress chamber and pot evaluation under semi-controlled conditions. Mutants were derived from the seeds of the double haploid (DH) rice line HS1-28-1-5, which was previously developed through anther culture and exhibited potential abiotic stress adaptability. DH seeds were exposed to gamma irradiation (200–1000 Gy) as the M1 population. Based on radiosensitivity evaluation, 200 and 400 Gy were selected and used in the present study as the M2 populations. Rice M2 evaluation results indicated that 200 Gy irradiation enhanced phenotypic variability with improved performance, whereas M2 400 Gy resulted in broader but less stable variation. Yield components were strongly associated with weight per clump, with panicle length being the primary direct contributor and weight per panicle mediating indirect effects. Principal component analysis accounted for 89.13% of the total variation, which was predominantly driven by yield traits. Integrated weighted average absolute score–tolerance score analysis classified genotypes into tolerance groups, identifying 33 putative tolerant mutants, with M2 200 Gy mutants demonstrating superior adaptability to drought-heat stress. These findings suggest that moderate irradiation coupled with multi-trait index selection provides a reproducible framework for identifying putative drought-heat-tolerant rice candidates at early stages while retaining relevance to subsequent yield recovery.

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