Mutation-driven Improvement of Yield Components in Advanced Aromatic Rice Mutants
DOI:
https://doi.org/10.23910/1.2026.6868Keywords:
Induced mutant, variability, character association, aromatic riceAbstract
The study was conducted during kharif season (June–December) 2019 at Agriculture Farm, Visva-Bharati, Sriniketan. The present investigation evaluated the yield-contributing traits of forty-six advanced-generation (M4) mutant families along with their mother genotype, with the aim of identifying promising lines for future improvement of this valuable aromatic rice cultivar. A yield assessment by applying RCBD was carried out on a population of forty-six advanced generation (M4) morphologically distinct induced mutants derived from the popular short-grain aromatic non-basmati cultivar ‘Badshabhog’ of eastern India. Replicated mean data of twelve quantitative characters of forty-six mutants along with parent were applied for statistical analysis by Windostat Version 9.2. The results revealed that high (>20%) GCV and PCV were observed for panicle exertion, number of productive tillers hill-1, spikelets panicle-1, and seed weight indicated low sensitivity in fluctuating environments. High estimates of broad-sense heritability accompanied with genetic advance as percentage of mean were observed for days to 50% flowering, culm length, panicle exertion, number of productive tillers hill-1, panicle length, number of spikelets panicle-1, seed weight and grain yield hill-1. These results suggested that selection for culm length, panicle exertion, productive tillers hill-1, spikelets panicle-1, and seed weight could effectively enhance grain yield. Grain yield hill-1 showed a significant positive association with productive tillers hill-1 and spikelet fertility (%) at both genotypic and phenotypic levels. Overall, the findings indicated that high-yielding, short-stature, and early-duration mutants could be developed through simultaneous selection for more productive tillers, enhanced spikelet fertility, and balanced panicle- and leaf-related traits.
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Copyright (c) 2026 Achal Kant, N. R. Chakraborty

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