Genetic Variability, Character Association and Path Analysis for Yield and its Related Traits in Rice (Oryza sativa L.) Genotypes

S. Singh, Pooja Singh, Amrutlal R. Khaire, M. Korada, D. Singh, P. K. Majhi, S. Jayasudha
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Abstract

Assessment of variability and trait associations in a crop helps to enhance selection efficiency. With this objective, a study was conducted to estimate the genetic variability, character association and path coefficient analysis for grain yield and its component traits in 80 rice genotypes during Kharif-2020. Eighty genotypes including eight checks were evaluated in alpha lattice design with three replications. For all of the traits studied, the results revealed significant variance in all genotypes.PCV was found to be slightly more than the corresponding GCV for all the characters, indicating the role of environment in the expression of these traits. However, high GCV and high PCV were observed for number of effective tillers, grain yield per plot, number of filled grains per panicle, number of unfilled grains per panicle, biomass yield, harvest index, grain yield per plant and grain yield per hectare. Furthermore, all of the variables investigated had strong heritability and high genetic progress as a percentage of mean, with the exception of days to 50% blooming, days to maturity, and kernel breadth. Days to first flowering, days to 50% flowering, days to maturity, spikelet fertility percentage, number of filled grains per panicle, harvest index and kernel length showed a significant and positive association with grain yield per plot. Highest direct contribution to grain yield per plot was manifested by kernel length, harvest index and spikelet fertility percent. Days to first flowering, days to maturity, number of effective tillers, number of unfilled grains per panicle, test weight, biomass yield were also found to exert a positive effect on yield, thus can be considered as desirable traits for selection in high yielding genotypes.
水稻产量及其相关性状的遗传变异、性状关联及通径分析基因型
对作物的变异和性状关联进行评估有助于提高选择效率。为此,对80个水稻基因型在Kharif-2020期间的产量及其组成性状进行了遗传变异、性状关联和通径分析。80个基因型,包括8个检查,在alpha格子设计中进行了3次重复评估。对于所研究的所有性状,结果显示所有基因型都存在显著差异。所有性状的PCV均略高于相应的GCV,说明环境对这些性状的表达有影响。有效分蘖数、亩产、每穗结实粒数、每穗未结实粒数、生物量产量、收获指数、单株籽粒产量和每公顷籽粒产量均呈现高GCV和高PCV。此外,除开花至50%天数、成熟天数和籽粒宽度外,所有变量均具有较强的遗传力和较高的遗传进展率。开花期、开花期至50%期、成熟期、小穗育性率、每穗实粒数、收获指数和粒长与单株产量呈显著正相关。籽粒长、收获指数和小穗肥力率对亩产的直接贡献最大。开花期、成熟期、有效分蘖数、每穗未灌浆粒数、试验重、生物量产量对产量也有正向影响,可作为高产基因型选择的理想性状。
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