Exploring Genetic Variability and Diversity in Advanced Breeding Lines of Rice for Yield-Attributing and Grain Quality Traits
Kuna Sharmila, Deepak Gauraha, Abhinav Sao, Sagi Indumathi, Dharavath Nagaraju
Journal of Advances in Biology & Biotechnology · pp. 42–56 · Published 7 Apr 2025
10.9734/jabb/2025/v28i42167Abstract
Genetic variability and diversity are crucial for enhancing yield and grain quality in rice (Oryza sativa L.). A field experiment was conducted during Kharif, 2023 at the Research cum Instructional Farm, Department of Genetics and Plant Breeding, College of Agriculture, IGKV, Raipur (C.G.). Thirty-three advanced breeding lines were evaluated for 30 yield-attributing and grain quality traits using a Randomized Block Design (RBD) with two replications. Analysis of variance revealed highly significant differences among the lines, indicating substantial genetic variability. Genetic parameter evaluation showed higher PCV values than GCV, indicating the influence of environmental factors on the expression of the trait. Gel consistency, alkali spreading value and amylose percentage exhibited high GCV and PCV values, indicating a strong genetic influence and potential for selection. Traits with high heritability and high genetic advance as % of the mean included number of effective tillers per plant, panicle length (cm), breadth of flag leaf (cm), 100 seed weight (g), biological yield per plant (g), grain yield per plant (g), gel consistency, alkali spreading value, amylose percentage and head rice recovery (%), indicating the predominance of additive gene action. Genetic diversity analysis through agglomerative hierarchical clustering based on Euclidean Distance grouped the lines into five distinct clusters. Cluster II was the largest, followed by Cluster I, while Clusters III, IV, and V contained 2, 5, and 1 line(s), respectively. The maximum inter-cluster distance was between Clusters I and V. Cluster III had the highest mean values for several traits, including grain yield per plant, making these lines promising candidates for hybrid breeding programs to improve yield and grain quality.
Cited by 2
Hongwei Yang, Liying Zhang, Xiangquan Gao · Agronomy · 2025
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