Estimation of Genetic Variability Parameters and Correlation Coefficients for Grain Yield Characters of Rice (Oryza sativa L.)

Dheeraj, Gade and Ramesh, Bura and Raghu, Namileti and Lavanya, G. Roopa (2023) Estimation of Genetic Variability Parameters and Correlation Coefficients for Grain Yield Characters of Rice (Oryza sativa L.). International Journal of Plant & Soil Science, 35 (19). pp. 1852-1861. ISSN 2320-7035

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Abstract

Twenty-six rice genotypes were examined, and an experiment was carried out by using a Randomized Block Design with three replications at the Department of Genetics and Plant breeding, Sam Higginbottom University of Agriculture, Technology and Sciences, Naini Allahabad, U.P during the kharif season of 2022. The analysis of variance revealed significant differences between genotypes for all 13 characters, showing that there is a wide scope for selecting traditional rice varieties for yield and its components from the current gene pool. WGL-915 (43.05g) had the highest grain production per hill among the 26 genotypes, followed by JGL-21078 (36.99g), WGL-283 (32.60g), WGL-13400 (28.51g), WGL-14377 (28.25g), and WGL-347 (27.76g). When compared to the check genotype NDR-359, all of these genotypes produced significantly higher yields (22.67g). High estimates of heritability and genetic advance as a percentage of mean were observed for test weight, number of spikelets per panicle, biological yield, and grain production per hill. These qualities are governed by additive gene effects and have the best chance of improvement via simple selection. The length of the flag leaf, the length of the panicle, the biological yield, the harvest index, and the test weight all had positive and very significant correlation associations with grain production per hill. The selection of these features will thus be effective in increasing rice grain yield.

Item Type: Article
Subjects: Apsci Archives > Agricultural and Food Science
Depositing User: Unnamed user with email support@apsciarchives.com
Date Deposited: 13 Oct 2023 09:37
Last Modified: 13 Oct 2023 09:37
URI: http://eprints.go2submission.com/id/eprint/1903

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