Genetic Variability, Heritability and Genetic Advance for Yield and Yield Related Traits in Rice (Oryza Sativa L.)
Year: 2024
Type: article
Abstract: Aims: To evaluate genetic variability, heritability, and genetic advance for key agronomic traits in rice to identify traits with high potential for selection and improvement in breeding programs. Experimental Design: The experiment was conducted in a randomized block design (RBD) with three replications. Place and Duration of Study: Regional Sugarcane and Rice Research Station (RS&RRS), Rudrur, Nizamabad, during the kharif 2022 season. Methodology: Eighteen Advanced Varietal Trial (AVT) entries were evaluated with a spacing of 20 cm × 15 cm. Data were recorded from five randomly selected plants per entry in each replication for agronomic and yield-related traits: days to 50% flowering (DFF), plant height (PH), panicle length, number of panicles per square meter, filled grains per panicle, 1000-grain weight, and grain yield per hectare (GY/ha). Analysis of variance (ANOVA) and genetic parameters, including environmental coefficient of variation (ECV), genotypic and phenotypic coefficients of variation (GCV and PCV), heritability (h²), and genetic advance as a percentage of the mean (GAM), were calculated using Windostat Version 9.1. Results: The ECV was low across all traits, indicating minimal environmental influence. GCV was low for DFF (4.957%) and PH (4.789%) but moderate for filled grains per panicle (15.874%) and 1000-grain weight (16.33%). PCV was slightly higher than GCV for most traits, confirming limited environmental effects. Heritability ranged from medium (37.4% for GY/ha) to very high (99.7% for 1000-grain weight). GAM was high for filled grains per panicle (31.96%) and 1000-grain weight (33.586%), indicating strong potential for genetic improvement. Conclusion: Traits with high heritability and genetic advance, such as filled grains per panicle and 1000-grain weight, are ideal for selection. These findings will aid in enhancing rice breeding programs through targeted genetic improvement.
Authors: B. Soundharya, B. Edukondalu, G.Narender, A. Dinesh
Language: English
Topic: Genetics and Plant Breeding
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4406343166