Genetic parameters and association analysis for grain yield and yield attributing traits in rice (Oryza sativa L.) germplasm lines
2023
Mohan, Yeshala Chandra | Krishna, Kasanaboina | Krishna, Lavuri | Singh, Thakur Veerendar Jeet | Jagadeeshwar, R.
The intensity of trait association and genetic variability of yield attributing variables in 217 rice genotypes was investigated during kharif 2018. The existence of genetic variability among the genotypes was demonstrated by analysis of variance, which recorded significant differences for all the seven studied parameters. The estimation of variability indicated that The full grain number per panicle (37.2 % and 34.1 %) & single plant yield (24.7 % and 20.55 %) had the highest intensity of phenotypic coefficients of variation (PCV) and genotypic coefficients of variation ( GCV), and High heritability along with high genetic advance as a per cent of mean (GAM) was found in Plant height (98.9 % and 20.8 %), panicle number per plant (95.4 % and 36 %), panicle length(96.8 % and 35.9 %), full grain number per panicle(99.5 % and 61.6 %), thousand seed weight (98.1 % and 40.25 %) and single plant yield (69.2 % and 35.2 %) , depicting additive gene action in inheritance of these parameters. A simple selection procedure can help to enhance these characteristics even further. Correlation and regression coefficient findings indicated that plant height (0.193**) and the full grain number per panicle (0.177**) had a significant impact on single plant yield. The full grain number per panicle (0.265**), followed by thousand seed weight (0.194**) and plant height (0.110**), had the maximum direct positive effect on single plant yield, as per path coefficient analysis. As a result, accessions with a higher full grain number per panicle, thousand seed weight and plant height would be suitable for yield enhancement programme.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par Action for Sustainable Efficacious Development and Awareness
Découvrez la collection de ce fournisseur de données dans AGRIS