Genetic analysis of zinc rich landraces for yield, quality and nutritional traits in rice (Oryza sativa L.)

Abstract

Aim: To study genetic variability, correlation, path and Principal Component Analysis (PCA) in a set of 100 zinc rich rice landraces along with four checks. Methodology: The study was carried out at the Regional Agricultural Research Station (RARS), Maruteru, during Rabi season, 2020-2021 in an Augmented Randomized Block Design. Results: Grain yield per plant, grains per panicle, productive tillers m-2 and test weight showed moderate genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) coupled with high heritability and genetic advance as per cent mean. These traits also had positive and significant association coupled with high positive direct effect on grain yield per plant. They also contributed maximum variance to the total variability indicating the effectiveness of direct phenotypic selection for these traits for improving the grain yield per plant. Further, cluster analysis grouped the zinc rich rice landraces along with checks into three clusters. Cluster II had the highest genotypes (42), while Cluster I had 32 genotypes and Cluster III consisted of 30 zinc rich landraces along with three check varieties. Interpretation: Grains per panicle, productive tillers and test weight were identified as effective selection criteria for the improvement of grain yield towards development of high yielding zinc-rich rice varieties to curtail micronutrient malnutrition in areas with rice as staple food. Key words: Cluster analysis, Landraces, Oryza sativa, Path analysis, PCA, Zinc