Assessment of genetic variability for seed yield and its components in sesame (Sesamum indicum L.) based on multivariate analysis
DOI: 10.37992/2022.1303.126
Abstract
Sesame is an important oilseed crop in India. The productivity of sesame is considerably low owing to several production challenges. Developing high yielding varieties with resistance to biotic and abiotic stresses remains a major goal in sesame breeding. In this study, a total of 55 sesame genotypes were evaluated for 16 quantitative traits related to seed yield. Genetic relationship and variability in the genotypes were assessed based on correlation, principal component analysis (PCA) and cluster analysis. The results showed that seed yield had a high positive correlation with the number of capsules per plant and a high negative correlation with days to maturity. The PCA revealed six components contributing to the total variance, which were components 1 (plant height, the number of primary branches, leaf length and leaf width), 2 (seed yield per plant and thousand seed weight in the positive direction and days to maturity in the negative direction), 3 (days to flower initiation and days to 50 per cent flowering), 4 (capsule width and seeds per capsule), 5 (the number of capsules per plant) and 6 (the number of seeds per capsule) in the order of importance. Cluster analysis showed five clusters of genotypes in accordance with the phenotypic traits. Overall results indicated that the number of capsules per plant, the number of seeds per capsule and thousand seed weights were the most critical traits for selecting high yielding genotypes in sesame.
Keywords: Correlation, principal component analysis, cluster, genetic resources, evaluation
Assessment of genetic variability for seed yield and its components in sesame Sesamum indicum L. based on multivariate analysis
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