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Research Article Open access CC BY 4.0

Multivariate Analysis of Genetic Diversity in Linseed Genotypes for Yield and Its Component Traits

Sandhya, Manoj Kumar, Mukul, Pawan Kumar, Akash Gaurav

International Journal of Environment and Climate Change · pp. 537–544 · Published 22 Dec 2023

10.9734/ijecc/2023/v13i123711

Abstract

In the present investigation a total 30 linseed genotypes including released varieties were evaluated during Rabi 2021-22 at Agricultural Research Station, Ummedganj, Kota, Rajasthan (India) for understanding genetic diversity for grain yield and its component traits using principal component analysis. PCA was utilized to examine the variation and to estimate the relative contribution of various traits for total variability, first four principal components have more than one eigen values and accounted for 70.87% of total cumulative variance among 11 traits. PC1 had the contribution from traits viz., days to maturity, plant height, capsule per plant, seed per capsule, plant stand, test weight, branches per plant, germination per cent and yield per plant, which accounted for 26.08% of the total variability whereas PC2, PC3 and PC4 exhibited 20.13%,13.43% and 11.23% to the total variability respectively. Thus, the results of principal component analysis revealed the wide genetic variation in linseed genotypes indicating that these accessions may be used as donors to improve the yield and quality traits in varietal development program. On the basis of Ward’s linkage cluster analysis, five cluster were formed to identify relative closeness among 30 genotypes. Cluster V consisted of maximum 9 genotypes followed by cluster I and IV (8), cluster III (3) and cluster II (2). Maximum inter cluster distance was recorded between cluster I and IV indicating the possibilities of high heterosis if individual from these clusters were cross-bred. Cluster I had the highest mean values for plant height, seed per capsule, plant stand and yield per plant. Hence, suggesting that the genotypes constituted in these clusters may be used as a parent for future hybridization programs.

Cluster diversity eigen value linseed principal component analysis.

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