Author(s): Vaibhav V Ujjainkar

Abstract: Cotton is essential to Indian agriculture, serving as a key cash crop offering raw materials for the global textile industry, provides significant income and job opportunities for millions. Genetic diversity is essential component for any breeding adventure; the genetic diversity in terms of phenotypic expression offers the opportunity to select desirable genotypes that possess multiple advantageous traits simultaneously. By converting extensive datasets comprising morpho-qualitative traits into significant patterns, Principal Component Analysis (PCA) offers breeders statistical assurance to make well-informed choices, resulting in more efficient selection and accelerated advancement of breeding outcomes. With this view, the set of thrity-four genotypes of Gossypium hirsutum were tested in randomozed block design with tree replications for fourteen morphological traits including fibre quality components. Analysis of variance exhibited the presence of substantial degree of variability in experimental material which was confirmed by Principal Components (PCs). The 80.46 per cent of total variability present in genepool was accounted by seven principal components, the PC-I contributed the maximum of 27.19 per cent of variability. The trait viz., ginning outturn and lint index were major contributors towards divergence based on first two PCs, whereas, genotypes viz., G-22, G-16, G-29 and G-20 were found to be better and having potential to be included in cotton improvement program.

DOI: 10.22271/27889289.2025.v5.i2e.235

Pages: 372-375 | Views: 20 | Downloads: 11

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