Assessment of genetic diversity among upland cotton for earliness, fiber quality and yield-related traits using correlation, principal component and cluster analysis
Abstract
A field experiment was conducted at Cotton Research Farm, Gazipur in Kharif season 2017 with 100 genotypes to evaluate their genetic diversity. The results of the study showed a significant positive link between the number of bolls and seed cotton output, as well as between maturity and boll split. Cluster analysis, Principal Component Analysis (PCA), and correlation were used to categorize the major characters that account for the variation in yield contributing traits. Data were recorded at maturity, bolls plant-1, seed cotton yield, ginning outturn, fiber length and fiber strength. The first four PCs with Eigen value >1 contributed 65.15% variability among the cotton accessions. The genotypes were grouped into ten clusters through multivariate analysis. Cluster III contained a maximum number of genotypes (29) while clusters I (15), II (9), IV (23) and V (13) contained genotypes, cluster VII (4), VI, VIII and X contained genotypes (2) and cluster IX contained only 1 genotype. In all cases, the inter-cluster distances were greater than those of intra-cluster distances, which indicate a wider genetic diversity among the genotypes. Cluster I and IX had the largest inter-cluster distance (35.13), while cluster VI and VIII had the smallest (1.68)-. The results revealed a diverse and close relationship among the genotypes of those clusters. The single boll weight and days to boll split showed a higher contribution to the genetic divergence among 14 characters. Based on genetic diversity results and early-maturity, VII (BC-0451, BC-0456, BC-0491 and BC-0495), VIII (SR-16), IX (BC-0479) and X (BC-0493 and BC-0459) genotypes could be used to develop the short-term cotton variety as following the standard procedure.
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PDFDOI: https://doi.org/10.33865/ijcrt.006.01.1372
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Copyright (c) 2024 Jahangir Alam, Ahmed Khairul Hasan, Abdul Kader, Md Amzad Hossain, Faruk Ahmed
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E-ISSN = 2707-5281