Madras Agricultural Journal
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Research Article | Open Access | Peer Review

Genetic Diversity Based on Cluster and Principal Component Analyses for Yield and its Contributing Characters in Wheat (Triticum aestivum L.)

Volume : 100
Issue: Apr-jun
Pages: 320 - 323
Published: April 30, 2023
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Abstract


An experiment was carried out to assess genetic diversity by cluster and principal component analysis (PCA) for yield and its nine contributing characters in 24 bread wheat genotypes at BHU Agricultural Research Farm during Rabi 2010-11. The cluster analysis grouped all the 24 wheat genotypes into four major clusters. Extreme divergence was observed among clusters. Second cluster with two genotypes (WH 542 and ATTILA) had better yield potential as compared with fourth cluster which had also two genotypes (WL 711 and MALAVIYA 206). The result of PCA revealed that all the 4 principal components (PC1, PC2, PC3 and PC 4) contributed 89.68% of the total variability and accounted with values of 45.38, 20.69, 12.43 and 11.17 respectively. The third principal component had high positive component loading for all variables except spike length and grain spike-1. The result of present study could be exploited in planning and execution of future breeding programme in wheat.

DOI
Pages
320 - 323
Creative Commons
Copyright
© The Author(s), 2025. Published by Madras Agricultural Students' Union in Madras Agricultural Journal (MAJ). This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited by the user.

Keywords


PCA Cluster analysis Dendrogram Eigen vector wheat.
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