Multivariate Analysis in Pearl Millet Parental Lines for Diversity Estimation and Association Study of Yield Contributing Traits for Genetic Improvement of Hybrids


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Diversity analysis of pearl millet

Authors

  • vikas - khandelwal

https://doi.org/10.59512/aaz.2023.62.1.7

Abstract

Sixty parental lines of pearl millet containing R and B lines were evaluated at ICAR-AICRP on Pearl millet, Mandor, Rajasthan during Kharif-2020 to determine the extent of genetic diversity and association among yield and yield contributing traits. Multivariate techniques such as Principal component analysis (PCA) and cluster analysis were used to analyze the data. The results of PCA revealed four principal components with eigen values greater than one, explaining 33.53%, 18.51%, 14.06% and 8.49% of the total variability, respectively, with a cumulative effect of 74.59%. The study identified the traits such as number of productive tillers, dry fodder yield and plant height as excellent selection indicators that exhibit positive loading toward genetic diversity. Cluster analysis sorted all the parental lines into seven distinct clusters, with cluster VII having the highest number of lines followed by cluster III due to similar ancestry of parental lines. The parental lines J-2591, PPMI-1267 and RIB-109-120-S/19, RIB 3135-18, ICMB 95222, ICMB 94555, ICMB 04999, ICMB 93333 and ICMB 97111 display diversity in both cluster and PCA analyses, indicating the utilization of these lines for hybridization programme to harness heterosis and to select superior segregants in pearl millet.

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Author Biography

  • vikas - khandelwal
    Scientist

References

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Submitted

2023-03-23

Published

2023-03-31

How to Cite

Multivariate Analysis in Pearl Millet Parental Lines for Diversity Estimation and Association Study of Yield Contributing Traits for Genetic Improvement of Hybrids : Diversity analysis of pearl millet. (2023). Annals of Arid Zone, 62(1), 65-75. https://doi.org/10.59512/aaz.2023.62.1.7
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