Selection of Soybean Genotypes (Glycine max (L.) Merrill) through Genetic Variability Analysis

Journal Title: Haya: The Saudi Journal of Life Sciences - Year 2017, Vol 2, Issue 3

Abstract

Abstract: The physiomorphological divergence was assessed in twenty-seven soybean genotypes by using cluster mean analysis, principal component and principal coordinate analysis and mean difference to identify parental genotypes for future breeding program in order to develop new high yielding varieties in randomized complete block design with three replications. Plant height, days to first flowering and days to 50% flowering have the highest percent of variations anomg the traits. The genotypes under the experiment were grouped into five clusters. The highest inter cluster distance was found between cluster I and IV followed by I and V. According to principal component scores F-85-11347 and ASSET-93-19-13have the prominent influence towards varietal improvement. Selecting genotypes from distant clusters probably provide promising recombinants and better segregants for future breeding platform. Keywords: Cluster, genotype, genetic variation, principal component analysis.

Authors and Affiliations

Kamrun Nahar Mili, Bir Jahangir Shirazy, Md. Mostofa Mahbub

Keywords

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  • EP ID EP382988
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How To Cite

Kamrun Nahar Mili, Bir Jahangir Shirazy, Md. Mostofa Mahbub (2017). Selection of Soybean Genotypes (Glycine max (L.) Merrill) through Genetic Variability Analysis. Haya: The Saudi Journal of Life Sciences, 2(3), 103-107. https://europub.co.uk/articles/-A-382988