2019
DOI: 10.53911/jae.2019.7104
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Assessment of genetic divergence using Mahalanobis D2analysis in mango

Abstract: Different genotypes are to be classified into clusters based on genetic diversity for any plant improvement programme. Further the extent of genetic divergence between them needs to be estimated. D 2 statistics is one of the powerful tools to assess the relative contribution of different component traits to the total diversity, to quantify the degree of divergence and to choose genetically diverse parents for obtaining desirable recombinants. The present study was conducted at Horticultural College and

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Cited by 2 publications
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“…The clusters with the minimum inter-cluster distance have signi cantly lower genetic differences among their genotypes and were not reliable for hybridization programme. These results are in accordance with the ndings of previous researcher viz., Indian et al (2019) Therefore, the D 2 distance of clusters alone is not reliable for choosing the genotypes for an effective hybridization programme. Hence, the cluster distance along with the average cluster mean value will provide a more accurate result for selection of a parent for the hybridization programme.…”
Section: Cluster Analysismentioning
confidence: 99%
“…The clusters with the minimum inter-cluster distance have signi cantly lower genetic differences among their genotypes and were not reliable for hybridization programme. These results are in accordance with the ndings of previous researcher viz., Indian et al (2019) Therefore, the D 2 distance of clusters alone is not reliable for choosing the genotypes for an effective hybridization programme. Hence, the cluster distance along with the average cluster mean value will provide a more accurate result for selection of a parent for the hybridization programme.…”
Section: Cluster Analysismentioning
confidence: 99%