Multivariate Analysis in Upland Cotton (Gossypium hirsutum L.)

  • BAYYAPU REDDY KAIPU ACHARYA N G RANGA AGRICULTURAL UNIVERSITY
Keywords: Key words, Hierarchical cluster analysis and principal component analysis, cotton.

Abstract

ABSTRACT

An experiment was conducted with 63 genotypes of cotton to assess the genetic diversity for seventeen characters at Regional Agricultural Research Station, Lam Farm, Guntur, Andhra Pradesh. The 63 genotypes were grouped into eight clusters based on hierarchial cluster analysis. Among the clusters, cluster I was the largest with 13 genotypes followed by cluster VI with 11 genotypes. Cluster VII had minimum intra cluster Euclidean2 distance value while, the inter cluster Euclidean2 distance was highest between the clusters VI and VIII indicating the usefulness of the genotypes of these clusters in the exploitation of heterosis. In principal component analysis first seven principal components with eigen value more than one contributed 84.00% towards the total variability. PC1 contributed maximum towards the total variability (23.799).

Author Biography

BAYYAPU REDDY KAIPU, ACHARYA N G RANGA AGRICULTURAL UNIVERSITY
SCIENTIST (SS&T)
Published
19-02-2016
How to Cite
BAYYAPU REDDY KAIPU
Multivariate Analysis in Upland Cotton Gossypium hirsutum L.. 2016. Electronic Journal of Plant Breeding, 6 4, 1019-1026. Retrieved from https://ejplantbreeding.org/index.php/EJPB/article/view/692
Issue
Vol 6 No 4 (2015)
Section
Research Article

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