Cluster and principal component analysis for yield and yield | 106879
An International Journal

Agricultural and Biological Research

ISSN - 0970-1907
RNI # 24/103/2012-R1


Cluster and principal component analysis for yield and yield related traits of bread wheat (Triticum aestivum L.) genotypes

Demeke Zewdu*, Fikru Mekonnen and Negash Geleta

Wheat (Triticum aestivum L.) is an important cereal crop that is cultivated worldwide and is one of the first crops to have been domesticated by human. The knowledge on traits contribution for total variation and genetic divergence of genotypes is essential for breeding program. Hence, the research was conducted at Kulumsa in 2022 to identify traits that contributed more to the total phenotypic variation and to cluster genotypes into genetically divergent groups and estimate the genetic distance between clusters of bread wheat genotypes. A total of 64 bread wheat genotypes were evaluated for 16 traits in 8*8 simple lattice design. The first four principal components accounted 76.76% of the total observed phenotypic variation with Eigen value greater than one. Cluster analysis classified the 64 bread wheat genotypes into five distinct clusters. The inter cluster distance between cluster I and cluster III, cluster IV and between cluster II and cluster III showed significant (P ≤ 0.05) and other cluster combination values had highly significant (P ≤ 0.01) compared with tabulated chi-square value and all inter cluster distances greater than intra cluster distances. The maximum inter cluster distance observed between cluster II and V followed by cluster III and V. Therefore, crossing genotypes between these clusters could result better genetic recombinant.

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