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Vol. 12, Issue 11 (2023)

Character association and genetic diversity assessment via hierarchical clustering in a diverse panel of improved wheat genotypes

Author(s):
Ashish Nain, Vikram Singh and Antim
Abstract:
The present study was conducted on fifty-seven diverse wheat genotypes at Wheat and Barley section, Department of Genetics and Plant Breeding, CCS HAU, Hisar to carried out character association and genetic diversity assessment via hierarchical clustering. A total of eleven morphological traits of each genotype was recoded and subjected to statistical analysis. Pearson correlation analysis was done and positive correlation was observed between grain yield and several key traits, including effective tillers per meter, spike length, spikelets per spike, grain per spike, 1000-grain weight, and biological yield per plot. To cluster the 57 wheat genotypes, 2-way clustering dendrogram were constructed and the genotypes were categorized into five clusters, while the traits/variables were classified into three groups. Among the five clusters, cluster I carries minimum one genotype i.e., C-306, while cluster III got maximum nineteen genotypes. Remaining clusters i.e., II, IV and V had thirteen, ten and fourteen genotypes, respectively. As per cluster mean table Cluster V carries superior genotypes performance better in the experiment which was recorded with highest spike length (12.74 cm), spikelet per spike (24.28), grains per spike (64.22), grain yield (1440.43 g/plot) and harvest index (41.71%). More genetically variable genotypes identified in the studies can be used in future crop improvement program along with utilization of superior genotypes as parent in hybridization.
Pages: 1506-1510  |  149 Views  83 Downloads


The Pharma Innovation Journal
How to cite this article:
Ashish Nain, Vikram Singh, Antim. Character association and genetic diversity assessment via hierarchical clustering in a diverse panel of improved wheat genotypes. Pharma Innovation 2023;12(11):1506-1510.

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