Principal Component and Cluster Analyses to Estimate Genetic Diversity in Bread Wheat (Triticum aestivum L.) Genotypes
Fouad, H. (2020). Principal Component and Cluster Analyses to Estimate Genetic Diversity in Bread Wheat (Triticum aestivum L.) Genotypes. EKB Journal Management System, 11(4), 325-331. doi: 10.21608/jpp.2020.90015
Hassan Fouad. "Principal Component and Cluster Analyses to Estimate Genetic Diversity in Bread Wheat (Triticum aestivum L.) Genotypes". EKB Journal Management System, 11, 4, 2020, 325-331. doi: 10.21608/jpp.2020.90015
Fouad, H. (2020). 'Principal Component and Cluster Analyses to Estimate Genetic Diversity in Bread Wheat (Triticum aestivum L.) Genotypes', EKB Journal Management System, 11(4), pp. 325-331. doi: 10.21608/jpp.2020.90015
Fouad, H. Principal Component and Cluster Analyses to Estimate Genetic Diversity in Bread Wheat (Triticum aestivum L.) Genotypes. EKB Journal Management System, 2020; 11(4): 325-331. doi: 10.21608/jpp.2020.90015

Principal Component and Cluster Analyses to Estimate Genetic Diversity in Bread Wheat (Triticum aestivum L.) Genotypes

Journal of Plant Production
Article 6, Volume 11, Issue 4, April 2020, Page 325-331  XML PDF (622.02 K)
Document Type: Original Article
DOI: 10.21608/jpp.2020.90015
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Author
Hassan Fouad email
Dept. of Agronomy, Fac. Agric., Minia Univ., El Minia, Egypt
Abstract
Analyze the genetic diversity of 22 bread wheat genotypes by principal component and cluster analyses were conducted at the Exper. Farm Fac. Agric., Minia Univ. Egypt during two seasons of 2017/18 and 2018/19. Principal component analysis (PCA) extracted three main components had eigenvalue >1 explained 79.59% of the total variation by 36.93% of PC1, 29.38% of PC2 and 13.28% of PC3. The most traits contributing in variation of first principal component were weight of spikes/plant, no. of grains/spike, weight of grains/spike, grain yield/plant, spike density and spikelet fertility. Cluster analysis divided the 22 bread wheat genotypes into five clusters. Each of them contained 8, 1, 3, 9 and 1 genotypes for cluster 1, 2, 3, 4 and 5, respectively. Average observed gain of cluster 1 showed positive increase for days to heading (DH), no. of spikelets/spike (NST/S) and spike density (SD) in percentage of mean overall genotypes. Cluster 3 had the highest yield potential. Nielain is separated in the second cluster and showed positive observed gain for plant height, NST/S and SD. Also, Genotype Emara1 is separated in cluster 5 and showed high positive observed gain for the most traits in percentage of mean all genotypes. So, hybridization between Nielain of cluster 2 and Emara1 of cluster 5 could give new recombination and transgressive segregations with long spike and high spike density in the progenies derived from their crossing.
Keywords
Eigenvalue; cluster; recombination; transgressive; segregations
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