Multivariate analysis of selected agro-morphological traits of common wheat genotypes for estimation of genetic diversity

Estimation of genetic diversity of plant species using agro morphological parameters is of very crucial importance in plant improvement programs. In view of that common wheat (Triticum aestivum L.) genotypes consisting of stripe rust resistant genes were analyzed by cluster analysis, principle component analysis and coefficient of correlation analysis for determination of genetic diversity. Experiment was conducted in fields of Hazara University Mansehra Pakistan. Eight groups were categorized by cluster analysis using UPGMA clustering method. AOC-YR/ATTILA (CGSS97Y0061S-23Y-1B-1B) (Sdf31) and 10790 (sdf2) are reported as more diversified by cluster analysis. Based on principal component analysis the first five clusters showed 88.94% of genetic variation. Grains per spike contributed more (0.7) to total variation in PCI. While Harvest Index was the major contributor (0.8) to total variation in PCII. 1056 (Sdf5), AOC-YR/ATTILA (CGSS97Y0061S-32Y-1B-1B) (sdf30), 1072 (sdf6), 1076 (sdf9), and LALBMONO4*4/PRL//LALB (CGSS99Y00093S-2F1-22Y-9GHB-1GHB) (sdf32) were observed superior in flag leaf area, spike length, grains per spike, plant height, biological yield, plant yield and harvest index. AOC-YR/ATTILA (CGSS97Y0061S-32Y-1B-1B) (Sdf30) was found as early maturing genotype. Correlation analysis showed positive and significant association of plant yield with flag leaf area, spike length and biological yield, while it is highly negatively correlated to no. of days to maturity. More diversified genotypes identified in this studies can be used in future breeding programs along with utilization of superior genotypes in hybridization.
Key words: cluster analysis, correlation, genetic diversity, principal component analysis, whea