Principal Component Analysis among Vegetable Soybean Genotypes (glycine Max L. Merrill)

In the present study, 33 soybean genotypes were selected to study the association between the fourteen quantitative characters under study and to assess the magnitude of divergence between 33 genotypes for 14 traits during Kharif, 2021. For all measured traits, the results revealed significant variation among tested entries. The principal component analysis (PCA) was conducted for the 1quantitative characters and only 7 showed > 1 Eigen value and showed about 81.748% of total variation and remaining 7 components having a eigen value less than 1.00 and contributed only 18.252% of total Variation. Among the traits studied PC1 showed 20.7235 while, PC2 to PC 14 exhibited 15.205%, 12.69%, 9.476%, 9.142%,7.271%, 7.241%, 6.171%, 4.089%, 2.865%, 2.185%, 1.506%, 0.897% and 0.536% variability, respectively. Scree plots explained the percentage of variance. A high PC score for a specific genotype shows high value for those variables like EC 915989, EC 915900, EC 915993, EC 915975, EC 915903, EC 915898 and EC 915959 in PC1 and this indicated that these genotypes have high values for traits such as 100 Fresh pod weight and 100 Fresh seed weight.