Principal Component Analysis in Advanced Genotypes of Soybean (Glycine max (L.) Merrill)” during Kharif-2014 Jha Avinash*, Shrivastava A.N., Mishra Stuti Dept of Plant Breeding and Genetics, College of Agriculture, JNKVV, Jabalpur, M.P. *email: avinashjha149@gmail.com
Online published on 23 December, 2016. Abstract The present investigation Principal component analysis was performed for Identification and ranking of advancedgenotypes of soybean based on combination of various phenotypic traits. Out of total principal components, five principal components were considered to be more important because they have more than one Eigen value that showed total variation among 50 soybean genotypes under study. The PC1 had the highest variability (31.953%) followed with PC2 (14.465%), PC3 (10.147%), PC4 (8.273%) and PC5 (7.338%) for traits under study. Five principal components exhibited about 72.175% variability among the traits studied. The PC1 showed positive effect for the specific traits under study i.e. biological yield/plant, seed yield/plant, number of pods/plant, number of pod clusters/plant, dry matter gain from full flowering to maturity, number of seeds/plant, days to fifty percent flowering, days to maturity, plant height at maturity, number of nodes/plant and plant height at full flowering. In second principal component the traits viz., fresh weight of nodules/plant, dry weight of nodules/plant and number of nodules/plant while, PC3 was consisting of number of branches/plant. Fourth principal component was more related with dry weight of plant at full flowering and 100 seed weight. Whereas, the fifth principal component was more related with harvest index. On the basis of PCA mostof the important yield andyield attributing traits were present in PC1, PC4 and PC5. Top Keywords Soybean, advanced genotypes and principal component analysis. Top |