Multivariate Analysis in Groundnut (Arachis hypogaea L.) Germplasm Accessions for Yield Traits by Principle Component Analysis

Background: The present study was conducted using groundnut germplasm lines obtained from ICRISAT, Hyderabad to classify 93 groundnut germplasm lines along with 5 checks using Principal component analysis (PCA) for yield traits. Methods: Using version 4.2.2 of R studio software, nine principle components had been extracted of which first six principal components showed over 93.3% of variation. Result: Characters were shown in the first two components biplot were plant dry weight, 100 seed weight, 100 pod weight, 100 shell weight, fresh weight, kernel color, shelling percentage, days to 50% flowering and plant height. Nine PC scores that had for almost 100% of the variation were used to perform cluster analysis, which divided the 98 accessions into eight groups. This allows the selection of superior genotypes from each cluster for various yield traits in the groundnut crop improvement.