Multivariate insights into selection Indices of farmers’ pea (Pisum sativum var. arvense L.) varieties from Vindhyan zone, Uttar Pradesh

Variability is the prerequisite for selection of superior traits and parents. Multivariate analysis acts as an aid to the process of selection indices. Therefore, twenty-two farmers’ varieties of pea (Pisum sativum var. arvense L.) of Vindhyan zone, Uttar Pradesh were studied at Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj (U.P.). The varieties were grown in randomized block design (RBD) during Rabi, 2019-20 and Rabi, 2020-21. The data obtained on 11 traits for the two consecutive years were pooled for principal component (PC) analyses. The result revealed that the four principal components (PC1, PC2, PC3 and PC4) had eigen value greater than unity. They contributed a total of 78.68% of variance. Days to maturity, pod length, pod width, number of effective nodes and yield per plant exhibited maximum variability for the characters, which can be exploited to a greater extent. Days to 50% flowering, days to maturity and harvest index had positive correlation with yield per plant. Number of seeds per pod, number of pods per plant and pod length exhibited negative association with yield per plant. Hence, selection of these traits could be useful to increase the productivity in farmers’ pea varieties. To the farmers’ varieties viz., PMKK-232 and PKKK-227 could be selected in PC1 for future breeding programme.