Vol. 10, Issue 9 (2021)

Author(s):
VL Ladumor, HE Patil and KG Modha

Abstract:
The easily assessment of the important quantitative traits, principal component analysis is a important statistical tool to study genetic diversity in plant breeding program. The experiment was conducted during kharif, 2019 with 35 finger millet genotypes to study genetic diversity for yield, yield attributing traits and quality traits at Hill Millet Research Station, NAU, Waghai, Niger Research Station, NAU, Vanarasi, College Farm, NAU, Navsari, Gujarat in a randomize block design. The observations for eighteen characters were recorded. The multivariate technique, principal component analysis were applied. Principal component analysis indicates that two principal components PC-1 and PC-2 contributed 74.89% and 24.26% respectively of the total variation. The genotypes viz., VL-314, Dapoli-1, Dapoli-2, KOPN-235, KOPN-942, Phule Nachni, VR-708, VR-847, PR-202, KMR-204 and GNN-7 were accumulated on positive side of PC1 axis which accounted for days to 50% flowering, days to maturity, plant height, main ear head length, finger length and harvest index contributed maximum towards divergence. On other axis, only two genotypes OEB-532 and Indira Ragi-1 are accumulated on positive side of PC-2 which accounted for chlorophyll content was important traits contributed maximum towards divergence. PC-1 and PC-2 was provide maximum genetic variation. The positive signifying genotypes could be useful in finger millet breeding. Hence, these genotypes can be utilized in hybridization programmes to produce superior recombinants.