Genetic diversity studies for yield and physiological traits using principal component analysis in little millet

Principal Component Analysis (PCA) was conducted to assess the genetic variability among 50 little millet genotypes based on yield and physiological traits. Results revealed six principal components with an Eigen value more than one, which accounted for 74.25% of the total variability. PC 1 contributed the most towards the total variability at 27.98%, while PC 2, PC 3, PC 4, PC 5, and PC 6 contributed 12.90%, 11.19%, 8.93%, 7.08%, and 6.14% respectively. Days to 50 per cent flowering, grain yield plot^-1, harvest index, leaf area index at both panicle and 15 days after panicle initiation, specific leaf weight at 15 days after panicle initiation, and main panicle weight were the foremost contributors to genetic diversity among the studied genotypes. The biplot diagram revealed that WV-167, BL-6, TNPsu-174 and GPUL-2 were the most diverse genotypes, with high yield potential compared to other entries. GPUL-1 and DLM-186 are likely to be drought resistance due to lower relative membrane injury (%). Hybridization among these genotypes could result in transgressive segregants with desirable traits for yield and physiological characteristics.