1Department of Mathematics, Statistics and Physics
2Oilseeds Section Department of Genetics and Plant Breeding, CCS Haryana Agricultural University, Hisar
Online published on 22 September, 2017.
The focus of this work has been to study the genetic divergence in Indian mustard and grouping them into different clusters based on yield and yield contributing traits for the hybridization programme. The Principal Component analysis (PCA) revealed that the first six PCs explained about 80% of the total variability and thus indicating seed yield/plant (g), days to 50% flowering, plant height (cm), siliqua length (cm), days to maturity and no. of siliquae on main shoot as the principal characters. Genetic divergence analysis was performed on the basis of Discriminant analysis using Mahalanobis’ D2-statistic. Based on the relative magnitude of D2-values; 43 genotypes of Indian mustard were grouped into five clusters and plant height, main shoot length and no. of siliquae on main shoot contributed more towards the genetic divergence i.e. the best discriminatory characters for selection of diverse genotypes.
Genetic diversity, Principal Component, cluster distance, D2-value, cluster mean
