1Department of Plant Breeding & Genetics, College of Agriculture, Orissa University of Agriculture & Technology, (OUAT), Bhubaneswar-751003, Odisha
2Directorate of Research on Women in Agriculture, Bhubaneswar-751003, Odisha
3Department of Plant Breeding & Genetics, OUAT, Bhubaneswar-751003, Odisha
*Author for Correspondence: E-mail: laxminrcwa@yahoo.co.in
Online published on 17 November, 2012.
Twenty two genotypes of little millet (Panicum sumatrense Roth.) were evaluated under 12 environments. Data on 14 metric traits including grain yield were analysed to classify the entries into different groups following four methods of multivariate analysis. The genotypes were grouped into different clusters following D2 analysis, canonical analysis, metroglyph analysis and numerical classificatory analysis. Clustering pattern in different methods indicated that the test genotypes were grouped into three clusters following D2 analysis as well as canonical analysis, while they were divided into five groups in metroglyph analysis. Following the UPGMA method of numerical taxonomic approach, the genotypes were grouped into four, five and eight clusters at 75%, 80% and 85% phenon levels, respectively. The study of clusters formed by different methods indicated that the metroglyph analysis was easy and simple, and useful method of initial grouping for large number of collections. But the numerical taxonomic approach for classification of the biological populations is more potent in comparison to other methods to distinctly discriminate the genotypes for their use in recombination breeding.
Canonical, D2 static, Little millet, Metroglyph and numerical classificatory analysis, Multivariate analysis, Panicum sumatrense
