Classificatory Analysis in Little Millet Germplasm Collections of Odisha

Abstract

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