Legume Research - An International Journal
Web of Science
  • Year: 2015
  • Volume: 38
  • Issue: 6

Multivariate analysis in green gram [Vigna radiata (L.) Wilczek]

  • Author:
  • Suhel Mehandi, I.P. Singh1, Abhishek Bohra1, Chandra Mohan Singh2
  • Total Page Count: 5
  • Page Number: 758 to 762

1Crop Improvement Division, Indian Institute of Pulses Research, Kanpur-208 024, India

2Department of Plant Breeding and Genetics, Rajendra Agricultural University, Bihar, Pusa, (Samastipur)-848 125, India

Department of Genetics and Plant Breeding, Sam Higginbottom Institute of Agriculture, Technology and Sciences (Deemed to-be-University), Allahabad-211 007, India

*Corresponding author's e-mail: suhelgpb@gmail.com

Online published on 7 December, 2015.

Abstract

The present study was undertaken to perform the multivariate analysis in green gram using twenty-one green gram genotypes. The extent of genetic divergence revealed that these genotypes could be grouped into ten and five clusters, following Tochersand non-hierarchical Euclidian clustering methods, respectively. Basedon them aximumdiversity obtained in Tochers method genotype KM 10–1064 of cluster V and genotypes KM 10–1046, KM 10–1059 and KM 10–1070 of cluster VI were found suitable for improving the plant structure, whereas concerning high diversity along with high trait contribution towards total divergence, the clusters KM 10–1064 of cluster V and KM 10–1042 of cluster VIII were found to be appropriate for hybridization. The genotype KM 10–1068, which represents the mono genotypic cluster in case of both the clustering methods signifies that it could be the most diverse from other genotypes and it would be the suitable candidate for hybridization with genotypes present in other clusters to tailor the agriculturally important traits and ultimately, to enhance the seed yield in green gram.

Keywords

Euclidean clustering, Genetic divergence, Green gram, Principal Component Analysis