Legume Research - An International Journal
Web of Science
  • Year: 2020
  • Volume: 43
  • Issue: 2

Preliminary morphological characterization and evaluation of selected Bambara groundnut [Vigna subterranea (L.) Verdc.] genotypes for yield and yield related traits

  • Author:
  • M.S. Mohammed1,, H.A. Shimelis2, M.D. Laing2
  • Total Page Count: 8
  • Page Number: 157 to 164

1Department of Plant Science, Institute for Agricultural Research Samaru, Faculty of Agriculture, Ahmadu Bello University, Zaria, Nigeria

2School of Agricultural, Earth and Environmental Sciences, African Center for Crop Improvement University of KwaZulu-Natal, South Africa

*Corresponding Author: M.S. Mohammed, Department of Plant Science, Institute for Agricultural Research Samaru, Faculty of Agriculture, Ahmadu Bello University, Zaria, Nigeria. Email: sagir007@gmail.com

Online published on 23 May, 2020.

Abstract

Forty nine (49) Bambara groundnut genotypes derived from single plant selection of diverse origin were evaluated for yield and yield components using 26 yield and yield related traits. Highly significant (P>0.001) differences were detected among the genotypes for canopy spread, petiole length, weight of biomass, seed weight and seed height, while seedling emergence, pod weight, seed length and seed width were significantly different (P>0.05). Principal component analysis identified nine influential components whereby PC1 and PC2 highly contributed to the total variation at 19% and 14%, respectively. Leaf colour at emergence, petiole colour, leaf joint pigmentation and calyx colour were highly correlated with PC1, while seed length, seed width and seed height had strong association with PC2. Both the principal component and cluster analyses displayed common association among most of the genotypes for agronomic and seed yield traits. Genotypes that showed high seed yield performance and greater biomass production can be tested for large-scale production, breeding or germplasm conservation.

Keywords

Cluster analysis, Germplasm, Principal component analysis, True-to-type