Electronic Journal of Plant Breeding

Open Access
SCOPUS
  • Year: 2021
  • Volume: 12
  • Issue: 3

Principal component analysis of yield and yield related traits in rice (Oryza sativa L.) landraces

  • Author:
  • G. Raiza Christina*, T. Thirumurugan, P. Jeyaprakash, V. Rajanbabu
  • Total Page Count: 5
  • Page Number: 907 to 911

Department of Plant Breeding and Genetics, Anbil Dharmalingam Agricultural College and Research Institute, Trichy-620 027, Tamil Nadu, India

*E-Mail: raizachrist1997@gmail.com

Online published on 30 October, 2021.

Abstract

A total of 49 rice landraces were investigated for eight traits using principal component analysis (PCA) for the determination of variation pattern, the relationship among genotypes and its traits. Out of eight principal components (PC), three PC's exhibited Eigenvalue more than one with 72.9 per cent of total variability among the characters. The highest positive Eigenvalue observed for the number of productive tillers per plant (0.148) and flag leaf length (0.148) in PC1 indicated their pronounced effect in the overall variation of the genotypes. The study revealed the traits that are contributing maximum for the variation. Hence, selective rice landraces can be utilized for improving these traits in high yielding cultivars through suitable breeding programmes.

Keywords

Principal component analysis, Rice landraces, Genetic diversity