Principal component analysis of yield and yield related traits in rice (Oryza sativa L.) landraces
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.
Key words: principal component analysis, rice landraces, genetic diversity
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