Dissecting genetic variability for yield components in wheat through multivariate analysis

Abstract

This study was aimed to evaluate genetic diversity, character associations, and multivariate structure among wheat genotypes to identify key traits for yield improvement. The analysis revealed that phenotypic variation marginally exceeded genotypic variation across traits, indicating a limited environmental influence on trait expression. Relatively higher variability was identified for number of tillers/plant,  while moderate for spike length, number of spikelets/ spike, number of grains /spike, biological yield  and grain yield/ plant and harvest index, suggesting greater scope for effective selection. High heritability in conjunction with substantial genetic advance was recorded for all major yield-contributing traits, reflecting the predominance of additive gene effects and their responsiveness to selection. Correlation indicates strong positive associations of grain yield with number of tillers /plant, spike length, number of spikelets/ spike, number of grains /spike, test weight biological yield, highlighting their importance as selection criteria. Principal component analysis demonstrated that first four principal components viz., PC1, PC2, PC3, PC4 accounted for a major proportion (69.20 %) of total variation, with the first component primarily representing yield-related traits. The biplot further confirmed strong positive clustering of yield-related traits, while phenological traits exhibited weak associations with yield. These findings suggest that improvement in yield can be achieved through the selection of genotypes possessing favorable yield contributing traits.