Multivariate genetic analyses unveil the complexity of grain yield and attributing traits diversity in Oryza sativa L. landraces from North-Eastern India

Abstract

In the North-Eastern region of India, rice stands as the predominant staple, with diverse cultivars evolving over the past six decades. This study systematically evaluated 20 rice landraces, analyzing eleven variables related to yield and its attributing traits. The aim was to identify promising genotypes for potential breeding programs and to ascertain the minimum number of components essential for explaining the total diversity. Among the eleven principal components (PCs) examined, four PCs exhibited eigenvalues surpassing 1.0, collectively contributing to 80.45% of the total variability in the traits. PC1, which explained 31.19% of the overall variance, was associated with plant height, days to 50% flowering, panicle length, grain breadth, and grain length-to-breadth ratio. Utilizing cluster analysis, the 20 rice landraces were categorized into seven distinct clusters. Maximum inter-cluster divergence was observed between clusters VI and I, as well as clusters VI and V, indicating greater genetic distinctiveness among genotypes in these clusters compared to others. Notably, rice landraces such as Borosolpana, Phougak, Satyaranjan, Kakcheng Phou, Moniram, Kanaklata, and Bahadur were identified as genetically divergent. These genotypes hold promise for generating segregating populations, serving as valuable source materials for targeted yield improvement through meticulous selection, as indicated by inter-cluster distances.