Vol. 12, Issue 7 (2023)

Author(s):
Bhagyasri Majhi and Sonali Kar

Abstract:
Multivariate analysis has been used frequently for genetic diversity analysis in rice by plant breeders which aids in study the characteristics of the genotypes separately and make a trade-off among the characteristics to arrive most suitable variety. The current study was held on 64 rice genotypes including 4 checks at Instructional cum Research Farm, Section of Genetics and Plant Breeding, S. G. College of Agriculture and Research Station, Jagdalpur during kharif 2022. In order to evaluate genetic diversity as well as character associations, 17 yield-attributing traits among genotypes were exposed to a multivariate analytic method called cluster analysis. ANOVA revealed that all characters under study were significant for variability. Using hierarchical cluster analysis, the dendrogram divided 64 rice genotypes into seven clusters. Cluster V recorded greatest intra-cluster distance recorded, while clusters V and IV recorded greatest inter-cluster distance. Cluster IV with 3 genotypes, viz., BNKR 121, MSN-119 and KHP-14 exhibited highest mean performance for grain yield followed by days to 50% flowering, plant height, flag leaf length and flag leaf width. The most genotypes were included in Cluster VII, which also had the highest cluster means for harvest index, grain width, and kernel width. As a result, genotypes grouped in clusters IV and VII with high yield potentiality should be prioritized. These genotypes were found to suitable genotypes for lowland ecology. Further, these promising genotypes could be recommended for varietal development.