Multivariate analysis based prediction of phenotypic diversity associated with yield and yield component traits in germplasm lines of rice (Oryza sativa L.)
DOI: 10.37992/2022.1303.129
Abstract
An investigation was conducted with 217 germplasm lines of rice to estimate potential variation among rice genotypes. Multivariate analyses viz., PCA and cluster analysis to assess genetic diversity were performed on seven agronomic traits. For the evaluated traits in the lines of germplasm, box plots and normal probability plots displayed substantial estimates of variability. PCA showed that PC1 and PC2 represented 46.15 per cent of variation. PC1 was responsible for the most variance (24%) for four characters, followed by PC2 (22.15%) for three parameters. Filled grain number per panicle, single plant yield, plant height and thousand grain weight were identified as vital traits contributing to variability. Based on agglomerative hierarchical cluster analysis, the germplasm lines were grouped into five clusters, which explained a lot of variation in the traits. The study identified that plant height and 1000 grain weight have the greatest impact on variation. The genotypes viz., WGL 1063, RNR 26085, OR 2511-3, Swarna, KNM 7123, WGL 1063, MGD-101, IVT MS-6130, IVT IM-4231, IVT IME-3948 and IVT NPT-6303 were found to be the best performing genotypes for the traits panicle length, plant height and single plant yield, which can be used in hybridisation programme to improve these traits.
Keywords: Rice, Box plot, diversity, germplasm, principal components and variability
Multivariate analysis based prediction of phenotypic diversity associated with yield and yield component traits in germplasm lines of rice Oryza sativa L.
. 2022. Electronic Journal of Plant Breeding, 13 3, 764-771. Retrieved from https://ejplantbreeding.org/index.php/EJPB/article/view/4257It is certified that:
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