Principal component analysis for yield and its contributing traits in rice germplasm (Oryza sativa L.)
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Date
2020-12
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Sher-e-Kashmir University of Agricultural Sciences and Technology Jammu, J&K
Abstract
Present study entitled, “Principal component analysis for yield and its contributing traits in rice germplasm (Oryza sativa L.)” was carried out during Kharif 2019 at Experimental Area of Division of Plant Breeding and Genetics with an aim to assess genetic variation among rice germplasm lines employing multivariate biometrical approach viz., Principal Component Analysis. 155 rice germplasm lines along with three checks were evaluated in Augmented Block Design with a plot size of 1.6 m2 (4 rows of 2 m length) with a spacing of 20 x 15 cm.
Analysis of variance indicated the presence of sufficient genetic variation among rice germplasm lines, while estimates of components of variation revealed maximum contribution of genotypic variance to the phenotypic variance suggesting its exploitation through selection and hybridization. Simultaneously, correlation estimates revealed significant positive association of grain yield with panicle length, 1000 grain weight and grain length indicating suitability of these traits for indirect selection.
Prior to Principal Component Analysis D2 statistics grouped germplasm lines into sixteen clusters and among these cluster I consists of 67 germplasm lines forming the largest cluster followed by cluster III (26 lines), cluster II (18 lines), cluster IV (15 lines), cluster V (13 lines), cluster VI (5 lines), cluster VIII (3 lines), cluster VII and cluster IX (2 lines each), while clusters X, XI, XII, XIII, XIV, XV, XVI (1 line each). Inter cluster distances were found to be higher than intra cluster distances and maximum inter cluster distance was observed between cluster IX and VI (73.47) followed by cluster IX and X (73.14).
Principal Component Analysis transformed eleven interrelated variables into four major principal components having eigen value of more than 1 thereby, indicating that these components were responsible for higher magnitude of variance in the population (76.60 per cent). Among these principal components first component accounted for 32.80 per cent of the total variation while, the second, third and fourth component explained 18.50 per cent, 13.90 per cent and 11.40 per cent of total variation, respectively. Factor loadings of the principal components revealed that principal component 1 had high positive loadings for grain length, panicle length, length/breadth ratio, 1000 grain weight and plant height whereas, principal component 2 had high positive loadings for total number of tillers per plant and number of effective tillers per plant indicating that the first two principal factors can be collectively designated as yield attributing factors. Principal component 3 had high positive loadings for grain breadth, 1000 grain weight and plant height whereas, principal component 4 had high positive loading for 1000 grain weight, days to maturity and days to 50 per cent flowering. PCA biplots revealed that germplasm lines viz., GPL-1, GPL-4, GPL-131, GPL-128, GPL-20, GPL-127, GPL-135, GPL-100, GPL-130 were found to be superior performers for desirable traits and can be used as parents in hybridization programme.
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Preferred for your work. Choudhary, M. 2020. Principal component analysis for yield and its contributing traits in rice germplasm (Oryza sativa L.). M.Sc. thesis, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, India.