International Journal of Chemical Studies
Vol. 5, Issue 4 (2017)
Characterization of rice (Oryza sativa L.) genotypes using principal component analysis including scree plot & rotated component matrix
Author(s): Lokesh Gour, SB Maurya, GK Koutu, SK Singh, SS Shukla and DK Mishra
Abstract: Total 83 rice genotypes comprising traditional landraces and released varieties from JNKVV was evaluated for 33 quantitative and quality traits by principal component analysis for determining the pattern of variation, relationship among individuals and their characteristics. Principal component analysis was utilized to examine the variation and to estimate the relative contribution of various traits for total variability. The PC1 showed 18.683%, while, PC2, PC3, PC4, and PC5 exhibited 15.404%, 13.401%, 9.433%, 8.037%, and 5.232% variability. Rotated component matrix revealed that PC3 accounts for yield & yield attributing traits. PC1 was also dominated by yield related traits. The PC2, PC4 & PC5 was dominated by quality traits.It can be observed that scoring germplasm R 304, Mahamaya, R-710, R-435, IR 64, Lakna, ShriRam, Rani Kajar, Surajone and Safari-17 comes in different principal component which has relation with yield and quality attributing trait both. Sugandha-2 comes in PC2, PC4 & PC5 which all related quality aspect. Thus the results of principal component analysis used in the study have revealed the traits contributing for the variation were identified. Resulting germplasm of that study will be greater beneficial to identify the parents for improving various yield and quality attributes with early maturity variety development.
Pages: 975-983 | 504 Views 27 Downloads
How to cite this article:
Lokesh Gour, SB Maurya, GK Koutu, SK Singh, SS Shukla, DK Mishra. Characterization of rice (Oryza sativa L.) genotypes using principal component analysis including scree plot & rotated component matrix. Int J Chem Stud 2017;5(4):975-983.