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Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 1344-1347 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 9 Number 11 (2020) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2020.911.158 Principal Component Analysis in Rabi Sorghum [Sorghum bicolor (L.) Moench] for Yield Attributing Traits Vaka Divya*, DPB. Jyothula, B. Vijaya lakshmi and Shaik Nafeez Umar Department of Genetics and Plant Breeding, Bapatla, Andhra pradesh, India *Corresponding author ABSTRACT Keywords Sorghum, Principal component analysis, Total variation Article Info Accepted: 12 October 2020 Available Online: 10 November 2020 An experiment was done to study the principal component analysis in rabi sorghum [Sorghum bicolor (L.) Moench] with a set of fifty genotypes of sorghum grown in Randomized Block Design with two replications for ten traits viz., days to 50% flowering, plant height (cm), total number of leaves per plant, leaf length (cm), leaf width(cm), ear head length(cm),ear head width(cm),100 grain weight(g), grain yield per plant(g) and harvest index(%). Principal component analysis revealed four principal components which explained about 68.60 % of variability. PC 1 loaded with 26.62 % maximum variability of total variation, PC 2 explained 17.76 % of total phenotypic variability and PC 3 had contributed 12.10 % and PC 4 loaded with 11.66% of total variation. Introduction Sorghum is the fifth most important cereal crop world-wide and it is grown for food and feed. Sorghum is the dietary staple for most of the developing countries. It is well adapted to the range of environmental conditions with high variability. Sorghum bicolor contains both cultivated and wild relative races, and it provides a substantial amount of genetic diversity for traits of agronomic importance to develop the crops different variety of interest for plant breeders. A better understanding of the genetic diversity in sorghum would greatly contribute to crop improvement with a view to food quality and other important agronomic traits. Therefore, there is a need to evaluate the available genotypes for genetic diversity and identify the best genotypes according to their performance. Materials and Methods Fifty germplasm lines were evaluated to study the genetic divergence analysis during rabi 2016-2017 at Agricultural college farm, Bapatla. The experiment was laid out in Randomized Block Design (RBD) with two replications. Spacing between row to row and plant to plant was kept 45cm and 15 cm respectively. Recommended package of practices were followed for raising a normal 1344 Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 1344-1347 crop. In each genotype 10 plants were selected and used for collecting data days to 50% flowering, plant height (cm), total number of leaves per plant, leaf length (cm), leaf width(cm), ear head length(cm), ear head width(cm),100 grain weight(g), grain yield per plant(g) and harvest index(%). The principal component analysis was carried out as suggested by Rao (1952) and was computed using the following formula: PCA PC1 = P £ 1 aj Xj Where; PC = Principal component, a1j = Linear coefficient – Eigen vectors Results and Discussion The analysis of variation revealed significant genetic diversity among the genotypes of sorghum for all the traits studied. Principal component analysis was performed in order to reduce a large set of phenotypic traits to a more meaningful smaller set of traits and to know which trait is contributing to maximum variability, because genetic improvement depends on the magnitude of genetic variation. Table.1 The eigen values, percent variability, cumulative percent variability for four principal components in sorghum [Sorghum bicolor (L) Moench] Eigen Value % Var. Exp. Cumulative total % variation Principal component 1 2.662 26.625 26.625 Principal Principal Principal component 2 component 3 component 4 1.777 1.211 1.166 17.766 12.107 11.660 44.391 56.498 68.158 Principal component 5 0.869 8.694 76.852 Table.2 Character loading of four principal components for different genotypes of sorghum [Sorghum bicolor (L) Moench] Character Days to 50% flowering Plant Height( cm) Leaves/ Plant Leaf Length (cm) Leaf Width( cm) Ear Head Length (cm) Ear Head Width (cm) Grain Yeild Per Plant (g) 100 grain Weight (g) Harvest Index (%) Principal component 1 0.205 Principal component 2 0.445 Principal component 3 0.136 Principal component 4 0.127 Principal component 5 0.295 0.340 0.166 0.157 -0.060 0.526 -0.428 -0.145 0.274 0.554 0.141 0.002 -0.583 -0.478 -0.212 -0.054 0.244 0.463 0.285 -0.278 -0.236 -0.288 -0.295 0.575 -0.486 -0.081 0.407 0.519 -0.066 0.082 -0.038 0.074 -0.210 -0.208 0.054 -0.115 0.076 0.264 -0.428 0.042 -0.185 0.570 -0.492 0.408 0.385 0.067 1345 Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 1344-1347 ig.1 Principal component analysis diagram for 50 sorghum genotypes Principal component analysis The four principal components explained about 68.60 % of total variation among genotypes of all traits (Nachimuthu et al., 2014) (Table 1 and Table 2). The first principal component (Fig. 1) obtained was 26.62% Ahmed et al., 2015of total variance and had high contributing factor loading from ear head length(cm) which was the most important contributing traits for relative magnitudes of eigen vectors for the first principal component, while the second principal component had high contributing factor loading from leaf width, which was 17.76 %, thirdly it had a high contributing factor from harvest index for the third principal component (12.107 %), and, finally it had a high contributing factor loading from number of leaves for plant for the fourth principal component (11.66 %).Similar results were also reported by Ganesamurthy et al., 2010, vara Prasad et al., 2019 Jain and Patel (2016). References Ahamed, K.U., Akhter, B., Islam, M.R., Alam, M.K., and Hossain., M.M. (2015). An assessment of genetic diversity in sorghum (Sorghum bicolor L. Moench) germplasm. Bull. Inst. Trop. Agr., Kyushu Univ., 38: 47-54. Ganesamurthy K, Punitha D, Elangovan M. (2010). Genetic diversity among the land races of sorghum collected in Tamil Nadu. Electron J Plant Breed 1:1375– 1379. Jain, S. K. and P. R. Patel. (2016). Principal component and cluster analysis in sorghum (Sorghum bicolor (l.) Moench) Forage Res.,42 (2): pp. 90- 95. Nachimuthu, V. V., Robin, S., Sudhakar, D., Raveendran, M., Rajeswari, S., and Manonmani, S. (2014). Evaluation of rice genetic diversity and variability in a population panel by principal component analysis. Indian J. Sci. Technol., 10: 1555- 1562. Rao, C. R. (1952). Advanced statistical methods in biometrical research. John Wiley and Sons Inc., New York. Pp. 236272. Vara Prasad, B. V. and Sridhar, V. (2019). Diversity Studies in Yellow Pericarp Sorghum [Sorghum bicolor (L.) Moench] Genotypes for Yield Attributes. Int.J.Curr.Microbiol.App.Sci. 8(12): 361366. 1346 Int.J.Curr.Microbiol.App.Sci (2020) 9(11): 1344-1347 How to cite this article: Vaka Divya, DPB. Jyothula, B. Vijaya lakshmi and Shaik Nafeez Umar. 2020. Principal Component Analysis in Rabi Sorghum [Sorghum bicolor (L.) Moench] for Yield Attributing Traits. Int.J.Curr.Microbiol.App.Sci. 9(11): 1344-1347. doi: https://doi.org/10.20546/ijcmas.2020.911.158 1347