International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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Original Research Articles                      Volume : 10, Issue:1, January, 2021

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : /
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2021.10(1): 3114-3123

Characterization of Environmental Covariates of Coimbatore District using Principal Component Analysis
Priyadharshini1, M. Radha*, R. Kumaraperumal2,G.Vanitha3 and Balaji Kannan4
1Agricultural Statistics, 2Remote Sensing & GIS, 3Computer Science, 4Soil and Water Conservation Engineering, Tamil Nadu Agricultural University, Coimbatore, India
*Corresponding author

The principal component analysis (PCA) is used to identify the most influencing variable. It is one of the statistical techniques for reducing the dimension of the data. The study was conducted in Coimbatore district, Tamil Nadu with 340 profile points. More than 30 environmental covariates are available for this analysis. To make the analysis easier and accurate the data has to be reduced. The principal components (PC1, PC2, PC3 and PC4) are selected for further analysis which accounts for 53.84% of variation. From the selected four principal components the variables which are having higher percentage of variation were identified. Hence it is one of the easiest methods to predict the most influencing variable using R software.

Keywords: Principal component analysis (PCA), Eigenvalues, Eigenvectors, correlation plot

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How to cite this article:

Priyadharshini, R., M. Radha, R. Kumaraperumal, Tmt.G.Vanitha and Balaji Kannan. 2021. Characterization of Environmental Covariates of Coimbatore District using Principal Component Analysis.Int.J.Curr.Microbiol.App.Sci. 10(1): 3114-3123. doi:
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.