Principal Component Analysis for the Characterization in the Application of Some Soil Properties
Commenced in January 2007
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Principal Component Analysis for the Characterization in the Application of Some Soil Properties

Authors: Kamolchanok Panishkan, Kanokporn Swangjang, Natdhera Sanmanee, Daoroong Sungthong

Abstract:

The objective of this research is to study principal component analysis for classification of 67 soil samples collected from different agricultural areas in the western part of Thailand. Six soil properties were measured on the soil samples and are used as original variables. Principal component analysis is applied to reduce the number of original variables. A model based on the first two principal components accounts for 72.24% of total variance. Score plots of first two principal components were used to map with agricultural areas divided into horticulture, field crops and wetland. The results showed some relationships between soil properties and agricultural areas. PCA was shown to be a useful tool for agricultural areas classification based on soil properties.

Keywords: soil organic matter, soil properties, classification, principal components

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058231

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References:


[1] Boruvka L., Vacek O. and Jehlicka J., 2005. Principal component analysis as a tool to indicative the origin of potentially toxic elements in soils. Geoderma 2005;128, pp.289-300.
[2] Dragovic S. and Onjia A. Classification of soil samples according to their geographic origin using gamma-ray spectrometry and principle component analysis. Journal of Environmental Radioactivity 2006; 89, pp.150-158.
[3] Sousa S.I.V., Fernando G. Matins, Maria C. Alvim-Ferra, and Maria C. Pereira. "Multiple linear regression and artificial neural networks based on principal component to predict ozone concentrations." Environmental Modelling & Software 22, 1 (January 2007), pp.97-103.
[4] Mico C., Recatala L., Peris M. and Sanchez J. Assessing heavy metal sources in agricultural soil of an European Mediteranean area by multivariate analysis. Chemoshere 2006; 65, pp.863-872.
[5] Jolliffe I.T. Principal component analysis. Springer-verlag, Newyork.1986.