{"title":"Principal Component Analysis for the Characterization in the Application of Some Soil Properties","authors":"Kamolchanok Panishkan, Kanokporn Swangjang, Natdhera Sanmanee, Daoroong Sungthong","volume":65,"journal":"International Journal of Environmental and Ecological Engineering","pagesStart":279,"pagesEnd":282,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/2959","abstract":"The objective of this research is to study principal\ncomponent analysis for classification of 67 soil samples collected from\ndifferent agricultural areas in the western part of Thailand. Six soil\nproperties were measured on the soil samples and are used as original\nvariables. Principal component analysis is applied to reduce the\nnumber of original variables. A model based on the first two\nprincipal components accounts for 72.24% of total variance. Score\nplots of first two principal components were used to map with\nagricultural areas divided into horticulture, field crops and wetland.\nThe results showed some relationships between soil properties and\nagricultural areas. PCA was shown to be a useful tool for agricultural\nareas classification based on soil properties.","references":"[1] Boruvka L., Vacek O. and Jehlicka J., 2005. Principal component\nanalysis as a tool to indicative the origin of potentially toxic elements in\nsoils. Geoderma 2005;128, pp.289-300.\n[2] Dragovic S. and Onjia A. Classification of soil samples according to\ntheir geographic origin using gamma-ray spectrometry and principle\ncomponent analysis. Journal of Environmental Radioactivity 2006; 89,\npp.150-158.\n[3] Sousa S.I.V., Fernando G. Matins, Maria C. Alvim-Ferra, and Maria C.\nPereira. \"Multiple linear regression and artificial neural networks based\non principal component to predict ozone concentrations.\"\nEnvironmental Modelling & Software 22, 1 (January 2007), pp.97-103.\n[4] Mico C., Recatala L., Peris M. and Sanchez J. Assessing heavy metal\nsources in agricultural soil of an European Mediteranean area by\nmultivariate analysis. Chemoshere 2006; 65, pp.863-872.\n[5] Jolliffe I.T. Principal component analysis. Springer-verlag,\nNewyork.1986.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 65, 2012"}