Biometrical Letters Vol. 54(1), 2017, pp. 43-59
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APPLICATION OF MULTIVARIATE STATISTICAL METHODS IN THE ASSESSMENT OF MOUNTAIN ORGANIC SOIL TRANSFORMATION IN THE CENTRAL SUDETES Bogna Zawieja1, Bartłomiej Glina2 1Department of Mathematical and Statistical Methods, Poznań University of Life Science, Wojska Polskiego 28, 60-637 Poznań, Poland; e-mail: bogna13@up.poznan.pl 2Department of Soil Science and Land Protection, Poznań University of Life Sciences, Poznań, Poland |
In studies of organic soil degradation and transformation, alongside the conventional methods used in soil science, an increase in the importance of advanced statistical methods can be observed. In this study some multivariate statistical methods were applied in an investigation of organic soil transformation in the central Sudetes. Andrews curves, linear and kernel discriminant variable analysis and cluster analysis were used. The similarities among peatland soils and their layers were determined. It can be stated that the application of statistical methods in soil science research related to organic soil transformation is a valuable tool. The use of various statistical methods (such as Andrews curves, linear and kernel discriminant variables and cluster analysis) can with high probability confirm earlier laboratory or field observations. This is particularly justified in the case of organic soils derived from varied geobotanical peat materials, different types of peatlands and water supply types, which impact the primary properties of the soil.
Andrews curves, degradation, kernel discriminant analysis, linear discriminant analysis, mountain peatlands
