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Methods of multivariate data analysis applied to the investigation of fen soils
Authors:Regina Kalhne  Mohamed Amin  Joachim Sobottka  Robert Sauerbrey
Institution:

a Department of Soil Science, Faculty of Agriculture and Horticulture, Humboldt University of Berlin, Gruppe Nachwachsende Rohstoffe, Philippstr. 13, D-10099 Berlin, Germany

b Department of Soil Science, Faculty of Agriculture and Horticulture, Humboldt University of Berlin, Fachgebiet Ökologie der Ressourcennutzung, Invalidenstr. 42, D-10099 Berlin, Germany

Abstract:Fen soils from two sites of the Rhin-Havel-Luch, a peatland in the north-east of Germany, have been investigated. The samples have been collected in two horizons, representing different degrees of degradation and mineralisation of peat. Gravimetric measurements, energy dispersive X-ray fluorescence (EDXRF), elemental analysis, and 1H low resolution nuclear magnetic resonance (LR-NMR) of the fen soil samples have been performed. By multivariate analysis of all the experimental data, especially by the principal component analysis (PCA) and by the cluster analysis, respectively, it was possible to classify the fen soils, to identify their characteristic properties, to detect temporal and local variations, and to prove representative field sampling. Furthermore, the correlation between variables of the applied analytical methods could be interpreted in context to the composition of fen soils and mutual influences of their properties.
Keywords:Fen soils  Principal component analysis  Cluster analysis  Low resolution nuclear magnetic resonance  X-ray fluorescence analysis
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