Although many studies indicate that the qualitative and quantitative interpretation of the mass spectra of humic substances (HS) is frequently very difficult, recent studies have demonstrated that the use of sophisticated statistical tools, such as principal components analysis (PCA) or multilayer neural networks, could permit the adequate classification of humic samples as a function of their origin and sampling places (1).
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