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Multivariate analysis of CPMAS 13 C‐NMR spectra of soils and humic matter as a tool to evaluate organic carbon quality in natural systems
Author(s) -
ŠMejkalová D.,
Spaccini R.,
Piccolo A.
Publication year - 2008
Publication title -
european journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 1351-0754
DOI - 10.1111/j.1365-2389.2007.01005.x
Subject(s) - soil water , principal component analysis , chemistry , soil organic matter , humic acid , nmr spectra database , carbon 13 nmr , organic matter , multivariate statistics , soil test , carbon fibers , linear discriminant analysis , spectral line , natural organic matter , total organic carbon , environmental chemistry , analytical chemistry (journal) , soil science , environmental science , mathematics , organic chemistry , statistics , fertilizer , physics , algorithm , astronomy , composite number
Summary A series of humic and fulvic acids isolated from different sources, size‐fractions separated from a humic acid, and three soils of different origin were subjected to CPMAS 13 C‐NMR spectroscopy to obtain the distribution of their carbon contents. The relative areas of chemical shift regions in NMR spectra were used to apply a principal component analysis (PCA) to the three sets of samples. The multivariate analysis was successful in efficiently differentiating samples on the basis of the quality of their organic carbon content. The PC biplots based on two principal components distinguished objectively among samples as accurately as it was possible to do by subjective qualitative evaluation of the original spectra. In the case of the soils, a discriminant analysis (DA) was applied to build a classification model that allowed the validation of the three soils according to their origin. Percentage of validation in the classification model is expected to increase when a large number of NMR spectra are accumulated and/or the concentration of organic carbon in samples is enhanced. The multivariate analyses described are likely to become a useful tool to increase the importance of CPMAS 13 C‐NMR spectra in the appraisal of natural organic matter variations in heterogeneous natural systems.