Molecular composition and chemometric differentiation and classification of soil organic matter in Podzol B-horizons

Whole soils from nine different Podzol B-horizons were analysed by wet-chemistry, solid-state cross-polarization/magic-angle spinning (CPMAS) C-13-NMR spectroscopy and pyrolysis-field ionization mass spectrometry (Py-FIMS). The wet-chemical analyses referred to site-specific contents of polysaccharides, lipids, lignins, fulvic acids, humic acids and humins in the organic matter of each horizon. All CPMAS C-13-NMR spectra for soils were characterized by intense signals from O-alkyl carbon and alkyl carbon. Aryl carbon and carboxyl carbon were less abundant. Correspondingly, the Py-FIMS spectra were dominated by signals from carbohydrates and lipids, especially sterols such as ethylcholestapentaene, ethylcholestatetraene, dehydroergosterol, ergosterol, stigmasterol, taraxerone and a-tocopherol. Lower relative abundances were registered for lignins and alkylaromatics. Both intact and microbially altered lignins accumulated in the B-horizons. Temperature-resolved Py-FIMS enabled two organic matter pools with different thermal stability to be detected. The thermolabile pool (evolution under 450 degrees C) consists mainly of carbohydrates, sterols and N-containing compounds, whereas the thermostable pool (evolution above 450 degrees C) is largely made up of condensed lignins, lipids and alkylaromatics. To visualize differences and/or similarities between the nine Podzol B-horizons according to their organic matter composition, the data sets obtained by wet-chemistry, CPMAS C-13-NMR spectroscopy and Py-FIMS were evaluated by chemometric methods. Using principal component analysis (PCA), neither the wet-chemical data nor the C-13-NMR spectra enabled the Podzol B-horizons to be classified according to vegetation or Podzol type. In contrast, PCA of 200 FISHER-weighted Py-FIMS signals clearly separated the B-horizons according to the composition of SOM. Soils with weak Podzol features are characterized mainly by signals from carbohydrates, phenols/lignin monomers, fatty acids, and constituents of plant waxes (e.g., nonacosanedione, nonacosanediol). Haplic Podzols show strong signals from lignin dimers, long-chain lipids and sterols. The results obtained by cluster analysis (CA) of the 200 FISHER-weighted Py-FIMS signals were visually well correlated with those derived from PCB. Both chemometric techniques enabled the classification of the nine Podzol B-horizons according to their degree of podzolization.