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United States Department of Agriculture

Agricultural Research Service

Research Project: DRYLAND CROPPING SYSTEMS MANAGEMENT FOR THE CENTRAL GREAT PLAINS

Location: Central Plains Resources Management Research

Title: Pyrolysis-Molecular Beam Mass Spectrometry to Characterize Soil Organic Matter Composition in Chemically Isolated Fractions from Differing Land Uses

Authors
item Plante, Alain - UNIV OF PENNSYLVANIA
item Magrini-Bair, Kim - UNIV OF PENNSYLVANIA
item Vigil, Merle
item Eldor, Paul - RETIRED

Submitted to: Biogeochemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 31, 2008
Publication Date: July 31, 2008
Citation: Plante, A.F., Magrini-Bair, K., Vigil, M.F., Eldor, P. 2008. Pyrolysis-Molecular Beam Mass Spectrometry to Characterize Soil Organic Matter Composition in Chemically Isolated Fractions from Differing Land Uses. Biogeochemistry. DOI 10.1007/s10533-008-9218-3.

Interpretive Summary: Pyrolysis Molecular Beam Mass Spectroscopy (py-MBMS) is an emerging laboratory-instrumentation technology for analyzing soils and other heterogeneous materials. In this research, py-MBMS was used to characterize the soil organic matter (SOM) and humus fractions of two soils in the USA. The soils were collected under different management regimes (native vegetation (range and forest), and cultivated farm land). Using py-MBMS, the whole soil and SOM fractions of these soils were characterized and we found separations in the characterizations that were related to long-term soil management and SOM chemical composition. Signal intensities from individual spectra generated in the py-MBMS analysis were interpreted using principal component analysis (PCA). That analysis indicated that py-MBMS can be used to specifically characterize SOM in chemically isolated fractions. Further experimentation, utilizing a range of internal standards, with more attention to the effects of different types and levels of mineral interferences, and better resolution of higher m/z materials, should allow a better quantification of generated spectral data and verification of peak identities. The large wealth of data obtained and the large throughput of samples in py-MBMS has convinced us that this is a powerful tool (when used in combination with biological, chemical, physical and soil surface interactions) to understand the controls on the dynamics of SOM.

Technical Abstract: Questions concerning the role of soil organic matter (SOM) in soil fertility, ecosystem functioning and global change requires knowledge of the controls on SOM stabilization and their interactions. Pyrolysis molecular beam mass spectrometry (py-MBMS) provides a powerful and rapid means of characterizing the biochemical composition of SOM. Chemical fractionation is frequently used to isolate homogeneous SOM components. However, the actual composition of the fractions remains unknown. In this study, we characterized the biochemical SOM composition of two soils from the USA, under contrasting land uses: cultivated agriculture and native vegetation. Bulk soils, as well as chemically isolated SOM fractions (humic acid, humin and non-acid hydrolysable), were analyzed using py-MBMS. Principal components analysis (PCA) showed distinct differences in the SOM composition of isolated fractions. Py-MBMS spectra and PCA loadings were dominated by low molecular weight fragments associated with peptides and other N-containing compounds. Results suggest that SOM composition was similar in native whole-soil samples, and that cultivation increased heterogeneity. A semi-quantitative approach based on previously published data on marker signals also suggests the importance of peptides in distinguishing samples. While the semi-quantitative approach described here represents significant progress in the characterization of changing SOM composition, a truly quantitative analysis might only be achieved using multiple internal standards and by correcting for inorganic interference during py-MBMS analysis. Overall, we have provided proof of principle that py-MBMS can be a powerful tool to understand the controls on SOM dynamics.

Last Modified: 10/1/2014