March 30, 2003, Savannah, GA, USA, ACD/Labs ENC Seminar

Identifying Residues in Natural Organic Matter through Spectral Prediction and Pattern Matching of 2-D datasets

Andre J. Simpson, Myrna Simpson, Brent Lefebvre, Arvin Moser, Antony Williams, Sergey Golotvin, Mikhail Kvasha, William L. Kingery, Brian Kelleher

Abstract

Humic substances (HS) in soils, sediments, and waters, the most abundant naturally occurring organic molecules on the Earth, are central to biodiversity, water quality, and sustainable food production. Mapping their chemical structures and organization, which define the nature of this reactivity, represents a major challenge to contemporary analytical science. It has become common practice to extract soils, mostly with a strong base (sodium hydroxide), to yield an organic extract. Multidimensional solution state NMR has proved a very versatile and powerful technique for the study of these extracts. However, the interpretation of the complex data sets can be very daunting. Here we demonstrate that the process of interpretation can be made simpler and less time consuming through the construction of searchable 2-D NMR databases. We show that lignin derived aromatic compounds can be identified as the major aromatic structures in a soil extract, and then demonstrate how these assignments are subsequently useful for extracting information from other soil extracts. Without the aid of ACD/Labs software such assignments would be virtually impossible.

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