Identifying residues in natural organic matter through spectral prediction and pattern matching of 2D NMR datasets

Abstract

This paper describes procedures for the generation of 2D NMR databases containing spectra predicted from chemical structures. These databases allow flexible searching via chemical structure, substructure or similarity of structure as well as spectral features. In this paper we use the biopolymer lignin as an example. Lignin is an important and relatively recalcitrant structural biopolymer present in the majority of plant biomass. We demonstrate how an accurate 2D NMR database of approximately 600 2D spectra of lignin fragments can be easily constructed, in approximately 2 days, and then subsequently show how some of these fragments can be identified in soil extracts through the use of various search tools and pattern recognition techniques. We demonstrate that once identified in one sample, similar residues are easily determined in other soil extracts. In theory, such an approach can be used for the analysis of any organic mixtures.