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Discrimination of Rice Products by Geographical Origins and Cultivars by Two‐Dimensional NMR Spectroscopy
Author(s) -
Chae Young Kee,
Kim Seol Hyun
Publication year - 2016
Publication title -
bulletin of the korean chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.237
H-Index - 59
ISSN - 1229-5949
DOI - 10.1002/bkcs.10914
Subject(s) - cultivar , metabolite , principal component analysis , metabolome , nuclear magnetic resonance spectroscopy , metabolomics , population , two dimensional nuclear magnetic resonance spectroscopy , spectroscopy , chemistry , microbiology and biotechnology , biology , nuclear magnetic resonance , botany , mathematics , physics , statistics , chromatography , biochemistry , demography , quantum mechanics , sociology
Rice is one of the most important crops that feed almost half of the world's population. With the increasing concern of consumers on the integrity of the product, efforts have been made to develop analytic techniques to discriminate rice products according to their origins or cultivars, but those efforts were mostly based on elemental analysis. We postulated that such discrimination would be possible with the global metabolite profiles. Nineteen metabolites of three different rice cultivars from four different geographical origins were identified from the extracts and compared with one another by the two‐dimensional nuclear magnetic resonance ( NMR ) spectroscopy. NMR data were analyzed with the help of the metabolome database and the statistics software. The different rice samples were successfully separated in the principal component space, showing that the global metabolite profiles can be used to discriminate geographic origins. Our results show that the metabolite analysis via 1 H– 13 C heteronuclear single quantum coherence spectra combined with the statistical method can be applied to discriminate the geographic origins or cultivars of rice samples, thus can provide a means to inspect and pick up fraudulent labeling or adulteration.