| Literature DB >> 22989016 |
Feifei Wei1, Kazuo Furihata, Masanori Koda, Fangyu Hu, Rieko Kato, Takuya Miyakawa, Masaru Tanokura.
Abstract
(13)C NMR-based metabolomics was demonstrated as a useful tool for distinguishing the species and origins of green coffee bean samples of arabica and robusta from six different geographic regions. By the application of information on (13)C signal assignment, significantly different levels of 14 metabolites of green coffee beans were identified in the classifications, including sucrose, caffeine, chlorogenic acids, choline, amino acids, organic acids, and trigonelline, as captured by multivariate analytical models. These studies demonstrate that the species and geographical origin can be quickly discriminated by evaluating the major metabolites of green coffee beans quantitatively using (13)C NMR-based metabolite profiling.Entities:
Mesh:
Substances:
Year: 2012 PMID: 22989016 DOI: 10.1021/jf3033057
Source DB: PubMed Journal: J Agric Food Chem ISSN: 0021-8561 Impact factor: 5.279