| Literature DB >> 27761615 |
Noelle Merchak1,2, Virginie Silvestre2, Denis Loquet2, Toufic Rizk1, Serge Akoka2, Joseph Bejjani3.
Abstract
Triacylglycerols, which are quasi-universal components of food matrices, consist of complex mixtures of molecules. Their site-specific 13C content, their fatty acid profile, and their position on the glycerol moiety may significantly vary with the geographical, botanical, or animal origin of the sample. Such variables are valuable tracers for food authentication issues. The main objective of this work was to develop a new method based on a rapid and precise 13C-NMR spectroscopy (using a polarization transfer technique) coupled with multivariate linear regression analyses in order to quantify the whole set of individual fatty acids within triacylglycerols. In this respect, olive oil samples were analyzed by means of both adiabatic 13C-INEPT sequence and gas chromatography (GC). For each fatty acid within the studied matrix and for squalene as well, a multivariate prediction model was constructed using the deconvoluted peak areas of 13C-INEPT spectra as predictors, and the data obtained by GC as response variables. This 13C-NMR-based strategy, tested on olive oil, could serve as an alternative to the gas chromatographic quantification of individual fatty acids in other matrices, while providing additional compositional and isotopic information. Graphical abstract A strategy based on the multivariate linear regression of variables obtained by a rapid 13C-NMR technique was developed for the quantification of individual fatty acids within triacylglycerol matrices. The conceived strategy was tested on olive oil.Entities:
Keywords: Fatty acids; INEPT; Multivariate linear regression; Olive oil; Squalene; Triacylglycerol
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Year: 2016 PMID: 27761615 DOI: 10.1007/s00216-016-0005-z
Source DB: PubMed Journal: Anal Bioanal Chem ISSN: 1618-2642 Impact factor: 4.142