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.
INEPT Multivariate linear regression Triacylglycerol Olive oil Fatty acids Squalene
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N.M. acknowledges the financial support of the Lebanese National Council for Scientific Research and the Research Council of Saint-Joseph University. The CORSAIRE platform from Biogenouest is also acknowledged. The authors acknowledge Anne Ancelin for linguistic assistance.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
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