Using phytosterol as a target compound to identify edible animal fats adulterated with cooked oil

A study of the lipid profile of Coix seeds from four areas based on untargeted lipidomics combined with multivariate algorithms to enable tracing of their origin

The geographical traceability of food products is seen as a distinctive feature of the future of food which is increasingly becoming a concern for consumers. In this research, differences in the lipid composition of Coix seed samples from four major Chinese origins were investigated using non-targeted lipidomics. By multivariate statistical analysis, unsupervised PCA and OPLS-DA based differentiation between the four origins of Coix seed samples could be achieved. The OPLS-DA VIP > 1 screened 72 lipids out of 1211 lipids as potential markers to distinguish Coix seeds from different origins. In addition, the potential markers (SPH(d16:0), Cer(d18:2/20:0 + O) and PC(8:0e/8:0) were combined with statistical analysis algorithms to construct a discriminant function for rapid differentiation of Coix seed samples from different origins and a specific function for different origins with 100% discrimination accuracy. In general, a rapid and accurate method combining multivariate chemometrics and algorithms was developed based on untargeted lipidomics to determine the geographical origin of Coix seed samples, which can also be applied to other agricultural products.

Accurate quantification of TAGs to identify adulteration of edible oils by ultra-high performance liquid chromatography-quadrupole-time of flight-tandem mass spectrometry

Edible oils play important roles in biological functions, and triacylglycerols (TAGs) in edible oils are complex mixtures. This makes accurate TAGs quantitation quite difficult that bring economically motivated food adulteration. Herein, we demonstrated a strategy for accurate quantification of TAGs in edible oils, which could be applied in identification of olive oil adulteration. The results showed that the proposed strategy could significantly improve the accuracy of TAG content determination, reduce the relative error of fatty acids (FAs) content determination, and present a wider accurate quantitative range than that of gas chromatography-flame ionization detection. Most important, this strategy coupled with principal component analysis could be used to identify adulteration of high-priced olive oil with cheaper soybean oils, rapeseed oils or camellia oils at a lower concentration of 2%. These findings indicated that the proposed strategy could be regarded as a potential method for edible oils quality and authenticity analysis.

Diacylglycerols ions as novel marker indicators for the classification of edible oils using ultrahigh resolution mass spectrometry

Diacylglycerols (DAGs) ions, instead of triacylglycerols (TAGs) ions, were established as marker indicators for an improved classification of edible oils using ultrahigh resolution mass spectrometry (UHRMS). DAGs ions can be used not only to identify triacylglycerols (TAGs) and their embedded fatty acids (FAs), but also to distinguish positional isomers of TAGs. In this work, DAGs ions were determined in edible oils by direct infusion atmospheric pressure chemical ionization-ultrahigh resolution mass spectrometry (APCI-UHRMS), where the ultrahigh resolving power up to 500,000 FWHM (full width at half maximum) can provide accurate molecular compositions and detailed fingerprints MS spectra in a minute. A total of 146 samples belonging to 22 species of plant oils and animal fats, were characterized. Chemometric analyses were performed using principal component analysis, partial least square-discriminant analysis and orthogonal partial least squares-discriminant analysis. DAGs ions were proved to be better than TAGs ions as marker indicators in the chemometric analyses. An overall correct rate of 93.40% was achieved for the classification of tested samples. In addition, blend oils and gutter oils were also characterized by this developed method.