A New Challenge in Food Authenticity: Application of a Novel Mathematical Model for Rapid Quantification of Vegetable Oil Blends by Gas Chromatography - Mass Spectrometry (GC-MS)

The aim of this paper was to quantify individual oils in binary oil blends. Oil samples were prepared by blending different mass proportions of olive oil and high-oleic sunflower oil (Blend I), as well as flaxseed oil and sunflower oil (Blend II). The pure oil samples and simulated blends were analyzed by gas chromatography - mass spectrometry (GC-MS). Peak surface areas of prominent fatty acids were used to create a numerical matrix for further data processing. In order to estimate the exact content of individual oils in each blend, a novel mathematical model was developed and applied, without the application of multivariate statistics. The results of mathematical estimations were compared with theoretical values. Linear dependences were observed in both oil blends, with the R-2 > 0.993 and p < 10(-8). In general, the employed GC-MS method coupled to the proposed mathematical model gave accurate and reliable results. This study represents a meaningful approach for the authentication of vegetable oils in terms to quantify the individual oils in adulterated oil blends.