Recently in European countries, control laboratories have revealed real cases of deceptive practices in which synthetic triacylglycerols (TAGs) were used for adulterating butterfat. The complex fat blends are difficult to detect with the classical methods of analysis, especially when the adulterating TAGs contain fatty acids (FAs) in the proportions similar to that of genuine butter. Nevertheless, because butyric acid (C4) exclusively occurs at the sn-3 position in milk fat TAGs, the determination of its distribution on the glycerol backbone provides a diagnostic indicator to differentiate genuine butter from mixtures with synthetic TAGs. Herein, we have demonstrated the straightforward application of mono-dimensional 13C NMR spectroscopy for detecting synthetic TAGs in mixtures with authentic butterfat. The method is based on the 13C NMR determination of the regioisomeric distribution of C4 between the sn-1,3- and sn-2-positions and boasts several analytical advantages, such as specificity, robustness and minimal sample handling. The limit of detection (LOD) and limit of quantification (LOQ) of the synthetic fats, estimated to be 1 and 2.5% w/w, respectively, easily surpass the limit of 10% at which a fraudulent practice might be economically attractive.
Practical applications We have developed a robust and efficient method, based on high resolution 13C NMR spectroscopy, for detecting the adulteration of butterfat with synthetic low- and medium-carbon number TAG mixtures. In milk fat TAGs, butyric acid is esterified exclusively at the sn-3 position of the glycerol backbone. Thus, the method relies on 13C NMR monitoring of the carbonyl resonance of butyric acid at the sn-2 glycerol position, which is diagnostic of synthetic or interesterified TAGs. The 13C NMR-based analysis overcomes the pitfalls of traditional pattern recognition methodologies for the assessment of butter authenticity, which can be ineffective when butter is adulterated with synthetic TAGs obtained from FA in proportions similar to those of natural milk fat. The method achieves reliable quantification up to 2.5% w/w of adulterating fats (LOQ) and can detect quantities as low as 1% w/w of synthetic TAGs blended with butter (LOD).