Milk fat is characterized by its unique composition, particularly its high content of short- and medium-chain fatty acids (FAs), which sets it apart from other fats and oils. The standard method for accurately determining the fatty acid profile (FAP) of milk and dairy products—gas chromatography (GC)—is both time-consuming and involves the use of hazardous chemicals, typically requiring nearly two hours per sample even with a skilled operator. As a result, there is a growing interest in faster, alternative techniques. In recent years, spectroscopic methods, such as NMR, combined with multivariate data analysis have gained attention due to their significantly quicker turnaround and more user-friendly procedures.

This study examined the limitations of the current method used to determine the fatty acid profile of oils and fats using nuclear magnetic resonance (¹H- and ¹³C- NMR) spectroscopy. According to the literature, in the case of dairy fats, the signal at 0.96 ppm originates both from the butyric acid moiety and n-3 fatty acids like linolenic acid (C18:3). As a result, the widely accepted NMR-based method for profiling fatty acids in fats is unreliable for detecting adulterationin dairy products. It risks misidentifying linolenic acid as butyric acid, which can lead to adulterated samples being incorrectly classified as genuine milk fats. As an alternative, we propose new descriptors based on the integral ratios of signals corresponding to CH₂ groups relative to those associated with butyric and n-3 fatty acids. These new markers offer a more reliable approach for identifying adulterated dairy products.

Acknowledgement:

This work was supported by a grant of the Ministry of Research, Innovation and Digitalization, CNCS-UEFISCDI, project number PN-IV-P2-2.1-TE-2023-0756, within PNCDI IV.