Detection of Milk Fat Adulteration by Linear Discriminant Analysis of Fatty Acid Data

Abstract

Abstract Analysis of the fatty acid (FA) profile of milk fat (MF) by gas-liquid chromatography is widely used to detect adulteration with foreign fats. On the basis of the FA spectra of 352 genuine Austrian MF samples collected over a 4-year period, the effectiveness of concentration ranges of the major FA of MF and of certain FA ratios to identify non-MF/MF mixtures was tested. FA ratios proved useful for the detection of coconut fat in MF and admixture of vegetable oils rich in linoleic acid down to a level of 2%. This approach failed to identify non-MF/MF blends containing beef tallow, lard, olive oil, or palm oil at a level less than 10% commingling. Linear discriminant analysis applied to FA data was successful in distinguishing pure MFfrom adulterated MF. Computer-simulated data were used to derive the discriminant functions. Saturated and un-saturated FA with 18 C atoms were the most useful discriminating variables selected by a stepwise variable selection procedure. More than 95% of a data set composed of pure MF, and non-MF/MF blends containing 3% of either tallow, lard, olive oil, or palm oil were correctly classified. The validity of the classification rule was also tested by 206 gravimetrically prepared fat mixtures. Mixtures containing >3% foreign fat were detected in all cases.