Detection of adulterations in milk fat by multiple regression analysis of total fatty acids profile

Abstract

The total fatty acids profile of a genuine milk fat from an important milk producing area of Argentina was determined together with the total fatty acids profiles of sunflower, soybean and coconut oils and bovine and porcine fats. These results were used for characterization of the fatty acid profile of genuine milk fat and for detection of the adulteration of milk fat with those oils and fats. Triglycerides were transesterified in an acid medium with ethanol – sulfuric acid. Ethyl esters were quantified by gas chromatography using two internal standards (C7:0 and C17:0 ) added to the anhydrous fat. The most characteristic fatty acids were determined. The fatty acids profiles of mixtures of milk fat with vegetable and animal fats were mathematically calculated. Vegetable oils were added from 2 to 10 %, while animal fats were added up to 15 %. In this way different data matrices were obtained. Stepwise multiple regression analysis was applied to these matrices with the aim of obtaining a relation between adulteration percentage and the total fatty acids profile for each fat selected as adulterant. Good correlation coefficients were obtained for analyzed matrices. Equations were validated by employing the cross validation method, and were applied to genuine samples of milk fat and to mixtures by mass balances of these milk fats with the different adulterant fats. A good prediction of adulterations was obtained with the application of equations.

Keywords

• adulteration
• stepwise multiple linear regression
• total fatty acids