Adulteration of Argentinean milk fats with animal fats: Detection by fatty acids analysis and multivariate regression techniques. (1st February 2016)

• Record Type: Journal Article
• Authors: Rebechi, S.R.; Vélez, M.A.; Vaira, S.; Perotti, M.C.
• Is Part Of: Food chemistry. Volume 192(2016)
• Page Start: 1025
• Page End: 1032
• Publication Date: 2016-02-01
• Subjects: Adulteration -- Milk fat -- Multiple Linear Regression; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2015.07.107
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Detection of adulterations of milk fat with animal fats was the aim of this work. GC analysis of FA profiles of MF jointly with MLR data processing was used. 70 MF, 10 tallow and 7 lard samples were collected and FA profiles were analyzed. Good suitable mathematical regression models were obtained for both adulterants. Adulterations greater than 5% for lard and 10% for tallow were detected. Abstract: The aims of the present study were to test the accuracy of the fatty acid ratios established by the Argentinean Legislation to detect adulterations of milk fat with animal fats and to propose a regression model suitable to evaluate these adulterations. For this purpose, 70 milk fat, 10 tallow and 7 lard fat samples were collected and analyzed by gas chromatography. Data was utilized to simulate arithmetically adulterated milk fat samples at 0%, 2%, 5%, 10% and 15%, for both animal fats. The fatty acids ratios failed to distinguish adulterated milk fats containing less than 15% of tallow or lard. For each adulterant, Multiple Linear Regression (MLR) was applied, and a model was chosen and validated. For that, calibration and validation matrices were constructed employing genuine and adulterated milk fat samples. The models were able to detect adulterations of milk fat at levels greater than 10% for tallow and 5% for lard.