Modeling for the Classification of Milk Tea Powder and Authenticity Assessment of Traditional Cheese Based on Amino Acid Fingerprint

In this study, a total of 138 milk tea powder samples were collected from the market of Inner Mongolia and classified into two categories based on the manufacturing process and major raw materials: traditional wet-processed and modern dry-mixed powder. In addition, 40 traditional cheese samples and 15 solid milk-containing cheese-like product samples were obtained from Inner Mongolia’s different regions. For comparison, five samples of raw milk, milk casein (not included in the total), milk powder, and tofu were also collected. Eighteen amino acids (AAs) were quantified using the national standard method and subjected to statistical analyses using orthogonal partial least squares discriminant analysis (OPLS-DA) and hierarchical cluster analysis (HCA). Results revealed significant differences in AA contents and fingerprint patterns between the two kinds of milk tea powder, as well as between traditional cheese and solid milk-containing products. OPLS-DA clearly differentiated between wet- and dry-processed milk tea powder, and between traditional cheese and solid milk-containing products. Notably, however, raw milk-derived milk tea powder and traditional cheese were closely clustered with the control samples (raw milk, milk casein, and milk powder). Tofu samples were clustered separately and distinctly from all other groups, indicating no incorporation of soybean-derived ingredients. External validation accuracies for the OPLS-DA models based on the absolute and relative contents of AAs in milk tea powder were 70.8% and 75.4%, respectively, and those for traditional cheese were 75.8% and 95.0%, respectively. These findings confirm the feasibility of authenticating milk tea powder and traditional cheese using AA fingerprints.