Identification of Geographical Origin of Milk by Amino Acid Profile Coupled with Chemometric Analysis

This study aimed to establish a method to identify the geographical origin of milk based on its amino acid profile. High-performance liquid chromatography (HPLC) was carried out to measure amino acid contents. The significant differences of amino acid profiles of milk samples from four regions in China (Hebei, Ningxia, Heilongjiang, and Inner Mongolia) were analyzed by ANOVA. Furthermore, the principal component analysis (PCA) demonstrated the feasibility of geographical origin identification using an amino acid profile, which the first 2 principal components account for 65.62% of total variance. The predictive model for the geographical origin of milk samples was established by orthogonal partial least squares-discriminant analysis (OPLS-DA) with a classification accuracy of 100% and the performance parameters of (RX)-X-2 0.98, (RY)-Y-2 0.82, and Q(2) 0.75. The excellent predictive ability of the model was validated using the validation data set. The analysis of variable importance in projection (VIP) showed that seven amino acids played a key role in the geographical origin identification. This method is a reliable strategy to identify the geographical origin of milk for protecting consumers against mislabeling fraud.

Automated summary

This study aimed to establish a method using amino acid profiles to identify the geographical origin of milk. The amino acid contents were measured using HPLC, and the significant differences in amino acid profiles among milk samples from different regions in China were analyzed using ANOVA and PCA. The predictive model for geographical origin of milk samples achieved a classification accuracy of 100% and demonstrated excellent predictive ability.