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The A2A2 genotype of bovine milk became interesting due to the differences of hydrolytic behavior during the gastrointestinal digestion. The identification of protein genic forms in milk may be acquired by genetic analysis, although new methods based on portable NIR spectroscopy and chemometric tools have turned as an option to evaluate A2 milk authentication. In this context, the study focused on preliminarily evaluate the possibility of authenticating A2 milk samples adulterated with non A2 milk using a NIR spectrometer microNIR combined with a one-class method. Bovine pasteurized milk samples were selected in regional markets of São Paulo, Brazil. Thirty-four samples of whole A2 milk were selected by their certification labeling and used as authentic set (AA), and 20 samples of non A2 milk were used for adulteration (AD), in four different ratios (10, 25, 50 and 100%). For data collection, MicroNIR (Viavi Solutions Inc., USA) was used. Full data of AA and AD were preprocessed with First derivative of Savitzky-Golay and Multiplicative Scatter Correction. A Data-driven Soft Independent Modeling of Class Analogy (DD-SIMCA) was applied. Using Kennard-Stone algorithm, the AA was split into two sets (26 for calibration and 8 for external validation). The AD samples were added into the external validation set, and the quality of the model was assessed by sensitivity and specificity values. The calibration procedure did not present external samples or outliers (α=0.01), and 100% of the samples were correctly classified as authentic A2 milk in external validation (β=1). Moreover, all AD set were classified as adulterated samples, indicating that the model was effective to recognize authentic samples. According to the results, one-class model showed satisfactory performance suitable with the portable equipment, through a fast and non-destructive technique that may be optimized and incorporated to industrial management, food control and labeling authentication of the A2 product.
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