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Discriminating traditional Coalho cheese by origin is important to ensure authenticity. The middle and near infrared spectroscopy and analytical measures associated with different chemometric approaches were used to characterise and discriminate Coalho cheese from different mesoregions of the State of Bahia, Brazil. Principal Component Analysis and Linear Discriminant Analysis were able to show the difference between cheeses. where better discrimination was observed using near infrared spectroscopy, which formed distinct groups by region and correct classification up to 90.00%. The infrared spectroscopy, especially the near infrared, showed to be very useful in the quick discrimination of cheeses according to their origin.

Mid-infrared spectroscopy (MID), chemical composition and physicochemical characteristics associated with chemometrics were used to rapidly detect and quantify the amount of cow's milk added in buffalo's milk. A total of 165 samples, divided into buffalo's milk, buffalo's milk added with cow's milk (10 to 90%) and cow's milk were evaluated to obtain fat, protein, lactose, total and defatted solids, urea, pH, acidity, cryoscopic index and band absorbances in the spectra associated with principal component analysis (PCA), multiple linear regression (MLR) and partial least squares regression (PLS). The treatments were separated into groups by PCA, allowing the classification of samples. MLR and PLS models were able to predict cow's milk contents in buffalo's milk. MID and results of the analytical measures studied when associated with chemometrics are efficient in the rapid quantitative detection of adulteration in buffalo's milk.

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