Fast Verification of Buffalo’s Milk Authenticity by Mid-Infrared Spectroscopy, Analytical Measurements and Multivariate Calibration

Abstract

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.

Discriminating Coalho cheese by origin through near and middle infrared spectroscopy and analytical measures. Discrimination of Coalho cheese origin

“…These techniques are extensively explored, especially when associated with chemometric analysis, since it is possible to extract information based on the chemical composition and conformation of the cheese’s components from the vibration of the functional groups that are part of the structure of these constituents, generating specific spectra, making it possible to achieve precise answers in the discrimination of samples quickly (Gonçalves et al . 2020; Jesus et al . 2020).…”

Mid-infrared (MIR) spectroscopy for the detection of cow’s milk in buffalo milk

“…The authors could detect differences between different milk species only accounting for 40% of adulteration and could not assess the content of cow’s milk added to buffalo milk, but only its presence. Also, Gonçalves et al [ 16 ] developed a similar method for the quantification of buffalo’s milk adulterants (e.g. cow’s milk) using MIR spectroscopy coupled to PLS and multiple linear regression (MLR).…”

“…The obtained results were similar to the ones here presented, with R 2 of 0.9938 and RMSEP of 3.484% for the adulteration. Durakli Velioglu et al [ 27 ], similarly to Gonçalves et al [ 16 ], when researching the authenticity of buffalo’s milk by fluorescence spectroscopy associated with principal component analysis (PCA) and PLS, found models with an R 2 of 0.98. Instead, RMSEC, RMSECV, and RMSEP values were determined as 2%, 7% and 4%, respectively, indicating slightly higher prediction errors than the values in our findings.…”

“…After leave-one-out cross validation, the number of the principal components (factors) that minimized the root mean square error of cross-validation (RMSECV) of the model was nine. After selecting the number of latent variables [ 16 ], the PLS model was used to recognize the concentration of cow’s milk in buffalo’s milk.…”

Application of infrared spectroscopic techniques to cheese authentication: A review

“…2008), fluid milk (Gonçalves et al . 2020), cheese whey (Andrade et al . 2019), butter (Koca et al .…”