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

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R-2 >= 0.99 (R(2)cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R(2)val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.

Automated summary

This study developed a quantitative analysis method using Fourier transform infrared spectroscopy (FTIR) and partial least square (PLS) regression to detect the adulteration of buffalo milk with cow milk. Samples of cow and buffalo milk from different dairy farms were collected to generate mixtures of different concentrations. The results showed that this method could effectively and rapidly detect adulteration in buffalo milk.