Fourier transform infrared spectroscopy (FTIR) attenuated total reflectance (ATR) spectroscopy, coupled
with chemometrics methods have been applied to the fast and non-destructive quantitative determination
of solid non fat (SNF) content in raw milk. Partial least squares regression (PLS) and support vector
machine (SVM) regression methods were used to model and predict SNF contents in raw milk based on
FTIR spectral transmission measurements. Both methods, PLS and SVM, showed good performances in
SNF prediction with relative prediction errors in the external validation of between 0.2% and 0.3%
depending on the spectral range and regression method. Coefficient of determination of the global fit
was always above 0.99. Since, the relative prediction errors were low, it can be concluded that FTIRATR
with chemometrics can be used for accurate quantitative determinations of SNF contents in raw milk
within the investigated calibration range of 79–100 g/L. The proposed procedure is fast, non-destructive,
simple and easy to implement.