Identification of Normalized and Reconstituted Milk by Digital Colorimetry and IR Spectroscopy

A rapid and easy to use method for identifying differentiating normalized and reconstituted milk using digital colorimetry and near-infrared spectroscopy is proposed. A box device with LEDs (λ = 365, 390, 850, 880 nm) was used, built in by means of resistors with a light scattering angle of 20°. A smartphone with PhotoMetrix PRO®, ColorGrab, RGBer applications and an IR-Fourier spectrometer for a near-IR region (4000–10 000 cm–1) were used to record the analytical signal. The applications TQ Analyst, The Unscrambler X, and XLSTAT were used to process the obtained diffuse reflectance spectra and colorimetric parameters. Pincipal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to identify and differentiate the analyzed milk samples. The mass fraction of fat and protein in dairy products was determined using the partial least squares (PLS) regression algorithm. The points corresponding to normalized and reconstituted milk are located in different quadrants on PCA plots in digital colorimetry and IR spectroscopy. The PCA and HCA graphs seemingly made it possible to distinguish the analyzed milk by type and differentiate skim milk by protein content. The possibility of determining the fat and protein content in the studied milk samples using chemometric analysis methods has been demonstrated. The relative standard deviation of the analysis results did not exceed 0.03 for reconstituted and normalized milk, and 0.02 for skim milk.