Single-drop technique for lactose prediction in dry milk on metallic surfaces: Comparison of Raman, FT – NIR, and FT – MIR spectral imaging

This study applies the single drop techniques to compare the efficacy of Raman, FT – NIR, and FT-MIR spectral imaging to quantify lactose concentration in dried whole milk on different metallic surfaces. Drying the samples avoids degradation problems such as water evaporation or oil degradation and scattering due to micelles. Spectral imaging techniques minimise sampling issues while also describing the sample spatial variation. The mean spectra of pre-processed images were used to build PLS regression models to predict lactose concentration. Raman, FT – NIR (5600–3730 cm⁻¹), FT–MIR (3533–600 cm⁻¹) models and the model obtained using the fusion of the three ranges were built independently and compared. This study confirms that is possible to quantify lactose rapidly using spectral imaging without adding standard references: the minimum RMSEP = 2.8 mg/mL (R² = 0.98) was achieved with FT – MIR spectral imaging.