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Milk is a complex emulsion of fat and water with proteins (such as caseins and whey), vitamins, minerals andlactose dissolved within. The purpose of this study is to automatically distinguish different dairy residues on substratescommonly used in the food industry using hyperspectral imaging. Fourier transform infrared (FT-IR) and Ramanhyperspectral imaging were compared as candidate techniques to achieve this goal. Aluminium and stainless-steel, types304-2B and 316-2B, were chosen as surfaces due to their widespread use in food production. Spectra of dried samplesof whole, skimmed, protein, butter milk and butter were compared. The spectroscopic information collected was not onlyaffected by the chemical signal of the milk composition, but also by surface signals, evident as baseline and multiplicativeeffects. In addition, the combination of the spectral information with spatial information can improve data interpretation interms of characterising spatial variability of the selected surfaces.

Raman and Fourier transform infrared hyperspectral imaging to study dairy residues on different surface