A Raman chemical imaging system for detection of contaminants in food

摘要

This study presented a preliminary investigation into the use of macro-scale Raman chemical imaging for the screening of dry milk powder for the presence of chemical contaminants. Melamine was mixed into dry milk at concentrations (w/w) of 0.2%, 0.5%, 1.0%, 2.0%, 5.0%, and 10.0% and images of the mixtures were analyzed by a spectral information divergence algorithm. Ammonium sulfate, dicyandiamide, and urea were each separately mixed into dry milk at concentrations of (w/w) of 0.5%, 1.0%, and 5.0%, and an algorithm based on self-modeling mixture analysis was applied to these sample images. The contaminants were successfully detected and the spatial distribution of the contaminants within the sample mixtures was visualized using these algorithms. Although further studies are necessary, macro-scale Raman chemical imaging shows promise for use in detecting contaminants in food ingredients and may also be useful for authentication of food ingredients.