Detecting multiple adulterants in dry milk using Raman chemical imaging

Abstract

This study investigated the potential of Raman chemical imaging for simultaneously detecting multiple adulterants in milk powder. Potential chemical adulterants, including ammonium sulfate, dicyandiamide, melamine, and urea, were together mixed into nonfat dry milk in the concentration range of 0.1%-5.0% for each adulterant. A benchtop point-scan Raman imaging system using a 785-nm laser was assembled to acquire hyperspectral images in the wavenumber range of 102-2538 cm^-1. Each mixture was imaged in an area of 25×25 mm² with a spatial resolution of 0.25 mm. Selfmodeling mixture analysis (SMA) was used to extract pure component spectra, by which the four types of the adulterants were identified at all concentration levels based on their spectral information divergence values to the reference spectra. Raman chemical images were created using the contribution images from SMA, and their use to effectively visualize identification and spatial distribution of the multiple adulterant particles in the dry milk was demonstrated.