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Authentication of Milk Powder using Raman Scattering Spectroscopy and Imaging

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Paper number  131591839,  2013 Kansas City, Missouri, July 21 - July 24, 2013. (doi: @2013
Authors:   Jianwei Qin, Kuanglin Chao, Moon S Kim, Yu-Che Cheng
Keywords:   Raman scattering; Spectroscopy; Imaging; Milk; Adulterant.

Abstract. This study investigates the potential of Raman scattering spectroscopy and imaging for detecting adulterants in milk powder. Potential chemical adulterants, including ammonium sulfate, dicyandiamide, melamine, and urea, were mixed into the skim milk powder in the concentration range of 0.1–5.0%. A Raman imaging system with a 785-nm laser was used to acquire hyperspectral images in the wavenumber range of 102–2538 cm–1 for a 25×25 mm2 area of each mixture. The hyperspectral Raman images were analyzed using two different methods. One method was based on self-modeling mixture analysis (SMA). 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. The other method was based on single-band images at unique Raman peaks of the adulterants. A polynomial curve-fitting method was used to correct for the fluorescence background in the Raman images. The adulterant type was determined using the unique Raman peaks of the adulterants. The contribution images from SMA and the single-band corrected images were used to generate the binary images of the individual adulterants. Raman chemical images were created to visualize identification and distribution of the multiple adulterant particles in the milk powder. The method based on single-band Raman images is simpler than the SMA method, and it is promising to be used in a future high-throughput inspection system for rapid and accurate authentication of milk powder and other powdered food and food ingredients.

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