Abstract
Adulteration and fraud for powdered foods and ingredients are rising food safety risks that threaten consumers’ health. In this study, a newly developed line-scan macro-scale Raman imaging system using a 5-W 785-nm line laser as excitation source was used to authenticate food powders. The system was used to collect hyperspectral Raman images in a wave number range of 102–2865 cm−1 from three representative food powders mixed with selected chemical adulterants with a concentration of 0.5 %, including milk powder and melamine, wheat flour and benzoyl peroxide, and corn starch and maleic anhydride. An acoustic mixer that generates high-intensity acoustic waves was used to create food-adulterant mixtures. Maximum penetration depths of the line laser through powders of milk, flour, and starch were all estimated at 3 mm using layered food-on-adulterant samples. All the mixed samples were placed in sample holders with a surface area of 50 mm × 50 mm and a depth of 3 mm to ensure the adulterant particles at the very bottom can still be detected. Raman spectral and image processing algorithms were developed based on fluorescence correction and single-band images at unique Raman peaks of the individual adulterants. Chemical images were created to show identification, spatial distribution, and morphological features of the adulterant particles mixed in the food powders. The potential of estimating mass concentrations of the adulterants using the percentages of the adulterant pixels in the chemical images (i.e., volume concentrations) was also demonstrated.
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