|Qin, Jianwei - Tony Qin|
|Chao, Kuanglin - Kevin Chao|
|CHO, BYOUNG-KWAN - Chungnam National University|
Submitted to: Food and Bioprocess Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/21/2015
Publication Date: 1/15/2016
Citation: Qin, J., Chao, K., Kim, M.S., Cho, B. 2016. Line-scan macro-scale Raman chemical imaging for authentication of powdered foods and ingredients. Food and Bioprocess Technology. 9(1):113-123.
Interpretive Summary: Many cases of human illness and even death have occurred as a result of deliberate, profit-driven adulteration of food ingredients. Adulteration incidents involving dry food powders supplied as ingredients for manufacture of mass-market food products has increased interest in development of rapid, high-volume screening methods for use by food processors to authenticate food ingredients for safety and quality. We have developed a new line-scan macro-scale Raman imaging system capable of fast image acquisition from large surface areas of powdered samples, reducing typical sampling time to minutes. This work used the spectral and spatial information from hyperspectral Raman images to identify and map the adulterant particles mixed into the food powders. Studies were conducted with three food-adulterant pairings: milk and melamine, flour and benzoyl peroxide, and starch and maleic anhydride. Because the maximum penetration depths of the line laser through milk, flour, and starch were estimated at 3mm, the mixed powder samples were presented in 3-mm thick layers over an area of 2500 mm2 for Raman image acquisition. Spectral and image processing was used to identify the adulterant particles and visualize their distribution against the food particle background in each image. The detection method developed in this study can be adapted and refined for use in inspecting other powdered foods and ingredients for chemical contaminants. This research will be of interest to other scientists, food processors, regulatory agencies and security agencies.
Technical 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 the food powders. The system was used to collect hyperspectral Raman images in the wavenumber range of 102–2865 cm-1 for samples of three representative food powders mixed with selected chemical adulterants at 0.5% concentrations, 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 ensure uniform particle distribution in each sample mixture. Maximum penetration depths of the line laser through the 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 that the adulterant particles at the very bottom could 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 identified in the chemical images (i.e., volume concentrations) was also demonstrated.