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Economically motivated adulteration and fraud to food powders are emerging food safety risks that threaten the health of the general public. In this study, targeted and non-targeted methods were developed to detect adulterants based on macro-scale Raman chemical imaging technique. Detection of potassium bromate (PB) (a flour improver banned in many countries) mixed in wheat flour was used as a case study to demonstrate the developed methods. A line-scan Raman imaging system with a 785 nm line laser was used to acquire hyperspectral image from the flour-PB mixture. Raman data analysis algorithms were developed to fulfill targeted and non-targeted contaminant detection. The targeted detection was performed using a single-band Raman image method. An image classification algorithm was developed based on single-band image at a Raman peak uniquely selected for the PB. On the other hand, a mixture analysis and spectral matching method was used for the non-targeted detection. The adulterant was identified by comparing resolved spectrum with reference spectra stored in a pre-established Raman library of the flour adulterants. For both methods, chemical images were created to show the PB particles mixed in the flour powder.
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Jianwei Qin, Moon S. Kim, Kuanglin Chao, Sagar Dhakal, Byoung-Kwan Cho, "Non-targeted and targeted Raman imaging detection of chemical contaminants in food powders," Proc. SPIE 10665, Sensing for Agriculture and Food Quality and Safety X, 106650G (15 May 2018); https://doi.org/10.1117/12.2304384