Non-Targeted and Targeted Raman Imaging Detection of Chemical Contaminants in Food Powders

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.