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Proceedings Paper

Raman spectroscopy-based detection of chemical contaminants in food powders
Author(s): Kuanglin Chao; Sagar Dhakal; Jianwei Qin; Moon Kim; Abigail Bae
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Paper Abstract

Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

Paper Details

Date Published: 17 May 2016
PDF: 6 pages
Proc. SPIE 9864, Sensing for Agriculture and Food Quality and Safety VIII, 98640Y (17 May 2016); doi: 10.1117/12.2224470
Show Author Affiliations
Kuanglin Chao, USDA-ARS (United States)
Sagar Dhakal, USDA-ARS (United States)
Jianwei Qin, USDA-ARS (United States)
Moon Kim, USDA-ARS (United States)
Abigail Bae, River Hill High School (United States)

Published in SPIE Proceedings Vol. 9864:
Sensing for Agriculture and Food Quality and Safety VIII
Moon S. Kim; Kuanglin Chao; Bryan A. Chin, Editor(s)

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