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Appl. Sci. 2017, 7(1), 1; doi:10.3390/app7010001

Identification and Evaluation of Composition in Food Powder Using Point-Scan Raman Spectral Imaging

1
Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, United States Department of Agriculture, 10300 Baltimore Avenue, Bldg 303 BARC- East, Beltsville, MD 20705, USA
2
National R&D Centre for Agro-Processing, China Agriculture University, 17 Qinghua East Road, Haidian, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Academic Editor: Costas Balas
Received: 20 October 2016 / Revised: 13 December 2016 / Accepted: 15 December 2016 / Published: 22 December 2016
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Abstract

This study used Raman spectral imaging coupled with self-modeling mixture analysis (SMA) for identification of three components mixed into a complex food powder mixture. Vanillin, melamine, and sugar were mixed together at 10 different concentration level (1% to 10%, w/w) into powdered non-dairy creamer. SMA was used to decompose the complex multi-component spectra and extract the pure component spectra and corresponding contribution images. Spectral information divergence (SID) values of the extracted pure component spectra and reference component spectra were computed to identify the components corresponding to the extracted spectra. The contribution images obtained via SMA were used to create Raman chemical images of the mixtures samples, to which threshold values were applied to obtain binary detection images of the components at all concentration levels. The detected numbers of pixels of each component in the binary images was found to be strongly correlated with the actual sample concentrations (correlation coefficient of 0.99 for all components). The results show that this method can be used for simultaneous identification of different components and estimation of their concentrations for authentication or quantitative inspection purposes. View Full-Text
Keywords: Raman spectral imaging; food powder; self modeling mixture analysis; spectral information divergence; food safety and quality Raman spectral imaging; food powder; self modeling mixture analysis; spectral information divergence; food safety and quality
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Dhakal, S.; Chao, K.; Qin, J.; Kim, M.; Peng, Y.; Chan, D. Identification and Evaluation of Composition in Food Powder Using Point-Scan Raman Spectral Imaging. Appl. Sci. 2017, 7, 1.

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