Detection of melamine in milk powder using MCT-based shortwave infrared hyperspectral imaging system

Authors: LEE, HOONSOO - Us Forest Service (FS); Kim, Moon; CHO, BYOUNG-KWAN - Chungnam National University

Submitted to: Journal of Food Additives & Contaminants
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/10/2018
Publication Date: 6/5/2018
Citation: Lee, H., Kim, M.S., Cho, B. 2018. Detection of melamine in milk powder using MCT-based shortwave infrared hyperspectral imaging system. Journal of Food Additives & Contaminants. 35(6):1027-1037. https://doi.org/10.1080/19440049.2018.1469050.
DOI: https://doi.org/10.1080/19440049.2018.1469050

Interpretive Summary: Extensive research using spectroscopic and spectral imaging methods has been conducted on non-destructive and rapid detection of melamine in powdered foods in the last decade. In this study, a recently developed short-wave infrared hyperspectral imaging system was used to develop multivariate algorithms to quantitatively detect melamine in milk powder. The hyperspectral images were obtained for melamine-milk samples with a range of melamine concentrations, pure melamine, and pure milk powder. The results showed that a melamine concentration as low as 50 ppm in melamine-milk powder samples could be detected. The research benefits food processing industries by providing insightful information on potential means to rapidly authenticate powder food ingredients.

Technical Abstract: Extensive research has been conducted on non-destructive and rapid detection of melamine in powdered foods in the last decade. While Raman and near-infrared (NIR) hyperspectral imaging techniques have been successful in terms of non-destructive and rapid measurement, they have limitations with respect to measurement time and detection capability, respectively. Therefore, the objective of this study was to develop a mercury-cadmium-telluride-based (MCT-based) short wave infrared (SWIR) hyperspectral imaging system and algorithm to quantitatively detect melamine in milk powder. The SWIR hyperspectral imaging system consisted of a custom-designed illumination system, an MCT-based SWIR hyperspectral camera, a data acquisition module, and a sample transfer table. SWIR hyperspectral images were obtained for melamine-milk samples with different melamine concentrations, pure melamine, and pure milk powder. Analysis of variance (ANOVA) and the partial least squares regression (PLSR) method with 1000–2500 nm wavelength region were used to develop an optimal model for detection. The results showed that a melamine concentration as low as 50 ppm in melamine-milk powder samples could be detected. Thus, the MCT-based SWIR hyperspectral imaging system has the potential for quantitative and qualitative detection of adulterants in powder samples.