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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #316823
Title: Raman-spectroscopy-based chemical contaminant detection in milk powder

Author
item DHAKAL, SAGAR - Orise Fellow
item Chao, Kuanglin - Kevin Chao
item Qin, Jianwei - Tony Qin
item Kim, Moon

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 5/18/2015
Publication Date: 5/20/2015
Citation: Dhakal, S., Chao, K., Qin, J., Kim, M.S. 2015. Raman-spectroscopy-based chemical contaminant detection in milk powder. Proceedings of SPIE 9488, Sensing for Agriculture and Food Quality and Safety VII, 94880E.

Interpretive Summary: The past decade has seen a recurrence of food safety and quality problems resulting from the addition of edible and inedible chemical contaminants in food materials for purposes of economic benefit. Some have resulted in severe health issues for consumers, including illness and death from consumption of food powder ingredients contaminated with chemical substances. Raman spectroscopy has been demonstrated as a non-destructive spectral method that has potential for use in detecting chemical contaminants. This study examines the effect of spatial resolution used during Raman spectral imaging collection for effective detection of melamine in dry milk powder. Using a point-scan Raman chemical imaging system equipped with a 200 mw laser, dry milk samples prepared at a depth of 2 mm were imaged using an exposure time of 0.1s and spatial resolutions of 0.05 mm, 0.15 mm, 0.25 mm, 0.5 mm, 1.0 mm, and 2.0mm. Analysis found that the spatial resolution of 0.25mm was optimal for effective chemical particle detection, as higher resolutions were prone to detect individual particles more than once and lower resolution were prone to missing particles. Using the 0.25mm imaging resolution, spectral image acquisition and analysis was then conducted for 5 different concentrations of milk-melamine mixture (1%, 0.5%, 0.1%, 0.05%, and 0.025%) to study the relationship between number of detected melamine pixels and corresponding sample concentration. Melamine concentration was found to have a linear relation with the number of melamine pixels detected. It can be concluded that the quantitative analysis of powder mixture is dependent on many factors including physical characteristics of mixture, experimental parameters, and sample depth. These results will be applied to development of quantitative detection models for rapid screening of melamine in milk powder as well as other contaminants and food ingredients. The methods developed will benefit food processors and regulatory agencies who need tools to help ensure the safety of food ingredients.

Technical Abstract: Addition of edible and inedible chemical contaminants in food powders for purposes of economic benefit has become a recurring trend. In recent years, severe health issues have been reported due to consumption of food powders contaminated with chemical substances. This study examines the effect of spatial resolution used during Raman spectral imaging to select the optimal spatial resolution for detecting melamine in milk powder. Sample depth of 2mm, laser intensity of 200mw, and exposure time of 0.1s were previously determined as optimal experimental parameters for Raman imaging. Analysis of images acquired using spatial resolutions of 0.05 mm, 0.15 mm, 0.25 mm, 0.5 mm, 1.0 mm, and 2.0 mm, found that 0.25mm was optimal for imaging-based detection of melamine particles in a milk-melamine mixture sample. Using the spatial resolution of 0.25mm, sample depth of 2mm, and laser intensity of 200mw (parameters obtained from previous study), Raman spectral images were acquired for 5 different concentrations of milk-melamine mixture (1%, 0.5%, 0.1%, 0.05%, and 0.025%) to study the relationship between number of detected melamine pixels and corresponding sample concentration. The result shows that melamine concentration has a linear relation with detected number of melamine pixels with correlation coefficient of 0.99. It can be concluded that the quantitative analysis of powder mixture is dependent on many factors including physical characteristics of mixture, experimental parameters, and sample depth. The results obtained in this study are promising. We plan to apply the result obtained from this study to develop quantitative detection model for rapid screening of melamine in milk powder. This methodology can also be used for detection of other chemical contaminants in milk powders.