|Chao, Kuanglin - Kevin Chao|
Submitted to: Journal of Food Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/1/2013
Publication Date: 9/23/2013
Citation: Fu, X., Kim, M.S., Chao, K., Qin, J., Lim, J., Lee, H., Ying, Y. 2013. Detection of melamine in milk powders based on NIR hyperspectral imaging and spectral similarity analyses. Journal of Food Engineering. 124:97-104. Interpretive Summary: Melamine is a nitrogen-rich chemical that is commonly found in the form of white crystals, and in several reported cases was found intentionally added to food products such as milk, infant formula, frozen yogurt, pet food, biscuits, and coffee drinks to boost the perceived protein content. The resulting cases of illness and death have raised concerns about food safety and the tools available to screen foods and food ingredients for harmful adulterants. Hyperspectral imaging techniques that combine the advantages of spectroscopy and imaging have been widely investigated for a variety of food quality and safety evaluations. In this study, a near-infrared hyperspectral imaging technique was used for rapid identification/detection of melamine particles in milk powders. We demonstrated that spectral similarity analyses of the hyperspectral imaging data successfully identified melamine particles in a range of melamine-milk powder mixtures, with melamine concentrations as low as 0.02% (200 ppm). This research provides insightful technical information to food technologists, food scientists, food industries, and regulatory agencies that are interested in rapid methods to detect food adulterants.
Technical Abstract: Melamine (2,4,6-triamino-1,3,5-triazine) contamination of food has become an urgent and broadly recognized topic as a result of several food safety scares in the past five years. Hyperspectral imaging techniques that combine the advantages of spectroscopy and imaging have been widely applied for a variety of food quality and safety evaluations. In this study, near-infrared (NIR) hyperspectral imaging technique was investigated to detect low levels (<=1.0%) of melamine particles in milk powders. Following image preprocessing (normalization and background removal), the spectrum of each pixel in the sample images was compared to the pure melamine spectrum by spectral similarity measures including spectral angle measure (SAM), spectral correlation measure (SCM), and Euclidian distance measure (EDM). The three similarity analysis methods provided comparable results for melamine particle detection where imaging allowed visualization of the distribution of melamine particles within images of milk powder mixture samples that were prepared with various melamine concentrations. The classification results were verified by spectral feature comparison between separated mean spectra of melamine pixels and milk powder pixels. The study demonstrated that a combination of NIR hyperspectral imaging technique and spectral similarity analyses was an effective method for melamine adulteration discrimination in milk powders. The method described in this study can also be applied to other chemicals or multi-chemicals adulterant detection in milk powders.