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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 #324758
Title: Detection of melamine in milk powders using Near-Infrared Hyperspectral imaging combined with regression coefficient of partial least square regression model

Author
item LIM, JONGGUK - Rural Development Administration - Korea
item KIM, GIYOUNG - Rural Development Administration - Korea
item MO, CHANGYEUN - Rural Development Administration - Korea
item Kim, Moon
item Chao, Kuanglin - Kevin Chao
item Qin, Jianwei - Tony Qin
item FU, XIAPING - Zhejiang University
item BAEK, INSUCK - Chungnam National University
item CHO, YOUNG-KWAN - Chungnam National University

Submitted to: Talanta
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/16/2016
Publication Date: 2/2/2016
Citation: Lim, J., Kim, G., Mo, C., Kim, M.S., Chao, K., Qin, J., Fu, X., Baek, I., Cho, Y. 2016. Detection of melamine in milk powders using Near-Infrared Hyperspectral imaging combined with regression coefficient of partial least square regression model. Talanta. 151:183-191.

Interpretive Summary: Illegal use of melamine to boost perceived protein content of food products such as milk, infant formula, frozen yogurt, pet food, biscuits, and coffee drinks has caused serious food safety problems. In this research, near-infrared (NIR) hyperspectral imaging combined with numerical analysis methods were investigated to detect melamine particles in milk powders at various concentrations ranging from 0.02 to 1%. Results show that the imaging method allowed successful detection of melamine particles in milk powder even at the mixture concentration level as low as 0.02 %. The imaging technology and methods demonstrated in this paper can be used in food processing facilities to provide a rapid means to assess contents of food adulterants. The research is beneficial to food technologists and the food processing industry.

Technical Abstract: Illegal use of nitrogen-rich melamine (C3H6N6) to boost perceived protein content of food products such as milk, infant formula, frozen yogurt, pet food, biscuits, and coffee drinks has caused serious food safety problems. Conventional methods to detect melamine in foods, such as Enzyme-linked immunosorbent assay (ELISA), High-performance liquid chromatography (HPLC), and Gas chromatography–mass spectrometry (GC-MS), are sensitive but they are time-consuming, expensive, and labor-intensive. In this research, near-infrared (NIR) hyperspectral imaging technique combined with regression coefficient of partial least squares regression (PLSR) model was used to detect melamine particles in milk powders easily and quickly. NIR hyperspectral reflectance imaging data in the spectral range of 990-1700 nm were acquired from melamine-milk powder mixture samples prepared at various concentrations ranging from 0.02 to 1%. PLSR models were developed to correlate the spectral data (independent variables) with melamine concentration (dependent variables) in melamine-milk powder mixture samples. PLSR models applying various pretreatment methods were used to reconstruct the two-dimensional PLS images. PLS images were converted to the binary images to detect the suspected melamine pixels in milk powder. As the melamine concentration was increased, the numbers of suspected melamine pixels of binary images were also increased. These results suggested that NIR hyperspectral imaging technique and the PLSR model can be regarded as an effective tool to detect melamine particles in milk powders.