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Detection of melamine in milk powders using near-infrared hyperspectral imaging combined with regression coefficient of partial least square regression model.
Talanta. 2016 May 01; 151:183-191.T

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 990-1700nm 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.

Authors+Show Affiliations

National Institute of Agricultural Science, Rural Development Administration, Jeonju 54875, Republic of Korea.National Institute of Agricultural Science, Rural Development Administration, Jeonju 54875, Republic of Korea.National Institute of Agricultural Science, Rural Development Administration, Jeonju 54875, Republic of Korea.Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, USDA, 10300 Baltimore Avenue, Beltsville, MD 20705, USA. Electronic address: moon.kim@ars.usda.gov.Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, USDA, 10300 Baltimore Avenue, Beltsville, MD 20705, USA.Environmental Microbial and Food Safety Laboratory, Agricultural Research Service, USDA, 10300 Baltimore Avenue, Beltsville, MD 20705, USA.College of Biosystems Engineering & Food Science, Zhejiang University, Hangzhou 310029, PR China.Department of Bioindustrial Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea.Department of Bioindustrial Machinery Engineering, Chungnam National University, Daejeon 34134, Republic of Korea.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

26946026

Citation

Lim, Jongguk, et al. "Detection of Melamine in Milk Powders Using Near-infrared Hyperspectral Imaging Combined With Regression Coefficient of Partial Least Square Regression Model." Talanta, vol. 151, 2016, pp. 183-191.
Lim J, Kim G, Mo C, et al. Detection of melamine in milk powders using near-infrared hyperspectral imaging combined with regression coefficient of partial least square regression model. Talanta. 2016;151:183-191.
Lim, J., Kim, G., Mo, C., Kim, M. S., Chao, K., Qin, J., Fu, X., Baek, I., & Cho, B. K. (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. https://doi.org/10.1016/j.talanta.2016.01.035
Lim J, et al. Detection of Melamine in Milk Powders Using Near-infrared Hyperspectral Imaging Combined With Regression Coefficient of Partial Least Square Regression Model. Talanta. 2016 May 1;151:183-191. PubMed PMID: 26946026.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Detection of melamine in milk powders using near-infrared hyperspectral imaging combined with regression coefficient of partial least square regression model. AU - Lim,Jongguk, AU - Kim,Giyoung, AU - Mo,Changyeun, AU - Kim,Moon S, AU - Chao,Kuanglin, AU - Qin,Jianwei, AU - Fu,Xiaping, AU - Baek,Insuck, AU - Cho,Byoung-Kwan, Y1 - 2016/01/18/ PY - 2015/10/23/received PY - 2016/01/14/revised PY - 2016/01/16/accepted PY - 2016/3/7/entrez PY - 2016/3/8/pubmed PY - 2016/12/15/medline KW - Hyperspectral imaging KW - Melamine KW - Milk powder adulteration KW - Partial least square regression KW - Regression coefficient SP - 183 EP - 191 JF - Talanta JO - Talanta VL - 151 N2 - 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 990-1700nm 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. SN - 1873-3573 UR - https://www.unboundmedicine.com/medline/citation/26946026/Detection_of_melamine_in_milk_powders_using_near_infrared_hyperspectral_imaging_combined_with_regression_coefficient_of_partial_least_square_regression_model_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0039-9140(16)30034-0 DB - PRIME DP - Unbound Medicine ER -