Line scan hyperspectral imaging spectroscopy for the early detection of melamine and cyanuric acid in feed


  • Fernández Pierna, J.A. , Vincke, D. , Dardenne, P. , Zengling, Y. , Lujia, H. & Baeten, V. (2014). Line scan hyperspectral imaging spectroscopy for the early detection of melamine and cyanuric acid in feed. Journal of Near Infrared Spectroscopy, 22: (2), 103-112.
Type Journal Article
Year 2014
Title Line scan hyperspectral imaging spectroscopy for the early detection of melamine and cyanuric acid in feed
Journal Journal of Near Infrared Spectroscopy
Label U15-1677-Fernandez-2014
Edition Journal Article
Recnumber 20
Volume 22
Issue 2
Pages 103-112
Endnote Keywords NIR, line-scan hyperspectral imaging, HIS, feed safety, contaminants, soybean meal, melamine, cyanuric acid
Abstract This study was aimed at exploring the feasibility of detecting and quantifying melamine, and the structural analogue cyanuric acid, contamination in soybean meal, using line-scan near infrared (NIR) hyperspectral imaging spectroscopy (HIS). Soybean meal is one of the main ingredients used in the feed industry because it offers a complete protein profile. Each year, demand increases for soybean products and soya oil, the consumption of which is directly boosted by Chinese consumers’ growing wealth, and for soybean meal, which is indirectly affected by the growing demand for meat. Recent cases of deliberate melamine contamination of soybean meal have been reported. This study focuses on the development of a methodology based on NIR–HIS for the acquisition, treatment and interpretation of images and spectra, as well as for the detection and quantification of melamine and cyanuric acid contamination in soybean meal. A total of 40 commercial soybean meal samples were collected, and 17 adulterated samples were prepared by adding different amounts of melamine/cyanuric acid to the samples, with concentrations varying between 0.5% and 5%. The spectral data were collected using line-scan NIR–HIS, and a qualitative model was created based on a principal-component analysis (PCA), whereas partial least-squares discriminant analysis was used to obtain a discrimination model and a semi-quantitative prediction of the content of contaminant. This study has permitted the detection of low levels of melamine and also revealed some limitations for the feasibility of quantifying melamine in soybean meal.
Fichier
Lien http://dx.doi.org/10.1255/jnirs.1109
Authors Fernández Pierna, J.A., Vincke, D., Dardenne, P., Zengling, Y., Lujia, H., Baeten, V.

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