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.

© 2014 IM Publications LLP

Line-scanning Raman imaging spectroscopy for detection of fingerprints

Sunan Deng, Le Liu, Zhiyi Liu, Zhiyuan Shen, Guohua Li, and Yonghong He
Appl. Opt. 51(17) 3701-3706 (2012)

4D line-scan hyperspectral imaging

Jiaqiong Li, Yi Zheng, Lingling Liu, and Beiwen Li
Opt. Express 29(21) 34835-34849 (2021)

Systematic meta-analysis of computer-aided detection to detect early esophageal cancer using hyperspectral imaging

Wei-Chih Liao, Arvind Mukundan, Cleorita Sadiaza, Yu-Ming Tsao, Chien-Wei Huang, and Hsiang-Chen Wang
Biomed. Opt. Express 14(8) 4383-4405 (2023)

Line-scanning hyperspectral imaging based on structured illumination optical sectioning

Yu John Hsu, Chih-Chiang Chen, Chien-Hsiang Huang, Chia-Hua Yeh, Li-Ying Liu, and Szu-Yu Chen
Biomed. Opt. Express 8(6) 3005-3016 (2017)

Integrated endoscopy system for simultaneous imaging and spectroscopy for early lung cancer detection

Haishan Zeng, Mirjan Petek, Marjeta Tercelj Zorman, Annette McWilliams, Branko Palcic, and Stephen Lam
Opt. Lett. 29(6) 587-589 (2004)