Journal
JOURNAL OF FOOD ENGINEERING
Volume 119, Issue 3, Pages 680-686Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jfoodeng.2013.06.039
Keywords
Hyperspectral imaging; Prawn; Gelatin; Adulteration; Imaging spectroscopy
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Funding
- Natural Science Foundation of China [31072247, 31201446]
- Zhejiang Provincial Natural Science Foundation of China [LQ12C20006]
- Ningbo Natural Science Foundation of China [2010A610015]
- Scientific Research Fund of Zhejiang Provincial Education Department [Y201122038]
- Fundamental Research Funds for the Central Universities
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In this study, the reliability and accuracy of hyperspectral imaging was investigated for detection of gelatin adulteration in prawn. The spectra of prawns were extracted according to the shape information of prawns contained in the hyperspectral images. Least-squares support vector machines (LS-SVM) was used to calibrate the gelatin concentrations of prawn samples with their corresponding spectral data. The combination of uninformation variable elimination (UVE) and successive projections algorithm (SPA) was applied for the first time to select the optimal wavelengths in the hyperspectral image analysis. The UVE-SPA-LS-SVM model led to a coefficient of determination (r(p)(2)) of 0.965 and was transferred to every pixel in the image for visualizing gelatin in all portions of the prawn. The results demonstrate that hyperspectral imaging has a great potential for detection of gelatin adulteration in prawn. (C) 2013 Elsevier Ltd. All rights reserved.
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