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Sensors 2017, 17(8), 1706; https://doi.org/10.3390/s17081706

Grading of Chinese Cantonese Sausage Using Hyperspectral Imaging Combined with Chemometric Methods

1
College of Mechanical and Electrical Engineering, Shenzhen Institute of Information Technology, Shenzhen 518172, China
2
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
*
Authors to whom correspondence should be addressed.
Received: 9 June 2017 / Revised: 20 July 2017 / Accepted: 24 July 2017 / Published: 25 July 2017
(This article belongs to the Special Issue Analysis of Multispectral and Hyperspectral Data)
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Abstract

Fast and accurate grading of Chinese Cantonese sausage is an important concern for customers, organizations, and the industry. Hyperspectral imaging in the spectral range of 874–1734 nm, combined with chemometric methods, was applied to grade Chinese Cantonese sausage. Three grades of intact and sliced Cantonese sausages were studied, including the top, first, and second grades. Support vector machine (SVM) and random forests (RF) techniques were used to build two different models. Second derivative spectra and RF were applied to select optimal wavelengths. The optimal wavelengths were the same for intact and sliced sausages when selected from second derivative spectra, while the optimal wavelengths for intact and sliced sausages selected using RF were quite similar. The SVM and RF models, using full spectra and the optimal wavelengths, obtained acceptable results for intact and sliced sausages. Both models for intact sausages performed better than those for sliced sausages, with a classification accuracy of the calibration and prediction set of over 90%. The overall results indicated that hyperspectral imaging combined with chemometric methods could be used to grade Chinese Cantonese sausages, with intact sausages being better suited for grading. This study will help to develop fast and accurate online grading of Cantonese sausages, as well as other sausages. View Full-Text
Keywords: near-infrared hyperspectral imaging; Chinese Cantonese sausage; random forest; quality grading near-infrared hyperspectral imaging; Chinese Cantonese sausage; random forest; quality grading
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Gong, A.; Zhu, S.; He, Y.; Zhang, C. Grading of Chinese Cantonese Sausage Using Hyperspectral Imaging Combined with Chemometric Methods. Sensors 2017, 17, 1706.

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