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Appl. Sci. 2017, 7(3), 213; doi:10.3390/app7030213

A Nondestructive Real-Time Detection Method of Total Viable Count in Pork by Hyperspectral Imaging Technique

College of Engineering, China Agricultural University, 17 Qinghua East Road, Haidian, Beijing 100083, China
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Author to whom correspondence should be addressed.
Academic Editor: Kuanglin Kevin Chao
Received: 10 November 2016 / Revised: 10 February 2017 / Accepted: 14 February 2017 / Published: 23 February 2017
(This article belongs to the Special Issue Applications of Hyperspectral Imaging for Food and Agriculture)
View Full-Text   |   Download PDF [2270 KB, uploaded 23 February 2017]   |  

Abstract

A nondestructive method was developed for assessing total viable count (TVC) in pork during refrigerated storage by using hyperspectral imaging technique in this study. The hyperspectral images in the visible/near-infrared (VIS/NIR) region of 400–1100 nm were acquired for fifty pork samples, and their VIS/NIR diffuse reflectance spectra were extracted from the images. The reference values of TVC in pork samples were determined by classical microbiological plating method. Both partial least square regression (PLSR) model and support vector machine regression model (SVR) of TVC were built for comparative analysis to achieve better results. Different transformation methods and filtering methods were applied to improve the models. The results show that both the optimized PLSR model and SVR model can predict the TVC very well, while the SVR model based on second derivation was better, which achieved with RP (correlation coefficient of prediction set) = 0.94 and SEP (standard error of prediction set) = 0.4570 log CFU/g in the prediction set. An image processing algorithm was then developed to transfer the prediction model to every pixel of the image of the entire sample; the visualizing map of TVC would be displayed in real-time during the detection process due to the simplicity of the model. The results demonstrated that hyperspectral imaging is a potential reliable approach for non-destructive and real-time prediction of TVC in pork. View Full-Text
Keywords: pork; total viable count; hyperspectral imaging; visible/near-infrared pork; total viable count; hyperspectral imaging; visible/near-infrared
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zheng, X.; Peng, Y.; Wang, W. A Nondestructive Real-Time Detection Method of Total Viable Count in Pork by Hyperspectral Imaging Technique. Appl. Sci. 2017, 7, 213.

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