Journal Title
Title of Journal: Food Bioprocess Technol
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Abbravation: Food and Bioprocess Technology
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Authors: Anguo Xie DaWen Sun Zhiwei Zhu Hongbin Pu
Publish Date: 2016/07/14
Volume: 9, Issue: 9, Pages: 1444-1454
Abstract
The freezing medium temperature and the freezing rate are two important parameters that affect the quality of frozen product The traditional measurement of freezing parameters will destroy the integrity of the sample and can only be implemented during the freezing process This study aimed to develop nondestructive hyperspectral imaging HSI methods to rapidly detect freezing parameters The spectral features of the porcine meat samples in frozen state were studied in which 90 pieces of porcine samples were frozen by different methods with different freezing medium air and liquid at different temperatures from −20 to −120 °C and freezing rates from 0307 to 51 cm/h The result showed that the freezing process would strongly influence spectra of the frozen sample The reflectance increased with the decrease in freezing medium temperatures and the negative correlation reached a highly significant level The freezing parameters did not change the position of the spectral peaks but altered the spectral intensity Most changes were near 1070 1172 1420 1586 and 1890 nm The partial leastsquares regression spectral models exhibited good performance for predicting freezing medium temperatures leftR c2=0898R p2=0844right and freezing rates leftR c2=0879R p2=0829right The study confirmed that could be used for measuring freezing parameters of frozen product This novel method will not damage the sample integrity and measurement can be implemented anytime rather than only during the freezing process by traditional methodsThe authors gratefully acknowledge the Guangdong Province Government China for its support through the program “Leading Talent of Guangdong Province DaWen Sun” This research was also supported by the National Key Technologies RD Program 2014BAD08B09 the International ST Cooperation Programme of China 2015DFA71150 the International ST Cooperation Projects of Guangdong Province 2013B051000010 the Natural Science Foundation of Guangdong Province 2014A030313244 the Key Projects of Administration of Ocean and Fisheries of Guangdong Province A201401C04 and the Collaborative Innovation Major Special Projects of Guangzhou City 201508020097 The authors also appreciate the assistance provided by Qian Yang and Hai Gao in the experiment and the contribution of Paul B McNulty Emeritus Professor of Biosystems Engineering University College Dublin Ireland in editing this manuscript
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