Using Multispectral Imaging for Spoilage Detection of Pork Meat

被引:1
|
作者
Bjørn Skovlund Dissing
Olga S. Papadopoulou
Chrysoula Tassou
Bjarne Kjaer Ersbøll
Jens Michael Carstensen
Efstathios Z. Panagou
George-John Nychas
机构
[1] Technical University of Denmark,Institute for Informatics and Mathematical Modelling
[2] Agricultural University of Athens,Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Technology
[3] Institute of Technology of Agricultural Products,Hellenic Agricultural Organisation ‘Demeter’
来源
关键词
Multispectral imaging; Meat spoilage; Chemometrics; Computational biology; Meat quality; Non-invasive methods; Converging technologies; Predictive modelling;
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摘要
The quality of stored minced pork meat was monitored using a rapid multispectral imaging device to quantify the degree of spoilage. Bacterial counts of a total of 155 meat samples stored for up to 580 h have been measured using conventional laboratory methods. Meat samples were maintained under two different storage conditions: aerobic and modified atmosphere packages as well as under different temperatures. Besides bacterial counts, a sensory panel has judged the spoilage degree of all meat samples into one of three classes. Results showed that the multispectral imaging device was able to classify 76.13 % of the meat samples correctly according to the defined sensory scale. Furthermore, the multispectral camera device was able to predict total viable counts with a standard error of prediction of 7.47 %. It is concluded that there is a good possibility that a setup like the one investigated will be successful for the detection of spoilage degree in minced pork meat.
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页码:2268 / 2279
页数:11
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