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Using Multispectral Imaging for Spoilage Detection of Pork Meat
Authors:Bjørn Skovlund Dissing  Olga S. Papadopoulou  Chrysoula Tassou  Bjarne Kjaer Ersbøll  Jens Michael Carstensen  Efstathios Z. Panagou  George-John Nychas
Affiliation:1. Institute for Informatics and Mathematical Modelling, Technical University of Denmark, Richard Petersens Plads, Building 321, 2800, Kgs Lyngby, Denmark
2. Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Technology, Agricultural University of Athens, Iera Odos 75, 11855, Athens, Greece
3. Hellenic Agricultural Organisation ‘Demeter’, Institute of Technology of Agricultural Products, Sofokli Venizelou 1, Lycovrissi, 141 23, Greece
Abstract: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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