Using Multispectral Imaging for Spoilage Detection of Pork Meat

被引:100
作者
Dissing, Bjorn Skovlund [1 ]
Papadopoulou, Olga S. [2 ,3 ]
Tassou, Chrysoula [3 ]
Ersboll, Bjarne Kjaer [1 ]
Carstensen, Jens Michael [1 ]
Panagou, Efstathios Z. [2 ]
Nychas, George-John [2 ]
机构
[1] Tech Univ Denmark, Inst Informat & Math Modelling, DK-2800 Lyngby, Denmark
[2] Agr Univ Athens, Lab Microbiol & Biotechnol Foods, Dept Food Sci & Technol, GR-11855 Athens, Greece
[3] Hellen Agr Org Demeter, Inst Technol Agr Prod, Lycovrissi 14123, Greece
关键词
Multispectral imaging; Meat spoilage; Chemometrics; Computational biology; Meat quality; Non-invasive methods; Converging technologies; Predictive modelling; TRANSFORM INFRARED-SPECTROSCOPY; ATMOSPHERE PACKAGING CONDITIONS; ARTIFICIAL NEURAL-NETWORKS; QUANTITATIVE DETECTION; MICROBIAL SPOILAGE; VISION TECHNOLOGY; MINCED PORK; BEEF; QUALITY; STORAGE;
D O I
10.1007/s11947-012-0886-6
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
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.
引用
收藏
页码:2268 / 2279
页数:12
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