Using Multispectral Imaging for Spoilage Detection of Pork Meat |
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| 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. |
| Keywords | Multispectral imaging, Meat spoilage, Chemometrics, Computational biology, Meat quality, Non-invasive methods, Converging technologies, Predictive modelling |
| Type | Journal paper [With referee] |
| Journal | Food and Bioprocess Technology |
| Year | 2013 Vol. 6 No. 9 pp. 2268-2279 |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics |