Using Multispectral Imaging for Spoilage Detection of Pork Meat

Bjørn Skovlund Dissing, Olga S. Papadopoulou, Chrysoula Tassou, Bjarne Kjær Ersbøll, Jens Michael Carstensen, Efstathios Z. Panagou, George-John Nychas

Research output: Contribution to journalJournal articleResearchpeer-review


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.
Original languageEnglish
JournalFood and Bioprocess Technology
Issue number9
Pages (from-to)2268-2279
Publication statusPublished - 2013


  • Multispectral imaging
  • Meat spoilage
  • Chemometrics
  • Computational biology
  • Meat quality
  • Non-invasive methods
  • Converging technologies
  • Predictive modelling


Dive into the research topics of 'Using Multispectral Imaging for Spoilage Detection of Pork Meat'. Together they form a unique fingerprint.

Cite this