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

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.
Original languageEnglish
JournalFood and Bioprocess Technology
Volume6
Issue number9
Pages (from-to)2268-2279
ISSN1935-5130
DOIs
Publication statusPublished - 2013

Keywords

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

Cite this

Dissing, B. S., Papadopoulou, O. S., Tassou, C., Ersbøll, B. K., Carstensen, J. M., Z. Panagou, E., & Nychas, G-J. (2013). Using Multispectral Imaging for Spoilage Detection of Pork Meat. Food and Bioprocess Technology, 6(9), 2268-2279. https://doi.org/10.1007/s11947-012-0886-6