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Meta-analysis of Kinetic Parameter Uncertainty on Shelf Life Prediction in the Frozen Fruits and Vegetable Chain

  • Maria C. GiannakourouEmail author
  • Petros S. Taoukis
Review Article
  • 25 Downloads

Abstract

Most studies on frozen foods’ deterioration focus on measurements of selected quality determining indices at the reference frozen storage conditions at limited time points (e.g., 6 and 12 months). This information is not sufficient to predict the frozen system behavior under a different storage temperature, or under the real, dynamic conditions of the actual cold chain. For this purpose, a systematic kinetic study is essential; additionally, the real uncertainty of model parameters needs to be taken into account, in order to proceed to realistic shelf life estimations. In this review work, published findings on kinetic data of deterioration of frozen food of plant origin were analyzed. Kinetic parameters (e.g., activation energy, shelf life, etc.) were extracted and some of them incorporated to a further investigation. The scope is to provide a critical assessment and a comprehensive meta-analysis of the literature information on quality loss modeling of frozen foods. Therefore, common quality indices for specific systems are reviewed, fundamental methodologies used to build kinetic models are assessed, and alternative approaches to improve practical applications of these models are proposed. Alternative methodologies are described in order to take into account the calculated uncertainty of models’ parameters when assessing the remaining shelf life of the product at any point within the cold chain. This was implemented in a FORTRAN code through a Monte Carlo scheme, on literature data of vitamin C loss in different frozen matrices, as well as for other quality indices (e.g., color). Results demonstrated the improved predictions obtained, with broader and more realistic confidence intervals.

Keywords

Quality kinetics Meta-analysis Frozen foods Parameter uncertainty Cold chain 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Food Science and TechnologyUniversity of West Attica (former Technological Educational Institute of Athens)EgaleoGreece
  2. 2.School of Chemical Engineering, Laboratory of Food Chemistry and TechnologyNational Technical University of AthensAthensGreece

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