MAP-OPT: A software for supporting decision-making in the field of modified atmosphere packaging of fresh non respiring foods

Abstract In this paper,we present the implementation of a dedicated software, MAP-OPT, for optimising the design of ModifiedAtmosphere Packaging of refrigerated fresh, nonrespiring food products. The core principle of this software is to simulate the impact of gas (O2/CO2) exchanges on the growth of gas-sensitive microorganisms in the packed food system. In its simplest way, this tool, associated with a data warehouse storing food, bacteria and packaging properties, allows the user to explore his/her system in a user-friendly manner by adjusting/changing the pack geometry, packaging material and gas composition (mixture of O2/CO2/N2). Via the @Web application, the data warehouse associated with MAP-OPT is structured by an ontology, which allows data to be collected and stored in a standardized format and vocabulary in order to be easily retrieved using a standard querying methodology. In an optimisation approach, the MAP-OPT software enables to determine the packaging characteristics (e.g. gas permeability) suitable for a target application (e.g. maximal bacterial population at the best-before-date). These targeted permeabilities are then used to query the packaging data warehouse using the@Web applicationwhich proposes a ranking of the most satisfying materials for the target application (i.e. packaging materialswhose characteristics are the closest to the target ones identified by the MAP-OPT software). This approach allows a more rational dimensioning of MAP of non-respiring food products by selecting the packaging material fitted to “just necessary” (and not by default, that with the greatest barrier properties). A working example of MAP dimensioning for a strictly anaerobic, CO2-sensitive microorganism, Pseudomonas fluorescens, is given to highlight the usefulness of the software.

[1]  John D. Floros,et al.  Introduction to modified atmosphere packaging , 2005 .

[2]  Nathalie Gontard,et al.  Modeling of Active Modified Atmosphere Packaging of Endives Exposed to Several Postharvest Temperatures , 2005 .

[3]  Nathalie Gontard,et al.  Role of packaging in the smorgasbord of action for sustainable food consumption , 2013 .

[4]  Nathalie Gontard,et al.  Predictive Microbiology Coupled with Gas (O2 /CO2 ) Transfer in Food/Packaging Systems: How to Develop an Efficient Decision Support Tool for Food Packaging Dimensioning. , 2015, Comprehensive reviews in food science and food safety.

[5]  R. Simpson,et al.  DESIGNING A MODIFIED ATMOSPHERE PACKAGING SYSTEM FOR FOODSERVICE PORTIONS ON NONRESPIRING FOODS: OPTIMAL GAS MIXTURE AND FOOD/HEADSPACE RATIO , 2004 .

[6]  M. G. Johnson,et al.  Growth, survival, proliferation and pathogenesis of Listeria monocytogenes under low oxygen or anaerobic conditions: a review. , 2009, Anaerobe.

[7]  J P Flandrois,et al.  Convenient Model To Describe the Combined Effects of Temperature and pH on Microbial Growth , 1995, Applied and environmental microbiology.

[8]  Liliana Ibanescu,et al.  Fuzzy Web Data Tables Integration Guided by an Ontological and Terminological Resource , 2013, IEEE Transactions on Knowledge and Data Engineering.

[9]  L. Guillier,et al.  Growth rate and growth probability of Listeria monocytogenes in dairy, meat and seafood products in suboptimal conditions , 2005, Journal of applied microbiology.

[10]  Ricardo Simpson,et al.  Mass transfer of CO2 in MAP systems: Advances for non-respiring foods , 2009 .

[11]  V. Guillard,et al.  Validation of a predictive model coupling gas transfer and microbial growth in fresh food packed under modified atmosphere. , 2016, Food microbiology.

[12]  Paolo Masi,et al.  Modelling the respiration rate of fresh-cut Annurca apples to develop modified atmosphere packaging. , 2009 .

[13]  J P Guyonnet,et al.  Modelling the growth kinetics of Listeria as a function of temperature, pH and organic acid concentration. , 2002, International journal of food microbiology.

[14]  József Baranyi,et al.  ComBase: a common database on microbial responses to food environments. , 2004, Journal of food protection.

[15]  Benno Kunz,et al.  Modeling the respiration of Pseudomonas fluorescens on solid-state lettuce-juice agar , 2006 .

[16]  V. Guillard,et al.  Mechanistic model coupling gas exchange dynamics and Listeria monocytogenes growth in modified atmosphere packaging of non respiring food. , 2015, Food microbiology.

[17]  Frank M. Rombouts,et al.  A decision support system for prediction of microbial spoilage in foods , 2005, Journal of Industrial Microbiology.

[18]  Thomas R. Gruber,et al.  A Translation Approach to Portable Ontologies , 1993 .

[19]  Frank Devlieghere,et al.  Growth of Listeria monocytogenes in modified atmosphere packed cooked meat products: a predictive model , 2001 .

[20]  Ricardo Simpson,et al.  MATHEMATICAL MODEL to PREDICT EFFECT of TEMPERATURE ABUSE IN MAP SYSTEMS APPLIED to PACIFIC HAKE (MERLUCCIUS AUSTRALIS) , 2003 .

[21]  L. Rosso,et al.  Modélisation et microbiologie prévisionnelle : élaboration d'un nouvel outil pour l'agro-alimentaire , 1995 .

[22]  B Leporq,et al.  The "Sym'Previus" software, a tool to support decisions to the foodstuff safety. , 2005, International journal of food microbiology.

[23]  Nathalie Gontard,et al.  Fresh food packaging design: A requirement driven approach applied to strawberries and agro-based materials , 2013 .

[24]  Susana C. Fonseca,et al.  Modelling respiration rate of fresh fruits and vegetables for modified atmosphere packages: a review , 2002 .

[25]  Sébastien Destercke,et al.  Evaluating Data Reliability: An Evidential Answer with Application to a Web-Enabled Data Warehouse , 2013, IEEE Transactions on Knowledge and Data Engineering.

[26]  Madalina Croitoru,et al.  A Decision Support System to design modified atmosphere packaging for fresh produce based on a bipolar flexible querying approach , 2015, Comput. Electron. Agric..