Résumé
Preserving fresh fruits and vegetables after harvest and during further storage is an important issue in the food industry. Beyond respect of the chill chain, modified atmosphere is an efficient way to delay senescence and spoilage without using controversial preservatives compounds or technologies. Modified atmosphere packaging (MAP) relies on modification of the atmosphere inside the package in order to extend food shelf life by reducing physiological degradation rate. MAP is achieved by the interplay of two processes: (1) the transfer of gases through the packaging and (2) the respiration of the product. MAP can be achieved by matching the film permeation rate (namely O2 and CO2 permeabilities) with the respiration rate of the product. A mathematical model (www.tailorpack.com) has been developed to design MAP for fresh fruits and vegetables. Such numerical tool simplify the package design steps by allowing to predict in advance the required window of packaging permeability for maintaining the quality and safety of the packed food. However, such a mathematical model required several input parameters such as maximal respiration rates that are obtained from experimental data and are characterized by high uncertainties due to the biological variation. Although uncertainty propagation during MAP modeling presents significant concerns, this subject has been seldom considered. It would be nevertheless indispensable to consider it in the development of a complete decision support system for the design of fresh products packaging. In this work, we present a complete decision support system (DSS) that aims at helping decision makers to find the best packaging material for a given fruit or vegetable. This DSS is composed of two distinct parts. The first part consists in an optimization system that uses the MAP mathematical model and food parameters to determine optimal permeabilities of packaging. In order to integrate existing uncertainties in the study and still keep a reasonable time to perform the optimization task, we propose to use an approach based on interval analysis rather than the more classical probabilistic approach. The approach has the advantage to make a minimal amount of assumption and to require only a few evaluations of the model. The results of this uncertainty studies are optimal values of permeabilities described by fuzzy sets. The second part of the DSS consists in a database where is stored information concerning various packaging material. The system considers, among other criteria, fuzzy sets obtaining in the first part to interrogate the database, and can consider other user preferences expressed by fuzzy sets (i.e., gradual preferences). It allows to differentiate between compulsory requirements (i.e. that the users absolutely wants to be satisfied) and desirable requirements (i.e. that users would like to satisfy, if possible).