Résumé
The selection of a food packaging solution is a multi-criteria process and compliance with these criteria is not always straightforward. Decision Support Systems (DSS) are elaborated numerical tools designed to help users in such decision-making processes. For food packaging, food needs must guide the decision process. However, this knowledge is not always available, or is scattered across the scientific literature and industry. The aim of this study was to provide an innovative DSS relying on a structured database allowing the collection and compilation of food and packaging material data for a simpler and more comprehensive food requirement-driven approach. It also relies on queries allowing this data to be combined to suggest optimal packaging materials for a food product. The novelty of this DSS relies also on the possibility to be used in a reverse mode, to provide food packaging applications for a material with given properties. The DSS was validated on three case studies: strawberries and processed spreadable cheese, as food case studies for which optimal packaging materials were provided, and a polymer-coated cardboard, as packaging material, for which food applications were found. This paper shows the relevance of the DSS architecture and process. The case studies highlighted the benefit of considering not only food sensitivities, but also storage temperature and desired shelf life as inputs to the DSS, demonstrated the ability of the tool to retrieve near-optimal solutions when no optimal solution was found, and the potential to find more sustainable alternative packaging materials to the current benchmark.