The “Sym'Previus” software, a tool to support decisions to the foodstuff safety

Abstract

Describing the Sym'Previus project, the software and its deliverable facilities is the aim of this present paper. This software concerns all the partners of the food industry who are involved in the management of food safety and allows food-borne pathogen behaviour in food to be predicted, as function of the environment (nature of the food, manufacturing process, conditions of conservation). This analysis of microbial behaviour has been possible thanks to the progress made in predictive microbiology since the 1980s. Sym'Previus offers to food industry professionals and their partners the possibility of applying this progress, by giving access to a database, to simulation systems and expertise.

The MIEL system: Uniform interrogation of structured and weakly-structured imprecise data

“…The communication between both subsystems and the MIEL interface is done through the TCP protocole via a communication module, written in C. Figure 17 and 18 show respectively the window allowing the expression of a query in the MIEL system and the window presenting the results to the user. The MIEL system has been successfully presented to our microbiologist partners and is now operational (Buche et al, 2003) a business plan which aims at commercializing a new expert tool in food predictive microbiology, which includes the MIEL system and a simulation tool (Leporq et al, 2005). The conceptual graph model appears to be an asset for the MIEL system since it allows non-specialists to add heterogeneous data into our database.…”

Principles and Methodologies for the Determination of Shelf-Life in Foods

“…Behind predictive software programs are the raw data upon which the models are built. Some of the most popular software are: GInaFiT (Geeraerd, et al, 2005), where different inactivation models are available (http://cit.kuleuven.be/ biotec/ downloads.php); DMFit (Baranyi & Roberts, 1994), with implementation of a dynamic growth primary model (http://www.combase.cc/index.php/en/downloads/category/11-dmfit); Pathogen Modeling Program (Buchanan, 1993), which incorporates a variety of models of different pathogens in broth culture and foods (http://pmp.arserrc.gov/ PMPOnline.aspx); Seafood Spoilage and Safety Predictor (SSSP) , offering models for specific spoilage microorganisms and also for L. monocytogenes in seafood (http://sssp.dtuaqua.dk/); ComBase , a predictive tool for important foodborne pathogenic and spoilage microorganisms (http:// www.combase.cc / index.php/en/predictive-models); Sym´Previus (Leporq et al, 2005), a tool with a collection of models and data to be applied in the food industry context, e.g. strengthening HACCP plans, developing new products, quantifying microbial behavior, determining shelf-lives and improving safety (http://www.symprevius.net/); Microbial Responses Viewer (Koseki, 2009), a new database consisting of microbial growth/no growth data derived from ComBase, and also modelling of the specific growth rate of microorganisms as a function of temperature, pH and a w (http:// mrv.…”

A review on growth/no growth Salmonella models

“…Sym'Previous (Leporq, Membré, Dervin, Buche, & Guyonnet, 2005) software offers a microbial database and a group of mathematical models, including a module of probabilistic models, which simulates the evolution of a particular initial microbial load throughout the food product's shelf-life and indicates the probability of exceeding a critical threshold at different stages of its shelf-life. By using tertiary models or computational applications of predictive models, food processors can easily assess appropriate food designs and processing conditions.…”

“…Knowledge of the rate at which Salmonella grows under different conditions (growth models) is very important, but even more important is to know if Salmonella is able to grow in foods with a particular combination of environmental factors, especially because Salmonella, as microbiological safety criterion, must be absence in a wide variety of foods (Regulation (EC) No. 2073No. / 2005.…”