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Predicting the microbial safety of food products stored in modified atmosphere packaging implies taking into account the effect of oxygen reduction on microbial growth. According to their respiratory-type, the micro-organisms are not impacted similarly by the oxygen concentration. The aim of this article was to quantify and model the oxygen effect on the growth rates of 5 bacterial species: Listeria monocytogenes and Bacillus weihenstephanensis (facultative anaerobic), Pseudomonas fluorescens (strict aerobic), Clostridium perfringens and Clostridium sporogenes (strict anaerobic). The results showed the oxygen concentration doesn't modify the behavior of both facultative anaerobic strains. The growth rate of P. fluorescens decreased with the oxygen concentration, but the effect is only noticeable when the oxygen concentration fell below 3% in the gaseous phase. Conversely, the oxygen acted as a growth inhibitor for both Clostridium species. But total inhibition is reached only for 3.26% and 6.61% respectively for C. sporogenes and C. perfringens. Two models have been fitted for both respiratory-types, the first is the Monod model considering oxygen as a substrate for growth, and the second is the classic inhibitory model based on minimal inhibitory concentration.

The effect of carbon dioxide, temperature, and pH on growth of Listeria monocytogenes and Pseudomonas fluorescens was studied, following a protocol to monitor microbial growth under a constant gas composition. In this way, the CO2 dissolution didn't modify the partial pressures in the gas phase. Growth curves were acquired at different temperatures (8, 12, 22 and 37 °C), pH (5.5 and 7) and CO2 concentration in the gas phase (0, 20, 40, 60, 80, 100% of the atmospheric pressure, and over 1 bar). These three factors greatly influenced the growth rate of L. monocytogenes and P. fluorescens, and significant interactions have been observed between the carbon dioxide and the temperature effects. Results showed no significant effect of the CO2 concentration at 37 °C, which may be attributed to low CO2 solubility at high temperature. An inhibitory effect of CO2 appeared at lower temperatures (8 and 12 °C). Regardless of the temperature, the gaseous CO2 is sparingly soluble at acid pH. However, the CO2 inhibition was not significantly different between pH 5.5 and pH 7. Considering the pKa of the carbonic acid, these results showed the dissolved carbon under HCO3- form didn't affect the bacterial inhibition. Finally, a global model was proposed to estimate the growth rate vs. CO2 concentration in the aqueous phase. This dissolved concentration is calculated according to the physical equations related to the CO2 equilibriums, involving temperature and pH interactions. This developed model is a new tool available to manage the food safety of MAP.

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.

The genetic diversity of two major yeast species found in cheese, Debaryomyces hansenii and Kluyveromyces marxianus, was analyzed within the yeast flora in French traditional cheesemaking. Based on the amplification of sequences separating long terminal repeat (LTR) retrotransposon sequences, a molecular typing method was developed for D. hansenii and K. marxianus. This method was applied to a total of 56 D. hansenii strains and 61 K. marxianus strains, mostly isolated during fermentation and ripening of traditional cheese from Normandy and Haute-Savoie (French Alps) regions. A total of 32 and 43 robust profiles were obtained for D. hansenii and K. marxianus, respectively. Cluster analysis confirmed the large genetic diversity already shown for D. hansenii and revealed an even larger diversity for K. marxianus. After its use with Saccharomyces cerevisiae, the inter-LTR PCR proved to be efficient to discriminate between strains of the two species, D. hansenii and K. marxianus, isolated from the same ecological niches, confirming the high intra-specific variability of species found in cheese. This strain typing could not correlate the analyzed strains with their origin, would it be the cheese type, the cheese-making facility or the cheese batch, showing a high discrimination power. The method described here will provide a fast and reliable tool for the biodiversity study of these two major cheese yeasts.

Predicting microbial safety of fresh products in modified atmosphere packaging implies to take into account the dynamic of O2, CO2 and N2 exchanges in the system and its effect on microbial growth. In this paper a mechanistic model coupling gas transfer and predictive microbiology was validated using dedicated challenge-tests performed on poultry meat, fresh salmon and processed cheese, inoculated with either Listeria monocytogenes or Pseudomonas fluorescens and packed in commercially used packaging materials (tray + lid films). The model succeeded in predicting the relative variation of O2, CO2 and N2 partial pressure in headspace and the growth of the studied microorganisms without any parameter identification. This work highlighted that the respiration of the targeted microorganism itself and/or that of the naturally present microflora could not be neglected in most of the cases, and could, in the particular case of aerobic microbes contribute to limit the growth by removing all residual O2 in the package. This work also confirmed the low sensitivity of L. monocytogenes toward CO2 while that of P. fluorescens permitted to efficiently prevent its growth by choosing the right combination of packaging gas permeability value and initial % of CO2 initially flushed in the pack.

L'industrie agroalimentaire et les pouvoirs publics sont contraints a une vigilance accrue sur la securite microbiologique des aliments proposes au consommateur en raison des graves consequences (cout humain, pertes commerciales et pertes d'image) que peut entrainer une non-conformite sur une marque ou un type de produits. Les acteurs des filieres agro-industrielles doivent repondre aux attentes du marche et etre capables d'assumer pleinement leur responsabilite quant a la securite de leur fabrication. La securite microbiologique des produits alimentaires exige des connaissances solides et complexes sur la contamination naturelle des matieres premieres et des produits transformes, sur la capacite de survie des micro-organismes au cours des traitements de transformation, et leur developpement aux differents stades de conservation. C'est dans ce contexte que s'inscrit le projet Sym'Previus ; il s'agit d'un outil d'aide a la prevision de l'evolution des populations microbiennes dans les aliments, a l'usage des professionnels de l'alimentation. Disponible sur Internet, cet outil rassemble d'une part, une base de donnees issues de la bibliographie, de l'industrie et de programmes de recherche, et d'autre part, un module de simulation du comportement microbien s'appuyant sur les outils actuels de la microbiologie previsionnelle. Hormis la possibilite de prevoir le niveau de contamination d'un microorganisme a un instant de la vie d'un produit (de la fabrication a la consommation), Sym'Previus permet d'optimiser un procede, une chaine du froid, mais aussi d'accompagner la formulation et le developpement d'un nouveau produit. = Predictive microbiology can be divided into two groups of models, named primary and secondary models. Primary models describe the evolution of the bacterial population with time. These models use parameters which may vary as the environmental factors change. Secondary models describe how those parameters vary with the environmental factors. Sym'Previus meets the French expertise in Predictive Microbiology of major food companies, technical centres and public research institutes. This project aims at proposing an assistance in the managing of the food safety. It is composed from two main softwares. Firstly, a database where information on the behaviour of microorganisms in/on foods and natural contamination of foods are structured. A query system, called MIEL, specifically developed for the database, allows to formulate specific interrogation with a specific selection of food and microorganisms. Secondly, a user-friendly software simulates the growth of microorganisms in food matrix.

The definitive version is available at ww3.interscience.wiley.com.; International audience; Aims: In this study, the heat resistance of coliform species isolated from cooked ham and ready-made meals was determined. Methods and Results: Thirteen coliform strains belonging to 12 different species were studied using laboratory medium in order to determine δ (first decimal reduction time) and zT values temperature increase leading to a 10-fold reduction of δ) using the Weibull model. For seven strains, δ-values were determined at temperatures ranging from 55 to 60°C, with, δ values between 0-52 and 2-98 min, at 59°C. For the other six strains, lower temperature values were determined with δ-values ranging from 0-47 to 1-64 min at 54°C. zT values calculated for the 13 strains were 3-1 to 7-5°C. For eight strains, plotting of the log of survivors was not linear but rather showed shoulders or shoulders and tails. Conclusions: Coliform species were sensitive to heat treatment with a decimal reduction time under 2 min at 60°C. Significance and Impact of the Study: The better knowledge of coliform heat resistance by determining thermal resistance parameters with confidence intervals will be useful for evaluating the efficiency of industrial thermal processes.

dans le cadre de la 4. International Conference on Predictive Modelling in Foods à Quimper du 15-19 juin 2003; Temperature effect on growth rates of Listeria monocytogenes, Salmonella, Escherichia coli, Clostridium perfringens and Bacillus cereus, was studied. Growth rates were obtained in laboratory medium by using a binary dilutions method in which 15 optical density curves were generated to determine one mu value. The temperature was in the range from 2 to 48 degrees C, depending on the bacterial species. Data were analysed after a square root transformation. No large difference between the strains of a same species was observed, and therefore all the strains of a same species were analysed together with the same secondary model. The variability of the residual error, including both measurements errors and biological strain difference, was homogenous for sub-optimal temperature values. To represent this variability in bacterial kinetic simulation, the 95% confidence interval based on an asymptotic Normal distribution, around the growth rate value was determined. With this modelling approach, the behaviour of bacterial species on food, irrespective of the strain or the laboratory, was described. This growth simulation with confidence limits has several applications, such as to facilitate comparisons between a challenge-test and simulation results, and, to appreciate if the temperature change has or has not a significant effect on a bacterial growth profile, with regard to the uncontrolled factors. The integration of this piece of work in the Sym&39;Previus software is now in process. Results obtained in five French laboratories will be extended by working on new food and new microbial species and improved by further work on variability estimation.

International audience; A stochastic modelling approach was developed to describe the distribution of Listeria monocytogenes contamination in foods throughout their shelf life. This model was designed to include the main sources of variability leading to a scattering of natural contaminations observed in food portions: the variability of the initial contamination, the variability of the biological parameters such as cardinal values and growth parameters, the variability of individual cell behaviours, the variability of pH and water activity of food as well as portion size, and the variability of storage temperatures. Simulated distributions of contamination were compared to observed distributions obtained on 5 day-old and 11 day-old cheese curd surfaces artificially contaminated with between 10 and 80 stressed cells and stored at 14°C, to a distribution observed in cold smoked salmon artificially contaminated with approximately 13 stressed cells and stored at 8°C, and to contaminations observed in naturally contaminated batches of smoked salmon processed by 10 manufacturers and stored for 10 days a 4°C and then for 20 days at 8°C. The variability of simulated contaminations was close to that observed for artificially and naturally contaminated foods leading to simulated statistical distributions properly describing the observed distributions. This model seems relevant to take into consideration the natural variability of processes governing the microbial behaviour in foods and is an effective approach to assess, for instance, the probability to exceed a critical threshold during the storage of foods like the limit of 100 CFU/g in the case of L. monocytogenes.

5th International Conference on Predictive Modelling in Foods; International audience; Time temperature integrators or indicators (TTIs) are effective tools making the continuous monitoring of the time temperature history of chilled products possible throughout the cold chain. Their correct setting is of critical importance to ensure food quality. The objective of this study was to develop a model to facilitate accurate settings of the CRYOLOG biological TTI, TRACEO®. Experimental designs were used to investigate and model the effects of the temperature, the TTI inoculum size, pH, and water activity on its response time. The modelling process went through several steps addressing growth, acidification and inhibition phenomena in dynamic conditions. The model showed satisfactory results and validations in industrial conditions gave clear evidence that such a model is a valuable tool, not only to predict accurate response times of TRACEO®, but also to propose precise settings to manufacture the appropriate TTI to trace a particular food according to a given time temperature scenario.

An experimental protocol to validate secondary-model application to foods was suggested. Escherichia coli , Listeria monocytogenes , Bacillus cereus , Clostridium perfringens , and Salmonella were observed in various food categories, such as meat, dairy, egg, or seafood products. The secondary model validated in this study was based on the gamma concept, in which the environmental factors temperature, pH, and water activity (aw) were introduced as individual terms with microbe-dependent parameters, and the effect of foodstuffs on the growth rates of these species was described with a food- and microbe-dependent parameter. This food-oriented approach was carried out by challenge testing, generally at 15 and 10°C for L. monocytogenes , E. coli , B. cereus , and Salmonella and at 25 and 20°C for C. perfringens . About 222 kinetics in foods were generated. The results were compared to simulations generated by existing software, such as PMP. The bias factor was also calculated. The methodology to obtain a food-dependent parameter (fitting step) and therefore to compare results given by models with new independent data (validation step) is discussed in regard to its food safety application. The proposed methods were used within the French national program of predictive microbiology, Sym′Previus, to include challenge test results in the database and to obtain predictive models designed for microbial growth in food products.