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 microorganisms 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 weihen-stephanensis (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 degrees 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 degrees C, which may be attributed to low CO2 solubility at high temperature. An inhibitory effect of CO2 appeared at lower temperatures (8 and 12 degrees 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. (C) 2017 Elsevier Ltd. All rights reserved.

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.

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.

By interacting with pathogens, lactic acid bacteria (LAB) are able to contribute to food safety. By means of their lactic acid production which induces pH decrease, LAB influence the growth of pathogens. The aim of this study is to model and simulate lactic acid production, pH evolution, according to carbohydrate concentration in media, temperature, water activity and ratio of both population.

It is of crucial importance for Ready-To-Eat (RTE) foodstuffs producers to guarantee the quality and safety of their products under the cold chain variations related to different time temperature profiles. Experimental designs were used to investigate and model the effects of temperature on safety and quality attributes of selected RTE meat products. Three types of RTE sliced pork products (cooked ham, cooked pate and smoked ham) were stored at different temperatures (5, 8, 12 and 15 degrees C) up to 6 weeks. Microbiological and physico-chemical attributes were followed. Growth parameters of Listeria monocytogenes were investigated by challenge testing for the three RTE products at the four temperatures. Two lactic acid bacteria (Lactobacillus sakei and Leuconostoc mesenteroides) were also investigated by challenge testing but only for cooked ham and cooked pate at 8 degrees C. Changes in quality indicators including colour, texture and water content, water activity and water dripping were evaluated over storage time for the three RTE products. Spoilage experiments were conducted (at 2, 8, 12, 15 degrees C for 48 days) on cooked ham and the production of ethanol, as a representative volatile deriving from bacterial metabolism, was correlated to bacterial outgrowth. Growth parameters of the three strains for the given food were mathematically modelled and validation tests were performed for L. monocytogenes in cooked ham and cooked pate. Physico-chemical attributes were not significantly affected by time temperature storage. The production of ethanol on spoiled cooked ham was related to growth of lactic acid bacteria, especially Leuconostoc. A threshold value of ethanol concentration was defined in relation with a threshold count numbers of LAB under the conditions studied. (C) 2014 Elsevier Ltd. All rights reserved.

Predicting microbial safety of fresh products in Modified Atmosphere Packaging (MAP) systems implies to take into account the dynamic of O2 and CO2 exchanges in the system and its effect on microbial growth. In this purpose we coupled mathematical models of gas transfer (permeation through packaging and solubilisation / diffusion within food) with predictive microbiology models that take into account the effect of CO2 and O2 partial pressure in headspace and corresponding dissolved concentrations in the food. This mechanistic model was validated in simplified and in real conditions using dedicated challenge-tests performed on poultry meat, fresh salmon and processed cheese, inoculated with either Listeria monocytogenes or Pseudomonas fluorescens. Once validated, this model could be used as a Decision Support Tool in order to optimize the initial packaging atmosphere (level of O2 and CO2) and / or the geometry (ratio headspace volume to food mass). This tool could also be used to identify the packaging gas permeability the most suitable for maintaining the targeted % of gas initially flushed in the pack within a given tolerance. This approach permits a better dimensioning of MAP of fresh produce by selecting the packaging material fitted to “just necessary” (and not by default the most barrier one). The connexion of this model with dedicated databases gathering gas permeabilities of commonly used packaging materials allows us to obtain as output a ranking of the most suitable materials. This tool would be very useful for all stakeholders of the fresh produce chain. A demonstration of this Decision Support Tool is here proposed with the pipeline between mathematical models and related databases.

Les performances des conditionnements sous gaz de denrees alimentaires perissables dependent principalement de la composition en gaz, de la qualite microbiologique initiale de l’aliment et de la nature de l’emballage. Les durees de vie des produits alimentaires sont limitees par le developpement bacterien et son impact sur la securite sanitaire et les proprietes organoleptiques. La solubilite du gaz, sa diffusivite dans l'aliment determineront egalement son efficacite. La permeabilite de l'emballage agira egalement sur la pression partielle en gaz. Des developpements informatiques et des methodes analytiques ont ete utilisees pour collecter les donnees necessaires a l'etablissement de modele mathematiques.....

Quantification of the impact of refrigeration technologies in terms of the quality of refrigerated food, energy usage, and environmental impact is essential to assess cold chain sustainability. In this paper, we present a software tool QEEAT (Quality, Energy and Environmental Assessment Tool) for evaluating refrigeration technologies. As a starting point, a reference product was chosen for the different main food categories in the European cold chain. Software code to predict the products temperature, based on validated heat and mass transfer models, were written in Matlab (The Mathworks Inc., Natick, USA). Also, based on validated kinetic models for the different quality indicators of the reference products, (including fruit, meat, fish, vegetables and dairy products) a software code was written to calculate the quality and safety evolutions of the food product, using the predicted product temperature as input. Finally, software code to calculate the energy usage and Total Equivalent Warming Impact (TEWI) value of different refrigeration technologies was also written in Matlab. All three software codes were integrated, and a graphical user interface was developed. Using the QEEAT, a user can tailor a cold chain scenario by adding cold chain blocks (different steps of a cold chain) and simulating the quality evolution, energy use and emission throughout the chain. Also, the user can modify properties of a cold chain block, by selecting different technologies, or changing set point values. Defaults are provided for input values, and are based on the current practice, and obtained by extensive literature studies and consultation with different experts of the cold chain. Furthermore, the user can build and simulate several chains simultaneously, allowing him/her to compare different chains with respect to quality, energy and emission.

Molds are responsible for spoilage of bakery products during storage. A modeling approach to predict the effect of water activity (aw) and temperature on the appearance time of Aspergillus candidus was developed and validated on cakes. The gamma concept of Zwietering was adapted to model fungal growth, taking into account the impact of temperature and aw. We hypothesized that the same model could be used to calculate the time for mycelium to become visible (tv), by substituting the matrix parameter by tv. Cardinal values of A. candidus were determined on potato dextrose agar, and predicted tv were further validated by challenge-tests run on 51 pastries. Taking into account the aw dynamics recorded in pastries during reasonable conditions of storage, high correlation was shown between predicted and observed tv when the aw at equilibrium (after 14 days of storage) was used for modeling (Af = 1.072, Bf = 0.979). Validation studies on industrial cakes confirmed the experimental results and demonstrated the suitability of the model to predict tv in food as a function of aw and temperature.

Food business operators producing Ready-To-Eat (RTE) foodstuffs must be able to demonstrate that the products will comply to regulatory specifications in terms of food safety. At the same time, various food quality aspects are also important to ensure the economic position of the food producers. For refrigerated products, it is obvious that the actual time-temperature profiles a food product undergoes in the cold chain, is of paramount importance for guaranteeing food safety and quality. This work is part of the EU-FP-7 project FRISBEE. More specifically, the objective of this work is to develop, identify and validate kinetic models for RTE pork meat products like pasteurized ham, pâte and raw ham. Hereto, dedicated storage experiments are designed and conducted. Attributes were identified: quality indicators including texture, drip-loss, water-loss, colour and microbiological indicators including Listeria monocytogenes and lactic acid bacteria. In parallel, heat transfer models were also identified and validated allowing to link the temperature in a certain step of the cold chain with the actual temperature as experienced by the food products. The developed models are an essential part of the FRISBEE software tool: a user-friendly software application that allows to mimic the effect of realistic time-temperature profiles in the cold chain on the final product safety and quality when reaching the consumer, and that at the same time calculates the energy requirements and environmental impact of the cooling technologies being part of the simulated cold chain.

For RTE foods that are able to support the growth of L. monocytogenes, a European Regulation (n°2073/2005) specifies that the 100-CFU/g limit “applies if the manufacturer is able to demonstrate that the product will not exceed the limit of 100 CFU/g throughout the shelf-life”. Many factors can interfere on the evolution of the pathogen (time-temperature history, pH, aw, associated microflora,...). The objective of this work was to demonstrate the impact of the cold chain on the shelf-life of a deli meat, sliced cooked ham. Sliced cooked ham data were obtained from challenge-tests with artificially inoculated packages with L. monocytogenes. These data are useful for estimating growth parameters and model validation. We tested different scenarios of storage temperature: from theoretical to more realistic scenarios based on data from a survey carried out in France. The variability of temperatures as well as characteristics of the product, and initial contamination level at the end of the manufacturing line, were taken into account in predictive models to calculate the time to reach the regulatory limit and to determine the shelf life. We showed that shelf-life determination is strongly dependant of the scenario chosen to simulate the cold chain.

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.

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.

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.

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.