Validation of a stochastic modelling approach for Listeria monocytogenes growth in refrigerated foods

Couvert, Olivier; Pinon, Anthony; Bergis, H.; Bourdichon, François; Carlin, Frédéric; Cornu, Marie; Denis, Catherine; Besse, Nathalie Gnanou; Guillier, Laurent; Jamet, Emmanuel; Mettler, Eric; Stahl, Valérie; Thuault, Dominique; Zuliani, Véronique; Augustin, Jean-Christophe

doi:10.1016/j.ijfoodmicro.2010.09.024

Cited by 69 publications

(48 citation statements)

References 28 publications

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“…This tool aims to provide reliable models for microbial behavior simulations in food products (Couvert et al, 2010). Therefore, the use of predictive models can have a very effective application in the food industry, providing reliable predictions able to prevent risks to consumer health in addition to making the process economically viable, by diminishing losses and helping in decision-making (Juneja et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Primary and secondary modeling of Brochothrix thermosphacta growth under different temperature and ph values

et al. 2018

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Bochothrix thermosphacta is an optional aerobic psychrotrophic related to the meat deterioration and consequently loss of a refrigerated cargo contaminated. Predictive microbiology can be used as a quality assurance tool, since it allows the prediction of microbial response based in pass observations. This work aimed model the growth of B. thermosphacta under variation of pH and temperature. For this purpose, the experimental growth data were fitted to the primary models of Baranyi and Roberts and the modified Gompertz model and the data for the maximum rate of growth (μmax) were adjusted to Ratkowsky extended secondary model. The results showed us that the influence of temperature on growth parameters was more evident than pH. Since, by fixing the temperature the change of pH little altered the μmax. However, as the temperature rises the elevation at the μmax is considerable, for example the comparison of predicted values for μmax, when the temperature exceeds 4 °C to 12 °C, it is clear that these rates are more than double. Finally, it is emphasized that all tested models feature good fit to the experimental data, which makes them validated for prediction growth of B. thermosphacta in the same conditions tested experimentally.Keywords: deterioration; refrigeration; predictive models. Pratical Application:To predict the growth of B. thermosphacta under varying temperature and pH conditions.

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Section: Introductionmentioning

confidence: 99%

Primary and secondary modeling of Brochothrix thermosphacta growth under different temperature and ph values

et al. 2018

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“…The importance of single-cell variability was raised after the recent developments in quantitative microbial risk assessment (9). Deterministic models that provide point estimates are generally not sufficient to satisfactorily manage microbial safety risks (10)(11)(12). Indeed, if, for instance, the consequences of unacceptable levels of pathogenic microorganisms in a food are grave, knowledge of only the mean population growth is unlikely to be a sufficient basis for management decisions on the safety risk.…”

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Stochasticity in Colonial Growth Dynamics of Individual Bacterial Cells

Koutsoumanis

Nychas

2013

Appl Environ Microbiol

101

104

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Conventional bacterial growth studies rely on large bacterial populations without considering the individual cells. Individual cells, however, can exhibit marked behavioral heterogeneity. Here, we present experimental observations on the colonial growth of 220 individual cells of Salmonella enterica serotype Typhimurium using time-lapse microscopy videos. We found a highly heterogeneous behavior. Some cells did not grow, showing filamentation or lysis before division. Cells that were able to grow and form microcolonies showed highly diverse growth dynamics. The quality of the videos allowed for counting the cells over time and estimating the kinetic parameters lag time () and maximum specific growth rate ( max ) for each microcolony originating from a single cell. To interpret the observations, the variability of the kinetic parameters was characterized using appropriate probability distributions and introduced to a stochastic model that allows for taking into account heterogeneity using Monte Carlo simulation. The model provides stochastic growth curves demonstrating that growth of single cells or small microbial populations is a pool of events each one of which has its own probability to occur. Simulations of the model illustrated how the apparent variability in population growth gradually decreases with increasing initial population size (N 0 ). For bacterial populations with N 0 of >100 cells, the variability is almost eliminated and the system seems to behave deterministically, even though the underlying law is stochastic. We also used the model to demonstrate the effect of the presence and extent of a nongrowing population fraction on the stochastic growth of bacterial populations.All the physical and chemical laws that are known to play an important part in the life of organisms are of statistical kind.

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“…In addition, the modelling approach followed in those studies that consider the inter-strain variability of the same microbial species has changed with respect to previous studies [18,19]. Latter developments in predictive modelling approaches have also resulted in new model equations [20], stochastic models [6,21,22] and models considering dynamic conditions [23].…”

Section: Recent Developments In Predictive Microbial Modellingmentioning

confidence: 99%

Towards transparent and consistent exchange of knowledge for improved microbiological food safety

Plaza‐Rodríguez

Haberbeck

Desvignes

et al. 2018

Current Opinion in Food Science

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Validation of a stochastic modelling approach for Listeria monocytogenes growth in refrigerated foods

Cited by 69 publications

References 28 publications

Primary and secondary modeling of Brochothrix thermosphacta growth under different temperature and ph values

Primary and secondary modeling of Brochothrix thermosphacta growth under different temperature and ph values

Stochasticity in Colonial Growth Dynamics of Individual Bacterial Cells

Towards transparent and consistent exchange of knowledge for improved microbiological food safety

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