Predictive model for the growth of Yersinia enterocolitica under modified atmospheres

Predictive growth modeling of Yersinia enterocolitica in fresh kimchi cabbage brassica pekinensis as a function of storage temperature

We developed a predictive growth model of Yersinia enterocolitica for fresh Kimchi cabbages as a function of storage temperature (5-20 °C). The Baranyi equation used for primary modeling at these storage temperatures was suitable as a model for obtaining lag time (LT) and specific growth rate (SGR) (R² = 0.97-0.98). As the temperature increased, the growth of Y. enterocolitica tended to increase, with SGR values of 0.33, 0.40, 0.60 and 0.68 log colony-forming units/h at 8, 11, and 15 °C, and LT values of 5.63, 3.54, 2.23 and 1.09 h, respectively. The secondary model was determined by the non-linear regression analysis. The suitability of the modeling results for the SGR and LT value was verified by determining the mean square error (<0.01), bias factor (0.919-0.999), and accuracy factor (1.032-1.136). The predicted models can be used to predict the growth of Y. enterocolitica in Kimchi cabbage at various temperatures and as an effective tool for maintaining the safe level of Y. enterocolitica in the production, processing, and distribution of fresh agricultural products.

Comparative genomic insights into Yersinia hibernica - a commonly misidentified Yersinia enterocolitica-like organism

Food-associated outbreaks linked to enteropathogenic Yersinia enterocolitica are of concern to public health. Pigs and their meat are recognized risk factors for transmission of Y. enterocolitica. This study aimed to describe the comparative genomics of Y. enterocolitica along with a number of misclassified Yersinia isolates, now constituting the recently described Yersinia hibernica. The latter was originally cultured from an environmental sample taken at a pig slaughterhouse. Unique features were identified in the genome of Y. hibernica, including a novel integrative conjugative element (ICE), denoted as ICEYh-1 contained within a 255 kbp region of plasticity. In addition, a zebrafish embryo infection model was adapted and applied to assess the virulence potential among Yersinia isolates including Y. hibernica.

Modeling carbon dioxide effect in a controlled atmosphere and its interactions with temperature and pH on the growth of L. monocytogenes and P. fluorescens

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.

Validation of a predictive model coupling gas transfer and microbial growth in fresh food packed under modified atmosphere

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.

Mechanistic model coupling gas exchange dynamics and Listeria monocytogenes growth in modified atmosphere packaging of non respiring food

A mechanistic model coupling O2 and CO2 mass transfer (namely diffusion and solubilisation in the food itself and permeation through the packaging material) to microbial growth models was developed aiming at predicting the shelf life of modified atmosphere packaging (MAP) systems. It was experimentally validated on a non-respiring food by investigating concomitantly the O2/CO2 partial pressure in packaging headspace and the growth of Listeria monocytogenes (average microbial count) within the food sample. A sensitivity analysis has revealed that the reliability of the prediction by this "super-parametrized" model (no less than 47 parameters were required for running one simulation) was strongly dependent on the accuracy of the microbial input parameters. Once validated, this model was used to decipher the role of O2/CO2 mass transfer on microbial growth and as a MAP design tool: an example of MAP dimensioning was provided in this paper as a proof of concept.

Effect of different concentrations of carbon dioxide and oxygen on the growth of pathogenic Yersinia enterocolitica 4/O:3 in ground pork packaged under modified atmospheres

The influence on Yersinia enterocolitica counts of a gradual increase of carbon dioxide concentrations (percentage by volume in air) during packaging and storage of ground pork meat artificially contaminated with this pathogen was evaluated. Ground meat was packaged under customary conditions using modified atmospheres with various carbon dioxide percentages (0, 30, 50, 70, and 100% CO2 by volume; for atmospheres of less than 100% CO2, the rest of the gas was O2). The packs were stored at 2 degrees C for 12 days. During the entire storage time, counts of Y. enterocolitica were determined by the spread plate method for direct plate counts (DPCs). Microbiological shelf life of the stored ground pork also was assessed by total mesophilic aerobic bacterial plate counts (APCs). Y. enterocolitica counts were not significantly different (P > or = 0.05) in the ground pork packaged under the various CO2-enriched atmospheres. The growth of Y. enterocolitica was nearly entirely inhibited in all tested modified atmospheres containing the protective CO2. However, in ground pork packaged with 100% oxygen, there was a significant decrease (P < or = 0.05) in the DPC for Y. enterocolitica from 4.30 log CFU/g (day 0) to 3.09 log CFU/g at the end of the storage time (day 12). The decrease was presumably due to the marked increase in APC seen only in those packages stored under 100% O2. Packaging with high CO2 concentrations had significant inhibitory effect (P < or = 0.05) on the growth of mesophilic aerobic bacteria.

Predictive modelling of growth and measurement of enzymatic synthesis and activity by a cocktail of Brochothrix thermosphacta

The possibility was examined of developing a predictive model that combined microbial growth (increase in cellular number) and extracellular enzyme activity of a cocktail of three strains of Brochothrix thermosphacta. Estimations of growth and enzyme activity were made within a three-dimensional matrix of conditions: temperature 2-20 degrees C, pH value 4.0-7.5 and water activity (a(w)) 0.95-0.995. A model which predicted growth based on increases in cell number was constructed. No extracellular lipases were detected, but slight proteolytic reactions were observed. Although it was not possible to model protease activity, the growth model and information relating to enzyme activity will be made freely available in a database on the Internet.

Analysis and validation of a predictive model for growth and death of Aeromonas hydrophila under modified atmospheres at refrigeration temperatures

Specific growth and death rates of Aeromonas hydrophila were measured in laboratory media under various combinations of temperature, pH, and percent CO(2) and O(2) in the atmosphere. Predictive models were developed from the data and validated by means of observations obtained from (i) seafood experiments set up for this purpose and (ii) the ComBase database (http://www.combase.cc; http://wyndmoor.arserrc.gov/combase/). Two main reasons were identified for the differences between the predicted and observed growth in food: they were the variability of the growth rates in food and the bias of the model predictions when applied to food environments. A statistical method is presented to quantitatively analyze these differences. The method was also used to extend the interpolation region of the model. In this extension, the concept of generalized Z values (C. Pin, G. García de Fernando, J. A. Ordóñez, and J. Baranyi, Food Microbiol. 18:539-545, 2001) played an important role. The extension depended partly on the density of the model-generating observations and partly on the accuracy of extrapolated predictions close to the boundary of the interpolation region. The boundary of the growth region of the organism was also estimated by means of experimental results for growth and death rates.

Predictive modelling of growth and enzyme production and activity by a cocktail of Pseudomonas spp., Shewanella putrefaciens and Acinetobacter sp

The possibility was examined of developing a predictive model that combined microbial growth (increase in cellular number) with extracellular lipolytic and proteolytic enzyme activity of a cocktail of four strains of Pseudomonas spp. and one strain each of Acinetobacter sp. and Shewanella putrefaciens. Environmental conditions within the following matrix of conditions were examined: temperature 2-20 degrees C, pH value 4.0-7.5 and water activity (a(w)) 0.95-0.995 and a model was constructed, which predicted growth based on increase in cell number. Data on lipase production and protease activity were generated and will be available as a database, but no function could be identified, which was a good fit to these data, since most enzymatic production and activity occurred, as expected, during transition from exponential to stationary phase. Even at lower cell numbers, in more unfavourable conditions, hydrolysing effects were detectable, which made it difficult to construct a model combining both microbiological and enzymatic data.

Analysing the lag-growth rate relationship of Yersinia enterocolitica

A generalised z-value concept has been applied to analyse the relationship between the lag and the growth rate of Yersinia enterocolitica at a range of temperature, atmospheric carbon dioxide and oxygen percentages. The product of the specific growth rate and the lag (the "work to be done" during the lag phase) is found to be independent of temperature. However, it does depend on the CO2 and O2 concentrations, though the effect of oxygen was less noticeable than the effect of carbon dioxide.