Predictive model for the growth of Yersinia enterocolitica under modified atmospheres

Pin, Carmen; Baranyi, József; Fernando, Gonzalo García de

doi:10.1046/j.1365-2672.2000.00991.x

Cited by 33 publications

(20 citation statements)

References 18 publications

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“…Broth experiments were performed as previously described (16). Bottles containing 200 ml of tryptic soy broth, with the pH adjusted to the target value and with different atmospheric compositions, were prepared and stored at the required experimental temperature.…”

Section: Methodsmentioning

confidence: 99%

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Analysis and Validation of a Predictive Model for Growth and Death ofAeromonas hydrophilaunder Modified Atmospheres at Refrigeration Temperatures

Diego

George

et al. 2004

Appl Environ Microbiol

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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. Most predictive models in food microbiology focus on the specific growth and/or death rate (or the doubling time [D value]) of a microorganism as a function of the main environmental factors, such as temperature, pH, and others. These models are commonly based on observations made in a welldefined and controlled laboratory environment, using microbiological media. It is also vital to validate the predictions in food environments, which can be highly complex and sometimes difficult to characterize.The overall error of a model is defined by means of the mean square error (MSE) between predictions and observations made in food (19). If extrapolations are omitted from the predictions, as they should be, then the overall error refers only to the interpolation region. Sometimes, depending on the experimental design and available data, it is difficult to determine the interpolation region of a multivariate empirical model based purely on observations. Baranyi et al. (3) defined it as a minimum convex polyhedron (MCP), or convex hull, in the space of environmental factors. As Fig. 1 shows, the MCP encompasses those combinations of the environmental conditions for which observations were made to generate the model. Its vertices can be calculated as described previously (3). Model predictions outside the MCP are extrapolations.Often, conditions observed in food fall outside of the interpolation region but are close enough to it that they can be useful for model validation. These observations can also help to extend the interpolation region of the model.In this paper, we report new experimental data about the growth and death rates of Aeromonas hydrophila which vary with temperature, pH, and percent CO 2 and O 2 in the atmosphere. Both death and growth data were used to estimate the growth-no growth boundary of the organism. The growth data were used to generate a predictive growth model, which was then extensively validated by comparing its predictions with various observations in food. Some observations were outside of but close enough to the interpolation region of the growth model to be useful for the validation procedure. We developed an algorithm to extend the interpolation region of the model in order to utilize those origina...

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Section: Methodsmentioning

confidence: 99%

“…10 4 CFU/ml. For each storage condition, 12 samples of each type of seafood (whole fish or fillet) were individually packaged under modified atmospheres as previously described (16). Table 2 shows the pH values of the seafood samples and the conditions in which they were stored.…”

Section: Methodsmentioning

confidence: 99%

Analysis and Validation of a Predictive Model for Growth and Death ofAeromonas hydrophilaunder Modified Atmospheres at Refrigeration Temperatures

Diego

George

et al. 2004

Appl Environ Microbiol

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“…Among the significant foodborne pathogenic bacterial species, Yersinia enterocolitica appears to be implicated in several foodborne outbreaks (Ackers et al 2000;Sakai et al 2005;GrahekOgden et al 2007). There have been several studies focusing on the growth behavior of Y. enterocolitica under the influence of extrinsic and intrinsic factors, both in culture broth and food systems Sutherland and Bayliss 1994;Bhaduri et al 1994Bhaduri et al , 1995Geer et al 1995;Pin et al 2000;Bozkurt and Erkmen 2001;Wei et al 2001;Virto et al 2005; Bari et al 2011). The intrinsic factors that greatly influence microbial growth are pH, moisture content, oxidationreduction potential (Eh), nutrients and antimicrobials.…”

Section: Introductionmentioning

confidence: 99%

Growth kinetics of a native toxigenic isolate of Yersinia enterocolitica CFR 2301 under the influence of incubation temperature, pH, sodium chloride and sodium nitrite

Divya

Varadaraj

2015

J Food Sci Technol

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Growth attributes such as lag phase duration (LPD) and growth rate (GR) estimates of a native toxigenic isolate of Yersinia enterocolitica CFR 2301 were studied in a broth medium under the influence of incubation temperature, pH, sodium chloride and sodium nitrite. The experimental growth curves derived from the central composite design based on 5 levels of factors namely incubation temperature (12-40°C), pH level (5.5-8.5), sodium chloride (0.5-5.5 %) and sodium nitrite (0-200 ppm) were fitted using Baranyi and Gompertz functions, individually. With both these functions, the observed LPD values were similar ranging from 2.0 to 20.0 h and with GR values ranging from 0.1 to 0.5/h. The predicted values of LPD and GR estimates related well with observed values. The experimental culture broths with GR estimates of 0.4 and 0.5/h revealed positive phospholipase activity that is associated with the toxigenic trait of phospholipase A in the culture of Y. enterocolitica CFR 2301. The generated response surface plots for LPDs and GR estimates show a definite behavioral pattern under the influence of a combination of selected factors and variables. Higher LPDs and lower GR estimates as the indices of microbial safety could be of significance in developing effective food safety protocols in the food chain.

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“…As an example of public health significance, in 1986, the FDA Dairy Safety Initiatives Program of US-FDA revealed the presence of Y. enterocolitica in pasteurized chocolate milk produced in Vermont (Donnelly 1990). There have been few studies on the behavior of Y. enterocolitica, both in culture broth and food systems under combined effects of intrinsic and extrinsic factors (Bhaduri et al 1994;Jones et al 1994;Sutherland and Baylis 1994;Geer et al 1995;Pin et al 2000;Bozkurt and Erkmen 2001;Wei et al 2001;Virto et al 2005).…”

Section: Introductionmentioning

confidence: 99%

Response Surface Plots for the Behavioral Pattern of Yersinia enterocolitica in Chocolate Milk as Affected by Trans-Cinnamaldehyde, a Spice Essential Oil Constituent

Divya

Varadaraj

2009

Food Bioprocess Technol

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Response surface plots were generated to determine the behavior of a native food isolate of Yersinia enterocolitica CFR 2301 in chocolate milk with added transcinnamaldehyde, an active spice essential oil constituent. The minimum inhibitory and bactericidal concentrations (MIC and MBC) for Y. enterocolitica in broth systems were 0.1 and 0.3 µl/ml, respectively, while in chocolate milk, the MBC was 0.9µl/ml. In chocolate milk devoid of cinnamaldehyde, the culture of Y. enterocolitica CFR 2301 was able to reach riskcausing population levels in 12 h at 30°C. In the presence of cinnamaldehyde, an inactivation model was generated for the behavior of Y. enterocolitica in chocolate milk, which revealed that, irrespective of initial inoculum levels, the death time (D T ) was primarily influenced by transcinnamaldehyde concentrations and incubation temperatures. The death times were found to decrease with higher cinnamaldehyde concentrations and incubation temperatures. Validation of the model revealed the adequacy of predictions derived for this inactivation model and potential application of compatible possibility to develop food formulations with inhibitory principles.

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Predictive model for the growth of Yersinia enterocolitica under modified atmospheres

Cited by 33 publications

References 18 publications

Analysis and Validation of a Predictive Model for Growth and Death ofAeromonas hydrophilaunder Modified Atmospheres at Refrigeration Temperatures

Analysis and Validation of a Predictive Model for Growth and Death ofAeromonas hydrophilaunder Modified Atmospheres at Refrigeration Temperatures

Growth kinetics of a native toxigenic isolate of Yersinia enterocolitica CFR 2301 under the influence of incubation temperature, pH, sodium chloride and sodium nitrite

Response Surface Plots for the Behavioral Pattern of Yersinia enterocolitica in Chocolate Milk as Affected by Trans-Cinnamaldehyde, a Spice Essential Oil Constituent

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