Combined deterministic and stochastic approaches for modelling the evolution of food products along the cold chain. Part II: A case study

Hoang, Hong-Minh; Flick, Denis; Derens, Evelyne; Álvarez, G.; Laguerre, Onrawee

doi:10.1016/j.ijrefrig.2011.12.009

Cited by 32 publications

(17 citation statements)

References 15 publications

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“…The experimental data regarding survival, inactivation, and growth of this foodborne pathogen during production and storage of meat products at different temperatures can be described mathematically by predictive models (2,15,17,32). Predictive microbiology is based on the assumption that the reaction of microorganisms to environmental factors is reproducible.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the growth rate ofListeria monocytogenesin cooked ham stored at different temperatures

Szczawinski

Szczawinska

Łobacz

et al. 2017

Journal of Veterinary Research

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Introduction: The purpose of the study was to determine and model the growth rates of L. monocytogenes in cooked cured ham stored at various temperatures. Material and Methods: Samples of cured ham were artificially contaminated with a mixture of three L. monocytogenes strains and stored at 3, 6, 9, 12, or 15ºC for 16 days. The number of listeriae was determined after 0, 1, 2, 3, 5, 7, 9, 12, 14, and 16 days. A series of decimal dilutions were prepared from each sample and plated onto ALOA agar, after which the plates were incubated at 37ºC for 48 h under aerobic conditions. The bacterial counts were logarithmised and analysed statistically. Five repetitions of the experiment were performed. Results: Both storage temperature and time were found to significantly influence the growth rate of listeriae (P < 0.01). The test bacteria growth curves were fitted to three primary models: the Gompertz, Baranyi, and logistic. The mean square error (MSE) and Akaike's information criterion (AIC) were calculated to evaluate the goodness of fit. It transpired that the logistic model fit the experimental data best. The natural logarithms of L. monocytogenes' mean growth rates from this model were fitted to two secondary models: the square root and polynomial. Conclusion: Modelling in both secondary types can predict the growth rates of L. monocytogenes in cooked cured ham stored at each studied temperature, but mathematical validation showed the polynomial model to be more accurate.

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Section: Introductionmentioning

confidence: 99%

“…Moreover, predictive microbial models are commonly being used by food inspectors and food technologists in their everyday work (2,17,33).…”

Section: Introductionmentioning

confidence: 99%

Modelling the growth rate ofListeria monocytogenesin cooked ham stored at different temperatures

Szczawinski

Szczawinska

Łobacz

et al. 2017

Journal of Veterinary Research

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“…The experimental data regarding survival or inactivation of this foodborne pathogen during production and cold storage of yogurt at different temperatures can be described mathematically by predictive models (Gibson et al 1988, Baranyi and Roberts 1994, Hoang et al 2012). Predictive microbiology is based on the premise that the response of microorganisms to environmental factors is reproducible.…”

Section: Introductionmentioning

confidence: 99%

Modeling the effect of temperature on survival rate of Listeria monocytogenes in yogurt

Szczawinski¹,

Me²,

Łobacz³

et al. 2016

Polish Journal of Veterinary Sciences

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The aim of the study was to (i) evaluate the behavior of Listeria monocytogenes in a commercially produced yogurt, (ii) determine the survival/inactivation rates of L. monocytogenes during cold storage of yogurt and (iii) to generate primary and secondary mathematical models to predict the behavior of these bacteria during storage at different temperatures.The samples of yogurt were inoculated with the mixture of three L. monocytogenes strains and stored at 3, 6, 9, 12 and 15 o C for 16 days. The number of listeriae was determined after 0, 1, 2, 3, 5, 7, 9, 12, 14 and 16 days of storage. From each sample a series of decimal dilutions were prepared and plated onto ALOA agar (agar for Listeria according to Ottaviani and Agosti).It was found that applied temperature and storage time significantly influenced the survival rate of listeriae (p<0.01). The number of L. monocytogenes in all the samples decreased linearly with storage time. The slowest decrease in the number of the bacteria was found in the samples stored at 6 o C (D-10 value = 243.9 h), whereas the highest reduction in the number of the bacteria was observed in the samples stored at 15 o C (D-10 value = 87.0 h). The number of L. monocytogenes was correlated with the pH value of the samples (p<0.01). The natural logarithm of the mean survival/inactivation rates of L. monocytogenes calculated from the primary model was fitted to two secondary models, namely linear and polynomial. Mathematical equations obtained from both secondary models can be applied as a tool for the prediction of the survival/inactivation rate of L. monocytogenes in yogurt stored under temperature range from 3 to 15 o C, however, the polynomial model gave a better fit to the experimental data.

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“…In recent years predictive microbiology has become an important supporting tool in food chain risk management and microbial models have been increasingly used by food producers as well as food inspectors in their routine work (Baranyi and Roberts 1994, Hoang et. al.…”

Section: Introductionmentioning

confidence: 99%

Modeling the effect of temperature on survival rate of Salmonella Enteritidis in yogurt

Szczawinski

Szczawinska

Łobacz³

et al. 2014

Polish Journal of Veterinary Sciences

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The aim of the study was to determine the inactivation rates of Salmonella Enteritidis in commercially produced yogurt and to generate primary and secondary mathematical models to predict the behaviour of these bacteria during storage at different temperatures. The samples were inoculated with the mixture of three S. Enteritidis strains and stored at 5 C for 24 h. The number of salmonellae was determined every two hours. It was found that the number of bacteria decreased linearly with storage time in all samples. Storage temperature and pH of yogurt significantly influenced survival rate of S. Enteritidis (p < 0.05). In samples kept at 5 o C the number of salmonellae decreased at the lowest rate, whereas at 25 o C the reduction in number of bacteria was the most dynamic. The natural logarithm of mean inactivation rates of Salmonella calculated from primary model was fitted to two secondary models: linear and polynomial. Equations obtained from both secondary models can be applied as a tool for prediction of inactivation rate of Salmonella in yogurt stored under temperature range from 5 to 25 o C; however, polynomial model gave the better fit to the experimental data.

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Combined deterministic and stochastic approaches for modelling the evolution of food products along the cold chain. Part II: A case study

Cited by 32 publications

References 15 publications

Modelling the growth rate ofListeria monocytogenesin cooked ham stored at different temperatures

Modelling the growth rate ofListeria monocytogenesin cooked ham stored at different temperatures

Modeling the effect of temperature on survival rate of Listeria monocytogenes in yogurt

Modeling the effect of temperature on survival rate of Salmonella Enteritidis in yogurt

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