A mathematical model for predicting growth/no-growth of psychrotrophic C. botulinum in meat products with five variables

Gunvig, Annemarie; Hansen, Flemming; Borggaard, Claus

doi:10.1016/j.foodcont.2012.06.046

Cited by 32 publications

(20 citation statements)

References 22 publications

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“…; Gunvig et al . ). In recent years, Hwang and Sheen () found that the presence of native microflora reduced the growth rate and lower the maximum population densities of L. monocytogenes in cooked ham at lower storage temperatures, and the effect diminished as the temperature increased.…”

Section: Resultsmentioning

confidence: 97%

“…Many predictive models in food are based on sterile irradiated samples to eliminate the effect of the background microflora (Juneja et al 2011;Gunvig et al 2013). In recent years, Hwang and Sheen (2011) found that the presence of native microflora reduced the growth rate and lower the maximum population densities of L. monocytogenes in cooked ham at lower storage temperatures, and the effect diminished as the temperature increased.…”

Section: Resultsmentioning

confidence: 99%

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Mathematical modelling of growth ofListeria monocytogenesin raw chilled pork

Wang

Liu

et al. 2017

Lett Appl Microbiol

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This study simulated the actual growth of Listeria monocytogenes in chilled pork to the maximum extent, and described its growth characteristics of L. monocytogenes during natural spoilage. This study showed that the background microflora had no impact on the growth parameters of L. monocytogenes, except for the lag phase at low temperature storage. The models developed in this study can be used to predict the growth of L. monocytogenes during refrigerated storage.

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Section: Resultsmentioning

confidence: 97%

Section: Resultsmentioning

confidence: 99%

Mathematical modelling of growth ofListeria monocytogenesin raw chilled pork

Wang

Liu

et al. 2017

Lett Appl Microbiol

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“…), which included among 7 environmental factors the impact of CO 2 in the packaging atmosphere (%), once again assumed to be constant. This model was developed for L. monocytogenes (Gunvig and others ) in different meat products and was applied recently for Clostridium botulinum (Gunvig and others ). The DRMI model was found to be more powerful to simulate growth curves (log CFU/g) than a classic logistic model (with R 2 significantly higher for the ANN than the classic model) but unfortunately its parameters lack physical meaning to draw some conclusions on the impact of CO 2 on the bacterial growth and to extrapolate to another species.…”

Section: Impact Of O2/co2 Gases On the Growth Of Microorganisms: Predmentioning

confidence: 99%

Predictive Microbiology Coupled with Gas (O₂/CO₂) Transfer in Food/Packaging Systems: How to Develop an Efficient Decision Support Tool for Food Packaging Dimensioning

Chaix

Couvert²,

Guillaume

et al. 2014

Comp Rev Food Sci Food Safe

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Coupling gas transfer with predictive microbiology is essential to rationally design modified atmosphere packaging (MAP) strategies to ensure and guarantee food safety. Nowadays, these strategies are generally empirically built and over-sized since packaging material with high barrier properties is often chosen by default even if such a high level of protection is not systematically required. Protection strategies could be improved using rational sizing based on quantitative analysis and mathematical modeling of mass transfer. This paper aims at reviewing the current knowledge available for developing such a tool and the further research needed. First there is a special focus on oxygen (O 2 ) and carbon dioxide (CO 2 ) solubility and diffusivity parameters, which are absolutely indispensable to accurately model mass transfer in MAP systems. Next, the current knowledge of the effect of O 2 /CO 2 on the growth of microorganisms is explored with an emphasis on predictive microbiology. The last part points out the main bottlenecks and further research needed to be carried out in order to develop an efficient MAP modeling tool for food safety coupling O 2 /CO 2 transfer and predictive microbiology.

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“…Actualmente, toda metodología de evaluación de riesgo debe ser requerida bajo un enfoque de gestión que permita la predicción sobre determinado com-portamiento (Pérez & Valero, 2013) y en este sentido, los múltiples resultados bajo pruebas de campo con medición real de indicadores (incluyendo minería de datos), resulta necesario (Gunvig, Hansen & Borggaard, 2013).…”

Section: Introductionunclassified

Predicción ecotoxicológica ante concentraciones no deseadas de cianuro libre en efluentes mineros-auríferos

Vilca

Pérez²

2017

Campus

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Predicción ecotoxicológica ante concentraciones no deseadas de cianuro libre en efluentes mineros-auríferos resumen El objetivo del estudio fue predecir la ecotoxicología ante concentraciones no deseadas de cianuro libre en efluentes mineros-auríferos. Se seleccionó durante el período de lluvia, cuatro muestras de efluentes donde se determinó la concentración de cianuro libre mediante el método del nitrato de plata. Con la mayor concentración se realizó el bioensayo de toxicidad letal aguda utilizando el modelo biológico de experimentación Eisenia andrei y con ambas determinaciones se estimó, la predicción ecotoxicológica, a través del modelo computacional Gecotoxic. Las concentraciones de las muestras de los efluentes fueron: 0,161±0,008; 0,142±0,008; 0,138±0,008 y 0,137±0,007 mg.L-1 , superándose el valor permisible por la norma ambiental utilizada (0,022 mg.L-1). La CL 50 calculada para efluentes fue de 0,078 mg.L-1 , observándose efectos letales mientras que, el modelo computacional Gecotoxic indicó, predicción de riesgo ambiental de tipo alta (68%). Se concluyó que, los efluentes mineros se vertieron con valores no deseados de cianuro libre que pueden ser perjudiciales para los cuerpos receptores.

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A mathematical model for predicting growth/no-growth of psychrotrophic C. botulinum in meat products with five variables

Cited by 32 publications

References 22 publications

Mathematical modelling of growth ofListeria monocytogenesin raw chilled pork

Mathematical modelling of growth ofListeria monocytogenesin raw chilled pork

Predictive Microbiology Coupled with Gas (O₂/CO₂) Transfer in Food/Packaging Systems: How to Develop an Efficient Decision Support Tool for Food Packaging Dimensioning

Predicción ecotoxicológica ante concentraciones no deseadas de cianuro libre en efluentes mineros-auríferos

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A mathematical model for predicting growth/no-growth of psychrotrophic C. botulinum in meat products with five variables

Cited by 32 publications

References 22 publications

Mathematical modelling of growth ofListeria monocytogenesin raw chilled pork

Mathematical modelling of growth ofListeria monocytogenesin raw chilled pork

Predictive Microbiology Coupled with Gas (O2/CO2) Transfer in Food/Packaging Systems: How to Develop an Efficient Decision Support Tool for Food Packaging Dimensioning

Predicción ecotoxicológica ante concentraciones no deseadas de cianuro libre en efluentes mineros-auríferos

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Product

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Predictive Microbiology Coupled with Gas (O₂/CO₂) Transfer in Food/Packaging Systems: How to Develop an Efficient Decision Support Tool for Food Packaging Dimensioning