2010
DOI: 10.1016/j.ijfoodmicro.2010.09.024
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Validation of a stochastic modelling approach for Listeria monocytogenes growth in refrigerated foods

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Cited by 70 publications
(48 citation statements)
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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%
“…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%
“…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.…”
mentioning
confidence: 99%
“…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%