Abstract Content: Consumer demand for safe and extended storage-life foods has encourage the industry to market products at conditions close to the growth/no-growth boundary of each pathogen of concern. It is therefore of importance to estimate if the pathogen growth is likely (P >0.1) or, vice versa, if the pathogen will die over time (P≤0.1; Polese et al. 2016). Both growth and inactivation behaviours are dependent on a variety of environmental factors, with temperature introducing the greatest variation in growth and death parameters. The Gamma concept has been successfully applied for non-thermal inactivation of Escherichia coli (Le Marc et al., 2011), Listeria (Coroller et al., 2012) and Salmonella, the latter also in dynamic process conditions (Coroller et al., 2015). In the attempt to support small producers in the safe management of foods, this work presents a non-thermal inactivation model, simulated through a conservative Gamma-like model, to be included in the simplified web-based application termed Praedicere Possumus. The kinetics of inactivation was predicted with the model of McQuestin et al., (2009) and the estimated bacterial behaviour was then modelled as a function of the specific sensitivity of each pathogen to temperature, pH and aw, and as a function of the two actual later explanatory factors. Datasets of S. enteritidis, L. monocytogenes and E. coli O157:H7 behaviours were collected from published data (Gabriel and Nakano, 2010) and used to evaluate the performance of the model. The correct inactivation prediction was 89%, whereas incorrect predictions were only fail-dangerous, which reflected the conservative performance of the non-thermal inactivation model. This model, allowing the quantification of a pathogen decrease for a given formulation or storage condition, could be a further element in the Praedicere Possumus aimed to assist users in attaining the desirable food safety level.

A further extension of the evergreen Gamma concept for modelling the non-thermal inactivation of a variety of foodborne pathogens

STECCHINI, Mara Lucia
2016-01-01

Abstract

Abstract Content: Consumer demand for safe and extended storage-life foods has encourage the industry to market products at conditions close to the growth/no-growth boundary of each pathogen of concern. It is therefore of importance to estimate if the pathogen growth is likely (P >0.1) or, vice versa, if the pathogen will die over time (P≤0.1; Polese et al. 2016). Both growth and inactivation behaviours are dependent on a variety of environmental factors, with temperature introducing the greatest variation in growth and death parameters. The Gamma concept has been successfully applied for non-thermal inactivation of Escherichia coli (Le Marc et al., 2011), Listeria (Coroller et al., 2012) and Salmonella, the latter also in dynamic process conditions (Coroller et al., 2015). In the attempt to support small producers in the safe management of foods, this work presents a non-thermal inactivation model, simulated through a conservative Gamma-like model, to be included in the simplified web-based application termed Praedicere Possumus. The kinetics of inactivation was predicted with the model of McQuestin et al., (2009) and the estimated bacterial behaviour was then modelled as a function of the specific sensitivity of each pathogen to temperature, pH and aw, and as a function of the two actual later explanatory factors. Datasets of S. enteritidis, L. monocytogenes and E. coli O157:H7 behaviours were collected from published data (Gabriel and Nakano, 2010) and used to evaluate the performance of the model. The correct inactivation prediction was 89%, whereas incorrect predictions were only fail-dangerous, which reflected the conservative performance of the non-thermal inactivation model. This model, allowing the quantification of a pathogen decrease for a given formulation or storage condition, could be a further element in the Praedicere Possumus aimed to assist users in attaining the desirable food safety level.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1102109
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