Predicting growth rates and growth boundary of Listeria monocytogenes - An international validation study with focus on processed and ready-to-eat meat and seafood
|Author(s)||Mejlholm Ole1, Gunvig Annemarie2, Borggaard Claus2, Blom-Hanssen Jesper2, Mellefont Lyndal3, Ross Tom3, Leroi Francoise4, Else Tony5, Visser Diana5, Dalgaard Paw1|
|Affiliation(s)||1 : Tech Univ Denmark, Natl Food Inst DTU Food, Div Seafood Res, DK-2800 Lyngby, Denmark.
2 : DMRI, Roskilde, Denmark.
3 : Univ Tasmania, TIAR, Hobart, Tas, Australia.
4 : IFREMER, Dept Sci & Tech Alimentaires Marines, Nantes, France.
5 : PURAC Biochem Bv, Gorinchem, Netherlands.
|Source||International Journal Of Food Microbiology (0168-1605) (Elsevier Science Bv), 2010-07 , Vol. 141 , N. 3 , P. 137-150|
|WOS© Times Cited||78|
|Keyword(s)||Predictive models, Bias and accuracy factors, Correct prediction percentage, Growth/no-growth predictions, Psi (psi) value|
|Abstract||The performance of six predictive models for Listeria monocytogenes was evaluated using 1014 growth responses of the pathogen in meat, seafood, poultry and dairy products. The performance of the growth models was closely related to their complexity i.e. the number of environmental parameters they take into account. The most complex model included the effect of nine environmental parameters and it performed better than the other less complex models both for prediction of maximum specific growth rates (mu(max) values) and for the growth boundary of L. monocytogenes. For this model bias and accuracy factors for growth rate predictions were 1.0 and 1.5, respectively, and 89% of the growth/no-growth responses were correctly predicted. The performance of three other models, including the effect of five to seven environmental parameters, was considered acceptable with bias factors of 1.2 to 1.3. These models all included the effect of acetic acid/diacetate and lactic acid, one of the models also included the effect of CO2 and nitrite but none of these models included the effect of smoke components. Less complex models that did not include the effect of acetic acid/diacetate and lactic acid were unable to accurately predict growth responses of L. monocytogenes in the wide range of food evaluated in the present study. When complexity of L monocytogenes growth models matches the complexity of foods of interest. i.e. the number of hurdles to microbial growth, then predicted growth responses of the pathogen can be accurate. The successfully validated models are useful for assessment and management of L monocytogenes in processed and ready-to-eat (RTE) foods. (C) 2010 Elsevier B.V. All rights reserved.|