Literature DB >> 18675486

Inactivation model equations and their associated parameter values obtained under static acid stress conditions cannot be used directly for predicting inactivation under dynamic conditions.

M Janssen1, A Verhulst, V Valdramidis, F Devlieghere, J F Van Impe, A H Geeraerd.   

Abstract

Organic acids (e.g., lactic acid, acetic acid and citric acid) are popular preservatives. In this study, the Listeria innocua inactivation is investigated under dynamic conditions of pH and undissociated lactic acid ([LaH]). A combined primary (Weibull-type) and secondary model developed for the L. innocua inactivation under static conditions [Janssen, M., Geeraerd, A.H., Cappuyns, A., Garcia-Gonzalez, L., Schockaert, G., Van Houteghem, N., Vereecken, K.M., Debevere, J., Devlieghere, F., Van Impe, J.F., 2007. Individual and combined effects of pH and lactic acid concentration on L. innocua inactivation: development of a predictive model and assessment of experimental variability. Applied and Environmental Microbiology 73(5), 1601-1611] was applied to predict the microbial inactivation under dynamic conditions. Because of its non-autonomous character, two approaches were proposed for the application of the Weibull-type model to dynamic conditions. The results quantitatively indicated that the L. innocua cell population was able to develop an induced acid stress resistance under dynamic conditions of pH and [LaH]. From a modeling point of view, it needs to be stressed that (i) inactivation model equations and associated parameter values, derived under static conditions, may not be suitable for use as such under dynamic conditions, and (ii) non-autonomous dynamic models reveal additional technical intricacies in comparison with autonomous models.

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Year:  2008        PMID: 18675486     DOI: 10.1016/j.ijfoodmicro.2008.06.009

Source DB:  PubMed          Journal:  Int J Food Microbiol        ISSN: 0168-1605            Impact factor:   5.277


  2 in total

1.  Relevance of the Induced Stress Resistance When Identifying the Critical Microorganism for Microbial Risk Assessment.

Authors:  Alberto Garre; Jose A Egea; Asunción Iguaz; Alfredo Palop; Pablo S Fernandez
Journal:  Front Microbiol       Date:  2018-07-24       Impact factor: 5.640

2.  On the use of in-silico simulations to support experimental design: A case study in microbial inactivation of foods.

Authors:  Alberto Garre; Jose Lucas Peñalver-Soto; Arturo Esnoz; Asunción Iguaz; Pablo S Fernandez; Jose A Egea
Journal:  PLoS One       Date:  2019-08-27       Impact factor: 3.240

  2 in total

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