Title of article :
Inactivation model equations and their associated parameter values obtained under static acid stress conditions cannot be used directly for predicting inactivation under dynamic conditions
Author/Authors :
Janssen، نويسنده , , M. and Verhulst، نويسنده , , A. and Valdramidis، نويسنده , , V. and Devlieghere، نويسنده , , F. and Van Impe، نويسنده , , J.F. and Geeraerd، نويسنده , , A.H.، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2008
Pages :
10
From page :
136
To page :
145
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.
Keywords :
Model prediction , lactic acid , Weibull-type model , Microbial inactivation , Dynamic modeling , Predictive microbiology
Journal title :
International Journal of Food Microbiology
Serial Year :
2008
Journal title :
International Journal of Food Microbiology
Record number :
2113883
Link To Document :
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