Performance of a growth-no growth model for Listeria monocytogenes developed for mayonnaise-based salads: influence of strain variability, food matrix, inoculation level, and presence of sorbic and benzoic acid.

A previously developed growth-no growth model for Listeria monocytogenes, based on nutrient broth data and describing the influence of water activity (a(w)), pH, and acetic acid concentrations, was validated (i) for a variety of L. monocytogenes strains and (ii) in a laboratory-made, mayonnaise-based surimi salad (as an example of a mayonnaise-based salad). In these challenge tests, the influence of the inoculation level was tested as well. Also, the influence of chemical preservatives on the growth probability of L. monocytogenes in mayonnaise-based salads was determined. To evaluate the growth-no growth model performance on the validation data, four quantitative criteria are determined: concordance index, % correct predictions, % fail-dangerous, and % fail-safe. First, the growth probability of 11 L. monocytogenes strains, not used for model development, was assessed in nutrient broth under conditions within the interpolation region. Experimental results were compared with model predictions. Second, the growth-no growth model was assessed in a laboratory-made, sterile, mayonnaise-based surimi salad to identify a possible model completeness error related to the food matrix, making use of the above-mentioned validation criteria. Finally, the effect on L. monocytogenes of common chemical preservatives (sorbic and benzoic acid) at different concentrations under conditions typical of mayonnaise-based salads was determined. The study showed that the growth-no growth zone was properly predicted and consistent for all L. monocytogenes strains. A larger prediction error was observed under conditions within the transition zone between growth-no growth. However, in all cases, the classification between no growth (P = 0) and any growth (P > 0) occurred properly, which is most important for the food industry, where outgrowth needs to be prevented in all instances. The results in the sterile mayonnaise-based salad showed again that the growth-no growth zone was well predicted but that also, in real food systems, a transition zone between growth and no growth exists. This became even more obvious for lower inoculation levels. The maximum-allowed concentration of benzoic and sorbic acid in mayonnaise-based salads, according to the European Union legislation, eliminated the growth of L. monocytogenes. Concentrations of 600 and 300 ppm were already sufficient to inhibit growth at 7 and 4 degrees C, respectively, under conditions associated with mayonnaise-based salads (pH 5.6; a(w), 0.985).

[1]  K Bernaerts,et al.  Influence of pH, water activity and acetic acid concentration on Listeria monocytogenes at 7 degrees C: data collection for the development of a growth/no growth model. , 2007, International journal of food microbiology.

[2]  M. Uyttendaele,et al.  Single cell variability of L. monocytogenes grown on liver pâté and cooked ham at 7°C: comparing challenge test data to predictive simulations , 2006, Journal of applied microbiology.

[3]  A. Standaert,et al.  Environmental factors influencing the relationship between optical density and cell count for Listeria monocytogenes , 2005, Journal of applied microbiology.

[4]  J. V. Van Impe,et al.  Reflections on the use of robust and least-squares non-linear regression to model challenge tests conducted in/on food products. , 2005, International journal of food microbiology.

[5]  C. Hwang Effect of mayonnaise pH and storage temperature on the behavior of Listeria monocytogenes in ham salad and potato salad. , 2005, Journal of food protection.

[6]  Cheng-An Hwang,et al.  The influence of mayonnaise pH and storage temperature on the growth of Listeria monocytogenes in seafood salad. , 2005, International journal of food microbiology.

[7]  V. Scott,et al.  Survey of Listeria monocytogenes in ready-to-eat foods. , 2003, Journal of food protection.

[8]  Pascal Delaquis,et al.  A probability model describing the interface between survival and death of Escherichia coli O157:H7 in a mayonnaise model system , 2002 .

[9]  J. McLauchlin,et al.  Listeria in ready-to-eat and unprocessed foods produced in Portugal , 2001 .

[10]  R. Leuschner,et al.  Standardized laboratory-scale preparation of mayonnaise containing low levels of Salmonella enterica serovar Enteritidis. , 2001, Journal of food protection.

[11]  J. Farber,et al.  A small outbreak of listeriosis potentially linked to the consumption of imitation crab meat , 2000, Letters in applied microbiology.

[12]  A Agresti,et al.  Summarizing the predictive power of a generalized linear model. , 2000, Statistics in medicine.

[13]  D G Altman,et al.  What do we mean by validating a prognostic model? , 2000, Statistics in medicine.

[14]  J Debevere,et al.  Incidence of Listeria monocytogenes in different types of meat products on the Belgian retail market. , 1999, International journal of food microbiology.

[15]  M C te Giffel,et al.  Validation of predictive models describing the growth of Listeria monocytogenes. , 1999, International journal of food microbiology.

[16]  S. McCarthy Incidence and Survival of Listeria monocytogenes in Ready-To-Eat Seafood Products. , 1997, Journal of food protection.

[17]  G. Flick,et al.  Listeria monocytogenes Occurrence and Growth at Refrigeration Temperatures in Fresh Blue Crab ( Callinectes sapidus ) Meat. , 1995, Journal of food protection.

[18]  C J McDonald,et al.  Validation of Probabilistic Predictions , 1993, Medical decision making : an international journal of the Society for Medical Decision Making.

[19]  S L Hui,et al.  Validation techniques for logistic regression models. , 1991, Statistics in medicine.

[20]  R. Hartemink,et al.  Incidence of Listeria species in seafood and seafood salads. , 1991, International journal of food microbiology.

[21]  R. B. Smittle Microbiology of Mayonnaise and Salad Dressing: A Review. , 1977, Journal of food protection.