New Term to Quantify the Effect of Temperature on p H min -Values Used in Cardinal Parameter Growth Models for Listeria monocytogenes

Abstract

The aim of this study was to quantify the influence of temperature on pH _min -values of Listeria monocytogenes as used in cardinal parameter growth models and thereby improve the prediction of growth for this pathogen in food with low pH. Experimental data for L. monocytogenes growth in broth at different pH-values and at different constant temperatures were generated and used to determined pH _min -values. Additionally, pH _min -values for L. monocytogenes available from literature were collected. A new pH _min -function was developed to describe the effect of temperatures on pH _min -values obtained experimentally and from literature data. A growth and growth boundary model was developed by substituting the constant pH _min -value present in the Mejlholm and Dalgaard (2009) model (J. Food. Prot. 72, 2132-2143) by the new pH _min -function. To obtain data for low pH food, challenge tests were performed with L. monocytogenes in commercial and laboratory-produced chemically acidified cheese including glucono-delta-lactone (GDL) and in commercial cream cheese. Furthermore, literature data for growth of L. monocytogenes in products with or without GDL were collected. Evaluation of the new and expanded model by comparison of observed and predicted μ _max -values resulted in a bias factor of 1.01 and an accuracy factor of 1.48 for a total of 1,129 growth responses from challenge tests and literature data. Growth and no-growth responses of L. monocytogenes in seafood, meat, non-fermented dairy products, and fermented cream cheese were 90.3% correctly predicted with incorrect predictions being 5.3% fail-safe and 4.4% fail-dangerous. The new pH _min -function markedly extended the range of applicability of the Mejlholm and Dalgaard (2009) model from pH 5.4 to pH 4.6 and therefore the model can now support product development, reformulation or risk assessment of food with low pH including chemically acidified cheese and cream cheese.

Keywords: food safety; mathematical modeling; model validation; predictive microbiology; product development; risk assessment.

Figure 1

Cardinal parameter values (pH_min) at different temperatures for a cocktail of L. monocytogenes strains [SLU 92, 612, LM19, 6, ()] and individual strains [ISO570 (), 99714 (), SLU 2493 (), SLU 2265 ()].

Figure 2

Observed and fitted pH_min-values from the present study and from literature. Data for L. monocytogenes cocktail of the strains [SLU92, 612, LM19, 6, ()] and individual strains [ISO570 (), 99714 (), SLU 2493 (), SLU 2265 ()] from the present study. Data from Aryani et al. (2015) (○), Brocklehurst et al. (1995) (), Duffy et al. (1994) (▴), Farber et al. (1989) (), George et al. (1988) (l), Koutsoumanis et al. (2004a) (), Petran and Zottola (1989) (), and Ryser and Marth (1988) (▾). Solid line (—) and dashed line (−−−) represent, respectively, the fitted model and confidence interval (95%).

Figure 3

Comparison of observed (□) and predicted (-) growth of L. monocytogenes at dynamic storage temperature. Chemically acidified cheese was studied at 4.4–25.4°C (A; CT 11) and 5.2–25.3°C (B; CT 12). Temperature profiles are shown as gray lines. Solid lines represent the predicted growth by model 1 with N_max of 6.8 log cfu/g.