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Dynamic kinetic analysis of growth of Listeria monocytogenes in a simulated comminuted, non-cured cooked pork product.
- Source :
-
Food Control . Jan2017, Vol. 71, p160-167. 8p. - Publication Year :
- 2017
-
Abstract
- The objective of this study was to directly construct a tertiary growth model for Listeria monocytogenes in a simulated comminuted, non-cured cooked pork product and simultaneously determine the kinetic parameters using a combination of dynamic and isothermal growth curves. Growth studies were conducted using a cocktail of 5 strains of L. monocytogenes in cooked pork under both dynamic and isothermal temperature profiles designed to examine the effect of temperature on bacterial growth. A direct kinetic analysis method was used to construct the growth models and determine the kinetic parameters. The bacterial growth was simulated by a set of differential equations, and the temperature effect was evaluated by the cardinal parameters model. A numerical analysis and optimization method was used to simultaneously solve the different equations and search for the best fits of kinetic parameters for the growth curves and models. The estimated minimum, optimum, and maximum growth temperatures were 0, 33.0, and 42.6 °C, matching well with typical growth characteristics of this microorganism. The root-mean-square error (RMSE) of curve-fitting was 0.42 log CFU/g. The growth models and kinetic parameters were validated using both independent dynamic and isothermal growth curves to check the accuracy of the models. The results showed that the RMSE of predicted growth was 0.49 log CFU/g. The residual errors of predictions follow a Laplace distribution, with 80.3% of the residual errors falling within ±0.5 log CFU/g of the observations. This study proves that the one-step dynamic analysis with both dynamic and isothermal temperature profiles can be an effective approach for simultaneously constructing a tertiary model and determining the kinetic parameters. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09567135
- Volume :
- 71
- Database :
- Academic Search Index
- Journal :
- Food Control
- Publication Type :
- Academic Journal
- Accession number :
- 117096416
- Full Text :
- https://doi.org/10.1016/j.foodcont.2016.06.043