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Pressure inactivation kinetics of Yersinia enterocolitica ATCC 35669
Haiqiang Chen1, Dallas G Hoover
1Department of Animal and Food Sciences, University of Delaware, 017 Townsend Hall, Newark, DE 19717-1303, USA.
Insights
Nonlinear models, specifically the log-logistic and Weibull models, accurately describe the inactivation of Yersinia enterocolitica using high hydrostatic pressure. A simplified log-logistic model also proved effective for predicting bacterial survival curves.
Area of Science:
- Food Microbiology
- Food Engineering
- Mathematical Modeling
Background:
- High hydrostatic pressure (HHP) is an emerging non-thermal processing technology for microbial inactivation.
- Understanding the kinetics of microbial inactivation is crucial for optimizing HHP treatments.
- Yersinia enterocolitica is a significant foodborne pathogen that can be targeted by HHP.
Purpose of the Study:
- To evaluate the performance of linear and nonlinear models in describing the survival curves of Yersinia enterocolitica ATCC 35669.
- To compare the fit of log-logistic, Weibull, and modified Gompertz models for HHP inactivation kinetics.
- To develop predictive models for Yersinia enterocolitica inactivation under varying HHP conditions.
Main Methods:
- Survival curves of Yersinia enterocolitica were generated at different high hydrostatic pressure levels (300-500 MPa) in sodium phosphate buffer and UHT whole milk.
- Linear regression and three nonlinear models (log-logistic, Weibull, modified Gompertz) were fitted to the survival data.
- Model performance was assessed using regression coefficients (R2) and mean square error (MSE).
Main Results:
- Tailing was observed in all survival curves, indicating incomplete inactivation.
- Nonlinear models (log-logistic and Weibull) provided a significantly better fit than the linear model.
- The log-logistic and Weibull models demonstrated high R2 values (0.944-0.982) and low MSE values (0.110-0.349).
- A simplified two-parameter log-logistic model showed comparable fit to the full model.
- Predictive models were developed based on the Weibull model's shape factors.
Conclusions:
- Log-logistic and Weibull models are superior for describing high hydrostatic pressure inactivation kinetics of Yersinia enterocolitica.
- A simplified log-logistic model offers an effective and parsimonious approach for predicting bacterial inactivation.
- The developed predictive models can estimate Yersinia enterocolitica survival curves at different pressures.
Abstract:
The survival curves of Yersinia enterocolitica ATCC 35669 inactivated by high hydrostatic pressure were obtained at four pressure levels (300, 350, 400, and 450 MPa) in sodium phosphate buffer (0.1 M, pH 7.0) and four pressure levels (350, 400, 450, 500 MPa) in UHT whole milk. Tailing was observed in all the survival curves. A linear model and three nonlinear models were fitted to these data and the performances of these models were compared. The linear regression model for survival curves at four pressure levels had regression coefficients (R2) values of 0.785-0.962 and mean square error (MSE) of 0.265-0.893. A residual plot strongly suggested that a linear regression function was not appropriate as there was strong curvature in the plotted data. The nonlinear regression model using the log-logistic had R2 values of 0.946-0.982 and MSE values of 0.110-0.320. The Weibull model had R2 values of 0.944-0.975 and MSE values of 0.153-0.349. These results indicated that both were better models to describe the pressure inactivation kinetics of Y. enterocolitica in milk and buffer. Among the three nonlinear models studied, the modified Gompertz model produced the poorest fit to data. The number of parameters of the log-logistic model was reduced from four to two so that the model was greatly simplified. The reduced log-logistic model still produced a fit comparable to the full model. Since pressure had no significant effect on the shape factors of the Weibull model at the pressure levels of 300-400 MPa for buffer and 400-500 MPa for milk, models were developed to predict survival curves of Y. enterocolitica at pressures different from the experimental pressures.