Submitted to: Journal of Food Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 29, 2011
Publication Date: October 1, 2011
Citation: Huang, L., Hwang, C., Phillips, J.G. 2011. Effect of temperature on microbial growth rate - thermodynamic analysis, the arrhenius and eyring-polanyi connection. Journal of Food Science. 76:553-560. Interpretive Summary: Temperature significantly affects the growth of pathogens in foods. It is necessary to develop mathematical models that can evaluate the effect of temperature on bacterial growth. The objective of this research is to develop a new thermodynamic model to accurately describe the temperature effect on bacterial growth. The result of this research can be used by regulatory agencies and food manufacturers for risk assessment.
Technical Abstract: The objective of this work is to develop a new thermodynamic mathematical model for evaluating the effect of temperature on the rate of microbial growth. The new mathematical model is derived by combining the Arrhenius equation and the Eyring-Polanyi transition theory. The new model, suitable for both suboptimal and the entire biokinetic temperature ranges, is validated using a collection of 24 randomly selected temperature-growth rate curves belonging to 5 groups of microorganisms, including Pseudomonas spp., Listeria monocytogenes, Salmonella spp., Clostridium perfringens, and Escherichia coli, from the published literature. The curve-fitting is accomplished by nonlinear regression using the Levenberg-Marquardt algorithm (NLIN, SAS 9.2). For curve-fitting, the mean square errors (mse) are very small. The resulting estimated growth rate (mu values are highly correlated to the data collected from the literature (R_square = 0.988, slope = 1.0, intercept = 0.0). The bias factor (Bf) of the new model is very close to 1.0, while the accuracy factor (Af) ranges from 1.0 to 1.22. The new model is compared with three additional secondary models, including the Ratkowsky Square-Root model, Belehrádek-type model, and a traditional Arrhenius- Eyring equation. The new model has the smallest average values of the Akaike Information Criterion (AICc) and Bayesian Information Criterion (BIC). The results of this work show that the new thermodynamics-based growth rate model is suitable for describing the effect of temperature on microbial growth rate.