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United States Department of Agriculture

Agricultural Research Service

Research Project: MICROBIAL MODELING AND BIOINFORMATICS FOR FOOD SAFETY AND SECURITY

Location: Residue Chemistry and Predictive Microbiology

Title: Evaluating the effect of temperature on microbial growth rate - the Ratkowsky and a Belehrádek type models

Authors
item Huang, Lihan
item Hwang, Cheng-An
item Phillips, John

Submitted to: Journal of Food Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 1, 2011
Publication Date: October 1, 2011
Citation: Huang, L., Hwang, C., Phillips, J.G. 2011. Evaluating the effect of temperature on microbial growth rate - the Ratkowsky and a Belehrádek type models. Journal of Food Science. 76(8):547-557.

Interpretive Summary: Temperature is one of the most important factors affecting the growth of foodborne pathogens in foods. Accurate estimation on the effect of temperature on bacterial growth is critical for microbial risk assessment. The objective of this research is to evaluate the accuracy of a new mathematical model for describing the temperature effect. The results indicate that the new mathematical model is an accurate model for evaluating the effect of temperature on bacterial growth. The obtained information will provide risk assessors with a more reliable tool for estimating potential growth of pathogens in foods.

Technical Abstract: The objective of this paper to conduct a parallel comparison of a new Belehradek-type growth rate (Huang model), Ratkowsky Square-root, and Ratkowsky Square equations as secondary models for evaluating the effect of temperature on the growth of microorganisms. Growth rates of psychrotrophs and mesophiles were randomly selected from the literature, and independently analyzed with the three models using nonlinear regression. Analysis of variance (ANOVA) was used to compare the means of growth rate (mu), estimated minimum temperature (Tmin), approximate standard errors (SE) of Tmin, model mean square errors (MSE), accuracy factor (Af), bias factor (Bf), relative residual errors (delta), Akaike Information Criterion (AICc), and Bayesian Information Criterion (BIC). Based on the estimated Tmin values, the Huang model distinctively classified the bacteria into two groups (psychrotrophs and mesophiles). No significant difference (p > 0.05) was observed among the means of the mu values reported in the literature or estimated by the three models, suggesting that all three models were suitable for curve-fitting. Nor was there any significant difference in MSE, SE, delta, Af, Bf, AICc, and BIC. The Tmin values estimated by the Huang model were significantly higher than those estimated by the Ratkowsky models. The Ratkowsky models systematically underestimated the minimum growth temperatures, leading to derived Tmin values generally lower than the biological minimums reported in the literature. The Tmin values estimated by the Huang model, however, were in closer agreement with the biological minimum temperatures for both psychrotrophs and mesophiles. In addition, statistical estimation showed that the mean exponent for the new Belehradek-type growth rate model may indeed be 1.5, further supporting the validity of the Huang model.

Last Modified: 9/21/2014
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