Lihan Huang

Publications (2)3.32 Total impact

• Article: Effect of temperature on microbial growth rate-mathematical analysis: the Arrhenius and Eyring-Polanyi connections.

  Lihan Huang, Andy Hwang, John Phillips
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  ABSTRACT: The objective of this work is to develop a mathematical model for evaluating the effect of temperature on the rate of microbial growth. The new mathematical model is derived by combination and modification of the Arrhenius equation and the Eyring-Polanyi transition theory. The new model, suitable for both suboptimal and the entire growth temperature ranges, was validated using a collection of 23 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. The resulting estimated growth rate (μ) values are highly correlated to the data collected from the literature (R(2) = 0.985, slope = 1.0, intercept = 0.0). The bias factor (B(f) ) of the new model is very close to 1.0, while the accuracy factor (A(f) ) ranges from 1.0 to 1.22 for most data sets. The new model is compared favorably with the Ratkowsky square root model and the Eyring equation. Even with more parameters, the Akaike information criterion, Bayesian information criterion, and mean square errors of the new model are not statistically different from the square root model and the Eyring equation, suggesting that the model can be used to describe the inherent relationship between temperature and microbial growth rates. The results of this work show that the new growth rate model is suitable for describing the effect of temperature on microbial growth rate. Practical Application:  Temperature is one of the most significant factors affecting the growth of microorganisms in foods. This study attempts to develop and validate a mathematical model to describe the temperature dependence of microbial growth rate. The findings show that the new model is accurate and can be used to describe the effect of temperature on microbial growth rate in foods.
  Journal of Food Science 10/2011; 76(8):E553-60. · 1.66 Impact Factor
• Article: Evaluating the effect of temperature on microbial growth rate--the Ratkowsky and a Bělehrádek-type models.

  Lihan Huang, Cheng-An Hwang, John Phillips
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  ABSTRACT: The objective of this paper to conduct a parallel comparison of a new Bělehrádek-type growth rate (with an exponent of 1.5, or the 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 selected from the literature, and independently analyzed with the 3 models using nonlinear regression. Analysis of variance (ANOVA) was used to compare the means of growth rate (μ), estimated minimum temperature (T(min) ), approximate standard errors (SE) of T(min) , model mean square errors (MSE), accuracy factor (A(f) ), bias factor (B(f) ), relative residual errors (δ), Akaike information criterion (AICc), and Bayesian information criterion (BIC). Based on the estimated T(min) values, the Huang model distinctively classified the bacteria into 2 groups (psychrotrophs and mesophiles). No significant difference (P > 0.05) was observed among the means of the μ values reported in the literature or estimated by the 3 models, suggesting that all 3 models were suitable for curve fitting. Nor was there any significant difference in MSE, SE, δ, A(f) , B(f) , AICc, and BIC. The T(min) values estimated by the Huang model were significantly higher than those estimated by the Ratkowsky models, but were in closer agreement with the biological minimum temperatures for both psychrotrophs and mesophiles. The T(min) values estimated by the Ratkowsky models systematically underestimated the minimum growth temperatures. In addition, statistical estimation showed that the mean exponent for the new Bělehrádek-type growth rate model may indeed be 1.5, further supporting the validity of the Huang model.
  Journal of Food Science 10/2011; 76(8):M547-57. · 1.66 Impact Factor