4.3 Article

A predictive model for the growth rate of Bacillus cereus in broth by response surface methodology

Journal

BIOTECHNOLOGY AND BIOPROCESS ENGINEERING
Volume 14, Issue 2, Pages 202-206

Publisher

KOREAN SOC BIOTECHNOLOGY & BIOENGINEERING
DOI: 10.1007/s12257-008-0187-0

Keywords

response surface methodology (RSM); Bacillus cereus; growth rates; predictive model; Gompertz

Funding

  1. Chung-Ang University Research Scholarship

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A response surface methodology (RSM) was developed for predicting the growth rate of Bacillus cereus in a tryptic soy broth medium as a function of temperature (10 to 40A degrees C), pH (5.5 to 8.5), and the NaCl concentration (0 to 8%). The primary model showed a good fit (r(2) = 0.920 to 0.999) to a Gompertz equation to obtain growth rates each condition. The quadratic polynomial model was found to be significant (p < 0.0001) and predicted values were found to be in good agreement with experimental values (R-2 value of 0.9486). The evaluation of RSM for describing the growth rate of B. cereus used the bias factor (B-f) and the accuracy factor (A(f)). Both the B-f value (1.11) and the A(f) value (1.50) were within acceptable ranges. This model was provided an efficient and accurate method for predicting the growth of B. cereus as a function of the controlling factors.

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