학술논문

Predictive Modeling of the Growth and Survival of Listeria monocytogenes Using a Response Surface Model
Document Type
Article
Text
Source
Food Science and Biotechnology, 10/30/2006, Vol. 15, Issue 5, p. 715-720
Subject
Listeria monocytogenes
predictive model
temperature
specific growth rate
lag time
Language
English
ISSN
1226-7708
Abstract
This study was performed to develop a predictive model for the growth kinetics of Listeria monocytogenes in tryptic soy broth (TSB) using a response surface model with a combination of potassium lactate (PL), temperature, and pH. The growth parameters, specific growth rate (SGR), and lag time (LT) were obtained by fitting the data into the Gompertz equation and showed high fitness with a correlation coefficient of R2 ≥0.9192. The polynomial model was identified as an appropriate secondary model for SGR and LT based on the coefficient of determination for the developed model ( F2 = 0.97 for SGR and R2 = 0.86 for LT). The induced values that were calculated using the developed secondary model indicated that the growth kinetics of L. monocytogenes were dependent on storage temperature, pH, and PL. Finally, the predicted model was validated using statistical indicators, such as coefficient of determination, mean square error, bias factor, and accuracy factor. Validation of the model demonstrates that the overall prediction agreed well with the observed data. However, the model developed for SGR showed better predictive ability than the model developed for LT, which can be seen from its statistical validation indices, with the exception of the bias factor (B1 was 0.6 for SGR and 0.97 for LT).