Development of a predictive mathematical model for the growth kinetics of Listeria monocytogenes in sesame leaves

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Title
Development of a predictive mathematical model for the growth kinetics of Listeria monocytogenes in sesame leaves
Author(s)
S Y Park; J W Choi; D H Chung; Min-Gon Kim; K H Lee; K S Kim; G J Bahk; D H Bae; S K Park; K Y Kim; C H Kim; S D Ha
Bibliographic Citation
Food Science and Biotechnology, vol. 16, no. 2, pp. 238-242
Publication Year
2007
Abstract
Square root models were developed for predicting the kinetics of growth of Listeria monocytogenes in sesame leaves as a function of temperature (4, 10, or 25°C). At these storage temperatures, the primary growth curves fit well (R2=0.898 to 0.980) to a Gompertz equation to obtain lag time (LT) and specific growth rate (SGR). The square root models for natural logarithm transformations of the LT and SGR as a function of temperature were obtained by SAS's regression analysis. As storage temperature (4-25°C) decreased, LT increased and SGR decreased, respectively. Square root models were identified as appropriate secondary models for LT and SGR on the basis of most statistical indices such as coefficient determination (R2=0.961 for LT, 0.988 for SGR), mean square error (MSE=0.197 for LT, 0.005 for SGR), and accuracy factor (Af=1.356 for LT, 1.251 for SGR) although the model for LT was partially not appropriate as a secondary model due to the high value of bias factor (Bf=1.572). In general, our secondary model supported predictions of the effects of temperature on both LT and SGR for L. monocytogenes in sesame leaves.
Keyword
gompertz equationlisteria monocytogenesesame leavesquare root modeltemperature
ISSN
1226-7708
Publisher
Korea Soc-Assoc-Inst
Type
Article
Appears in Collections:
1. Journal Articles > Journal Articles
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