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Development of Predictive Growth Model of Listeria monocytogenes Using Mathematical Quantitative Assessment Model  

Moon, Sung-Yang (Faculty of Marine Bioscience & Technology, Kangnung National University)
Woo, Gun-Jo (Korea Food and Drug Administration)
Shin, Il-Shik (Faculty of Marine Bioscience & Technology, Kangnung National University)
Publication Information
Korean Journal of Food Science and Technology / v.37, no.2, 2005 , pp. 194-198 More about this Journal
Abstract
Growth curves of Listeria monocytogenes in modified surimi-based imitation crab (MIC) broth were obtained by measuring cell concentration in MIC broth at different culture conditions [initial cell numbers, $1.0{\times}10^{2},\;1.0{\times}10^{3}\;and\;1.0{\times}10^{4}$, colony forming unit (CFU)/mL; temperature, 15, 20, 25, 37, and $40^{\circ}C$] and applied to Gompertz model to determine microbial growth indicators, maximum specific growth rate constant (k), lag time (LT), and generation time (GT). Maximum specific growth rate of L. monocytogenes increased rapidly with increasing temperature and reached maximum at $37^{\circ}C$, whereas LT and GT decreased with increasing temperature and reached minimum at $37^{\circ}C$. Initial cell number had no effect on k, LT, and GT (p > 0.05). Polynomial and square root models were developed to express combined effects of temperature and initial cell number using Gauss-Newton Algorism. Relative coefficients of experimental k and predicted k of polynomial and square root models were 0.92 and 0.95, respectively, based on response surface model. Results indicate L. monocytogenes growth was mainly affected by temperature and square root model was more effective than polynomial model for growth prediction.
Keywords
predictive growth model; Listeria monocytogenes; polynomial model; square root model; maximum specific growth rate constant (k);
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