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

수학적 정량평가모델을 이용한 Listeria monocytogenes의 성장 예측모델의 개발

  • 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)
  • 문성양 (강릉대학교 해양생명공학부) ;
  • 우건조 (식품의약품안전청) ;
  • 신일식 (강릉대학교 해양생명공학부)
  • Published : 2005.04.30


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.


predictive growth model;Listeria monocytogenes;polynomial model;square root model;maximum specific growth rate constant (k)


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