Korean Journal of Fisheries and Aquatic Sciences (한국수산과학회지)

The Korean Society of Fisheries and Aquatic Science (한국수산과학회)
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Dynamic Modeling and Sensitivity Analysis for Predicting the Pseudomonas spp. Concentration in Alaska Pollack along the Distribution Path

명태 유통 중 Pseudomonas spp. 농도의 예측 모델링과 민감도 분석

  • Shim, Soo-Dong (Department of Food Science and Technology, Dongguk University) ;
  • Sung, Jae-Ung (Department of Food Science and Technology, Pukyong National University) ;
  • Lee, Jung-Young (Department of Food Science and Technology, Dongguk University) ;
  • Lee, Da-Sun (Department of Food Science and Technology, Pukyong National University) ;
  • Kim, Seon-Bong (Department of Food Science and Technology, Pukyong National University) ;
  • Hong, Kwang-Won (Department of Food Science and Technology, Dongguk University) ;
  • Lee, Yang-Bong (Department of Food Science and Technology, Pukyong National University) ;
  • Lee, Seung-Ju (Department of Food Science and Technology, Dongguk University)
  • Received : 2009.10.16
  • Accepted : 2010.06.06
  • Published : 2010.06.30
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Abstract

Dynamic modeling was used to predict the Pseudomonas spp. concentration in Alaska pollack under dynamic temperature conditions in a programmable incubator using Euler's method. The model evaluation showed good agreement between the predicted and measured concentrations of Pseudomonas spp. In the simulation, three kinds of distribution path were assumed: consumers buying from a distribution center (A), manufacturer (B), or direct market (C). Each of these distribution paths consists of six phases: shipping, warehousing/shipment, warehousing/storing, processing, market exhibition, and sale/consumption. Sensitivity analysis of each phase was also implemented. The Pseudomonas concentrations and sensitivities ($S_k$) at the terminal phases of the three paths were estimated to be (A) 11.174 log CFU/g and 10.550 log $S_k$, (B) 10.948 log CFU/g and 10.738 log $S_k$, and (C) 8.758 log CFU/g and 9.602 log $S_k$, respectively. The sensitivities indicated that path A has the highest risk of failure in managing the relevant phases.

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References

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