Dynamic Modeling and Sensitivity Analysis for Predicting the Pseudomonas spp. Concentration in Alaska Pollack along the Distribution Path

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.