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Modeling logistic performance in quantitative microbial risk assessment

(2010) RISK ANALYSIS. 30(1). p.20-31
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Abstract
In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage times, temperatures, gas conditions, and their distributions) are determined. However, the logistic chain with its queues (storages, shelves) and mechanisms for ordering products is usually not taken into account. As a consequence, storage times-mutually dependent in successive steps in the chain-cannot be described adequately. This may have a great impact on the tails of risk distributions. Because food safety risks are generally very small, it is crucial to model the tails of (underlying) distributions as accurately as possible. Logistic performance can be modeled by describing the underlying planning and scheduling mechanisms in discrete-event modeling. This is common practice in operations research, specifically in supply chain management. In this article, we present the application of discrete-event modeling in the context of a QMRA for Listeria monocytogenes in fresh-cut iceberg lettuce. We show the potential value of discrete-event modeling in QMRA by calculating logistic interventions (modifications in the logistic chain) and determining their significance with respect to food safety.
Keywords
fresh-cut vegetables, Discrete-event simulation, Listeria monocytogenes, logistic performance, quantitative microbial risk assessment, EQUILIBRIUM-MODIFIED ATMOSPHERE, LISTERIA-MONOCYTOGENES GROWTH, FRESH-CUT PRODUCE, EXPOSURE ASSESSMENT, ICEBERG LETTUCE, MICROBIOLOGICAL QUALITY, DELI MEATS, FOOD, PHASE, VEGETABLES

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Citation

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Chicago
Rijgersberg, Hajo, Seth Tromp, Liesbeth Jacxsens, and Mieke Uyttendaele. 2010. “Modeling Logistic Performance in Quantitative Microbial Risk Assessment.” Risk Analysis 30 (1): 20–31.
APA
Rijgersberg, H., Tromp, S., Jacxsens, L., & Uyttendaele, M. (2010). Modeling logistic performance in quantitative microbial risk assessment. RISK ANALYSIS, 30(1), 20–31.
Vancouver
1.
Rijgersberg H, Tromp S, Jacxsens L, Uyttendaele M. Modeling logistic performance in quantitative microbial risk assessment. RISK ANALYSIS. 2010;30(1):20–31.
MLA
Rijgersberg, Hajo, Seth Tromp, Liesbeth Jacxsens, et al. “Modeling Logistic Performance in Quantitative Microbial Risk Assessment.” RISK ANALYSIS 30.1 (2010): 20–31. Print.
@article{1019691,
  abstract     = {In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage times, temperatures, gas conditions, and their distributions) are determined. However, the logistic chain with its queues (storages, shelves) and mechanisms for ordering products is usually not taken into account. As a consequence, storage times-mutually dependent in successive steps in the chain-cannot be described adequately. This may have a great impact on the tails of risk distributions. Because food safety risks are generally very small, it is crucial to model the tails of (underlying) distributions as accurately as possible. Logistic performance can be modeled by describing the underlying planning and scheduling mechanisms in discrete-event modeling. This is common practice in operations research, specifically in supply chain management. In this article, we present the application of discrete-event modeling in the context of a QMRA for Listeria monocytogenes in fresh-cut iceberg lettuce. We show the potential value of discrete-event modeling in QMRA by calculating logistic interventions (modifications in the logistic chain) and determining their significance with respect to food safety.},
  author       = {Rijgersberg, Hajo and Tromp, Seth and Jacxsens, Liesbeth and Uyttendaele, Mieke},
  issn         = {0272-4332},
  journal      = {RISK ANALYSIS},
  keywords     = {fresh-cut vegetables,Discrete-event simulation,Listeria monocytogenes,logistic performance,quantitative microbial risk assessment,EQUILIBRIUM-MODIFIED ATMOSPHERE,LISTERIA-MONOCYTOGENES GROWTH,FRESH-CUT PRODUCE,EXPOSURE ASSESSMENT,ICEBERG LETTUCE,MICROBIOLOGICAL QUALITY,DELI MEATS,FOOD,PHASE,VEGETABLES},
  language     = {eng},
  number       = {1},
  pages        = {20--31},
  title        = {Modeling logistic performance in quantitative microbial risk assessment},
  url          = {http://dx.doi.org/10.1111/j.1539-6924.2009.01338.x},
  volume       = {30},
  year         = {2010},
}

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