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Related Experiment Videos

Risk Assessment and Predictive Microbiology.

Robert L Buchanan1, Richard C Whiting1

  • 1Microbial Food Safety Research Unit, U.S. Department of Agriculture, Agricultural Research Service, Eastern Regional Research Center, 600 East Mermaid Lane, Philadelphia, PA 19118, USA.

Journal of Food Protection
|April 7, 2017
PubMed
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Quantitative microbial risk assessments (QRA) in food processing are challenging due to bacterial population dynamics. Predictive food microbiology models offer a solution by integrating with risk assessment to predict food safety outcomes.

Area of Science:

  • Food safety science
  • Microbiology
  • Risk assessment

Background:

  • Quantitative microbial risk assessment (QRA) is crucial for food processing and preparation.
  • Limited application of QRA is due to challenges in modeling bacterial population changes during food processing.

Purpose of the Study:

  • To explore the integration of predictive food microbiology models with risk assessment.
  • To overcome limitations in applying QRA to food processing operations.

Main Methods:

  • Utilizing predictive food microbiology models.
  • Integrating these models with quantitative risk assessment frameworks.
  • Applying the integrated approach to hypothetical single-step and multiple-step food processing operations.
Keywords:
Modelingrisk analysis

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Main Results:

  • Demonstrated the potential of predictive modeling to account for bacterial population changes.
  • Showcased how integrating predictive models with risk assessment can estimate the impact of processing changes on food safety.
  • Provided hypothetical examples of application in food processing.

Conclusions:

  • Predictive food microbiology models are key to advancing QRA in food processing.
  • Integration of modeling and risk assessment enables better prediction of food safety.
  • This approach can guide improvements in food processing and preparation operations.