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Modeling Applications.

Thomas A McMEEKIN1, Thomas Ross1

  • 1Department of Agricultural Science, University of Tasmania, GPO Box 252C, Hobart Tasmania 7001 Australia.

Journal of Food Protection
|April 7, 2017
PubMed
Summary
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Predictive microbiology models are now validated for many food types, offering significant industry benefits. These models interpret environmental data to ensure food quality and safety.

Area of Science:

  • Food science and technology
  • Microbiology
  • Data science

Background:

  • Predictive microbiology models have advanced through experimental design, development, and validation.
  • Validated models offer general rules applicable to specific microorganism/food combinations.
  • Confidence in predictive models is growing, indicating substantial benefits for the food industry.

Purpose of the Study:

  • To highlight the benefits of validated predictive microbiology models in the food industry.
  • To address the challenge of integrating environmental monitoring systems for informed decision-making.
  • To explore specific applications of predictive modeling for food quality and safety assurance.

Main Methods:

  • Utilizing validated predictive models to interpret microbial proliferation based on environmental histories (e.g., temperature).
Keywords:
Predictive microbiologyapplications technologymodel developmentmodel softwaremodel use

Related Experiment Videos

  • Developing user-friendly, reliable, and secure systems for collecting and interpreting environmental data.
  • Leveraging quantitative data and inherent model qualities for enhanced predictions.

    • Main Results:

    • Sufficient confidence exists for certain microorganism/food combinations to demonstrate substantial benefits.
    • Environmental monitoring devices provide crucial data for predictive model interpretation.
    • Predictive models enable objective, rapid assessment of environmental impacts on microbial growth.

    Conclusions:

    • Validated predictive models offer increased precision and confidence in food safety predictions.
    • These models provide flexibility in monitoring processing, distribution, and storage to assure shelf life.
    • The integration of predictive modeling systems empowers industrial users to make informed decisions regarding food quality and safety.