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Related Experiment Videos

Predicting microbial growth: graphical methods for comparing models.

N Bratchell1, P J McClure, T M Kelly

  • 1AFRC Institute of Food Research, Reading Laboratory, Shinfield, U.K.

International Journal of Food Microbiology
|December 1, 1990
PubMed
Summary
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Computer graphics visually compared microbial growth models for Salmonella. Differences in predictions for pH, salt, and temperature were evident, aiding model selection for food safety applications.

Area of Science:

  • Microbiology
  • Food Science
  • Computational Biology

Background:

  • Predicting microbial growth is crucial for food safety.
  • Various models exist to predict Salmonella growth under different conditions.
  • Accurate models are needed to assess food spoilage and safety risks.

Purpose of the Study:

  • To compare different computer-based models for predicting Salmonella growth.
  • To evaluate the sensitivity of graphical methods in differentiating model predictions.
  • To assess the utility of various plotting techniques for model comparison.

Main Methods:

  • Utilized simple computer-based graphics for model comparison.
  • Employed simple linear regression, contour plots, and 3D surface plots.

Related Experiment Videos

  • Compared model predictions for Salmonella growth responses to pH, sodium chloride, and incubation temperature.

    • Main Results:

    • Graphical methods revealed significant differences between predicted growth parameters from various models.
    • Regression and contour plots demonstrated higher sensitivity to subtle variations in model outputs.
    • Three-dimensional surface plots offered a comprehensive visual overview of model performance.

    Conclusions:

    • Computer-based graphical comparisons are effective for evaluating microbial growth models.
    • Different plotting techniques offer distinct advantages for visualizing model discrepancies.
    • These methods aid in selecting appropriate models for predicting Salmonella behavior in food systems.