Modeling Microbial Responses in Food

Modeling Microbial Responses in Food

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ISBN 9780849312373
Cat# 1237
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ISBN 9780203503942
Cat# TFE1246
 

Features

  • Provides information on experimental design and use of primary and secondary models, with examples of fitting strategies
  • Presents methods and approaches for relating models to food and food processing
  • Discusses growth and survival models with a primary focus on microbial applications
  • Includes information on fitting models to experimental data, sources of variation, pitfalls, and solutions
  • Summary

    The first state-of-the-art review of this dynamic field in a decade, Modeling Microbial Responses in Foods provides the latest information on techniques in mathematical modeling of microbial growth and survival. The comprehensive coverage includes basic approaches such as improvements in the development of primary and secondary models, statistical fitting strategies, and novel data collection methods.

    An international team of experts explore important developing areas, including specific applications, challenges in applying models to foods, variability and uncertainty, and new modeling strategies. The authors present detailed descriptions of non-linear regression fitting, methods, approaches relevant to 'real world' situations, and extensive applications of predictive models. They conclude by highlighting the strengths and weaknesses in the field and areas for future work, and attempt to resolve some of the outstanding conflicts.

    The book includes strategies for combining databases, improving researcher networks, and standardization of applications packages. Providing the uninitiated with enough information to begin developing their own models, Modeling Microbial Responses in Foods covers all aspects of growth and survival modeling from the primary stage of gathering data to the implementation of final models in appropriate delivery systems.

    Table of Contents

    EXPERIMENTAL DESIGN AND DATA COLLECTION, M. Rasch
    Experimental Design
    Data Collection
    Conclusion
    References

    PRIMARY MODELS, R.C. McKellar and X. Lu
    Growth Models
    Survival Models
    References

    SECONDARY MODELS, T. Ross and P. Dalgaard
    Introduction
    Secondary Models for Growth Rate and Lag Time
    Secondary Models for Inactivation
    Probability Models
    Characterization of Environmental Parameters Affecting Microbial Kinetics in Food
    References

    MODEL FITTING AND UNCERTAINTY, D.A. Ratkowsky
    Overview
    Model Fitting
    Uncertainty in Lag Times, Generation Times, and Its Consequences
    Epilogue
    Appendix
    References

    CHALLENGE OF FOOD AND THE ENVIRONMENT, T. Brocklehurst
    Role of Food Heterogeneity
    Modeling the Food Environment
    Hurdle Concept
    Competition with Other Microorganisms
    Adaptation and Injury
    Validation in Foods
    References

    SOFTWARE PROGRAMS TO INCREASE THE UTILITY OF PREDICTIVE MICROBIOLOGY INFORMATION, M. Tamplin, J. Baranyi, and G. Paoli
    Introduction
    Model Interfaces
    Databases
    Expert Systems
    Conclusions
    References

    MODELING MICROBIAL DYNAMICS UNDER TIME-VARYING CONDITIONS, K. Bernaerts, E. Dens, K. Vereecken, A. Geeraerd, F. Devlieghere, J. Debevere, and J.F. Van Impe
    Introduction
    General Dynamic Modeling Methodology
    Example I: Individual-Based Modeling of Microbial Lag
    Example II. Modeling Microbial Interaction with Product Inhibition
    Conclusions
    Acknowledgments
    References

    PREDICTIVE MICROBIOLOGY IN QUANTITATIVE RISK ASSESSMENT, A.M. Lammerding and R.C. McKellar
    Introduction
    Assessing Microbial Risks
    Role of Predictive Microbiology in QRA
    Scope of Risk Assessments
    Process Risk Modeling
    Examples of Risk Modeling
    Modifying Risk: Concentration vs. Prevalence
    What is the Right Model to Use?
    Future Directions
    Conclusions
    References

    MODELING THE HISTORY EFFECT ON MICROBIAL GROWTH AND SURVIVAL: DETERMINISTIC AND STOCHASTIC APPROACHES, J. Baranyi and C. Pin
    Introduction
    Modeling the History Effect at Population Level (Deterministic Modeling)
    Modeling the History Effect at Single-Cell Level (Stochastic Modeling)
    Concluding Remarks
    Acknowledgment References

    MODELS - WHAT COMES AFTER THE NEXT GENERATION? D.W. Schaffner
    Introduction
    Cross-Contamination
    Inoculum Size Modeling
    Cross-Contamination and Inoculum Size
    Summary
    References

    PREDICTIVE MYCOLOGY, P. Dantigny
    Introduction
    Concerns
    Mold Specificities
    Models
    Perspectives
    References

    AN ESSAY ON THE UNREALIZED POTENTIAL OF PREDICTIVE MICROBIOLOGY, T. McMeekin
    Introduction
    A Short History and the Philosophy of Predictive Microbiology
    The Basics of Predictive Modeling
    Addressing Concerns in Predictive Modeling
    Modeling Fungal Growth
    Application of Predictive Microbiology
    Concluding Remarks
    Acknowledgments
    References
    Index

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