McKellar / Lu Modeling Microbial Responses in Food

1. Auflage 2003
ISBN: 978-1-135-51374-0
Verlag: CRC Press
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 360 Seiten

Reihe: Contemporary Food Science

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.

Zielgruppe

Researchers in food science, microbiology, engineering, biotechnology, water quality: industry quality control managers; HACCP specialists; process engineers; agricultural engineers; students

Autoren/Hrsg.

McKellar, Robin C.

Lu, Xuewen

Fachgebiete

• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Lebensmitteltechnologie und Getränketechnologie

Inhaltsverzeichnis

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