Modelling microbial responses in foods 1st Edition by Robin McKellar, Xuewen Lu 084931237X 9780849312373
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ISBN 10: 084931237X
ISBN 13: 9780849312373
Author: Robin C. McKellar, Xuewen Lu
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
Table of contents:
1. EXPERIMENTAL DESIGN AND DATA COLLECTION
1.1. EXPERIMENTAL DESIGN
1.2. DATA COLLECTION
1.3. CONCLUSION
REFERENCES
2. PRIMARY MODELS
2.1. GROWTH MODELS
2.2. SURVIVAL MODELS
REFERENCES
3. SECONDARY MODELS
3.1. INTRODUCTION
3.2. SECONDARY MODELS FOR GROWTH RATE AND LAG TIME
3.3. SECONDARY MODELS FOR INACTIVATION
3.4. PROBABILITY MODELS
APPENDIX A3.1 — CHARACTERIZATION OF ENVIRONMENTAL PARAMETERS AFFECTING MICROBIAL KINETICS IN FOODS
REFERENCES
4. MODEL FITTING AND UNCERTAINTY
4.1. OVERVIEW
4.2. MODEL FITTING
4.3. UNCERTAINTY IN LAG TIMES AND GENERATION TIMES, AND ITS CONSEQUENCES
4.4. EPILOGUE
APPENDIX
REFERENCES
5. CHALLENGE OF FOOD AND THE ENVIRONMENT
5.1. ROLE OF FOOD HETEROGENEITY
5.2. MODELING THE FOOD ENVIRONMENT
5.3. HURDLE CONCEPT
5.4. COMPETITION WITH OTHER MICROORGANISMS
5.5. ADAPTATION AND INJURY
5.6. VALIDATION IN FOODS
REFERENCES
6. SOFTWARE PROGRAMS TO INCREASE THE UTILITY OF PREDICTIVE MICROBIOLOGY INFORMATION
6.1. INTRODUCTION
6.2. MODEL INTERFACES
6.3. DATABASES
6.4. EXPERT SYSTEMS
6.5. CONCLUSIONS
REFERENCES
7. MODELING MICROBIAL DYNAMICS UNDER TIME-VARYING CONDITIONS
7.1. INTRODUCTION
7.2. GENERAL DYNAMIC MODELING METHODOLOGY
7.3. EXAMPLE I: INDIVIDUAL-BASED MODELING OF MICROBIAL LAG
7.4. EXAMPLE II. MODELING MICROBIAL INTERACTION WITH PRODUCT INHIBITION
7.5. CONCLUSIONS
ACKNOWLEDGMENTS
REFERENCES
8. PREDICTIVE MICROBIOLOGY IN QUANTITATIVE RISK ASSESSMENT
8.1. INTRODUCTION
8.2. ASSESSING MICROBIAL RISKS
8.3. ROLE OF PREDICTIVE MICROBIOLOGY IN QRA
8.4. SCOPE OF RISK ASSESSMENTS
8.5. PROCESS RISK MODELING
8.6. EXAMPLES OF RISK MODELING
8.7. MODIFYING RISK: CONCENTRATION VS. PREVALENCE
8.8. WHAT IS THE RIGHT MODEL TO USE?
8.9. FUTURE DIRECTIONS
8.10. CONCLUSIONS
REFERENCES
9. MODELING THE HISTORY EFFECT ON MICROBIAL GROWTH AND SURVIVAL: DETERMINISTIC AND STOCHASTIC APPROACHES
9.1. INTRODUCTION
9.2. MODELING THE HISTORY EFFECT AT POPULATION LEVEL (DETERMINISTIC MODELING)
9.3. MODELING THE HISTORY EFFECT AT SINGLE-CELL LEVEL (STOCHASTIC MODELING)
9.4. CONCLUDING REMARKS
ACKNOWLEDGMENT
REFERENCES
10. MODELS — WHAT COMES AFTER THE NEXT GENERATION?
10.1. INTRODUCTION
10.2. CROSS-CONTAMINATION
10.3. INOCULUM SIZE MODELING
10.4. CROSS-CONTAMINATION AND INOCULUM SIZE
10.5. SUMMARY
REFERENCES
11. PREDICTIVE MYCOLOGY
11.1. INTRODUCTION
11.2. CONCERNS
11.3. MOLD SPECIFICITIES
11.4. MODELS
11.5. PERSPECTIVES
REFERENCES
12. AN ESSAY ON THE UNREALIZED POTENTIAL OF PREDICTIVE MICROBIOLOGY
12.1. INTRODUCTION
12.2. A SHORT HISTORY AND THE PHILOSOPHY OF PREDICTIVE MICROBIOLOGY
12.3. THE BASICS OF PREDICTIVE MODELING
12.4. ADDRESSING CONCERNS IN PREDICTIVE MODELING
12.5. IDENTIFYING OPPORTUNITIES FROM PREDICTIVE MODELING
12.6. MODELING ATTACHMENT TO AND DETACHMENT FROM SURFACES
12.7. MODELING FUNGAL GROWTH
12.8. APPLICATION OF PREDICTIVE MICROBIOLOGY
12.9. CONCLUDING REMARKS
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Tags: Robin McKellar, Xuewen Lu, Modelling, responses