Modelling Microorganisms in Food

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ISBN: 9781845690069 | 1845690060
Cover: Hardcover
Copyright: 3/12/2007

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Predicting the growth and behaviour of microorganisms in food more successfully has long been an aim in food microbiology research. In recent years, microbial models have evolved to become more exact. The discipline of quantitative microbial ecology has also gained increasing importance for food safety management, particularly as modern processing methods more often operate closer to microbial death, survival and growth boundaries and therefore require more precise models. Modelling microorganisms in food assesses the latest developments and provides an outlook for the future of microbial modelling.

Contributor contact details	p. xi
Introduction	p. 1
References	p. 4
Building models for predictive microbiology
Predictive microbiology: past, present and future	p. 7
Introduction	p. 7
Turning data into knowledge	p. 11
Case studies of critical analysis	p. 12
Recent systematic analysis of literature and the advent of quantitative microbial risk assessment (QMRA)	p. 15
QMRA and predictive microbiology	p. 15
Advances in technology for the application of predictive models	p. 17
Conclusions	p. 18
References	p. 19
Experimental design, data processing and model fitting in predictive microbiology	p. 22
Introduction	p. 22
Experimental design	p. 24
Data processing	p. 34
Model fitting	p. 36
Future trends	p. 38
Sources of further information and advice	p. 39
References	p. 39
Appendix	p. 42
Uncertainty and variability in predictive models of microorganisms in food	p. 44
Introduction	p. 44
Case study - part 1	p. 45
Imprecise predictive models	p. 46
Case study - part 2	p. 48
A closer look at variability	p. 51
A closer look at uncertainty	p. 52
Separation of uncertainty and variability	p. 54
Case study - epilogue	p. 57
Categorising questions of food professionals	p. 59
GMPs for unpredictable microbes	p. 60
Current developments and future trends: towards novel predictive models	p. 63
Conclusions	p. 65
References	p. 65
Modelling lag-time in predictive microbiology with special reference to lag phase of bacterial spores	p. 67
Introduction: general aspects of lag-time	p. 67
Lag-time of bacterial spores, transformation of the spore to vegetative cells	p. 69
Quantitative aspects, mathematical modelling	p. 73
Lag-times in real foods	p. 78
Conclusions	p. 79
References	p. 79
Application of models and other quantitative microbiology tools in predictive microbiology	p. 82
Introduction	p. 82
Definitions	p. 82
Applications of models and databases	p. 83
Access to models	p. 93
Other quantitative microbiology tools	p. 98
Future trends	p. 103
Sources of further information and advice	p. 104
Acknowledgements	p. 105
References	p. 106
Predictive models in microbiological risk assessment	p. 110
Quantitative microbiological risk assessment	p. 110
Quantitative microbiology	p. 111
Recontamination	p. 112
Linking models	p. 113
Information sources	p. 119
Representativeness of models	p. 120
Food Safety Objectives and risk assessment	p. 121
Examples of structured approaches of risk assessment	p. 122
Conclusions	p. 124
References	p. 125
New approaches to microbial modelling in specific areas of predictive microbiology
The non-linear kinetics of microbial inactivation and growth in foods	p. 129
Introduction	p. 129
The traditional primary models of inactivation and growth	p. 130
Traditional secondary models	p. 132
Sigmoid isothermal survival curves	p. 143
Non-isothermal inactivation	p. 145
Empirical growth models	p. 149
Simulation of non-isothermal growth curves	p. 154
Conclusions	p. 156
Acknowledgements	p. 158
References	p. 158
Modelling of high-pressure inactivation of microorganisms in foods	p. 161
Introduction	p. 161
Factors affecting microbial inactivation by high-pressure processing	p. 162
Current models: strengths and weaknesses	p. 169
Further developments in the modelling of pressure-temperature processes	p. 183
Conclusions	p. 190
References	p. 191
Mechanistic models of microbial inactivation behaviour in foods	p. 198
Introduction	p. 198
Case for mechanistic models	p. 199
Development of mechanistic models for microbial inactivation	p. 203
Model validation and comparison with others	p. 205
Applications of microbial inactivation mechanistic models	p. 208
Strengths, weaknesses, and limitations of mechanistic models	p. 210
Future trends with mechanistic models	p. 211
Sources of further information and advice	p. 212
References	p. 212
Modelling microbial interactions in foods	p. 214
Introduction	p. 214
Measuring growth and interactions of bacteria in foods	p. 216
Developing models of microbial interactions	p. 217
Applications and implications for food processors	p. 221
Future trends	p. 222
References	p. 224
A kinetic model as a tool to understand the response of Saccharomyces cerevisiae to heat exposure	p. 228
Introduction	p. 228
Experimental data	p. 230
The model	p. 237
Validation	p. 239
Conclusions	p. 240
References	p. 242
Addendum	p. 246
Systems biology and food microbiology	p. 250
Introduction	p. 250
Systems biology: biology at last	p. 250
Systems biology and food microbiology	p. 259
Food production: metabolic engineering	p. 261
Food safety	p. 270
Areas for systems food microbiology in microbial food spoilage research	p. 273
Models of microbial ecology and food consumption	p. 274
Sources of further information and advice	p. 276
Acknowledgements	p. 277
References	p. 277
Addendum 1	p. 282
Addendum 2	p. 286
Index	p. 289
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