Advanced Quantitative Microbiology for Foods and Biosystems: Models for Predicting Growth and Inactivation
Features
Summary
Presenting a novel view of the quantitative modeling of microbial growth and inactivation patterns in food, water, and biosystems, Advanced Quantitative Microbiology for Foods and Biosystems: Models for Predicting Growth and Inactivation describes new models for estimating microbial growth and survival. The author covers traditional and alternative models, thermal and non-thermal preservation, water disinfection, microbial dose response curves, interpretation of irregular count records, and how to estimate the frequencies of future outbursts. He focuses primarily on the mathematical forms of the proposed alternative models and on the rationale for their introduction as substitutes to those currently in use.
The book provides examples of how some of the methods can be implemented to follow or predict microbial growth and inactivation patterns, in real time, with free programs posted on the web, written in MS ExcelÒ, and examples of how microbial survival parameters can be derived directly from non-isothermal inactivation data and then used to predict the efficacy of other non-isothermal heat treatments. Featuring numerous illustrations, equations, tables, and figures, the book elucidates a new approach that resolves several outstanding issues in microbial modeling and eliminates inconsistencies often found in current methods.
Table of Contents
Isothermal Microbial Heat Inactivation
Primary Models — the Traditional Approach
The Survival Curve as a Cumulative Form of the Heat Distribution Resistances
Secondary Models
Nonisothermal Heat Inactivation
The Traditional Approach
The Proposed Alternative
Nonisothermal Weibuillian Survival
Non Weibullian Survival Models
Experimental Verification of the Model
Heat-Induced Chemical and Physical Changes
Generating Nonisothermal Heat Inactivation Curves with Difference Equations in Real Time (Incremental Method)
The Difference Equation of the Weibullian–Log Logistic
Non-isothermal Survival Model
Non Weibullian Survival Curves
Comparison between the Continuous and
Incremental Models
Estimation of Microbial Survival Parameters from Nonisothermal Inactivation Data
The Linear Case
The Nonlinear Case
Concluding Remarks
Isothermal Inactivation with Stable and Dissipating Chemical Agents
Chemical Inactivation under “Constant” Agent Concentration
Microbial Inactivation with a Dissipating Chemical Agent
Estimation of Survival Parameters from Data Obtained during Treatments with a Dissipating Agent
Discrete Version of the Survival Model
High CO2 and Ultrahigh Hydrostatic Pressure Preservation
Microbial Inactivation under High CO2 Pressure
Ultrahigh Pressure
How to Use the Model
Dose–Response Curves
The Fermi (Logistic) Distribution
The Weibull Distribution
Mixed Populations
Isothermal and Nonisothermal Bacterial Growth in a Closed Habitat
The Traditional Models
The Logistic–Fermi Combination Model
Simulation of Non-isothermal Growth Patterns
Using the Logistic–Fermi Model
Prediction of Non-isothermal Growth Patterns from Isothermal Growth Data
Interpretation of Fluctuating Microbial Count Records in Foods and Water
Microbial Quality Control in a Food Plant
The Origins and Nature of Microbial Count Fluctuations
Asymmetry between Life and Death
Estimating the Frequency of Future Outbursts — the Principle
Testing Counts Independence
Uneven Rounding and Record De-rounding
Choosing a Distribution Function
Extinction and Absence
Special Patterns
Estimating Frequencies of Future Microbial High Counts or Outbursts in Foods and Water — Case Studies
Microbial Counts in a Cheese-Based Snack
Rating Raw Milk Sources
Frozen Foods
E. coli in Wash Water of a Poultry Plant
Fecal Bacteria in Lake Kinneret
Characterization of Truncated Count Distributions
Issues of Concern
A Probabilistic Model of Historic Epidemics
The Model
Mortality from Smallpox and Measles in 18th Century England
Potential Uses of the Model in Contemporary Epidemiology
Aperiodic Microbial Outbursts with Variable Duration
Microbial Fluctuations in a Water Reservoir
A Model of Pathogen Outbursts in Foods
Other Potential Applications of the Model
Outstanding Issues and Concluding Remarks
Inactivation Models
Growth Models
Fluctuating Records in Water and Foods
A Few Last Remarks
Freeware Index
Editorial Reviews
“… skills in mathematical modelling to describing the behaviuor of micro-organisms in foods and other systems. This book describes much of this work. … Inactivation models such as the Weibullian power law that more accurately reflects the non-log-linear survival curves frequently found in practice, are described in detail in the context of heat and other inimical treatments. …”
— Martin Adams, University of Surrey, in Society for General Microbiology, (SGM), current Issue, Quarterly Review
