Advanced Quantitative Microbiology for Foods and Biosystems: Models for Predicting Growth and Inactivation (Hardback) book cover

Advanced Quantitative Microbiology for Foods and Biosystems

Models for Predicting Growth and Inactivation

By Micha Peleg

Series Editor: Fergus M. Clydesdale

© 2006 – CRC Press

456 pages | 175 B/W Illus.

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Hardback: 9780849336454
pub: 2006-04-12
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pub: 2006-04-12
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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.


“… 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

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

About the Series

Contemporary Food Science

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