Advanced Quantitative Microbiology for Foods and Biosystems Models for Predicting Growth and Inactivation

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.

Isothermal and Non-Isothermal Heat Inactivation. Modeling Non-isothermal Heat Inactivation with Difference Equations in Real Time (The Incremental Method). Estimation of the Weibulian-Log Logistic Survival Parameters from Non-Isothermal Inactivation Data. Isothermal Inactivation with Stable and Dissipating Chemical Agents. Inactivation by CO2 and Ultra High Hydrostatic Pressure. Microbial Dose Response Curves. Isothermal and Non-Isothermal Growth in a Closed Habitat. Interpretation of Fluctuating Microbial Records in Quality Control of Foods and Water. Discontinuous Growth and Decay Patterns. Outstanding Issues.