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 cures, 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 programs written in MS Excel and posted on the Web. It also shows 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 figues, the book offers a new approach that resolves several outstanding issues in microbial modeling and eliminates inconsistencies often found in the conventional methods.

Content - 1 Isothermal Microbial Heat Inactivation, 2    Nonisothermal Heat Inactivation, 3 Generating Nonisothermal Heat Inactivation  Curves with Difference Equations in Real Time (Incremental Method), 4 Estimation of Microbial Survival Parameters from Nonisothermal Inactivation Data, 5 Isothermal Inactivation with Stable and Dissipating Chemical Agents, 6 High CO₂ and Ultrahigh Hydrostatic Pressure Preservation, 7 Dose-Response Curves, 8 Isothermal and Nonisothermal Bacterial Growth in a Closed Habitat, 9 Interpretation of Fluctuating Microbial Count Records in Foods and Water, 10 Estimating Frequencies of Future Microbial High Counts or Outbursts in Foods and Water - Case Studies, 11 A Probabilistic Model of Historic Epidemics, 12 Aperiodic Microbial Outbursts with Variable Duration, 13 Outstanding Issues and Concluding Remarks, References, Freeware, Index