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

by Micha Peleg

Book Details

Format Hardback or Cased Book
ISBN-10 0849336457
ISBN-13 9780849336454
Publisher Taylor & Francis Inc
Imprint CRC Press Inc
Country of Manufacture GB
Country of Publication GB
Publication Date Apr 12th, 2006
Print length 456 Pages
Weight 749 grams
Product Classification: Molecular biologyFood & beverage technology
Ksh 42,300.00
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Presenting a fresh view of the quantitative modeling of microbial growth and inactivation patterns in food, water and biosystems, this book describes various models to predict microbial growth and survival under a variety of conditions. It covers traditional and alternative models of thermal and non-thermal 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.

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