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

By: (Author) Micha Peleg

Werezi Extended Catalogue
Delivery in 34 days

Ksh 39,600.00

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 biology
Food & beverage technology

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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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