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Modeling Microbial Responses in Food
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Product Details
Author:
Robin C. McKellar, Xuewen Lu
Format:
Paperback
Pages:
360
Publisher:
CRC Press (September 19, 2019)
Language:
English
ISBN-13:
9780367394653
Weight:
16oz
Dimensions:
6.125" x 9.1875"
File:
TAYLORFRANCIS-TayFran_260403050946149-20260403.xml
Folder:
TAYLORFRANCIS
List Price:
$89.99
Case Pack:
1
As low as:
$85.49
Publisher Identifier:
P-CRC
Discount Code:
H
Audience:
Professional and scholarly
Country of Origin:
United States
Pub Discount:
30
Imprint:
CRC Press
Overview
The first state-of-the-art review of this dynamic field in a decade, Modeling Microbial Responses in Foods provides the latest information on techniques in mathematical modeling of microbial growth and survival. The comprehensive coverage includes basic approaches such as improvements in the development of primary and secondary models, statistical fitting strategies, and novel data collection methods.
An international team of experts explore important developing areas, including specific applications, challenges in applying models to foods, variability and uncertainty, and new modeling strategies. The authors present detailed descriptions of non-linear regression fitting, methods, approaches relevant to 'real world' situations, and extensive applications of predictive models. They conclude by highlighting the strengths and weaknesses in the field and areas for future work, and attempt to resolve some of the outstanding conflicts.
The book includes strategies for combining databases, improving researcher networks, and standardization of applications packages. Providing the uninitiated with enough information to begin developing their own models, Modeling Microbial Responses in Foods covers all aspects of growth and survival modeling from the primary stage of gathering data to the implementation of final models in appropriate delivery systems.
An international team of experts explore important developing areas, including specific applications, challenges in applying models to foods, variability and uncertainty, and new modeling strategies. The authors present detailed descriptions of non-linear regression fitting, methods, approaches relevant to 'real world' situations, and extensive applications of predictive models. They conclude by highlighting the strengths and weaknesses in the field and areas for future work, and attempt to resolve some of the outstanding conflicts.
The book includes strategies for combining databases, improving researcher networks, and standardization of applications packages. Providing the uninitiated with enough information to begin developing their own models, Modeling Microbial Responses in Foods covers all aspects of growth and survival modeling from the primary stage of gathering data to the implementation of final models in appropriate delivery systems.








