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Predictive Microbiology in Foods

  • Book
  • © 2013

Overview

Authors:
  1. Fernando Perez-Rodriguez

    1. , Dpt Bromatologia y Tec. de los Alimentos, University of Córdoba, Córdoba, Spain

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  2. Antonio Valero

    1. , Dpt Bromatologia y Tec. de los Alimentos, University of Córdoba, Córdoba, Spain

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: SpringerBriefs in Food, Health, and Nutrition (BRIEFSFOOD, volume 5)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-vi
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  2. Predictive Microbiology in Foods

    • Fernando Pérez-Rodríguez, Antonio Valero
    Pages 1-10

  3. Experimental Design and Data Generation

    • Fernando Pérez-Rodríguez, Antonio Valero
    Pages 11-23

  4. Predictive Models: Foundation, Types, and Development

    • Fernando Pérez-Rodríguez, Antonio Valero
    Pages 25-55

  5. Other Models and Modeling Approaches

    • Fernando Pérez-Rodríguez, Antonio Valero
    Pages 57-74

  6. Software and Data Bases: Use and Application

    • Fernando Pérez-Rodríguez, Antonio Valero
    Pages 75-85

  7. Application of Predictive Models in Quantitative Risk Assessment and Risk Management

    • Fernando Pérez-Rodríguez, Antonio Valero
    Pages 87-97

  8. Future Trends and Perspectives

    • Fernando Pérez-Rodríguez, Antonio Valero
    Pages 99-106

  9. Erratum to: Predictive Models: Foundation, Types, and Development

    • Fernando Pérez-Rodríguez, Antonio Valero
    Pages E1-E2

  10. Back Matter

    Pages 107-128
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Keywords

About this book

Predictive microbiology is a recent area within food microbiology, which studies the responses of microorganisms in foods to environmental factors (e.g., temperature, pH) through mathematical functions. These functions enable scientists to predict the behavior of pathogens and spoilage microorganisms under different combinations of factors. The main goal of predictive models in food science is to assure both food safety and food quality.   Predictive models in foods have developed significantly in the last  20 years due to the emergence of powerful computational resources and sophisticated statistical packages. This book presents the concepts, models, most significant advances, and future trends in predictive microbiology. It will discuss the history and basic concepts of predictive microbiology. The most frequently used models will be explained, and the most significant software and databases (e.g., Combase, Sym’Previus) will be reviewed.  Quantitative Risk Assessment, which uses predictive modeling to account for the transmission of foodborne pathogens across the food chain, will also be covered. ​

Authors and Affiliations

  • , Dpt Bromatologia y Tec. de los Alimentos, University of Córdoba, Córdoba, Spain

    Fernando Perez-Rodriguez, Antonio Valero

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