Predictive Microbiology in Foods

1. Front Matter

   Pages i-vi

   PDF

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

    PDF

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. ​

• Foodborne pathogens
• Model validation
• Predictive Modelling
• Probability model
• Quantitative Microbial Risk Assessment
• Shelf-life prediction

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

  Fernando Perez-Rodriguez, Antonio Valero

Policies and ethics