Predictive Microbiology in Foods [electronic resource] /by Fernando Perez-Rodriguez, Antonio Valero.
by Perez-Rodriguez, Fernando [author.]; Valero, Antonio [author.]; SpringerLink (Online service).
Material type:
BookSeries: SpringerBriefs in Food, Health, and Nutrition: 5Publisher: New York, NY : Springer New York : 2013.Description: VI, 128 p. 21 illus., 11 illus. in color. online resource.ISBN: 9781461455202.Subject(s): Chemistry | Microbiology | Food science | Chemistry | Food Science | Microbiology | Applied MicrobiologyDDC classification: 641.3 | 664 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| MAIN LIBRARY | TP248.65.F66 (Browse shelf) | Available |
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| TP248.65.F66 Statistics in Food Science and Nutrition | TP248.65.F66 HACCP | TP248.65.F66 Handbook on Sourdough Biotechnology | TP248.65.F66 Predictive Microbiology in Foods | TP248.65.F66 Proteomics in Foods | TP248.65.F66 Bacterial Communication in Foods | TP248.65.F66 Laboratory Exercises for Sensory Evaluation |
1. Predictive Microbiology in Foods.- 2. Experimental Design and Data Generation -- 3. Predictive Models: Foundation, Types and Development -- 4. Other Models and Modeling Approaches -- 5. Software and Data Bases: Use and Application -- 6. Application of Predictive Models in Quantitative Risk Assessment and Risk Management -- 7. Future Trends and Perspectives. .
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.
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