Predictive Microbiology in Foods

Nonfiction, Science & Nature, Science, Biological Sciences, Microbiology, Technology, Food Industry & Science
Cover of the book Predictive Microbiology in Foods by Fernando Perez-Rodriguez, Antonio Valero, Springer New York
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Author: Fernando Perez-Rodriguez, Antonio Valero ISBN: 9781461455202
Publisher: Springer New York Publication: December 12, 2012
Imprint: Springer Language: English
Author: Fernando Perez-Rodriguez, Antonio Valero
ISBN: 9781461455202
Publisher: Springer New York
Publication: December 12, 2012
Imprint: Springer
Language: English

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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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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