Predictive Microbiology in Foods (SpringerBriefs in Food, Health, and Nutrition Book 5)
معرفی کتاب «Predictive Microbiology in Foods (SpringerBriefs in Food, Health, and Nutrition Book 5)» نوشتهٔ Fernando Perez-Rodriguez, Antonio Valero (auth.) در سال 2013. این کتاب در فرمت pdf، زبان انگلیسی ارائه شده است.
"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."-- Publisher's website Front Matter....Pages i-vi Predictive Microbiology in Foods....Pages 1-10 Experimental Design and Data Generation....Pages 11-23 Predictive Models: Foundation, Types, and Development....Pages 25-55 Other Models and Modeling Approaches....Pages 57-74 Software and Data Bases: Use and Application....Pages 75-85 Application of Predictive Models in Quantitative Risk Assessment and Risk Management....Pages 87-97 Future Trends and Perspectives....Pages 99-106 Erratum to: Predictive Models: Foundation, Types, and Development....Pages E1-E2 Back Matter....Pages 107-128 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. .
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