Modelling Microorganisms In Food

Predicting the growth and behaviour of microorganisms in food has long been an aim in food microbiology research. In recent years, microbial models have evolved to become more exact and the discipline of quantitative microbial ecology has gained increasing importance for food safety management, particularly as minimal processing techniques have become more widely used. These processing methods operate closer to microbial death, survival and growth boundaries and therefore require even more precise models. Written by a team of leading experts in the field, Modelling microorganims in food assesses the latest developments and provides an outlook for the future of microbial modelling. Part one discusses general issues involved in building models of microbial growth and inactivation in foods, with chapters on the historical background of the field, experimental design, data processing and model fitting, the problem of uncertainty and variability in models and modelling lag-time. Further chapters review the use of quantitative microbiology tools in predictive microbiology and the use of predictive microbiology in risk assessment. The second part of the book focuses on new approaches in specific areas of microbial modelling, with chapters discussing the implications of microbial variability in predictive modelling and the importance of taking into account microbial interactions in foods. Predicting microbial inactivation under high pressure and the use of mechanistic models are also covered. The final chapters outline the possibility of incorporating systems biology approaches into food microbiology. Modelling microorganisms in food is a standard reference for all those in the field of food microbiology. Assesses the latest developments in microbial modelling Discusses the issues involved in building models of microbial growth Chapters review the use of quantitative microbiology tools in predictive microbiology

Microorganisms are essential for the production of many foods, including cheese, yoghurt, and bread, but they can also cause spoilage and diseases. Quantitative Microbiology of Food Processing: Modeling the Microbial Ecology explores the effects of food processing techniques on these microorganisms, the microbial ecology of food, and the surrounding issues concerning contemporary food safety and stability. Whilst literature has been written on these separate topics, this book seamlessly integrates all these concepts in a unique and comprehensive guide. Each chapter includes background information regarding a specific unit operation, discussion of quantitative aspects, and examples of food processes in which the unit operation plays a major role in microbial safety. This is the perfect text for those seeking to understand the quantitative effects of unit operations and beyond on the fate of foodborne microorganisms in different foods. Quantitative Microbiology of Food Processing is an invaluable resource for students, scientists, and professionals of both food engineering and food microbiology.

The first state-of-the-art review of this dynamic field in a decade, Modeling Microbial Responses in Foods provides the latest information on techniques in mathematical modeling of microbial growth and survival. The comprehensive coverage includes basic approaches such as improvements in the development of primary and secondary models, statistical

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. ​

This volume brings together papers detailing the latest advances in the field of predictive microbiology in foods presented at the 10th International Conference on Predictive Modelling in Food, held in Córdoba, Spain, in 2016. Predictive microbiology is a scientific area providing mathematical models to predict microbial behaviour in the food environment, providing valuable tools for food risk managers, food scientists and the food industry as a whole. The book introduces the reader to the most used and recognized modelling techniques for food, providing a thorough overview of this discipline and establishing the basis for future investigations. It is presented as a compendium of several high-quality research studies developed across the world, representing a unique contribution to the field as it shows recent discoveries and new trends of modelling in food and risk assessment. The most innovative methods, such as the use of genomic information for risk assessment and the application of quantitative risk assessment technology for foodborne pathogenic microorganisms, are also included here.

Predictive microbiology primarily deals with the quantitative assessment of microbial responses at a macroscopic or microscopic level, but also involves the estimation of how likely an individual or population is to be exposed to a microbial hazard. This book provides an overview of the major literature in the area of predictive microbiology, with a special focus on food. The authors tackle issues related to modeling approaches and their applications in both microbial spoilage and safety. Food spoilage is presented through applications of best-before-date determination and commercial sterility. Food safety is presented through applications of risk-based safety management. The different modeling aspects are introduced through probabilistic and stochastic approaches, including model and data uncertainty, but also biological variability. Features an extensive review of modelling terminology Presents examples of all available microbial models (i.e., growth, inactivation, growth/no growth) and applicable software Revisits all statistical aspects related to exposure assessment Describes realistic examples of implementing microbial spoilage and safety modeling approaches

Four authors with backgrounds in food microbiology, food chemistry, mathematics, and statistics, explain how techniques of predictive microbiology can allow an objective evaluation of the effects of processing, distribution, and storage on the microbiological safety and quality of foods. The trick is to understand the microbial ecology of a process or of a food at a particular point in the chain, then use mathematical relationships between microbial growth and the expected environmental conditions, to predict the growth or survival of selected organisms. Annotation copyright by Book News, Inc., Portland, OR