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. ​

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

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

Presenting a novel view of the quantitative modeling of microbial growth and inactivation patterns in food, water, and biosystems, Advanced Quantitative Microbiology for Foods and Biosystems: Models for Predicting Growth and Inactivation describes new models for estimating microbial growth and survival. The author covers traditional and alte

While predictive microbiology has made a major contribution to food safety, many uncertainties linger, such as the growing evidence that traditional microbial inactivation models do not always fit the experimental data and that all the bacteria of one population do not necessarily behave homogeneously. These problems are all the more acute because of a growing interest in minimal processing techniques that is requiring greater precision from models. Edited by leading authorities, this volume reviews current developments in quantitative microbiology. Part 1 discusses best practice in constructing quantitative models and Part 2 looks at specific areas in new approaches to modelling microbial behavior.

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.