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Risk assessment has been extensively developed in several scientific fields, such as environmental science, economics, and civil engineering, among others. In the aftermath of the SPS and GATT agreements on the use of risk analysis framework in food trade, signed in the 1990s, international organisations and governments adopted risk assessment as a science-based process to ensure food safety along the food chain. The food industry can also benefit from the use of this approach for food process optimisation and quality assurance. Risk Assessment Methods for Biological and Chemical Hazards in Food introduces the reader to quantitative risk assessment methods encompassing general concepts to specific applications to biological and chemical hazards in foods. In the first section, the book presents food risk assessment as methodology and addresses, more specifically, new trends and approaches such as the development of risk rating methods, risk metrics, risk-benefit assessment studies and quality assessment methods. Section II is dedicated to biological hazards. This section identifies the most relevant biological hazards along the food chain and provides an overview on the types of predictive microbiology models used to describe the microbial response along the food chain. Chapter 12 specifically deals with cross contamination and the quantitative methods that can be applied to describe this relevant microbial process. The development and application of dose-response models (i.e. mathematical function describing the relationship between pathogen dose and health response) are also covered in this section. In Section III, the book translates risk assessment concepts into the area of chemical hazards, defining the process steps to determine chemical risk and describing the uncertainty and variability sources associated with chemicals. Key Features: Presents new trends and approaches in the field of risk assessment in foods Risk assessment concepts are illustrated by practical examples in the food sector Discusses how quantitative information and models are integrated in a quantitative risk asssment framework Provides examples of applications of quantitative chemical risk assessment in risk management The book, written by renowned experts in their field, is a comprehensive collection of quantitative methods and approaches applied to risk assessment in foods. It can be used as an extensive guide for food safety practitioners and researchers to perform quantitative risk assessment in foods

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.

This book focuses on the food safety challenges in the vegetable industry from primary production to consumption. It describes existing and innovative quantitative methods that could be applied to the vegetable industry for food safety and quality, and suggests ways in which such methods can be applied for risk assessment. Examples of application of food safety objectives and other risk metrics for microbial risk management in the vegetable industry are presented. The work also introduces readers to new preservation and packaging methods, advanced oxidative processes (AOPs) for disinfection, product shelf-life determination methods, and rapid analytic methods for quality assessment based on chemometrics applications, thus providing a quantitative basis for the most important aspects concerning safety and quality in the vegetable sector.

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. ​

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. ​