Artificial Neural Networks In Food Processing

Artificial Neural Networks (ANNs) is a powerful computational tool to mimic the learning process of the mammalian brain. This book gives a comprehensive overview of ANNs including an introduction to the topic, classifications of single neurons and neural networks, model predictive control and a review of ANNs used in food processing. Also, examples of ANNs in food processing applications such as pasteurization control are illustrated.

Artificial Neural Networks (ANNs) is a powerful computational tool to mimic the learning process of the mammalian brain. This book gives a comprehensive overview of ANNs including an introduction to the topic, classifications of single neurons and neural networks, model predictive control and a review of ANNs used in food processing. Also, examples of ANNs in food processing applications such as pasteurization control are illustrated.

A comprehensive survey of thermal processing and modelling techniques in food process engineering. It combines theory and practice to solve actual problems in the food processing industry - emphasizing heat and mass transfer, fluid flow, electromagnetics, stochastic processes, and neural network analysis in food systems. There are specific case studies with over 350 numerical and computational equations and solutions.

Written by experts from all over the world, the book comprises the latest applications of mathematical and models in food engineering and fermentation. It provides the fundamentals on statistical methods to solve standard problems associated with food engineering and fermentation technology. Combining theory with a practical, hands-on approach, this book covers key aspects of food engineering. Presenting cuttingedge information, the book is an essential reference on the fundamental concepts associated with food engineering.

Written by international experts from industry, research centers, and academia, Mathematical Modeling of Food Processing discusses the physical and mathematical analysis of transport phenomena associated with food processing. The models presented describe many of the important physical and biological transformations that occur in food during proces

Thermal processing remains one of the most important processes in the food industry. Now in its second edition, Thermal Food Processing: New Technologies and Quality Issues continues to explore the latest developments in the field. Assembling the work of a worldwide panel of experts, this volume highlights topics vital to the food industry today and pinpoints the trends in future research and development. Topics discussed include: Thermal properties of foods, including heat capacity, conductivity, diffusivity, and density Heat and mass transfer and related engineering principles, mechanisms, and models The development and application of deterministic heat transfer models for predicting internal product temperatures Modeling thermal processing using artificial neural networks (ANN) and computational fluid dynamics (CFD) Thermal processing of meat, poultry, fish, and dairy products; canned foods; ready meals; and vegetables The effect of ultrahigh temperature (UHT) treatment processing on milk, including the impact on nutrient composition, safety, and organoleptic aspects Ohmic, radio frequency (RF) dialectric, infrared, and pressure-assisted heating pH-assisted thermal processing In addition to updating all content, this second edition includes five new chapters: Thermal Effects in Food Microbiology, Modeling Thermal Microbial Inactivation Kinetics, Thermal Processing of Food and Fruit Juices, Aseptic Processing and Packaging, and Microwave Heating. The final chapter of the book examines systems used in the evaluation of thermal processes and the development of time temperature integrators (TTIs) to ensure the safety of thermally processed food. An up-to-date survey of essential techniques and the science behind them, this volume is a critical reference for food industry professionals.

Food process modelling provides an authoritative review of one of the most exciting and influential developments in the food industry. The modelling of food processes allows analysts not only to understand such processes more clearly but also to control them more closely and make predictions about them. Modelling thus aids the search for greater and more consistent food quality. Written by a distinguished international team of experts, Food process modelling covers both the range of modelling techniques and their practical applications across the food chain.

Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible.