The creation of plant-based foods is one of the most rapidly advancing areas in the modern food industry. Many consumers are adopting more plant-based foods in their diets because of concerns about global warming and its devastating impacts on the environment and biodiversity. In addition, consumers are adopting plant-based diets for ethical and health reasons. As a result, many food companies are developing plant-based analogs of animal-based foods like dairy, egg, meat, and seafood products. This is extremely challenging because of the complex structure and composition of these animal-based foods. Next-Generation Plant-based Foods: Design, Production and Properties presents the science and technology behind the design, production, and utilization of plant-based foods. Readers will find a review of ingredients, processing operations, nutrition, quality attributes, and specific plant-based food categories such as milk and dairy products, egg and egg products, meat and seafood products, providing the fundamental knowledge required to create the next generation of healthier and more sustainable plant-based food alternatives.

Over the past three decades, "landscape" has become an umbrella term to describe many different strands of archaeology. From the processualist study of settlement patterns to the phenomenologist's experience of the natural world, from human impact on past environments to the environment's impact on human thought, action, and interaction, the term has been used. In this volume, for the first time, over 80 archaeologists from three continents attempt a comprehensive definition of the ideas and practices of landscape archaeology, covering the theoretical and the practical, the research and conservation, and encasing the term in a global framework. As a basic reference volume for landscape archaeology, this volume will be the benchmark for decades to come. All royalties on this Handbook are donated to the World Archaeological Congress.

Recent developments in nanoparticle and microparticle delivery systems are revolutionizing delivery systems in the food industry. These developments have the potential to solve many of the technical challenges involved in creating encapsulation, protection, and delivery of active ingredients, such as colors, flavors, preservatives, vitamins, minerals, and nutraceuticals. Nanoparticle- and Microparticle-based Delivery Systems: Encapsulation, Protection and Release of Active Compounds explores various types of colloidal delivery systems available for encapsulating active ingredients, highlighting their relative advantages and limitations and their use. Written by an international authority known for his clear and rigorous technical writing style, this book discusses the numerous kinds of active ingredients available and the issues associated with their encapsulation, protection, and delivery. The author takes a traditional colloid science approach and emphasizes the practical aspects of formulation of particulate- and emulsion-based delivery systems with food applications. He then covers the physicochemical and mechanical methods available for manufacturing colloidal particles, highlighting the importance of designing particles for specific applications. The book includes chapters devoted specifically to the three major types of colloidal delivery systems available for encapsulating active ingredients in the food industry: surfactant-based, emulsion-based, and biopolymer-based. It then reviews the analytical tools available for characterizing the properties of colloidal delivery systems, presents the mathematical models for describing their properties, and highlights the factors to consider when selecting an appropriate delivery system for a particular application backed up by specific case studies. Based on insight from the author's own experience, the book describes why delivery systems are needed, the important factors to consider when designing them, methods of characterizing them, and specific examples of the range of food-grade delivery systems available. It gives you the necessary knowledge, understanding, and appreciation of developments within the current research literature in this rapidly growing field and the confidence to perform reliable experimental investigations according to modern international standards.

Continuing the mission of the first two editions, Food Emulsions: Principles, Practices, and Techniques, Third Edition covers the fundamentals of emulsion science and demonstrates how this knowledge can be applied to control the appearance, stability, and texture of emulsion-based foods. Initially developed to fill the need for a single resource covering all areas of food emulsion formation, stability, characterization, and application, the first two editions raised the bar for references in this field. This third edition is poised to do the same. See What's New in the Third Edition: New chapters have been added on Emulsion-Based Delivery Systems and the Gastrointestinal Fate of Emulsions All chapters have been revised and updated, including new methods of fabricating and characterizing emulsions New figures have been included, and previous ones have been redrawn As in previous editions, the main focus of this book is on presenting the fundamental principles of emulsion science and technology that underlie all types of emulsion-based food products. It highlights practical applications and provides an overview of modern areas of research. Figures and diagrams add emphasis to important concepts and present the underlying theory in a clear and approachable manner. These features and more give you a firm grounding in basic principles that will aid in the rational design of new products, the improvement of existing products, and the more rapid solution of processing problems.

Recent developments in nanoparticle and microparticle delivery systems are revolutionizing delivery systems in the food industry. These developments have the potential to solve many of the technical challenges involved in creating encapsulation, protection, and delivery of active ingredients, such as colors, flavors, preservatives, vitamins, minerals, and nutraceuticals. Nanoparticle- and Microparticle-based Delivery Systems: Encapsulation, Protection and Release of Active Compounds explores various types of colloidal delivery systems available for encapsulating active ingredients, highlighting their relative advantages and limitations and their use. Written by an international authority known for his clear and rigorous technical writing style, this book discusses the numerous kinds of active ingredients available and the issues associated with their encapsulation, protection, and delivery. The author takes a traditional colloid science approach and emphasizes the practical aspects of formulation of particulate- and emulsion-based delivery systems with food applications. He then covers the physicochemical and mechanical methods available for manufacturing colloidal particles, highlighting the importance of designing particles for specific applications. The book includes chapters devoted specifically to the three major types of colloidal delivery systems available for encapsulating active ingredients in the food industry: surfactant-based, emulsion-based, and biopolymer-based. It then reviews the analytical tools available for characterizing the properties of colloidal delivery systems, presents the mathematical models for describing their properties, and highlights the factors to consider when selecting an appropriate delivery system for a particular application backed up by specific case studies. Based on insight from the author's own experience, the book describes why delivery systems are needed, the important factors to consider when designing them, methods of characterizing them, and specific examples of the range of food-grade delivery systems available. It gives you the necessary knowledge, understanding, and appreciation of developments within the current research literature in this rapidly growing field and the confidence to perform reliable experimental investigations according to modern international standards.

Over the past three decades, "landscape" has become an umbrella term to describe many different strands of archaeology. From the processualist study of settlement patterns to the phenomenologist's experience of the natural world, from human impact on past environments to the environment's impact on human thought, action, and interaction, the term has been used. In this volume, for the first time, over 80 archaeologists from three continents attempt a comprehensive definition of the ideas and practices of landscape archaeology, covering the theoretical and the practical, the research and conservation, and encasing the term in a global framework. As a basic reference volume for landscape archaeology, this volume will be the benchmark for decades to come. All royalties on this Handbook are donated to the World Archaeological Congress.

The creation of plant-based foods is one of the most rapidly advancing areas in the modern food industry. Many consumers are adopting more plant-based foods in their diets because of concerns about global warming and its devastating impacts on the environment and biodiversity. In addition, consumers are adopting plant-based diets for ethical and health reasons. As a result, many food companies are developing plant-based analogs of animal-based foods like dairy, egg, meat, and seafood products. This is extremely challenging because of the complex structure and composition of these animal-based foods. Next-Generation Plant-based Foods: Design, Production and Properties presents the science and technology behind the design, production, and utilization of plant-based foods. Readers will find a review of ingredients, processing operations, nutrition, quality attributes, and specific plant-based food categories such as milk and dairy products, egg and egg products, meat and seafood products, providing the fundamental knowledge required to create the next generation of healthier and more sustainable plant-based food alternatives.

Nanotechnology is increasingly being utilized within the food industry to create innovative products with new or improved properties. This book introduces the history of nanotechnology applications in the food industry. It then discusses the key physicochemical and structural characteristics of the different kinds of nanoparticles found in foods, as well as showing how these characteristics lead to their unique functional attributes. Applications of nanotechnology in the food and agricultural industries are then covered, including the creation of nanopesticides, nanofertilizers, nutrient delivery systems, functional ingredients, smart packaging materials, nanofilters, and sensors, as well as for the conversion of waste materials into value-added products. Finally, the potential toxicity of both organic and inorganic nanoparticles found in foods is critically assessed. The author is a Distinguished Professor of food science who uses physics, chemistry, and biology to improve the quality, safety, and healthiness of foods. He has published over a thousand scientific articles and numerous books in this area and is currently the most highly cited food scientist in the world. He has won numerous awards for his scientific achievements. The aim of this book is to provide scientists and technologists with an understanding of the basic principles of nanotechnology and how they can be used in the food and agricultural industry to improve the quality, sustainability, safety, and healthiness of our foods.

Biodegradable and Edible Food Packaging: Trends and Technologies presents the concept, status and recent advancements of Biodegradable and Edible packaging materials. The book offers broad and available information regarding principles of food packaging and its applications in different area of food and non-food. Chapters bring a detailed overview of the interaction of constituents and properties like physiochemical, mechanical, microbiological and engineering. The book also serves latest information regarding the packaging requirements of almost all food groups, including knowledge regarding biodegradable and edible food packaging materials that reduce environmental pollution. This is a solid reference book that helps readers understand different benefits of using biodegradable and edible films and their development and suitability with various foods.

Reducing the amount of meat in our diet would have major environmental benefits, including reducing greenhouse gas emissions, pollution, deforestation, and biodiversity loss.  Moreover, it would have wide-ranging ethical benefits by decreasing the huge number of livestock animals confined and killed each year for food. For consumers, there may also be health benefits from a meat-less diet, provided it was carefully planned. Advances in modern science and technology, including plant-based, microbial, lab-grown, and insect meats, are revolutionizing the food industry and making it easier for consumers worldwide to maintain a meat-less diet. In Meat Less: The Next Food Revolution I outline my own journey as a food scientist who became a vegetarian in solidarity with my daughter. In writing this book I take the viewpoint that there are no easy answers and that everyone must make the decision to eat meat or not based on their own values. The first chapters examine the impact of meat consumption on the environment, human health, and animal welfare, including the important questions of how much does eating meat really contribute to greenhouse gas emissions, pollution, and biodiversity loss, what are the ethical implications of raising and killing animals for food, and the impact of reducing meat consumption on human nutrition and health. I then discuss some of the new technologies that are being developed to create alternatives to meat, including plant-based meat, cultured (lab-grown) meat, microbial meat, and insect meat.  I present the science behind these new technologies and their potential for making a difference to climate change and human health. In the final chapter, I discuss why I remain a vegetarian and have decided to dedicate the rest of my scientific career to finding sustainable and healthy alternatives to meat, presenting my vision of the human diet in 2050.

Through a collection and analysis of carefully selected readings, Rethinking Debatable Moments in the Civil Rights Movement: Learning for the Present Moment highlights particular issues, tensions, and dynamics within the Civil Rights Movement. The text asks pointed questions regarding debatable moments of the Civil Rights Movement in order to encourage critical study, stimulate thinking about possible consequences then and now, seek answers or refine the questions, and seek direction for the present moment. The readings are organized in chapters according to the debatable moments: 1) Should the NAACP have pursued the case of Claudette Colvin in combating bus segregation in Montgomery?; 2) Should Dr. Martin Luther King, Jr., have joined the Freedom Riders when invited to do so in 1961?; 3) Should children have been allowed to participate in the Birmingham Campaign protests in 1963?; 4) Should SNCC's John Lewis have agreed to amend his speech in the 1963 March on Washington?; and 5) Should Dr. Martin Luther King, Jr., have turned the marchers around at the Edmund Pettus Bridge in Selma after Bloody Sunday? General and chapter introductions and an epilogue explore the context, the key players, the issues, the nature of the crisis, and the consequences and implications of each debatable moment. Rethinking Debatable Moments in the Civil Rights Movement is an excellent supplementary text for courses in anthropology, sociology, black studies, and related social science disciplines.

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing. Key Features Clear and concise explanations Gives important insights into deep learning models Practical demonstration of key concepts Book DescriptionPyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. What you will learn Set up the deep learning environment using the PyTorch library Learn to build a deep learning model for image classification Use a convolutional neural network for transfer learning Understand to use PyTorch for natural language processing Use a recurrent neural network to classify text Understand how to optimize PyTorch in multiprocessor and distributed environments Train, optimize, and deploy your neural networks for maximum accuracy and performance Learn to deploy production-ready models Who this book is forDevelopers and Data Scientist familiar with Machine Learning but new to deep learning, or existing practitioners of deep learning who would like to use PyTorch to train their deep learning models will find this book to be useful. Having knowledge of Python programming will be an added advantage, while previous exposure to PyTorch is not needed.

Design efficient machine learning systems that give you more accurate results About This Book * Gain an understanding of the machine learning design process * Optimize machine learning systems for improved accuracy * Understand common programming tools and techniques for machine learning * Develop techniques and strategies for dealing with large amounts of data from a variety of sources * Build models to solve unique tasks Who This Book Is For This book is for data scientists, scientists, or just the curious. To get the most out of this book, you will need to know some linear algebra and some Python, and have a basic knowledge of machine learning concepts. What You Will Learn * Gain an understanding of the machine learning design process * Optimize the error function of your machine learning system * Understand the common programming patterns used in machine learning * Discover optimizing techniques that will help you get the most from your data * Find out how to design models uniquely suited to your task In Detail Machine learning is one of the fastest growing trends in modern computing. It has applications in a wide range of fields, including economics, the natural sciences, web development, and business modeling. In order to harness the power of these systems, it is essential that the practitioner develops a solid understanding of the underlying design principles. There are many reasons why machine learning models may not give accurate results. By looking at these systems from a design perspective, we gain a deeper understanding of the underlying algorithms and the optimisational methods that are available. This book will give you a solid foundation in the machine learning design process, and enable you to build customised machine learning models to solve unique problems. You may already know about, or have worked with, some of the off-the-shelf machine learning models for solving common problems such as spam detection or movie classification, but to begin solving more complex problems, it is important to adapt these models to your own specific needs. This book will give you this understanding and more. Style and approach This easy-to-follow, step-by-step guide covers the most important machine learning models and techniques from a design perspective.

Leverage benefits of machine learning techniques using Python About This Book * Improve and optimise machine learning systems using effective strategies. * Develop a strategy to deal with a large amount of data. * Use of Python code for implementing a range of machine learning algorithms and techniques. Who This Book Is For This title is for data scientist and researchers who are already into the field of data science and want to see machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts. What You Will Learn * Learn to write clean and elegant Python code that will optimize the strength of your algorithms * Uncover hidden patterns and structures in data with clustering * Improve accuracy and consistency of results using powerful feature engineering techniques * Gain practical and theoretical understanding of cutting-edge deep learning algorithms * Solve unique tasks by building models * Get grips on the machine learning design process In Detail Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. It is one of the fastest growing trends in modern computing, and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a learning path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems. The course begins with getting your Python fundamentals nailed down. It focuses on answering the right questions that cove a wide range of powerful Python libraries, including scikit-learn Theano and Keras.After getting familiar with Python core concepts, it's time to dive into the field of data science. You will further gain a solid foundation on the machine learning design and also learn to customize models for solving problems. At a later stage, you will get a grip on more advanced techniques and acquire a broad set of powerful skills in the area of feature selection and feature engineering. Style and approach This course includes all the resources that will help you jump into the data science field with Python. The aim is to walk through the elements of Python covering powerful machine learning libraries. This course will explain important machine learning models in a step-by-step manner. Each topic is well explained with real-world applications with detailed guidance.Through this comprehensive guide, you will be able to explore machine learning techniques.