EUNICE LI-CHAN, PhD, is Professor of Food, Nutrition and Health in the Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, Canada.
BO JIANG, PhD, is Professor of Food Science and Executive Director of the Key State Laboratory of Food Science and Technology, Jiangnan University, Wuxi, China.
This volume presents practical information on over 80 natural extracts that can be used as food flavors and colors, drawing on the author's 50 years of food chemistry and technology expertise in both research and industry. The book is divided into three parts: Part I deals with manufacture, quality, analysis, and regulatory aspects. Part II describes the various sources of natural flavors and colorants that are currently available, alphabetized for convenient reference. Part III covers future directions that can be pursued by research workers and manufacturers.
Food scientists, researchers and product development professionals alike will find Natural Food Flavors and Colorants an invaluable resource for understanding and using these commercially important natural food ingredients.
Thermal Processing: Control and Automation presents an overview of various facets of thermal processing and packaging from industry, academic, and government representatives. The book contains information that will be valuable not only to a person interested in understanding the fundamental aspects of thermal processing (eg graduate students), but also to those involved in designing the processes (eg process specialists based in food manufacturing) and those who are involved in process filing with USDA or FDA. The book focuses on technical aspects, both from a thermal processing standpoint and from an automation and process control standpoint. Coverage includes established technologies such as retorting as well as emerging technologies such as continuous flow microwave processing. The book addresses both the theoretical and applied aspects of thermal processing, concluding with speculations on future trends and directions.
Key features:Analyzes the most active fields of research currently performed on nondigestible carbohydrates Focuses on the growing opportunity to deliver digestive health benefits through fibers and other novel carbohydrates Authors include highly recognized researchers from academe and industry experts Explores new possibilities in prebiotics and fermentable carbohydrates
This book contains three parts. The first part explores the fundamental tools of data science. It includes basic graph theoretical methods, statistical and AI methods for massive data sets. In second part, chapters focus on the procedural treatment of data science problems including machine learning methods, mathematical image and video processing, topological data analysis, and statistical methods. The final section provides case studies on special topics in variational learning, manifold learning, business and financial data recovery, geometric search, and computing models.
Mathematical Problems in Data Science is a valuable resource for researchers and professionals working in data science, information systems and networks. Advanced-level students studying computer science, electrical engineering and mathematics will also find the content helpful.