Artificial Intelligence in Food Science: Transforming Food and Bioprocess Development covers the AI and machine learning techniques that are reshaping the food science landscape, introducing innovative solutions to improve food processing, safety, and sustainability. This book delves into the transformative potential of these cutting-edge technologies, exploring how they optimize food production, enhance bioprocess development, and tailor products to meet specific consumer needs. By integrating AI, researchers and industry professionals can address challenges such as resource efficiency and quality assurance, paving the way for a more sustainable and technologically advanced food system.
Beyond optimization, the book examines AI applications in predicting food trends, analyzing complex datasets, and developing personalized nutrition plans. It provides insights into how AI enhances food storage, packaging design, and even consumer engagement through predictive models. With detailed case studies and forward-thinking perspectives, this book serves as a comprehensive guide for harnessing AI's power to revolutionize food science and bioprocess innovations.
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Dr. Tanmay Sarkar is currently working as a Lecturer in the Government of West Bengal. With 9 years of experience in both teaching and research, his areas of interest include bioactive components from natural sources, ethnic foods, mathematical modeling, and phytochemicals. He is an editor for several SCI, SCIE, and Scopus- indexed journals and has edited numerous books with Elsevier and Springer.
Artificial Intelligence in Food Science Transforming Food and Bioprocess Development, looks at the advancements in both AI and Machine Learning (ML) and the potential for leveraging these latest technologies to optimize and elevate various aspects of the food sciences. From ingredient discovery and recipe formulation to flavor profiling, quality control and bioprocess optimization, Artificial Intelligence in Food Science Transforming Food and Bioprocess Development, will show nutritionists, food scientists and researchers and developers how they can enhance efficiency while innovating in their field. Through data analysis, predictive modelling, case studies and industry examples of successful AI and ML implementation, this book also highlights the benefits, challenges, and potential limitations of using AI and ML techniques, while providing insights into best practices. Readers will discover how AI and ML intersect with nutrition, traceability and blockchain technology, food waste valorization, shelf-life, recipe and new product development, food safety, and more.
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