Editors:
Demonstrates how mathematical modeling can enrich spectral data analysis
Includes multi-target regression methods used to enhance the spectral data analysis experience
Interdisciplinary in focus, it will appeal to a broad audience
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Table of contents (5 chapters)
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Front Matter
About this book
Given its scope, the book will appeal to novice researchers and students in the area of food science. It offers an equally exciting read for food scientists and engineers working in the food industry.
Editors and Affiliations
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Department of Physics, Ewing Christian College, Prayagraj, India
Ashutosh Kumar Shukla
About the editor
Bibliographic Information
Book Title: Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis
Editors: Ashutosh Kumar Shukla
DOI: https://doi.org/10.1007/978-981-15-6495-6
Publisher: Springer Singapore
eBook Packages: Biomedical and Life Sciences, Biomedical and Life Sciences (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2020
Hardcover ISBN: 978-981-15-6494-9Published: 21 August 2020
Softcover ISBN: 978-981-15-6497-0Published: 21 August 2021
eBook ISBN: 978-981-15-6495-6Published: 20 August 2020
Edition Number: 1
Number of Pages: XI, 121
Number of Illustrations: 21 b/w illustrations, 22 illustrations in colour
Topics: Biomedical Engineering/Biotechnology, Food Science, Nutrition, Analytical Chemistry