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Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis/ edited by Ashutosh Kumar Shukla.
其他作者:	Shukla, Ashutosh Kumar.
面頁冊數:	XI, 121 p. 43 illus., 22 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Biomedical engineering. -
電子資源:	https://doi.org/10.1007/978-981-15-6495-6
ISBN:	9789811564956

Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis
Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis[electronic resource] /edited by Ashutosh Kumar Shukla. - 1st ed. 2020. - XI, 121 p. 43 illus., 22 illus. in color.online resource.

Chapter 1: Laser Induced Breakdown spectroscopy in food analysis -- Chapter 2: The use of FTIR spectroscopy combined with multivariate analysis in Food composition Analysis -- Chapter 3: Spectrophotometric methods and Electronic Spin Resonance for evaluation antioxidant capacity of food -- Chapter 4: Thermoluminescence the method for the detection of irradiated foodstuffs -- Chapter 5: Advantages of Multi-target modeling for spectral regression.

This informative book discusses the various spectroscopic techniques applied in the analysis of food and beverages. The respective chapters cover techniques such as Laser-Induced Breakdown Spectroscopy (LIBS), FTIR spectroscopy, Electron Spin Resonance (ESR) spectroscopy and Thermoluminescence. The book also presents artificial intelligence applications that can be used to enhance the spectral data analysis experience in food safety and quality analysis. 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.

ISBN: 9789811564956

Standard No.: 10.1007/978-981-15-6495-6doiSubjects--Topical Terms:

588770
Biomedical engineering.

LC Class. No.: R856-R857

Dewey Class. No.: 610.28

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