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Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis [[electronic resource] /] / edited by Ashutosh Kumar Shukla



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Titolo: Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis [[electronic resource] /] / edited by Ashutosh Kumar Shukla Visualizza cluster
Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020
Edizione: 1st ed. 2020.
Descrizione fisica: 1 online resource (XI, 121 p. 43 illus., 22 illus. in color.)
Disciplina: 664.07
Soggetto topico: Biomedical engineering
Food—Biotechnology
Nutrition   
Analytical chemistry
Biomedical Engineering/Biotechnology
Food Science
Nutrition
Analytical Chemistry
Aliments
Química analítica
Intel·ligència artificial
Espectroscòpia
Soggetto genere / forma: Llibres electrònics
Persona (resp. second.): ShuklaAshutosh Kumar
Nota di contenuto: 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.
Sommario/riassunto: 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.
Titolo autorizzato: Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis  Visualizza cluster
ISBN: 981-15-6495-7
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910416099103321
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