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Record Nr. |
UNINA9910416099103321 |
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Titolo |
Spectroscopic Techniques & Artificial Intelligence for Food and Beverage Analysis / / edited by Ashutosh Kumar Shukla |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XI, 121 p. 43 illus., 22 illus. in color.) |
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Disciplina |
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Soggetti |
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Biomedical engineering |
Food—Biotechnology |
Nutrition |
Analytical chemistry |
Biomedical Engineering/Biotechnology |
Food Science |
Nutrition |
Analytical Chemistry |
Aliments |
Química analítica |
Intel·ligència artificial |
Espectroscòpia |
Llibres electrònics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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This informative book discusses the various spectroscopic techniques applied in the analysis of food and beverages. The respective chapters |
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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. |
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