Simultaneous spectrophotometric determination of caffeine and theobromine in Iranian tea by artificial neural networks and its comparison with PLS

In order to determine the amount of caffeine and theobromine, spectrophotometry was used as a simple, rapid and economical method. Because of severe overlapping between these components, artificial neural network was used. The 230–300 nm spectral window with 1 nm interval was used for data acquisiti...

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Bibliographic Details
Published in:Food chemistry 2007, Vol.103 (3), p.1062-1068
Main Authors: Khanchi, Ali Reza, Mahani, Mohamad Khayatzadeh, Hajihosseini, Majid, Maragheh, Mohamad Ghanadi, Chaloosi, Marzieh, Bani, Farhad
Format: Article
Language:English
Subjects:
Artificial neural networks
Biological and medical sciences
Caffeine
chemical composition
Coffee, tea and other stimulative beverage industries
Food industries
Fundamental and applied biological sciences. Psychology
least squares
neural networks
new methods
PLS
spectroscopy
Tea
tea (beverage)
Theobromine
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Summary:In order to determine the amount of caffeine and theobromine, spectrophotometry was used as a simple, rapid and economical method. Because of severe overlapping between these components, artificial neural network was used. The 230–300 nm spectral window with 1 nm interval was used for data acquisition. An artificial neural network (5-5-3) with linear transfer function between input-hidden and hidden-output layers was trained and applied for prediction of concentration of these methylxanthines in four Iranian tea samples. The model was compared with PLS modeling method. HPLC technique was used as a standard method.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2006.07.035