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

Abstract 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.

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