Article

Simultaneous determination of total polyphenols and caffeine contents of green tea by near-infrared reflectance spectroscopy

Faculty of Engineering and Technology, Yunnan Agricultural University, 650201 Kunming, P.R. China
Microchemical Journal (Impact Factor: 3.58). 06/2006; 83(1):42-47. DOI: 10.1016/j.microc.2006.01.023

ABSTRACT This paper indicates the possibility to use near infrared (NIR) spectroscopy as a rapid method to predict quantitatively the content of caffeine and total polyphenols in green tea. A partial least squares (PLS) algorithm is used to perform the calibration. To decide upon the number of PLS factors included in the PLS model, the model is chosen according to the lowest root mean square error of cross-validation (RMSECV) in training. The correlation coefficient R between the NIR predicted and the reference results for the test set is used as an evaluation parameter for the models. The result showed that the correlation coefficients of the prediction models were R = 0.9688 for the caffeine and R = 0.9299 for total polyphenols. The study demonstrates that NIR spectroscopy technology with multivariate calibration analysis can be successfully applied as a rapid method to determine the valid ingredients of tea to control industrial processes.

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    • "Therefore, the development of analytical methods for polyphenols represents an important and exciting topic for analytical chemists. For total and/or particular phenol analysis, numerous methods have been reported based, for example, on spectroscopy [5] [6], chemiluminescence [7], spectrophotometry [8] [9] [10], chromatography [3] [11], electrochemistry [12] [13] [14] [15] [16], and so forth. In spite of the fact that many methods are available, most of them lack versatility, simplicity, and suitability for large-scale analyses. "
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    ABSTRACT: A flow injection system using an unmodified gold screen-printed electrode was employed for total phenol determination in black and green teas. In order to avoid passivation of the electrode surface due to the redox reaction, preoxidation of the sample was realized by hexacyanoferrate(III) followed by addition of an EDTA solution. The complex formed in the presence of EDTA minimizes or avoids polymerization of the oxidized phenols. The previously filtered tea sample and hexacyanoferrate(III) reagent were introduced simultaneously into two-carrier streams producing two reproducible zones. At confluence point, the preoxidation of the phenolic compounds occurs while this zone flows through the coiled reactor and receives the EDTA solution before phenol detection. The consumption of ferricyanide was monitorized at 360mV versus Ag/AgCl and reflected the total amount of phenolic compounds present in the sample. Results were reported as gallic acid equivalents (GAEs). The proposed systemis robust, versatile, environmentally-friendly (since the reactive is used only in the presence of the sample), and allows the analysis of about 35–40 samples per hour with detection limit = 1mg/L without the necessity for surface cleaning after each measurement. Precise results are in agreement with those obtained by the Folin-Ciocalteu method.
    International Journal of Analytical Chemistry 12/2010; 2010(doi:10.1155/2010/143714-143714). · 0.90 Impact Factor
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    • "Therefore, the development of analytical methods for polyphenols represents an important and exciting topic for analytical chemists. For total and/or particular phenol analysis, numerous methods have been reported based, for example, on spectroscopy [5] [6], chemiluminescence [7], spectrophotometry [8] [9] [10], chromatography [3] [11], electrochemistry [12] [13] [14] [15] [16], and so forth. In spite of the fact that many methods are available, most of them lack versatility, simplicity, and suitability for large-scale analyses. "
    [Show abstract] [Hide abstract]
    ABSTRACT: A flow injection system using an unmodified gold screen-printed electrode was employed for total phenol determination in black and green teas. In order to avoid passivation of the electrode surface due to the redox reaction, preoxidation of the sample was realized by hexacyanoferrate(III) followed by addition of an EDTA solution. The complex formed in the presence of EDTA minimizes or avoids polymerization of the oxidized phenols. The previously filtered tea sample and hexacyanoferrate(III) reagent were introduced simultaneously into two-carrier streams producing two reproducible zones. At confluence point, the pre-oxidation of the phenolic compounds occurs while this zone flows through the coiled reactor and receives the EDTA solution before phenol detection. The consumption of ferricyanide was monitorized at 360 mV versus Ag/AgCl and reflected the total amount of phenolic compounds present in the sample. Results were reported as gallic acid equivalents (GAEs). The proposed system is robust, versatile, environmentally-friendly (since the reactive is used only in the presence of the sample), and allows the analysis of about 35-40 samples per hour with detection limit = 1 mg/L without the necessity for surface cleaning after each measurement. Precise results are in agreement with those obtained by the Folin-Ciocalteu method.
    International Journal of Analytical Chemistry 01/2010; 2010:143714. DOI:10.1155/2010/143714 · 0.90 Impact Factor
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    ABSTRACT: 2008): Nondestructive identification of tea (Camellia sinensis L.) varieties using FT-NIR spectroscopy and pattern recognition. Czech J. Food Sci., 26: 360–367. Due to more and more tea varieties in the current tea market, rapid and accurate identification of tea (Camellia sinen-sis L.) varieties is crucial to the tea quality control. Fourier Transform Near-Infrared (FT-NIR) spectroscopy coupled with the pattern recognition was used to identify individual tea varieties as a rapid and non-invasive analytical tool in this work. Seven varieties of Chinese tea were studied in the experiment. Linear Discriminant Analysis (LDA) and Artificial Neural Network (ANN) were compared to construct the identification models based on Principal Component Analysis (PCA). The number of principal components factors (PCs) was optimised in the constructing model. The experimental results showed that the performance of ANN model was better than LDA models. The optimal ANN model was achieved when four PCs were used, identification rates being all 100% in the training and prediction sets. The overall results demonstrated that FT-NIR spectroscopy technology with ANN pattern recognition method can be successfully applied as a rapid method to identify tea varieties.
    Czech Journal of Food Sciences 01/2008; 26(5):360-367. · 0.74 Impact Factor
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