Rapid sensing of total theaflavins content in black tea using a portable electronic tongue system coupled to efficient variables selection algorithms

Abstract This study attempted to detect the total theaflavins content in black tea using a portable electronic tongue integrated with chemometric algorithms. Glassy carbon as a working electrode was used to collect the cyclic voltammetry current signals from the black tea samples. The synergy interval partial least square with competitive adaptive reweighted sampling (Si-CARS-PLS) was attempted to optimize and select the most informative current signal variables at special potentials for the prediction of the total theaflavins content in black tea. Models were optimized via cross validation. Compared with other characteristic variables selection methods, Si-CARS-PLS showed the best performance, employing only 13 variables (0.23% of the total variables), to achieve Rp = 0.8302 and RMSEP = 0.257 in the prediction set. The portable electronic tongue based on glassy carbon electrode and cyclic voltammetry combined with variable selection algorithm Si-CARS-PLS, proved a promising, rapid and cost-effective method to measure the total theaflavins content in black tea.

[1]  F. Nanjo,et al.  Highly efficient synthesis of theaflavins by tyrosinase from mushroom and its application to theaflavin related compounds , 2017 .

[2]  Jiewen Zhao,et al.  Measurement of total flavone content in snow lotus (Saussurea involucrate) using near infrared spectroscopy combined with interval PLS and genetic algorithm. , 2010, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[3]  A. Doménech‐Carbó,et al.  Screening and authentication of tea varieties based on microextraction-assisted voltammetry of microparticles , 2015 .

[4]  A. Legin,et al.  On the application of simple matrix methods for electronic tongue data processing: Case study with black tea samples , 2014 .

[5]  M. Lean,et al.  Bioavailability of Black Tea Theaflavins: Absorption, Metabolism, and Colonic Catabolism. , 2017, Journal of agricultural and food chemistry.

[6]  Quansheng Chen,et al.  Nondestructive detection of total volatile basic nitrogen (TVB-N) content in pork meat by integrating hyperspectral imaging and colorimetric sensor combined with a nonlinear data fusion , 2015 .

[7]  Zhiguang Zhou,et al.  Simultaneous determination of eight catechins and four theaflavins in green, black and oolong tea using new HPLC-MS-MS method. , 2016, Journal of pharmaceutical and biomedical analysis.

[8]  Bipan Tudu,et al.  Prediction of theaflavin and thearubigin content in black tea using a voltammetric electronic tongue , 2012 .

[9]  Z. Apostolides,et al.  Analysis of black tea theaflavins by non-aqueous capillary electrophoresis. , 2001, Journal of chromatography. A.

[10]  Hongdong Li,et al.  Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration. , 2009, Analytica chimica acta.

[11]  R. Bandyopadhyay,et al.  Detection of theaflavins in black tea using a molecular imprinted polyacrylamide-graphite nanocomposite electrode , 2017 .

[12]  Frans van den Berg,et al.  Review of the most common pre-processing techniques for near-infrared spectra , 2009 .

[13]  Santanu Ghorai,et al.  Feature Fusion for Prediction of Theaflavin and Thearubigin in Tea Using Electronic Tongue , 2017, IEEE Transactions on Instrumentation and Measurement.

[14]  M. Friedman.  Overview of antibacterial, antitoxin, antiviral, and antifungal activities of tea flavonoids and teas , 2006, Molecular nutrition & food research.

[15]  C. F. Hsu,et al.  Chain-breaking antioxidant activity and cyclic voltammetry characterization of polyphenols in a range of green, oolong, and black teas. , 2003, Journal of agricultural and food chemistry.

[16]  M Palit,et al.  Classification of Black Tea Taste and Correlation With Tea Taster's Mark Using Voltammetric Electronic Tongue , 2010, IEEE Transactions on Instrumentation and Measurement.

[17]  Hua-Feng He.  Research progress on theaflavins: efficacy, formation, and preparation , 2017, Food & nutrition research.

[18]  Saskia M. van Ruth,et al.  Analytical techniques combined with chemometrics for authentication and determination of contaminants in condiments: A review , 2015 .

[19]  Wenxiu Pan,et al.  Real-time monitoring of process parameters in rice wine fermentation by a portable spectral analytical system combined with multivariate analysis. , 2016, Food chemistry.

[20]  Chunjiang Zhao,et al.  Using Vis/NIR Diffuse Transmittance Spectroscopy and Multivariate Analysis to Predicate Soluble Solids Content of Apple , 2016, Food Analytical Methods.

[21]  Di Wu,et al.  A primary study on forecasting the days before decay of peach fruit using near-infrared spectroscopy and electronic nose techniques , 2017 .

[22]  U. Malik,et al.  Tea and Its Consumption: Benefits and Risks , 2015, Critical reviews in food science and nutrition.

[23]  K. Li,et al.  Simultaneous determination of theanine, gallic acid, purine alkaloids, catechins, and theaflavins in black tea using HPLC. , 2010 .

[24]  Zhonghua Liu,et al.  Preparative isolation and purification of theaflavins and catechins by high-speed countercurrent chromatography. , 2008, Journal of chromatography. B, Analytical technologies in the biomedical and life sciences.

[25]  Bipan Tudu,et al.  Classification of black tea liquor using cyclic voltammetry , 2012 .