A Machine Vision System For Estimation Of Theaflavins And Thearubigins In Orthodox Black Tea

Orthodox black tea quality depends upon the amount of certain organic compounds present and out of these, theaflavins (TF) and thearubigins (TR) are the most important ones While TF is responsible for attractive golden colour, increased brightness and astringency in tea liquor, TR is reddish brown, reduces the brightness of tea liquor and contribute mostly for the ashy taste of the liquor with minor improvement in astringency. The rapid estimation of TF and TR thus may resolve the problem of certain uncertainty or ambiguity tha t may arise during quality assessment of tea by the tea tasters. In this paper, a new method for rapid measurement of concentration of TF and TR is described using a machine vision system taking imag es of tea liquor and employing artificial neural networks (ANN). The results show good correlation f estimated values of TF and TR with the actual concentrations obtained using ultraviolet-visible s pectrophotometer (UV-VIS).

[1]  Gurpreet Singh,et al.  Machine Vision System for Tea Quality Determination - Tea Quality Index (TQI) , 2013 .

[2]  Manabendra Bhuyan,et al.  Quality indexing by machine vision during fermentation in black tea manufacturing , 2003, International Conference on Quality Control by Artificial Vision.

[3]  P. K. Mahanta,et al.  Colour and Flavour Characteristics of Made Tea , 1988 .

[4]  E. A. H. Roberts,et al.  Spectrophotometric measurements of theaflavins and thearubigins in black tea liquors in assessments of quality in teas , 1961 .

[6]  Harry E. Nursten,et al.  Use of an HPLC photodiode-array detector in a study of the nature of a black tea liquor , 1990 .

[7]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  D. Bendall,et al.  Production and HPLC analysis of black tea theaflavins and thearubigins during in vitro oxidation , 1983 .

[9]  Amod Kumar,et al.  Monitoring and grading of tea by computer vision – A review , 2011 .

[10]  Hsien-Yi Hsiao,et al.  Determination of tea fermentation degree by a rapid micellar electrokinetic chromatography , 2010 .

[11]  Matthias M. Bauer,et al.  General Regression Neural Network for Technical Use , 1995 .

[12]  Mohammed R. Ullah,et al.  The effect of withering on fermentation of tea leaf and development of liquor characters of black teas , 1984 .

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

[14]  Nabarun Bhattacharyya,et al.  Electronic Nose for Black Tea Classification and Correlation of Measurements With “Tea Taster” Marks , 2008, IEEE Transactions on Instrumentation and Measurement.

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

[16]  R. Bandyopadhyay,et al.  Estimation of theaflavin content in black tea using electronic tongue , 2012 .

[17]  Ajit K. Biswas,et al.  Biological and chemical factors affecting the valuation of North East Indian plains teas. III. Statistical Evaluation of the Biochemical Constituents and their Effects on Colour, Brightness and Strength of Black Teas , 1973 .

[18]  R. T. Ellis,et al.  Estimation of the market value of Central African tea by theaflavin analysis , 1972 .

[19]  Amod Kumar,et al.  Discrimination analysis of Indian tea varieties based upon color under optimum illumination , 2013, Journal of Food Measurement and Characterization.

[20]  Manabendra Bhuyan,et al.  A computer based system for matching colours during the monitoring of tea fermentation , 2005 .

[21]  Luis Mateus Rocha,et al.  Singular value decomposition and principal component analysis , 2003 .

[22]  D. A. A. C. Ratnaweera,et al.  A hybrid approach for online tea color separation , 2011, 2011 6th International Conference on Industrial and Information Systems.

[23]  Suprijanto,et al.  Compact computer vision for black tea quality evaluation based on the black tea particles , 2011, 2011 2nd International Conference on Instrumentation Control and Automation.

[24]  Harjeet Singh,et al.  Color Analysis of Black Tea Liquor using Image Processing Techniques , 2011 .

[25]  Druin Burch,et al.  Tea , 2000, The Lancet.