Estimation of Theaflavins (TF) and Thearubigins (TR) Ratio in Black Tea Liquor Using Electronic Vision System

被引:2
|
作者
Akuli, Amitava [1 ]
Pal, Abhra [1 ]
Ghosh, Arunangshu [2 ]
Bhattacharyya, Nabarun [1 ]
Bandhopadhyya, Rajib [2 ]
Tamuly, Pradip [3 ]
Gogoi, Nagen [3 ]
机构
[1] C DAC, Kolkata Plot E-2-1,Block GP,Sect 5, Kolkata 700091, W Bengal, India
[2] Jadavpur Univ, Inst Engn Dept, Kolkata, India
[3] Tea Res Assoc, Tocklai Experiment Station, Jorhat, Assam, India
关键词
Electronic Vision; Theaflavins; Thearubigins; Black tea; Principal component analysis; Multi-linear regression; Multiple Discriminate Analysis;
D O I
10.1063/1.3626379
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Quality of black tea is generally assessed using organoleptic tests by professional tea tasters. They determine the quality of black tea based on its appearance (in dry condition and during liquor formation), aroma and taste. Variation in the above parameters is actually contributed by a number of chemical compounds like, Theaflavins (TF), Thearubigins (TR), Caffeine, Linalool, Geraniol etc. Among the above, TF and TR are the most important chemical compounds, which actually contribute to the formation of taste, colour and brightness in tea liquor. Estimation of TF and TR in black tea is generally done using a spectrophotometer instrument. But, the analysis technique undergoes a rigorous and time consuming effort for sample preparation; also the operation of costly spectrophotometer requires expert manpower. To overcome above problems an Electronic Vision System based on digital image processing technique has been developed. The system is faster, low cost, repeatable and can estimate the amount of TF and TR ratio for black tea liquor with accuracy. The data analysis is done using Principal Component Analysis (PCA), Multiple Linear Regression (MLR) and Multiple Discriminate Analysis (MDA). A correlation has been established between colour of tea liquor images and TF, TR ratio. This paper describes the newly developed E-Vision system, experimental methods, data analysis algorithms and finally, the performance of the E-Vision System as compared to the results of traditional spectrophotometer.
引用
收藏
页码:253 / +
页数:2
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