Title of article :
Estimation of theaflavin content in black tea using electronic tongue Original Research Article
Author/Authors :
Arunangshu Ghosh، نويسنده , , Pradip Tamuly، نويسنده , , Nabarun Bhattacharyya، نويسنده , , Bipan Tudu، نويسنده , , Nagen Gogoi، نويسنده , , Rajib Bandyopadhyay، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Abstract :
Biochemical components like theaflavins (TF) play very important role in the quality of finished CTC (cut, torn, and curled) variety of tea. TF are known to provide characteristic astringency to the taste of finished CTC tea. The quality indicators like brightness, briskness, strength, color and overall quality of tea liquor are also due to the amount of TF present. A positive correlation is normally observed between the amount of TF and the quality scores of finished tea. Biochemical tests that yield the percentage of TF are often time consuming, require meticulous effort of sample preparation, storage and measurement. This paper proposes an alternative approach of quality evaluation of CTC tea by predicting the amount of TF that may be present in a given tea sample, using a voltammetric electronic tongue.
Keywords :
Artificial Neural Network (ANN) , Scaled conjugate gradient (SCG) , Gradient descent (GD) , Principle component analysis (PCA) , Black tea , Theaflavins (TF) , Voltammetric electronic tongue
Journal title :
Journal of Food Engineering
Journal title :
Journal of Food Engineering