Electronic nose for on-line quality evaluation of black tea using incremental SOM techniques

The limitations of the classical pattern recognition algorithms may be addressed by an incremental way of learning, through which the existing knowledge base can be expanded from the information gathered solely from new set of samples. In this study, a novel incremental Self Organizing Map (i-SOM) algorithm is proposed and applied on the data generated from an electronic nose for black tea quality evaluation. The algorithm enables data with similar features (data points corresponding to different batches of black tea having similar aroma content) to be clustered together without the necessity of access to previously generated dataset

Sensing technology: current status and future trends

This book is written for academic and industry professionals working in the field of sensing, instrumentation and related fields, and is positioned to give a snapshot of the current state of the art in sensing technology, particularly from the applied perspective.  The book is intended to give a broad overview of the latest developments, in addition to discussing the process through which researchers go through in order to develop sensors, or related systems, which will become more widespread in the future.  This book is written for academic and industry professionals working in the field of sensing, instrumentation and related fields, and is positioned to give a snapshot of the current state of the art in sensing technology, particularly from the applied perspective.  The book is intended to give a broad overview of the latest developments, in addition to discussing the process through which researchers go through in order to develop sensors, or related systems, which will become more widespread in the future

A New Method For Rapid Detection Of Total Colour (TC), Theaflavins (TF), Thearubigins (TR) and Brightness (TB) In Orthodox Teas

Theaflavins (TF) and thearubigins (TR) are the important chemical compounds, which contribute to the colour and brightness of tea liquor. Estimation of TF and TR in black tea is generally done using a spectrophotometer. But, the analysis technique undergoes rigorous time consuming effort for sample preparation; also the operation of costly spectrophotometer requires expert manpower. To overcome above problems an electronic vision system (E-Vision system) based on image processing has been developed, which is faster, low cost, repeatable and can estimate the amount of Total Colour (TC), Brightness (TB), Theaflavins (TF) and TF/TR ratio for orthodox tea liquors. This paper describes the newly developed E-Vision system, experimental methods using orthodox black tea sample, data analysis algorithms and finally, the performance of the E-Vision system as compared to the results of traditional spectrophotometer. The data analysis is done using Principal Component Analysis (PCA) and Multiple Linear Regression (MLR). A correlation has been established between colour of tea liquor images and TC, TB, TR and TF/TR ratio

Sensing Technology: Current Status and Future Trends II

VIII, 265 p. 131 illus., 5 illus. in color.onlin

Sensing Technology: Current Status and Future Trends I

X, 327 p. 221 illus.online resource