Discrimination of varieties of tea using near infrared spectroscopy

Yong He; Xunfei Deng; Xiaoli Li

doi:10.1117/12.710918

27 October 2006 Discrimination of varieties of tea using near infrared spectroscopy

Yong He, Xunfei Deng, Xiaoli Li

Proceedings Volume 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine; 604721 (2006) https://doi.org/10.1117/12.710918
Event: Fourth International Conference on Photonics and Imaging in Biology and Medicine, 2005, Tianjin, China

Abstract

This work is aim to present a new approach for discrimination of varieties of tea by means of infrared spectroscopy (NIRS) (325-1075nm). The relationship has been established between the reflectance spectra and tea varieties. The data set consists of a total of 150 samples of tea. First, the spectra data was analyzed with principal component analysis. It appeared to provide the reasonable clustering of the varieties of tea. PCA compressed thousands of spectral data into a small quantity of principal components and described the body of spectra the scores of the first 6 principal components computed by PCA had been applied as inputs to a back propagation neural network with one hidden layer. 125 samples of five varieties were selected randomly, which were used to build BP-ANN model. This model had been used to predict the varieties of 25 unknown samples; the residual error for the calibration samples is 1.267 x 10^-4. The recognition rate of 100% was achieved. This model is reliable and practicable. So this paper put forward a new method to the fast discrimination of varieties of tea.

Citation Download Citation

Yong He, Xunfei Deng, and Xiaoli Li "Discrimination of varieties of tea using near infrared spectroscopy", Proc. SPIE 6047, Fourth International Conference on Photonics and Imaging in Biology and Medicine, 604721 (27 October 2006); https://doi.org/10.1117/12.710918

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available