The Identification of Green Tea Based on Feature Extraction

Abstract:

In order to identify the green tea quickly and accurately, the infrared spectra of teas measured by Fourier transform infrared spectroscopy are analyzed by using informatics method of feature extraction in this work. By comparing the different characteristic bases found by different feature genes of different tea samples, it is concluded that when green tea, yellow tea and white tea are chosen to constitute the standardized spectrum data matrix, and its first and third feature gene are selected to build characteristic basis, the green tea can be visually distinguished and the same samples have a very good aggregation. While when the characteristic basis is built by the first and second feature gene or the second and third feature gene, or the samples which are used to make up of standardized spectrum data matrix are all green tea, the recognition effect of green tea is bad. A linear arbiter of green tea is set up according to neutrality line principle on the above effectively characteristic basis, when all samples are projected onto the characteristic basis it is shown that all the green tea fall on the right of arbiter, and all not green teas are on the left of arbiter, consequently, the green tea can be identified.

• Periodical: Advanced Materials Research (Volumes 718-720)
• Pages: 580-585
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.718-720.580
• Online since: July 2013
• Authors: Rong Xiang Zhang, Wei Zhang, Xiao Hui Zhao, Yan Wei Zhang, Guang Li, Xiao Wei Li
• Keywords: Feature Extraction, Green Tea, Identification, Infrared Spectroscopy

References

[1] X. Capron, J. Smeyers-Verbeke, and D.L. Massart, Multivariate determination of the geographical origin of wines from four different countries, Food Chemistry. 101(2007)1585–1597.

DOI: 10.1016/j.foodchem.2006.04.019

[2] W. L. Lian, M. J. Wu, X. J. Sun, and Z. H. He, Influence of data pre-processing on NIR prediction model for tobacco chemical composition, Tobacco Chemistry. (2005)19–23.

[3] Y. Q. Liu, X. W. Zhang, S. Wang, H. H. Zhao, and P. Zhao, Study of infrared spectroscopic analysis of Chinese traditional medicines Liuweidihuangwan, Spectroscopy and Spectral Analysis. 26(2006)275–278.

[4] S. Q. Sun, X. Zhang, Z. Qin, and Y. X. Hu, Direct determination of raw plant drugs by FTIR, Spectroscopy and Spectral Analysis. 19(1999) 542–545.

[5] B. Chen, G. Cui, S. Z. Jin, and X. T. Wang, Application of near infrared spectra in rapid inspection of cotton content, Journal of Jiangsu University (Natural Science Edition). 28(2007) 185–188.

[6] Q. Gu, J. S. Lu, and B. C. Ye, Tea Chemistry, University of Science and Technology of China Press, 2005.

[7] J. S. Gong, P. Y. Liu, Q. J. Liu, and S. M. Qu, Determination of quality-related constituents of tea drink by near-infrared spectroscopy, Food Science. 25(2004) 135–140.

[8] Y. G. Sun, M. Lin, J. Lü, and L. H. Xu, Determination of the contents of free amino acids, caffeine and tea polyphenols in green tea by Fourier transform near-infrared spectroscopy, Chinese Journal of Spectroscopy Laboratory. 21(2004) 940–943.

[9] L. H. Xu, J. Lü, M. Lin, and Y. G. Sun, NIR spectrometric analysis of 3 kinds of main components in tea as a rapid method of qualification of tea, Physical and Chemical Test-Partial Volume of Chemistry. 42(2006) 334–336.

[10] H. C. Chen, J. Lü, X. D. Chen, and H. J. Liu, Near infrared spectroscopic model for determinating total catechins in tea polyphenol powder based on radical basis function network, Optics and Precision Engineering. 14(2006) 58–62.

[11] Z. S. Cheng, Also on China's tea classification, sericulture tea Communications. (2009) 31–32.

[12] Y. W. Zhang, X. W. Li, R. X. Zhang, S. H. Zhang, and L. S. Zhang, Influence of pretreating methods on the score result of principlal component analysis of tea, Proceedings of 2010 International Conference on Machine Learning and Cybernetics. 3(2010) 1116–1119.

DOI: 10.1109/icmlc.2010.5580935

[13] R. X. Zhang, Y. W. Zhang, X. H. Zhao, G. Li, J. F. Zhang, X. W. Li, Clustering analysis for parted band based on infrared spectra of tea, 2010 3rd International Congress on Image and Signal Processing. 7(2010) 3345–3349.

DOI: 10.1109/cisp.2010.5647636