Discrimination of the production season of Chinese green tea by chemical analysis in combination with supervised pattern recognition

Journal of Agricultural and Food Chemistry

Volumn 60, Issue 28, 2012, Pages 7064-7070

  Xu, Wenping ^a,b   Song, Qiushuang ^a   Li, Daxiang ^a   Wan, Xiaochun ^a  

^a ANHUI AGRICULTURAL UNIVERSITY   (China)

^b NATIONAL INSTITUTE OF MEASUREMENT AND TESTING TECHNOLOGY   (China)

Author keywords

chemical composition; green tea; K nearest neighbor method; pattern recognition; tea production season

Indexed keywords

BAYESIAN DISCRIMINANTS; CHEMICAL COMPOSITIONS; CROSS-VALIDATION TESTS; FREE AMINO ACIDS; GREEN TEA; K-NEAREST NEIGHBOR METHOD; LINEAR DISCRIMINANT ANALYSIS; OPTIMAL ACCURACY; RESUBSTITUTION; SUPERVISED PATTERN RECOGNITION; TEA PRODUCTION SEASON;

AMINO ACIDS; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; PHENOLS;

PATTERN RECOGNITION;

AMINO ACID; CAFFEINE; CATECHIN;

ARTICLE; BAYES THEOREM; CHEMISTRY; CHINA; COMPARATIVE STUDY; DISCRIMINANT ANALYSIS; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; SEASON; TEA;

AMINO ACIDS; BAYES THEOREM; CAFFEINE; CAMELLIA SINENSIS; CATECHIN; CHINA; CHROMATOGRAPHY, HIGH PRESSURE LIQUID; DISCRIMINANT ANALYSIS; SEASONS; TEA;

EID: 84863979331     PISSN: 00218561     EISSN: 15205118     Source Type: Journal    
DOI: 10.1021/jf301340z     Document Type: Article

References (32)

1. Chacko, S. M.; Thambi, P. T.; Kuttan, R.; Nishigaki, I. Beneficial effects of green tea: a literature review Chin. Med. 2010, 5, 13
2. Zhaopeng, S.; Zhonghua, L. Probe into mathematical model of chemical essence of bitterness and astringency in summer green tea. J. Tea Sci. 1987, 2, 7-12.
3. Chen, Y.; Jiang, Y.; Duan, J.; Shi, J.; Xue, S.; Kakuda, Y. Variation in catechin contents in relation to quality of 'Huang Zhi Xiang' Oolong tea (Camellia sinensis) at various growing altitudes and seasons Food Chem. 2010, 119, 648-652
4. Yu, H.; Wang, J.; Zhang, H.; Yu, Y.; Yao, C. Identification of green tea grade using different feature of response signal from E-nose sensors Sens. Actuators, B 2008, 128, 455-461
5. Chen, Q.; Zhao, J.; Vittayapadung, S. Identification of the green tea grade level using electronic tongue and pattern recognition Food Res. Int. 2008, 41, 500-504
6. Scharbert, S.; Hofmann, T. Molecular definition of black tea taste by means of quantitative studies, taste reconstitution, and omission experiments J. Agric. Food Chem. 2005, 53, 5377-5384
7. Valera, P.; Pablos, F.; Gustavo González, A. Classification of tea samples by their chemical composition using discriminant analysis Talanta 1996, 43, 415-419
8. Liang, Y. R.; Lu, J. L.; Zhang, L. Y.; Wu, S.; Wu, Y. Estimation of black tea quality by analysis of chemical composition and colour difference of tea infusions Food Chem. 2003, 80, 283-290
9. Wright, L. P.; Mphangwe, N. I. K.; Nyirenda, H. E.; Apostolides, Z. Analysis of caffeine and flavan-3-ol composition in the fresh leaf of Camellia sinesis for predicting the quality of the black tea produced in Central and Southern Africa J. Sci. Food Agric. 2000, 80, 1823-1830
10. Togari, N.; Kobayashi, A.; Aishima, T. Pattern recognition applied to gas chromatographic profiles of volatile components in three tea categories Food Res. Int. 1995, 28, 495-502
11. Dutta, R.; Hines, E. L.; Gardner, J. W.; Kashwan, K. R.; Bhuyan, A. Tea quality prediction using a tin oxide-based electronic nose: an artificial intelligence approach Sensors Actuators B-Chem. 2003, 94, 228-237
12. Chen, Q.; Guo, Z.; Zhao, J. Identification of green tea's (Camellia sinensis (L.)) quality level according to measurement of main catechins and caffeine contents by HPLC and support vector classification pattern recognition J. Pharm. Biomed. Anal. 2008, 48, 1321-1325
13. Herrador, M. á.; González, A. G. Pattern recognition procedures for differentiation of green, black and oolong teas according to their metal content from inductively coupled plasma atomic emission spectrometry Talanta 2001, 53, 1249-1257
14. Fernández, P. L.; Pablos, F.; Martín, M. J.; González, A. G. Multi-element analysis of tea beverages by inductively coupled plasma atomic emission spectrometry Food Chem. 2002, 76, 483-489
15. Moreda-Piñeiro, A.; Fisher, A.; Hill, S. J. The classification of tea according to region of origin using pattern recognition techniques and trace metal data J. Food Compos. Anal. 2003, 16, 195-211
16. McKenzie, J. S.; Jurado, J. M.; de Pablos, F. Characterisation of tea leaves according to their total mineral content by means of probabilistic neural networks Food Chem. 2010, 123, 859-864
17. Chen, Q.; Zhao, J.; Zhang, H.; Wang, X. Feasibility study on qualitative and quantitative analysis in tea by near infrared spectroscopy with multivariate calibration Anal. Chim. Acta 2006, 572, 77-84
18. Zhao, J.; Chen, Q.; Huang, X.; Fang, C. H. Qualitative identification of tea categories by near infrared spectroscopy and support vector machine J. Pharm. Biomed. Anal. 2006, 41, 1198-1204
19. Chen, Q.; Zhao, J.; Lin, H. Study on discrimination of roast green tea (Camellia sinensis L.) according to geographical origin by FT-NIR spectroscopy and supervised pattern recognition Spectrochim. Acta Part A: Mol. Biomol. Spectrosc. 2009, 72, 845-850
20. Wu, D.; Yang, H.; Chen, X.; He, Y.; Li, X. Application of image texture for the sorting of tea categories using multi-spectral imaging technique and support vector machine J. Food Eng. 2008, 88, 474-483
21. Scharbert, S.; Holzmann, N.; Hofmann, T. Identification of the astringent taste compounds in black tea infusions by combining instrumental analysis and human bioresponse J. Agric. Food Chem. 2004, 52, 3498-3508
22. Kaneko, S.; Kumazawa, K.; Masuda, H.; Henze, A.; Hofmann, T. Molecular and sensory studies on the umami taste of Japanese green tea J. Agric. Food Chem. 2006, 54, 2688-2694
23. BSI. Determination of Substances Characteristic of Green and Black Tea. Content of Total Polyphenols in Tea. Colorimetric Method Using Folin-Ciocalteu Reagent; British Standards Institution: London, U.K., 2005; Vol. ISO 14502-1.
24. SAC. Tea - Determination of Caffeine Content; China Standards Institution: Beijing, China, 2002; Vol. GB/T 8312.
25. Callejon, R. M.; Tesfaye, W.; Torija, M. J.; Mas, A.; Troncoso, A. M.; Morales, M. L. HPLC determination of amino acids with AQC derivatization in vinegars along submerged and surface acetifications and its relation to the microbiota Eur. Food Res. Technol. 2008, 227, 93-102
26. Paramas, A. M. G.; Barez, J. A. G.; Marcos, C. C.; Garcia-Villanova, R. J.; Sanchez, J. S. HPLC-fluorimetric method for analysis of amino acids in products of the hive (honey and bee-pollen) Food Chem. 2006, 95, 148-156
27. Ye, Y.; Chen, X.; Tang, D.; Su, L.; Yin, J. Comparative study of taste compounds levels of yuelu green tea produced in different season J. Zhejiang Agric. Sci. 2008, 6, 705-706
28. Fang, S.; Zhang, X.; Xia, T.; Wan, X. Influence of tea cultivars, processing technology and seasons on quality of oolong tea J. Tea Sci. 2002, 22, 135-139
29. Wang, X.; Chunlei, M.; Yao, M.; Jin, J.; Yang, Y. Biochemical components affected the seasonal differences of green tea quality Acta Bot. Boreal.-Occident. Sin. 2011, 31, 1229-1237
30. Shi, Z.; Chen, B.; Zeng, Q.; Sun, H. Study of the chemicals yielding bitterness and astringency of summer green tea J. Tea Sci. 1984, 61-62
31. Derde, M. P.; Buydens, L.; Guns, C.; Massart, D. L.; Hopke, P. K. Comparison of rule-building expert systems with pattern-recognition for the classification of analytical data Anal. Chem. 1987, 59, 1868-1871
32. Alsberg, B. K.; Goodacre, R.; Rowland, J. J.; Kell, D. B. Classification of pyrolysis mass spectra by fuzzy multivariate rule induction-comparison with regression, K -nearest neighbour, neural and decision-tree methods Anal. Chim. Acta 1997, 348, 389-407