New Method for Identifying Different Teas Based on Liquid Colorimetric Sensor†

doi:10.7503/cjcu20150922

Abstract

Abstract:

A liquid colorimetric sensor array was presented for cross-reactive discrimination of tea fusions based on complexation reaction and redox reaction of tea polyphenols with ferric ions and ceria nanoparticles, respectively. Hydrothermal reaction was applied to synthesize different kinds of ceria nanoparticles, hollow nanospheres and nanorods of zinc silicate to immobilized ferric thiocyanate[Fe(SCN)₃], which were subsequently combined to construct a 3×3 colorimetric sensor array. Performance of the colorimetric sensor array was evaluated using 5 kinds of tea polyphenols and 14 kinds of tea fusions with 5 repeated parallels. Hierarchical clustering analysis(HCA) and principal component analysis(PCA) of the colorimetric profiles suggested that all 5 kinds of tea polyphenols can be easily differentiated with good reproducibility. Correct discrimination of 14 kinds of tea fusions was also realized according to individual quality grade and categories. Our preliminary study provides a potential alternative for fast visible detection and discrimination of teas within different qualities and grades.

Key words: Tea polyphenol, Colorimetric sensor, Zinc silicate nanomaterial, Ceria nanoparticles, Ferric thiocyanate

CLC Number:

O657

TrendMD:

HUO Danqun, FU Beibei, LI Junjie, YANG Mei, SHEN Caihong, LUO Huibo, HOU Changjun. New Method for Identifying Different Teas Based on Liquid Colorimetric Sensor^†[J]. Chem. J. Chinese Universities, 2016, 37(5): 873.

Figures/Tables 12

Fig.1 Schematic diagram of 3×3 colorimetric cross-responsive array and detection system

Fig.2 SEM images(A, C, E) and TEM images(B, D) of zinc silicate hollow spheres(A, B), nanorods(C, D), CeO2 bone-like architecture(E) and TEM image(F) of CeO2 octahedron-like architecture

Fig.3 Response of TA with different zinc silicate nano-materials(A) and with different CeO2 nano-materials(B)

Scheme 1 Summary of 5 kinds of tea polyphenols

Fig.4 Hierarchical clustering analysis(A) and principal component analysis(B) for 5 kinds of polyphenols

Table 1 Summary of 14 kinds of teas

Name	Brand	Species	Category
FGB	First grade Biluochun	Biluochun	Green tea
SGB	Special grade Biluochun	Biluochun	Green tea
DTB	Dongting Biluochun	Biluochun	Green tea
XYB	Xinyang Biluochun	Biluochun	Green tea
SGL	Special grade Longjing	Longjing	Green tea
FGL	First grade Longjing	Longjing	Green tea
KDT	Kuding	Kuding	Scented tea
JJM	Jinjunmei	Jinjunmei	Black tea
SBT	Starbucks tea	Starbucks	Black tea
TGY	Tieguanyin	Tieguanyin	Oolong tea
SGT	Special grade Tieguanyin	Tieguanyin	Oolong tea
FGT	Special grade Tieguanyin	Tieguanyin	Oolong tea
GST	Gaoshan Tieguanyin	Tieguanyin	Oolong tea
DHP	Dahongpao	Dahongpao	Oolong tea

Fig.5 Colorimetric array responses for 14 kinds of tea samples

Fig.6 Principal component analysis for 14 kinds of tea samples

Fig.7 Scatter diagram(A) and (B) for 14 kinds of tea samples

Fig.8 Hierarchical clustering analysis for different grades(A) and different regions(B) of tea samples

Table 2 Summary of 3 grades of Tieguanyin

Name	Brand	Species	Grade
SGT	Special grade Tieguanyin	Tieguanyin	Special grade
FGT	First grade Tieguanyin	Tieguanyin	First grade
TGY	Tieguanyin	Tieguanyin	Ordinary grade

Table 3 Summary of 3 regions of Tieguanyin

Name	Brand	Species	Region
Tai	Gaoshan Tieguanyin	Tieguanyin	Taiwan
Anx	Diancang Tieguanyin	Tieguanyin	Anxi
Cho	Tieguanyin	Tieguanyin	Chongan

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