Abstract

This study aimed to construct objective and accurate geographical discriminant models for tea leaves based on multielement concentrations in combination with chemometrics tools. Forty mineral elements in 87 tea samples from three growing regions in Guizhou Province (China), namely Meitan and Fenggang (MTFG), Anshun (AS) and Leishan (LS) were analyzed. Chemometrics evaluations were conducted using a one-way analysis of variance (ANOVA), principal component analysis (PCA), linear discriminant analysis (LDA), and orthogonal partial least squares discriminant analysis (OPLS-DA). The results showed that the concentrations of the 28 elements were significantly different among the three regions (p < 0.05). The correct classification rates for the 87 tea samples were 98.9% for LDA and 100% for OPLS-DA. The variable importance in the projection (VIP) values ranged between 1.01–1.73 for 11 elements (Sb, Pb, K, As, S, Bi, U, P, Ca, Na, and Cr), which can be used as important indicators for geographical origin identification of tea samples. In conclusion, multielement analysis coupled with chemometrics can be useful for geographical origin identification of tea leaves.

Details

Title
Multielemental Analysis Associated with Chemometric Techniques for Geographical Origin Discrimination of Tea Leaves (Camelia sinensis) in Guizhou Province, SW China
Author
Zhang, Jian 1   VIAFID ORCID Logo  ; Yang, Ruidong 1 ; Chen, Rong 2 ; Li, Yuncong C 3 ; Peng, Yishu 1 ; Liu, Chunlin 1 

1  College of Resource and Environmental Engineering, Guizhou University, Guiyang 550025, China 
2  College of Mining, Guizhou University, Guiyang 550025, China 
3  Department of Soil and Water Sciences, Tropical Research and Education Center, IFAS, University of Florida, Homestead, FL 33031, USA 
First page
3013
Publication year
2018
Publication date
2018
Publisher
MDPI AG
e-ISSN
14203049
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.3390/molecules23113013
ProQuest document ID
2582845152
Copyright
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.