Use of mineral multi-elemental analysis to authenticate geographical origin of different cultivars of tea in Guizhou, China

J Sci Food Agric. 2020 May;100(7):3046-3055. doi: 10.1002/jsfa.10335. Epub 2020 Feb 27.

Abstract

Background: The geographical origin of tea (Camellia sinensis) can be traced using mineral elements in its leaves as fingerprints. However, the role that could be played by soil mineral elements in the geographical authentication of tea leaves has been unclear. In this study, 22 mineral elements in 73 pairs of tea leaves and soils from three regions (Pu'an, Duyun, and Liping) in Guizhou, China, were determined using inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES). The mineral element concentrations were processed by multivariate statistical analysis, including one-way analysis of variance (ANOVA), correlation analysis, principal component analysis (PCA), and stepwise linear discriminant analysis (S-LDA).

Results: Based on a one-way ANOVA, tea leaves and soils with different origins possessed unique mineral element fingerprints. Sixteen mineral element concentrations in tea leaves were significantly correlated with those in soils (P < 0.05). The geographical origins of tea leaves were effectively differentiated using the 16 correlated mineral elements combined with PCA. The S-LDA model offered a 100% differentiation rate, and six indicative elements (phosphorus, Sr, U, Pb, Cd, and Cr) were selected as important fingerprinting markers for the geographic traceability of tea leaves. The accurate discrimination rate of geographical origin was unaffected by the cultivars of tea in the S-LDA model.

Conclusions: Mineral elements in soils played an important role in the geographical authentication of tea leaves. Mineral elemental concentrations with significant correlations between tea leaves and soils could be robust, and could be used to trace the geographical origins of tea leaves. © 2020 Society of Chemical Industry.

Keywords: ICP-MS; mineral multi-elemental fingerprints; multivariate statistical analysis; provenance soils; tea leaves.

MeSH terms

  • Camellia sinensis / chemistry*
  • Camellia sinensis / classification
  • China
  • Discriminant Analysis
  • Geography
  • Mass Spectrometry
  • Minerals / analysis
  • Plant Leaves / chemistry
  • Plant Leaves / classification
  • Principal Component Analysis
  • Spectrophotometry, Atomic
  • Tea / chemistry
  • Trace Elements / analysis*

Substances

  • Minerals
  • Tea
  • Trace Elements