Accurate discrimination of tea from multiple geographical regions by combining multi-elements with multivariate statisti
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ORIGINAL PAPER
Accurate discrimination of tea from multiple geographical regions by combining multi‑elements with multivariate statistical analysis Minglu Zhang1 · Congwei Huang2,3 · Jiangyang Zhang2,3 · Haoran Qin1 · Guicen Ma2,3 · Xin Liu2,3 · Jie Yin1 Received: 10 February 2020 / Accepted: 21 July 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract This study focused on building accurate and robust statistical models for geographical discrimination of teas, especially for the application on classification of the core geographical region teas from the non-core regions in tea. In order to achieve this goal, the content of mineral elements of tea samples was investigated. To be specific, taking Duyun maojian (DYMJ) tea as a sample, we applied inductively coupled plasma mass spectrometry (ICP-MS) combined with multivariate statistical analysis to profile the mineral elements of DYMJ collected from five adjacent production areas. Results demonstrated that a total of 39 elements were significantly different among the 5 regions, and in the stepwise linear discriminant analysis model (S-LDA), a satisfying prediction ability (88.3%) was obtained by cross-validation for the whole 5 regions, in which the correct classification rates for the geographical region (Duyun county) teas could reach 96.0%. The overall results suggested that the combination of ICP-MS with S-LDA could be successfully used as a rapid and reliable method for geographical origin identification of teas. At the end, the benefit of the essential elements supplement and also the risk of the toxic elements excess have been assessed during people’s daily consumption of tea. Keywords Tea · ICP-MS · Geographical origin · Multi-element analysis · Multivariate statistical analysis
Introduction Geographical indications (GI) is defined as the name of a region used to remark an agricultural or food product with a distinct geographical connotation [1]. The GI products possessed some specific quality, reputation, or other characteristics, which are considered primarily related to the geographic region [2]. It is not only influencing the overall perception of the products in terms of quality and price but Minglu Zhang and Congwei Huang contributed equally to this work. * Minglu Zhang [email protected] * Jie Yin [email protected] 1
College of Tea Science, Guizhou University, Jiaxiu South Road, Guiyang 550025, Guizhou, China
2
Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou 310008, China
3
China National Laboratory for Tea Safety Risk Assessment, Hangzhou 310008, China
can be a crucial identification when consumers purchase the congeneric products. Therefore, the protection of GI is becoming increasingly significant for both producers and consumers. Tea is one of the most important non-alcoholic beverages in the world [3]. Benefit from its aroma, flavor, and functional components (e.g., polyphenol, caffeine, and polysaccharide, etc.), the consumption of tea is significantly growing in recent y
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