期刊
FOOD CONTROL
卷 59, 期 -, 页码 714-720出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.foodcont.2015.06.037
关键词
Green tea; Geographical origin; Multielement; ICP-MS; Multivariate statistics
资金
- Modern Agro-Industry Technology Research System [nycytx-26]
- Innovative Research Team in Chinese Academy of Agricultural Sciences [CAAS-ASTIP-2014-TRICAAS]
Geographic origin of food is topic of interest for both consumers and producers since the prices of agricultural products can vary greatly according to their geographic origins. Determining the geographic origins of green teas produced in specific regions is very important. Here, we take one of the Chinese famous green teas Dongting Biluochun (DTBLC) as a model to classify its geographic origin based on the metal element analysis combined with the statistical analysis. A total of 37 metal elements including rare earth elements were analyzed by ICP-MS and PCA, CA and LDA were used to describe the relationship of BLC tea profiles from different geographical origins. High recognition (98.2%) and satisfactory predictive ability (96.4%) of the developed LDA model proved that the proposed method is a powerful, practical tool which is suitable for tracing unclassified BLC samples. Moreover, the authentic DTBLC from different protection areas also achieved as high as 95.2% classification rate. Besides, the method of determining the geographic origin of DTBLC was also suitable for other green teas from close regions. Our study provides a high classification rate, good sensitivities and powerful tool to address the quality control and food authenticity concerns regarding green tea which is of great importance for the green tea industry. (C) 2015 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据