| 贵州铜仁梵净山地区绿茶的产地溯源 |
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| 引用本文： | 张明露,黄聪薇,黎礼科,肖一璇,余海游,赵泰然,尹杰. 贵州铜仁梵净山地区绿茶的产地溯源[J]. 食品科学, 2021, 42(8): 299-304. DOI: 10.7506/spkx1002-6630-20200401-003 |
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| 作者姓名： | 张明露 黄聪薇 黎礼科 肖一璇 余海游 赵泰然 尹杰 |
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| 作者单位： | （1.贵州大学茶学院,贵州 贵阳 550025;2.中国农业科学院茶叶研究所,农业农村部茶叶产品质量安全风险评估实验室,浙江 杭州 310008;3.贵州省农业农村厅,贵州 贵阳 550025;4.贵州省铜仁市农业农村局,贵州 铜仁 554300） |
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| 基金项目： | 贵州省教育厅青年科技人才成长项目（黔教合KY字[2018]094）;省科技厅攻关项目（黔科合KY字[2008]023） |
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| 摘 要： | 采用电感耦合等离子体质谱分析法测定贵州省铜仁市4个产茶县42个绿茶样品中31种微量元素含量,采用相关性分析对各微量元素之间的关系进行分析,利用主成分分析、逐步线性判别分析和正交偏最小二乘-判别分析(orthogonal partial least squares-discriminant analysis,OPLS-D...
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| 关 键 词： | 绿茶 微量元素 多元统计 产地溯源 |
Geographical Origin Traceability of Green Tea from Fanjing Mountain Area,Tongren, Guizhou |
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| ZHANG Minglu,HUANG Congwei,LI Like,XIAO Yixuan,YU Haiyou,ZHAO Tairan,YIN Jie. Geographical Origin Traceability of Green Tea from Fanjing Mountain Area,Tongren, Guizhou[J]. Food Science, 2021, 42(8): 299-304. DOI: 10.7506/spkx1002-6630-20200401-003 |
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| Authors: | ZHANG Minglu HUANG Congwei LI Like XIAO Yixuan YU Haiyou ZHAO Tairan YIN Jie |
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| Affiliation: | (1. College of Tea Science, Guizhou University, Guiyang 550025, China;2. Laboratory of Quality and Safety Risk Assessment of Tea Products, Ministry of Agriculture and Rural Affairs, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou310008, China;3. Department of Agriculture and Rural Affairs of Guizhou Province, Guiyang 550025, China;4. Tongren Municipal Bureau of Agriculture and Rural Affairs, Guizhou Province, Tongren 554300, China) |
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| Abstract: | The contents of 31 trace elements in 42 green tea samples collected from four tea-producing counties in Tongren city, Guizhou province were determined by inductively coupled plasma mass spectrometry (ICP-MS). The correlation between these elements was analyzed. Principal components analysis (PCA), stepwise linear discriminant analysis (S-LDA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to develop classification models for the tea samples from different geographic origins. The results indicated that the contents of Co, Mo, Ag, Cd, Zn, Al, Y, Nd, Sc, Pr, Gd, Sm, Dy, Er, Yb, Ho, Tb, Tm and Lu in tea samples were significantly different among the different producing areas (P < 0.05). There was a synergistic correlation between some of the elements, while others showed an antagonistic correlation between each other. The OPLS-DA model displayed the best classification performance with a correct discrimination rate of 92.86%. This study revealed that the multivariate statistical classification model based on trace elements contents could effectively distinguish tea samples from neighboring producing areas, which will be useful for tea quality and safety traceability in the tea industry. |
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| Keywords: | green tea trace elements multivariate statistics geographical origin traceability, |
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