Abstract
The isotope ratio of five kinds of heavy metal elements in tea samples from different areas was measured, and the variance, cluster and discriminant analyses were undertaken using SAS (statistical analysis system) software. The results showed that 206Pb/207Pb, 66Zn/67Zn, 68Zn/67Zn, 114Cd/110Cd, 112Cd/110Cd, 26Mg/25Mg 6 indexes existed significant differences in the three regions (99% significant level). The cluster analysis results of the six indexes showed that the clustering accuracy of samples form three regions as Guzhang (78.26%), Shimen (94.44%) and Anhua (92.10%). The discriminant analysis results showed that the discriminant accuracy of samples form three regions , they were 86.96%, 94.44% and 97.37% respectively. Moreover, these two methods of identification are consistent with each other. Therefore, the otherness of isotope ratio combined with the cluster and discriminant analyses of SAS software could be used to identify the tea producing areas.
Publication Date
10-28-2017
First Page
74
Last Page
77
DOI
10.13652/j.issn.1003-5788.2017.10.016
Recommended Citation
Jianhui, ZHANG; Xiali, WANG; Yonghui, HU; Xuanqi, FANG; Xuan, DAI; Li, ZHANG; and Lansong, LIU
(2017)
"Regional discrimination of three kinds of tea by Isotope ratio analysis,"
Food and Machinery: Vol. 33:
Iss.
10, Article 16.
DOI: 10.13652/j.issn.1003-5788.2017.10.016
Available at:
https://www.ifoodmm.cn/journal/vol33/iss10/16
References
[1] 许咏梅. 中国茶叶区域生产、消费和流通[J]. 茶叶, 2011, 37(3): 152-156.
[2] 管曦. 我国茶叶消费相关数据的讨论: 基于消费者层面的分析[J]. 中国茶叶, 2015(10): 11-12.
[3] 袁玉伟, 胡桂仙, 邵圣枝, 等. 茶叶产地溯源与鉴别检测技术研究进展[J]. 核农学报, 2013, 27(4): 452-457.
[4] BIZJAK B K, ELER K, MAZEJ D, et al. Isotopic and elemental characterisation of Slovenian apple juice according to geogra-phical origin: Preliminary results[J]. Food Chemistry, 2016, 203: 86-94.
[5] HORACEK M, MINJ S. Discrimination of Korean beef from beef of other origin by stable isotope measurements[J]. Food Chemistry, 2010, 121(2): 517-520.
[6] PILGRIM T S, WATLING R, GRICE K. Application of trace element and stable isotope signatures to determine the provenance of tea (Camellia Sinensis) samples [J]. Food Chemistry, 2010, 118(4): 921-926.
[7] 汪海波, 罗莉, 吴为, 等. SAS统计分析与应用从入门到精通[M]. 2版. 北京: 人民邮电出版社, 2013.
[8] 李晓燕, 李忠海, 杨代明, 等. 基于模糊聚类分析的辣椒制品表观辣度分级研究[J]. 食品与机械, 2009, 25(2): 42-47.
[9] 刘晓伟, 李忠海, 杨代明, 等. 高效液相指纹图谱对食醋的掺伪判定研究[J]. 中国调味品, 2010, 35(6): 96-98, 105.
[10] 康海宁, 杨妙峰, 陈波, 等. 利用矿质元素的测定数据判别茶叶的产地和品种[J]. 岩矿测试, 2006, 25(1): 22-26.
[11] 申丽娟, 丁恩俊, 谢德体, 等. 电感耦合等离子体原子发射光谱法测定不同产地山银花金属元素主成分及其聚类分析[J]. 食品科学, 2014, 35(2): 173-176.
[12] 课净璇, 黎杉珊, 申光辉, 等. 基于双指标分析法和聚类分析法的花椒红外指纹图谱研究[J]. 食品与机械, 2017, 33(3): 55-61.
[13] 胡国梁, 徐立荣, 许生陆, 等. 基于电子鼻的食用油氧化判别分析[J]. 食品科学, 2016, 37(20): 141-145.
[14] 王同珍, 陈孝建, 安爱, 等. 气相色谱-质谱技术结合化学计量学对5种动物油进行判别分析[J]. 分析测试学报, 2016, 35(5): 557-562.
[15] 谭超, 戴波, 刘华戎, 等. 不同品种红茶及茶膏的Fisher判别分析[J]. 食品科学, 2016, 37(7): 62-65.
[16] 张玥, 王朝辉, 张亚婷, 等. 基于主成分分析和判别分析的大米产地溯源[J]. 中国粮油学报, 2016, 31(4): 1-5.
[17] 陈辰, 鲁晓翔, 张鹏, 等. 基于电子鼻技术的玫瑰香葡萄贮藏期快速判别[J]. 食品与机械, 2015, 31(6): 137-141.