1. Instrumental Analysis Center, Huaqiao University, Xiamen 361021, China
2. College of Chemical Engineering, Huaqiao University, Xiamen 361021, China
3. Xiamen Academy of Environmental Sciences, Xiamen 361021, China
Abstract：Anxi is the origin of Tieguanyin, with hundreds of millions of gross output values yearly. However, the price of Tieguanyin with different quality is uneven, and the counterfeit and shoddy phenomenon exists in the market. Anxi County and Hua’an County in Fujian Province are the main tea producing areas of Tieguanyin. Although these two counties have a relatively high market share in tea-production and are geographically adjacent, the quality and flavor of tea are different, causing troubles for the tea market. Detecting the types and contents of microelements in Tieguanyin is of great significance in tracing its origin. In the study, standard less semi-quantitative X-ray fluorescence spectrometry (XRF) analysis and microwave digestion-inductively coupled plasma mass spectrometry (ICP-MS) is used to quantitative analyze the element contents of 30 Tieguanyin samples from Anxi (Gande, Xiping, Xianghua) and Hua’an (Liangcun, Huafeng, Xiandu) counties. The element types detected by XRF are K, Ca, S, P, Mg, Al, Si, Cl, Fe, Mn, Rb, Zn, Na, Sr,and there are certain differences in element content. For comparison, we use the ICP-MS method to detect the metallic elements found by XRF. According to the results of the XRF method, tea samples were diluted quickly and accurately for ICP-MS to meet the requirements of trace detection. When detecting Ca, Mg, Al, Fe, Mn and Zn metal elements, the correlation coefficient R2 of the XRF and ICP-MS methods is between 0.824 8 and 0.892 8, and the slope of the trend line is between 0.806 0 and 0.944 9, which shows good comparability. It shows that the XRF and ICP-MS methods are suitable for detecting these six elements. XRF and ICP-MS determined one Tieguanyin sample, the relative standard deviations were less than 6.0% and 3.0%, respectively. Compared with the ICP-MS method, the XRF method is simpler and less time-consuming in the pretreatment. Therefore, when low-cost, fast and easy detection of the content of Ca, Mg, Al, Fe, Mn and Zn in tea samples is required, the XRF detection method is preferred. K, Ca, Mg, Al, Fe, Mn, Rb, Zn, Na and Sr metal elements detected by ICP-MS were used for stepwise discriminant analysis, and the Fisher discriminant model was established to realize the recognition of Tieguanyin tea samples in Anxi County and Hua’an County. The discriminant rate of origin test, cross-validation and test samples established by the model was 96.7%, 96.7% and 100%, respectively. ICP-MS combined with stepwise discriminant analysis is feasible for Tieguanyin tea samples in Anxi County and Hua’an County.
郭小华，赵 鹏，吴雅清，唐雪平，耿 頔，翁连进. XRF与ICP-MS法在福建省安溪县和华安县的铁观音茶中元素含量测定的应用研究[J]. 光谱学与光谱分析, 2022, 42(10): 3124-3129.
GUO Xiao-hua, ZHAO Peng, WU Ya-qing, TANG Xue-ping, GENG Di, WENG Lian-jin. Application of XRF and ICP-MS in Elements Content Determinations of Tieguanyin of Anxi and Hua’an County, Fujian Province. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(10): 3124-3129.
[1] Sun J W, Hu G R, Liu K K, et al. Environmental Geochemistry and Health, 2019, 41(3): 1291.
[2] Fang S M, Ning J M, Huang W J, et al. Journal of the Science of Food and Agriculture, 2019, 99(9): 4344.
[3] Meng W J, Xu X N, Cheng K K, et al. Food Analytical Methods, 2017, 10(11): 3508.
[4] Zhou P, Li Z Y, Ouyang L Q, et al. Analytical Methods, 2019, 11(3): 346.
[5] Ma G C, Zhang J Y, Zhang L, et al. Journal of Food Composition and Analysis, 2019, 82: 103246.
[6] Rajapaksha D, Waduge V, Padilla-Alvarez R, et al. X-Ray Spectrometry, 2017, 46(4): 220.
[7] MA Chong-xian, LIU Jie, LIU Wei(马冲先, 刘 洁, 刘 巍). Chinese Journal of Analysis Laboratory(分析试验室), 2019, 38(6): 732.
[8] FANG Ping, ZOU Wen, SHI Xian-xiao, et al(方 萍, 邹 雯, 史先肖, 等). Chinese Journal of Pharmaceutical Analysis(药物分析杂志), 2017, 37(7): 1280.
[9] YANG Chun, YAN Hong-fei, LÜ Xiao-yuan, et al(杨 纯, 颜鸿飞, 吕小园, 等). Food Science(食品科学), 2020, 41(16): 286.
[10] LIU Chang, YUAN Zhi-qian, XUE Li-dong, et al(刘 畅，苑芷茜，薛荔栋, 等). Environmental Science & Technology(环境科学与技术), 2018, 41(4): 66.
[11] CHEN Yu-e, SUN Yang-yang, ZHONG Hui-yi, et al(陈玉娥, 孙杨杨, 钟慧怡, 等). Chinese Journal of Pharmaceutical Analysis(药物分析杂志), 2020, 40(3): 562.
