基于电感耦合等离子体发射光谱法（ICP-OES）多元素分析和化学计量学多变量分析的茶叶产地溯源地理判别
Geographical discrimination of tea for origin traceability based on multielement analysis by ICP-OES and chemometrics multivariate.
作者信息
Guo Na, Wu Qi, Shi Chen, Shu Rengeng
机构信息
School of Pharmacy, Jiangxi University of Chinese Medicine, Nanchang 330004, China.
出版信息
Chin Herb Med. 2022 Sep 27;15(1):63-68. doi: 10.1016/j.chmed.2022.05.005. eCollection 2023 Jan.
OBJECTIVE
This paper focused on the geographical discrimination of tea for origin traceability based on multielement analysis by ICP-OES and chemometrics multivariate.
METHODS
In this study, eleven trace element concentrations were determined by ICP-OES and processed by multivariate statistical analysis.
RESULTS
Based on ANOVA, the mean concentrations of 10 elements except Co differed significantly among six origins. Pearson's correlation analysis showed that 11 pairs of elements have a positive significant correlation and 12 pairs have a negative significant correlation. The geographical origins were effectively differentiated using the eleven elements combined with PCA. And the S-LDA model offered a 100% differentiation rate.
CONCLUSION
The overall results suggested that the combination of multielement analysis by ICP-OES and chemometrics multivariate could trace the geographical origins of tea. And the paper can provide reference for quality control and quality evaluation of in the future.
目的
本文基于电感耦合等离子体发射光谱仪（ICP - OES）的多元素分析和化学计量学多变量分析，着重研究茶叶产地溯源的地理判别。
方法
本研究通过ICP - OES测定了11种微量元素的浓度，并进行多变量统计分析。
结果
基于方差分析，除钴元素外，其他10种元素在六个产地间的平均浓度存在显著差异。皮尔逊相关分析表明，11对元素呈显著正相关，12对元素呈显著负相关。利用这11种元素结合主成分分析（PCA）有效地区分了地理产地。而且软独立建模分类法（S - LDA）模型的判别率为100%。
结论
总体结果表明，ICP - OES多元素分析和化学计量学多变量分析相结合能够追溯茶叶的地理产地。本文可为今后的质量控制和质量评估提供参考。
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