Suppr超能文献

通过多元素和稳定同位素的化学计量分析监测普洱茶的真实性。

Monitoring the authenticity of pu'er tea via chemometric analysis of multielements and stable isotopes.

机构信息

College of Food Science, Southwest University, Chongqing 400715, China; Chongqing University of Education, Chongqing Collaborative Innovation Center for Functional Food, Chongqing Engineering Research Center of Functional Food, Chongqing Engineering Laboratory for Research and Development of Functional Food, Chongqing 400067, China.

Chongqing Furen High School, Chongqing 400067, China.

出版信息

Food Res Int. 2020 Oct;136:109483. doi: 10.1016/j.foodres.2020.109483. Epub 2020 Jun 26.

Abstract

Mineral elements and stable isotopes combined with stoichiometric methods were used as a potential tool for first authenticating Chinese tea according to it's production year. A total of 86 mineral elements and stable isotope compositions were determined from the Xiangzhujing Pu'er tea in five different production years using ICP-MS and ICP-OES. On the basis of 78 statistically significant mineral elements and stable isotopes, HCA, PCA, PLS-DA, BP-ANN, and LDA were employed to build authentication models for predicting the Pu'er tea with different production years. The clustering results of the HCA and PCA were worse than that of PLS-DA, BP-ANN, and LDA. The PLS-DA model displayed a perfect model performance (RX = 0.86, RY = 0.974, and Q = 0.922). The authentication performance of LDA and BP-ANN revealed their 100% recognition sensitivity and prediction ability and was thus better than that of PLS-DA. Mn, Zn, and Tl were the markers for enabling the successful authentication of Pu'er tea with different production years. This study contributes toward generalizing the use of mineral element and stable isotope fingerprinting combined with LDA and BP-ANN as a promising tool for authentication of tea worldwide.

摘要

采用矿物元素和稳定同位素相结合的化学计量学方法,作为一种潜在的工具,根据茶叶的生产年份对其进行真伪鉴别。本研究采用电感耦合等离子体质谱仪(ICP-MS)和电感耦合等离子体发射光谱仪(ICP-OES)对五个不同年份的西双版纳普洱茶中的 86 种矿物元素和稳定同位素组成进行了测定。基于 78 种具有统计学意义的矿物元素和稳定同位素,采用层次聚类分析(HCA)、主成分分析(PCA)、偏最小二乘判别分析(PLS-DA)、反向传播神经网络(BP-ANN)和线性判别分析(LDA)构建了鉴别不同年份普洱茶的鉴定模型。HCA 和 PCA 的聚类结果不如 PLS-DA、BP-ANN 和 LDA 理想。PLS-DA 模型表现出了极好的模型性能(RX=0.86,RY=0.974,Q=0.922)。LDA 和 BP-ANN 的鉴定性能表明它们具有 100%的识别灵敏度和预测能力,优于 PLS-DA。Mn、Zn 和 Tl 可作为成功鉴别不同年份普洱茶的标记物。本研究为推广使用矿物元素和稳定同位素指纹图谱结合 LDA 和 BP-ANN 作为全球茶叶真伪鉴别的一种有前途的工具提供了依据。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验