该文章用iNose电子鼻进行实验，开展了如下实验。

【摘要】 本研究旨在开发一种 基于电子鼻和电子舌试验及其组合的 快速简便的方法来追踪 在中国种植的黑果枸杞（ LRM ）的 地理来源，收获年份和品种 。应用 主成分分析（PCA）和线性判别分析（LDA） 进行 定性分类和定量预测。结果 表明： 电子鼻和电子舌 的 测定及其组合未能 识别 LRM 的 收获年份和种类，但是在追踪LRM地理来源方面取得了可靠的结果 ， 总分类能力分别为86.4％，86.8％和92.6％。除此之外 ， 与仪器 分析或传统方法如化学分析方法和感官评估 相比，分析程序需要更短的时间和更少的化学试剂。这项研究表明，多变量统计分析结合电子鼻和电子舌测定可能是一个可靠 简便的 追踪LRM地理起源的方法。

【关键词】 电子鼻 ；气味指纹分析系统；气体分析仪；质构仪；电子舌；气味分析仪；离子迁移谱；生物芯片；3D打印机；肉嫩度仪；物性测试仪；凝胶强度测定仪；微量过滤系统

【ABSTRACT】： This study aims to develop a fast and simple method to trace the geographical origins, harvest years and varieties of Lycium ruthenicum Murray (LRM) grown in China by employing e-nose and e-tongue assays and their combination.

Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied for qualitative classification and quantitative prediction. The results showed that e-nose and e-tongue assays and their combination failed to recognize harvest years and varieties of LRM, but achieved reliable results for tracing LRM geographical origins with a total classification ability of 86.4%, 86.8% and 92.6% respectively. In addition, the analysis procedure required shorter time and less chemical reagents as compared to high-end instrumental analysis or traditional methods like chemical analytical methods and sensory evaluation. This study demonstrated that the m*riate statistical analysis combined with e-nose and e-tongue assays could be a reliable and simplified method of tracing the geographical origins of LRM。