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。