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Multivariate statistical analysis combined with e-nose and e-tongue assays simplifies the tracing of geographical origins of Lycium ruthenicum Murray grown in China

机译:多变量统计分析与电子鼻子和电子舌剂分析简化了枸杞林林林林林林的地理起源的追踪

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摘要

This study aims to develop a fast and simple method to trace the geographical origins, harvest years and varieties of Lyciwn 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 multivariate statistical analysis combined with e-nose and e-tongue assays could be a reliable and simplified method of tracing the geographical origins of LRM.
机译:本研究旨在通过采用电子鼻子和电子舌剂和它们的组合,开发一种快速简单的方法来追踪在中国种植的Lyciwn ruthenicum Murray(LRM)的地理起源,收集年份和品种。主要成分分析(PCA)和线性判别分析(LDA)用于定性分类和定量预测。结果表明,电子鼻子和电子舌剂和它们的组合未能识别收获年份和LRM的各种品种,但追溯到追踪LRM地理起源的可靠结果,总分类能力分别为86.4%,86.8%和92.6%。此外,与高端乐器分析或传统方法等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。该研究表明,多变量统计分析与电子鼻和电子舌剂相结合的是可靠且简化的追踪LRM的地理起源的方法。

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