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首页> 外文期刊>Journal of Analytical Atomic Spectrometry >Classification of ginseng according to plant species, geographical origin, and age using laser-induced breakdown spectroscopy and hyperspectral imaging
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Classification of ginseng according to plant species, geographical origin, and age using laser-induced breakdown spectroscopy and hyperspectral imaging

机译：使用激光诱导的击穿光谱和高光谱成像，根据植物物种，地理来源和年龄的植物物种，地理来源和年龄进行分类

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摘要

Because of the increasing demand and consumption of ginseng products, rapid and effective technologies verifying the authenticity of ginseng are strongly needed. The constituents of ginseng differ by plant species, geographical origin, and age, thus resulting in different medicinal values and market prices. Traditional methods for the quality assessment of ginseng have generally been based on sensory analysis and wet chemistry, which are time-consuming and require specialized knowledge. In this work, we used laser-induced breakdown spectroscopy (LIBS) and hyperspectral imaging (HSI) combined with chemometrics to determine the plant species, geographical origin, and age of ginseng samples. Ginseng slices were pretreated into pressed pellets and then emission and reflectance spectra were acquired. Partial least-squares discriminant analysis (PLS-DA) was used to construct models based on spectra and label information. The classification accuracies of the spectroscopic measurements of ginseng by plant species, geographical origin, and age were greater than 93%, 94%, and 99%, respectively. Measurement fusion further improved the results of geographical origin classification by at least 2%. In addition, we selected the key wavelengths for the LIBS measurement and identified the chemical elements related to classification. The experimental results demonstrated the effectiveness of LIBS and HSI in the rapid assessment of ginseng authenticity.
机译：由于人参产品的需求越来越多，强烈需要核实人参真实性的快速有效技术。人参成分因植物物种，地理来源和年龄而异，从而导致不同的药用价值和市场价格。人参质量评估的传统方法一般都是基于感官分析和湿化学，这是耗时的，需要专门的知识。在这项工作中，我们使用激光诱导的击穿光谱（Libs）和Hyperspectral成像（HSI）与化学计量学相结合，以确定人参样本的植物物种，地理来源和年龄。人参切片预处理压制颗粒，然后获得发射和反射光谱。部分最小二乘判别分析（PLS-DA）用于构建基于光谱和标签信息的模型。植物物种，地理来源和年龄的人参光谱测量的分类精度分别大于93％，94％和99％。测量融合进一步改善了地理原因分类的结果至少2％。另外，我们选择了Libs测量的关键波长，并识别与分类有关的化学元素。实验结果表明了LIBS和HSI在人参真实性的快速评估中的有效性。

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  • 来源
    《Journal of Analytical Atomic Spectrometry》 |2021年第8期|1704-1711|共8页
  • 作者

    Shangyong Zhao; Weiran Song; Zongyu Hou; Zhe Wang;

  • 作者单位

    State Key Lab of Power Systems International Joint Laboratory on Low Carbon Clean Energy Innovation Department of Energy and Power Engineering Tsinghua University Beijing 100084 China;

    State Key Lab of Power Systems International Joint Laboratory on Low Carbon Clean Energy Innovation Department of Energy and Power Engineering Tsinghua University Beijing 100084 China;

    State Key Lab of Power Systems International Joint Laboratory on Low Carbon Clean Energy Innovation Department of Energy and Power Engineering Tsinghua University Beijing 100084 China Shanxi Research Institute for Clean Energy Tsinghua University Taiyuan 030032 China;

    State Key Lab of Power Systems International Joint Laboratory on Low Carbon Clean Energy Innovation Department of Energy and Power Engineering Tsinghua University Beijing 100084 China Shanxi Research Institute for Clean Energy Tsinghua University Taiyuan 030032 China;

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