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Optimization and validation of the protocol used to analyze the taste of traditional Chinese medicines using an electronic tongue

机译:优化和验证用于使用电子舌分析中药味道的方案

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摘要

Tools to define the active ingredients and flavors of Traditional Chinese Medicines (TCMs) are limited by long analysis times, complex sample preparation and a lack of multiplexed analysis. The aim of the present study was to optimize and validate an electronic tongue (E-tongue) methodology to analyze the bitterness of TCMs. To test the protocol, 35 different TCM concoctions were measured using an E-tongue, and seven replicate measurements of each sample were taken to evaluate reproducibility and precision. E-tongue sensor information was identified and classified using analysis approaches including least squares support vector machine (LS-SVM), support vector machine (SVM), discriminant analysis (DA) and partial least squares (PLS). A benefit of this analytical protocol was that the analysis of a single sample took <15 min for all seven sensors. The results identified that the LS-SVM approach provided the best bitterness classification accuracy (binary classification accuracy, 100%; ternary classification accuracy, 89.66%). The E-tongue protocol developed showed good reproducibility and high precision within a 6 h measurement cycle. To the best of our knowledge, this is the first study of an E-tongue being applied to assay the bitterness of TCMs. This approach could be applied in the classification of the taste of TCMs, and serve important roles in other fields, including foods and beverages.
机译:定义中药(TCM)活性成分和风味的工具受到分析时间长,样品制备复杂和缺乏多重分析的限制。本研究的目的是优化和验证电子舌(E-舌)方法,以分析中药的苦味。为了测试方案,使用电子舌测量了35种不同的中药复方制剂,并对每个样品进行了7次重复测量以评估可重复性和精密度。使用分析方法对电子舌传感器信息进行识别和分类,包括最小二乘支持向量机(LS-SVM),支持向量机(SVM),判别分析(DA)和偏最小二乘(PLS)。这种分析方案的好处是,对于所有七个传感器,单个样品的分析花费了不到15分钟的时间。结果表明,LS-SVM方法提供了最佳的苦味分类精度(二进制分类精度为100%;三元分类精度为89.66%)。所开发的电子舌协议在6小时的测量周期内显示出良好的可重复性和高精度。据我们所知,这是首次将电子舌用于分析中药苦味的研究。该方法可用于中药口味的分类,并在其他领域(包括食品和饮料)中发挥重要作用。

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