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Data Fusion of ion Mobility Spectrometry Combined with Hierarchical Clustering Analysis for the Quality Assessment of Apple Essence

机译:离子迁移光谱的数据融合与苹果本质质量评估的分层聚类分析

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摘要

A fingerprinting approach was developed by means of high-performance ion mobility spectrometry with direct electrospray ionization (ESI-HPIMS) for the quality consistency and authentication of apple essence which contain many analytes. Thirty-four apple essence samples of the same brand and commercialized as a same product but brewed in four different manufacturers were used to establish the fingerprints. Hierarchical clustering analysis (HCA) was performed to evaluate the similarity and variation of these samples. A combined data matrix was constructed with the use of individual data matrix of ion mobility spectrum in positive and negative ion modes. For comparison, ion mobility spectrum fingerprints in positive and negative ion modes respectively were also applied to the quality assessment of the same samples. Finally, our study demonstrated that the fusion of fingerprints did indeed provide more information and could be used to comprehensively conduct the quality consistency evaluation and discrimination of apple essences from similar products. It is suggested that this fingerprint approach is suitable for analysis of other complex, multianalyte substances.
机译:通过高性能离子迁移光谱法开发了指纹识别方法,具有直接电喷雾电离(ESI-HPIMS),用于含有许多分析物的Apple Essence的质量稠度和认证。同一品牌的三十四个苹果精华样本和作为同一产品的商业化,但在四种不同的制造商中酿造地用于建立指纹。进行分层聚类分析(HCA)以评估这些样品的相似性和变化。通过使用正极和负离子模式的各个数据矩阵使用单独的数据矩阵来构建组合的数据矩阵。为了比较,分别应用于正极和负离子模式的离子迁移谱指纹也适用于相同样品的质量评估。最后,我们的研究表明,指纹的融合确实提供了更多信息,可用于全面开展类似产品的苹果精华的质量一致性评估和辨别。建议这种指纹方法适用于分析其他复杂的多共振物质。

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