ArticleAnalytical and bioanalytical chemistry2024
High-coverage characterization and discovery of molecular markers for quality control of natural fragrant plant extracts using UPLC-HRMS-based untargeted metabolomics.
Article in Analytical and bioanalytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- APGC-QTOF-MS-based metabolomics reveals markers associated with grapes quality during postharvest storage at different temperatures.Analytical and bioanalytical chemistry · 2026Article
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5 authors.
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Abstract
The chemical components of natural fragrant plant extracts are of high complexity, and the strategies for quality control (QC) and further discovery of fragrance mechanisms still need to be further investigated. This study integrated the strategies and methods of untargeted metabolomics and chemometrics and statistical modeling to attain the goal. The techniques of reversed-phase and HILIC analysis of ultra-performance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS) were simultaneously used to collect data in both positive and negative ion modes. The pattern analysis of fingerprints and discovery of characteristic molecular markers for QC analysis were comprehensively employed to reach in-depth analysis of the quality variation and discovery of differential molecules among natural fragrant plant extracts. The former uses fingerprint technique to analyze their overall similarities and differences, and the latter comprehensively discovers molecular substances characterizing the chemical characteristics of fragrant extracts with the help of metabolomics and univariate and multivariate methods. The findings are expected to be used as the molecular markers in product manufacturing, sales, and consumption to achieve accurate quality control and recognition of targeted molecules for potential quality monitoring using spectroscopy techniques. In this work, 27 natural fragrant extracts were applied as examples, and their chemical components were comprehensively analyzed with discovery of markers for quality control. After data integration, 1178 molecules were annotated, and 267 differential metabolite molecules with the values of variable importance in the projection (VIP) larger than 1.0 were found. The results show that the method proposed in this work is of great significance for high-coverage analysis, QC marker discovery, and aroma mechanism elucidation, which has potential applications in the areas of food, cosmetics, pharmaceuticals, tobacco, and others.
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