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Metabolomic fingerprinting of plant extracts

Authors: MATTOLI L; CANGI F; MAIDECCHI A; GHIARA C; RAGAZZI, EUGENIO; TUBARO M; STELLA L; +2 Authors

Metabolomic fingerprinting of plant extracts

Abstract

AbstractThe standardization and quality control of plant extracts is an important topic, in particular, when such extracts are used for medicinal purposes. Consequently, the development of fast and effective analytical methods for metabolomic fingerprinting of plant extracts is of high interest. In this investigation, electrospray mass spectrometry (ESI‐MS) and 1H NMR techniques were employed with further statistical analyses of the acquired data. The results showed that negative ion mode ESI‐MS is particularly effective for characterization of plant extracts. Different samples of the same species appear well‐clustered and separated from the other species. To verify the effectiveness of the method, two other batches of extracts from a species, in which the principal components were already identified (Cynara scolymus), were analyzed, and the components that were verified by the principal component analysis (PCA) were found to be within the region identified as characteristic of Cynara Scolymus extracts. The data from extracts of the other species were well separated from those pertaining to the species previously characterized. Only the case of a species that was strictly correlated from a botanical point of view, with extracts that were previously analyzed, showed overlapping. Copyright © 2006 John Wiley & Sons, Ltd.

Keywords

ELECTROSPRAY MASS-SPECTROMETRY; MAGNETIC-RESONANCE; METABONOMICS; PHARMACOGNOSY; METABOLOMICS; MULTIVARIATE ANALYSIS, Cimicifuga, Spectrometry, Mass, Electrospray Ionization, plant extracts, Plant Extracts, ESI/MS, metabolomics, NMR, Achillea, multivariate analysis, Cynara scolymus, Multivariate Analysis, Cluster Analysis, Helianthus, Protons, Salvia officinalis, Nuclear Magnetic Resonance, Biomolecular, Filipendula

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
56
Top 10%
Top 10%
Top 10%
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