Literature DB >> 26602542

An approach to evaluate the information in chromatographic fingerprints: Application to the optimisation of the extraction and conservation conditions of medicinal herbs.

T Alvarez-Segura1, E Cabo-Calvet1, J R Torres-Lapasió1, M C García-Álvarez-Coque2.   

Abstract

A new approach is reported for high-performance liquid chromatography to measure the level of information in fingerprints. For this purpose, the concept of peak prominence, which is the protruding part of each visible peak with regard to the valleys that delimit it, was used. The peaks in the fingerprints are ranked according to the areas of the peak prominences, and a threshold is established to discriminate between the significant peaks and those that are irreproducible. The approach was applied to evaluate the impact of several extraction conditions (solvent nature and composition, time and temperature of the treatment, amount of sample, and time and temperature of conservation of the extracts) on the number of significant peaks found in the fingerprints of a medicinal herb (a green tea sample), using Plackett–Burman designs. Acetonitrile, ethanol and methanol were used for the extraction, and a linear gradient for chromatographic analysis, where the acetonitrile content was increased from 5.0% to 42.5% (v/v) in 45 min. The maximal number of significant peaks in the fingerprints was obtained using a methanolwater mixture as extraction solvent, high ultrasonication time and high temperature. The reported approach can be generalised to other complex samples and situations.

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Year:  2015        PMID: 26602542     DOI: 10.1016/j.chroma.2015.10.020

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  1 in total

1.  A Novel and Practical Chromatographic "Fingerprint-ROC-SVM" Strategy Applied to Quality Analysis of Traditional Chinese Medicine Injections: Using KuDieZi Injection as a Case Study.

Authors:  Bin Yang; Yuan Wang; Lanlan Shan; Jingtao Zou; Yuanyuan Wu; Feifan Yang; Yani Zhang; Yubo Li; Yanjun Zhang
Journal:  Molecules       Date:  2017-07-23       Impact factor: 4.411

  1 in total

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