Chromatographic fingerprint-based analysis of extracts of green tea, lemon balm and linden: I. Development of global retention models without the use of standards.
Chromatographic fingerprints
Experimental designs
Global retention models
Medicinal plants
Multi-linear gradient elution
Journal
Journal of chromatography. A
ISSN: 1873-3778
Titre abrégé: J Chromatogr A
Pays: Netherlands
ID NLM: 9318488
Informations de publication
Date de publication:
07 Jun 2022
07 Jun 2022
Historique:
received:
23
02
2022
revised:
09
04
2022
accepted:
12
04
2022
pubmed:
28
4
2022
medline:
24
5
2022
entrez:
27
4
2022
Statut:
ppublish
Résumé
We report here the improvement of a procedure to obtain global models, able to describe the retention behaviour of several sample components simultaneously. The reported global models include parameters that account for the general effects of column and solvent on retention and are common for all components, whereas other parameters are specific of each sample component. These models are fitted by alternate regression and offer a prediction performance comparable to individual retention models. The approach is suitable to samples of natural products including a large number of components in extremely diverse concentrations and in the absence of standards. Guidelines are given for the successful development of sample-oriented experimental designs (i.e. adapted to the elution of the components of the natural products), constituted by multi-linear gradients. These designs also facilitate peak tracking. The model proposed by Neue and Kuss to describe the retention was found to yield the best predictions. The approach is applied to the extracts of samples of green tea, lemon balm and linden, yielding excellent predictions of retention for selected components.
Identifiants
pubmed: 35477073
pii: S0021-9673(22)00253-9
doi: 10.1016/j.chroma.2022.463060
pii:
doi:
Substances chimiques
Plant Extracts
0
Solvents
0
Tea
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
463060Informations de copyright
Copyright © 2022. Published by Elsevier B.V.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.