Retention Modelling of Phenoxy Acid Herbicides in Reversed-Phase HPLC under Gradient Elution.
2,4-Dichlorophenoxyacetic Acid
/ analogs & derivatives
Acetonitriles
/ chemistry
Algorithms
Benzoates
/ isolation & purification
Chromatography, High Pressure Liquid
Chromatography, Reverse-Phase
Fresh Water
/ chemistry
Herbicides
/ isolation & purification
Humans
Hydrogen-Ion Concentration
Least-Squares Analysis
Models, Statistical
Molecular Structure
Phenylacetates
/ isolation & purification
Picolinic Acids
/ isolation & purification
Solvents
/ chemistry
Water Pollutants, Chemical
/ isolation & purification
Water Purification
/ methods
HPLC
PLS regression
gradient elution
molecular descriptors
phenoxy acid herbicides
retention prediction
Journal
Molecules (Basel, Switzerland)
ISSN: 1420-3049
Titre abrégé: Molecules
Pays: Switzerland
ID NLM: 100964009
Informations de publication
Date de publication:
11 Mar 2020
11 Mar 2020
Historique:
received:
26
01
2020
revised:
01
03
2020
accepted:
11
03
2020
entrez:
15
3
2020
pubmed:
15
3
2020
medline:
22
12
2020
Statut:
epublish
Résumé
Phenoxy acid herbicides are used worldwide and are potential contaminants of drinking water. Reversed phase high-performance liquid chromatography (RP-HPLC) is commonly used to monitor phenoxy acid herbicides in water samples. RP-HPLC retention of phenoxy acids is affected by both mobile phase composition and pH, but the synergic effect of these two factors, which is also dependent on the structure and pKa of solutes, cannot be easily predicted. In this paper, to support the setup of RP-HPLC analysis of phenoxy acids under application of linear mobile phase gradients we modelled the simultaneous effect of the molecular structure and the elution conditions (pH, initial acetonitrile content in the eluent and gradient slope) on the retention of the solutes. In particular, the chromatographic conditions and the molecular descriptors collected on the analyzed compounds were used to estimate the retention factor k by Partial Least Squares (PLS) regression. Eventually, a variable selection approach, Genetic Algorithms, was used to reduce the model complexity and allow an easier interpretation. The PLS model calibrated on the retention data of 15 solutes and successively tested on three external analytes provided satisfying and reliable results.
Identifiants
pubmed: 32168813
pii: molecules25061262
doi: 10.3390/molecules25061262
pmc: PMC7144001
pii:
doi:
Substances chimiques
Acetonitriles
0
Benzoates
0
Herbicides
0
Phenylacetates
0
Picolinic Acids
0
Solvents
0
Water Pollutants, Chemical
0
2,4-Dichlorophenoxyacetic Acid
2577AQ9262
phenylacetic acid
ER5I1W795A
acetonitrile
Z072SB282N
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
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