Optimisation of the separation of herbicides by linear gradient high performance liquid chromatography utilising artificial neural networks.

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dc.contributor.author Tran, AT
dc.contributor.author Hyne, RV
dc.contributor.author Pablo, F
dc.contributor.author Day, WR
dc.contributor.author Doble, P
dc.date.accessioned 2009-06-26T04:10:55Z
dc.date.issued 2007-02
dc.identifier.citation Talanta, 2007, 71 (3), pp. 1268 - 1275
dc.identifier.issn 0039-9140
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/624
dc.description.abstract An artificial neural network (ANN) was employed to model the chromatographic response surface for the linear gradient separation of 10 herbicides that are commonly detected in storm run-off water in agricultural catchments. The herbicides (dicamba, simazine, 2,4-D, MCPA, triclopyr, atrazine, diuron, clomazone, bensulfuron-methyl and metolachlor) were separated using reverse phase high performance liquid chromatography and detected with a photodiode array detector. The ANN was trained using the pH of the mobile phase and the slope of the acetonitrile/water gradient as input variables. A total of nine experiments were required to generate sufficient data to train the ANN to accurately describe the retention times of each of the herbicides within a defined experimental space of mobile phase pH range 3.0-4.8 and linear gradient slope 1-4% acetonitrile/min. The modelled chromatographic response surface was then used to determine the optimum separation within the experimental space. This approach allowed the rapid determination of experimental conditions for baseline resolution of all 10 herbicides. Illustrative examples of determination of these components in Milli-Q water, Sydney mains water and natural water samples spiked at 0.5-1mug/L are shown. Recoveries were over 70% for solid-phase extraction using Waters Oasis((R)) HLB 6cm(3) cartridges.
dc.format Print-Electronic
dc.language eng
dc.relation.isbasedon 10.1016/j.talanta.2006.06.031
dc.subject artificial neural network (ANN), polar herbicides, HPLC, photodiode array, solid-phase extraction, Analytical Chemistry
dc.subject artificial neural network (ANN), polar herbicides, HPLC, photodiode array, solid-phase extraction; Analytical Chemistry
dc.title Optimisation of the separation of herbicides by linear gradient high performance liquid chromatography utilising artificial neural networks.
dc.type Journal Article
dc.parent Talanta
dc.journal.volume 3
dc.journal.volume 71
dc.journal.number 3 en_US
dc.publocation Amsterdam, Netherlands en_US
dc.identifier.startpage 1268 en_US
dc.identifier.endpage 1275 en_US
dc.cauo.name SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 0399 Other Chemical Sciences
dc.personcode 10090684 en_US
dc.personcode 100467 en_US
dc.personcode 0000020122 en_US
dc.personcode 99030482 en_US
dc.personcode 010494 en_US
dc.percentage 100 en_US
dc.classification.name Other Chemical Sciences en_US
dc.classification.type FOR-08 en_US
dc.description.keywords artificial neural network (ANN), polar herbicides, HPLC, photodiode array, solid-phase extraction en_US
dc.description.keywords artificial neural network (ANN), polar herbicides, HPLC, photodiode array, solid-phase extraction
dc.staffid 010494 en_US
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Science
pubs.organisational-group /University of Technology Sydney/Faculty of Science/School of Chemistry and Forensic Science
pubs.organisational-group /University of Technology Sydney/Strength - Forensic Science


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