dc.contributor.author |
Dinç, Erdal
|
|
dc.contributor.author |
Baleanu, Dumitru
|
|
dc.contributor.author |
Kanbur, Murat
|
|
dc.date.accessioned |
2020-04-18T13:44:22Z |
|
dc.date.available |
2020-04-18T13:44:22Z |
|
dc.date.issued |
2004 |
|
dc.identifier.citation |
Dinç, Erdal; Baleanu, Dumitru; Kanbur, M., "Spectrophotometric multicomponent determination of tetramethrin, propoxur and piperonyl butoxide in insecticide formulation by principal component regression and partial least squares techniques with continuous wavelet transform", Canadian Journal Of Analytical Sciences And Spectroscopy, Vol.49, No.4, pp.218-225, (2004). |
tr_TR |
dc.identifier.issn |
1205-6685 |
|
dc.identifier.uri |
http://hdl.handle.net/20.500.12416/3356 |
|
dc.description.abstract |
A continuous wavelet transform (CWT) followed by a principal component regression(PCR) and partial least squares (PLS) were applied for the quantitative determination of tetramethrin (TRM), propoxur (PPS) and piperonil butoxide (PPR) in their formulations. Absorbances of the concentration set formed by TRM, PPS and PPR mixtures were measured at 850 points between 220-350 nm with 0.1 nm intervals, and their absorbance values as absorbance data vectors were transferred into the wavelets domain. A CWT was applied to the absorbance data. The resulting CWT-coefficients (x-block) and concentration set (y-block) were used for the construction of CWT-PCR and CWT-PLS calibrations. The combination of both continuous wavelet and chemometrics techniques indicates good results for the determination of insecticide in synthetic mixtures and commercial formulation |
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dc.language.iso |
eng |
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dc.publisher |
Spectroscopy Soc Canada |
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dc.rights |
info:eu-repo/semantics/openAccess |
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dc.subject |
Continuous Wavelet Transform |
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dc.subject |
Chemometrics Technique |
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dc.subject |
Tetramethrin |
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dc.subject |
Propoxur |
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dc.subject |
Piperonil Butoxide |
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dc.title |
Spectrophotometric multicomponent determination of tetramethrin, propoxur and piperonyl butoxide in insecticide formulation by principal component regression and partial least squares techniques with continuous wavelet transform |
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dc.type |
article |
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dc.relation.journal |
Canadian Journal Of Analytical Sciences And Spectroscopy |
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dc.contributor.authorID |
56389 |
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dc.identifier.volume |
49 |
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dc.identifier.issue |
4 |
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dc.identifier.startpage |
218 |
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dc.identifier.endpage |
225 |
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dc.contributor.department |
Çankaya Üniversitesi, Fen Edebiyat Fakültesi, Matematik Bölümü |
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