Application of principal component analysis-multivariate adaptive regression splines for the simultaneous spectrofluorimetric determination of dialkyltins in micellar media.

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ID: 21857
2013
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Abstract
A new multicomponent analysis method, based on principal component analysis-multivariate adaptive regression splines (PC-MARS) is proposed for the determination of dialkyltin compounds. In Tween-20 micellar media, dimethyl and dibutyltin react with morin to give fluorescent complexes with the maximum emission peaks at 527 and 520nm, respectively. The spectrofluorimetric matrix data, before building the MARS models, were subjected to principal component analysis and decomposed to PC scores as starting points for the MARS algorithm. The algorithm classifies the calibration data into several groups, in each a regression line or hyperplane is fitted. Performances of the proposed methods were tested in term of root mean square errors of prediction (RMSEP), using synthetic solutions. The results show the strong potential of PC-MARS, as a multivariate calibration method, to be applied to spectral data for multicomponent determinations. The effect of different experimental parameters on the performance of the method were studied and discussed. The prediction capability of the proposed method compared with GC-MS method for determination of dimethyltin and/or dibutyltin.
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ghasemi2013applicationspectrochimica Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ghasemi, Jahan B;Zolfonoun, Ehsan;
Journal spectrochimica acta part a, molecular and biomolecular spectroscopy
Year 2013
DOI
10.1016/j.saa.2013.06.054
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Keywords Keywords not found

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