2005
Optimization of solid-phase extraction using artificial neural networks in combination with experimental design for determination of resveratrol by capillary zone electrophoresis in wines
SPANILÁ, Miroslava, Jiří PAZOUREK, Marta FARKOVÁ a Josef HAVELZákladní údaje
Originální název
Optimization of solid-phase extraction using artificial neural networks in combination with experimental design for determination of resveratrol by capillary zone electrophoresis in wines
Název česky
Optimization of solid-phase extraction using artificial neural networks in combination with experimental design for determination of resveratrol by capillary zone electrophoresis in wines
Autoři
SPANILÁ, Miroslava (203 Česká republika), Jiří PAZOUREK (203 Česká republika, garant), Marta FARKOVÁ (203 Česká republika) a Josef HAVEL (203 Česká republika)
Vydání
J. Chromatogr. A. Amsterdam (The Netherlands), Elsevier Science, 2005, 0021-9606
Další údaje
Jazyk
angličtina
Typ výsledku
Článek v odborném periodiku
Obor
10406 Analytical chemistry
Stát vydavatele
Nizozemské království
Utajení
není předmětem státního či obchodního tajemství
Impakt faktor
Impact factor: 3.138
Kód RIV
RIV/00216224:14330/05:00020146
Organizační jednotka
Fakulta informatiky
UT WoS
000230862600026
Klíčová slova anglicky
Solid-phase extraction; Artificial neural networks; Experimental design; Single variable approach; Multivariable approach; Capillary electrophoresis; trans-resveratrol
Štítky
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 6. 7. 2007 09:40, RNDr. JUDr. Vladimír Šmíd, CSc.
V originále
Solid-phase extraction (SPE) is often used for preconcentration of analytes from biological samples. Such an analytical step requires optimization for obtaining reliable results. Optimization in analytical chemistry is traditionally still often done with relaxation method, when an optimal value of a single variable is searched for (single variable approach, SVA). Nowadays, using artificial neural networks (ANN) as a multivariable approach (MVA) in optimization is rapidly expanding. In this work, the optimization of SPE using relaxation method (SVA) and optimization by ANN in combination with experimental design (MVA) are compared and the latter approach is practically illustrated. Advantages of MVA over SVA for optimization are discussed. The prediction of the optimal SPE conditions for determination cis- and trans-resveratrol in Australian wines by capillary zone electrophoresis is described and the improvement of efficiency of SPE using MVA is confirmed.
Česky
Solid-phase extraction (SPE) is often used for preconcentration of analytes from biological samples. Such an analytical step requires optimization for obtaining reliable results. Optimization in analytical chemistry is traditionally still often done with relaxation method, when an optimal value of a single variable is searched for (single variable approach, SVA). Nowadays, using artificial neural networks (ANN) as a multivariable approach (MVA) in optimization is rapidly expanding. In this work, the optimization of SPE using relaxation method (SVA) and optimization by ANN in combination with experimental design (MVA) are compared and the latter approach is practically illustrated. Advantages of MVA over SVA for optimization are discussed. The prediction of the optimal SPE conditions for determination cis- and trans-resveratrol in Australian wines by capillary zone electrophoresis is described and the improvement of efficiency of SPE using MVA is confirmed.
Návaznosti
| GA203/02/1103, projekt VaV |
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