SPANILÁ, Miroslava, Jiří PAZOUREK, Marta FARKOVÁ a Josef HAVEL. Optimization of solid-phase extraction using artificial neural networks in combination with experimental design for determination of resveratrol by capillary zone electrophoresis in wines. J. Chromatogr. A. Amsterdam (The Netherlands): Elsevier Science, 2005, roč. 1084, č. 1, s. 180-185. ISSN 0021-9606.
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Základní 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
Originální 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 artificial neural networks, Capillary electrophoresis, experimental design, Multivariable approach, Single variable approach, Solid-Phase Extraction, trans-Resveratrol
Příznaky Mezinárodní význam, Recenzováno
Změnil Změnil: RNDr. JUDr. Vladimír Šmíd, CSc., učo 1084. Změněno: 6. 7. 2007 09:40.
Anotace
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.
Anotace 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 VaVNázev: Umělé neuronové sítě a plánování pokusů v analytické chemii, zejména v separačních metodách
Investor: Grantová agentura ČR, Umělé neuronové sítě a plánování pokusů v analytické chemii, zejména v separačních metodách
VytisknoutZobrazeno: 4. 5. 2024 02:41