Orthogonal array design as a chemometric method for the optimization of analytical procedures. Part 3. Five-level design and its application in a polarographic reaction system for selenium determination

The theory and methodology of a five-level orthogonal array design for the optimization of analytical procedures were developed. In the theoretical section, the construction and characteristics of the OA25(56) matrix are described in detail while orthogonality is proved by means of a fourth-order polynomial model. Next, the assignment of experiments in the OA25(56) matrix is illustrated, followed by the data analysis strategy, in which significant/non-significant influence for each factor is quantitatively evaluated by the analysis of variance (ANOVA) technique including the percentage contribution, and the differences among five levels for each factor that has a significant influence are determined by Duncan's multiple F-test. Finally, the response surface methodology for the OA25(56) matrix is developed by using the equations obtained from the proof on orthogonality. In the application section, the reaction system for selenium determination by differential-pulse polarography, as a practical example, is employed to demonstrate the application of the OA25(56) matrix in the area of analytical chemistry.

[1]  J. Bayona,et al.  Optimization of a flame photometric detector for supercritical fluid chromatography of organotin compounds , 1993 .

[2]  Method development in high-performance liquid chromatography using retention mapping and experimental design techniques , 1989 .

[3]  H. Hill,et al.  Multiple-parameter optimization of a hydrogen-atmosphere flame ionization detector , 1984 .

[4]  Josephine M. Palasota,et al.  Mixture designs applied to the study of the liquid chromatographic separation of l-phenylalanine, l-tyrosine and l-tryptophan , 1992 .

[5]  P. Kaufmann,et al.  Optimized method for the determination of 1,2-diacyl-sn-glycero-3-phosphocholine and 1,2-diacyl-sn-glycero-3-phosphoethanolamine molecular species by enzymatic hydrolysis and gas chromatography , 1992 .

[6]  D. B. Hibbert.  Genetic algorithms in chemistry , 1993 .

[7]  Jean Pierre Brans,et al.  Multicriteria decision making: A case study , 1991 .

[8]  M. Bicking.  A Simplified Experimental Design Approach to Optimization of SFE Conditions for Extraction of an Amine Hydrochloride , 1992 .

[9]  James M. Minor,et al.  Optimization of solvent strength and selectivity for reversed-phase liquid chromatography using an interactive mixture-design statistical technique , 1980 .

[10]  A. Smilde,et al.  Multicriteria decision making , 1992 .

[11]  Y. M. Sin,et al.  Microwave digestion of fish tissue for selenium determination by differential pulse polarography. , 1994, Talanta.

[12]  Fluorescence lifetime data analysis using simplex searching and simulated annealing , 1992 .

[13]  G. R. Hecke,et al.  Attaining optimal conditions: An advanced undergraduate experiment that introduces experimental design and optimization , 1991 .

[14]  J. Vindevogel,et al.  Resolution optimization in micellar electrokinetic chromatography: use of Plackett-Burman statistical design for the analysis of testosterone esters , 1991 .