Selection of representative wavelength sets for monitoring in liquid chromatography with multichannel ultraviolet-visible detection

Fv, Warren; Ba, Bidlingmeyer; Mf, Delaney

doi:10.1021/ac00142a002

Cited by 12 publications

(14 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various criteria have already been developed to allow for automatic wavelength selection. − Among the proposed methods, the determinant and the condition number of calibration matrix are the most preferred criteria for prediction of the best wavelength combination. − Nevertheless, these two criteria are principally designed for exactly determined systems, although some modifications have been made to deal with overdetermined systems. [Most applications use RMSEP to characterize the performance of principal component regression (PCR) procedure, carried out under optimized conditions as obtained by the above criteria.]…”

mentioning

confidence: 99%

Wavelength Selection for Simultaneous Spectroscopic Analysis. Experimental and Theoretical Study

1996

View full text Add to dashboard Cite

Simultaneous multicomponent analysis is usually carried out by multivariate calibration models (such as principal component regression) that utilize the full spectrum. We demonstrate, by both experimental and theoretical considerations, that better results can be obtained by a proper selection of the spectral range to be included in calculations. We develop the theory that models the analytical uncertainty in multicomponent analysis and show the conditions where wavelength selection is essential (for example, when considerable spectral overlapping exists). An error indicator function is developed to predict the analytical performance under given experimental conditions, using a certain spectral range. This function is applied for allocation of the most informative spectral ranges to be utilized in multicomponent analysis. Selection of spectral ranges by this method is shown to ensure optimal results that considerably improve analytical performance in some cases. The similarity between the results obtained by this function and actual experimental results prove the validity of the proposed error indicator for wavelength selection. In addition to the experimental examples, extensive computer simulations have been carried out in order to study the validity of the theory over a wide range of the relevant parameters.Multicomponent spectral analysis is now gaining popularity. Numerous spectral data can be collected by modern instruments (such as photodiode arrays and CCD detectors), and several mathematical approaches have been designed to deal with these over-determined systems. [1][2][3][4][5][6] Early applications used complete spectra for determination of all components in a mixture. Ross and Pardue showed, however, that accuracy can be improved by a careful selection of wavelength ranges, which results in a collinearity or spectral overlap reduction. 7 The decision of how many data points and which wavelengths should be included in the analytical process is not trivial and is usually an empirical choice. 8 Various criteria have already been developed to allow for automatic wavelength selection. 8-25 Among the proposed meth-ods, the determinant and the condition number of calibration matrix are the most preferred criteria for prediction of the best wavelength combination. [8][9][10][11][12] Nevertheless, these two criteria are principally designed for exactly determined systems, although some modifications have been made to deal with overdetermined systems. [Most applications use RMSEP to characterize the performance of principal component regression (PCR) procedure, carried out under optimized conditions as obtained by the above criteria.] The major disadvantage of the current criteria is that all components are examined together with the same matrix, while in most cases, the optimal conditions for determination of each component is different and should be optimized separately. Recently, two stochastic search heuristics, namely, simulated annealing and genetic algorithms, have been suggested for wavelength selectio...

show abstract

mentioning

confidence: 99%

Wavelength Selection for Simultaneous Spectroscopic Analysis. Experimental and Theoretical Study

1996

View full text Add to dashboard Cite

show abstract

“…Various criteria are available for the optimization of spectral resolution. [20][21][22][23][24][25][26][27][28][29][30][31] Condition number and determinant are the generally accepted criteria and are widely used in wavelength selection. 25,30 Unfortunately, these methods are based on solving linear simultaneous equations and cannot be applied to the nonlinear problems of kinetic analysis.…”

Section: An Important Conclusion Is That Analytical Performance Is De...mentioning

confidence: 99%

“…Indeed, kinetic data are often considered as spectra. Various criteria are available for the optimization of spectral resolution. − Condition number and determinant are the generally accepted criteria and are widely used in wavelength selection. , Unfortunately, these methods are based on solving linear simultaneous equations and cannot be applied to the nonlinear problems of kinetic analysis. Although kinetic data are often considered as spectra, there is a big difference between them: the shape of an optical spectrum (as a function of wavelength) is usually independent of concentrations, while the kinetic spectrum of a component is concentration-dependent (with exception of unity reaction order).…”

mentioning

confidence: 99%

Optimization Method for Simultaneous Kinetic Analysis

Schechter

1996

Anal. Chem.

View full text Add to dashboard Cite

Kinetic analysis is often carried out for simultaneous determinations; thus, a theory to establish its optimal conditions is necessary. A very simple and fast model to find conditions for optimum analytical performance and to predict the quality of simultaneous kinetic analysis has been developed. It is general and applicable to any reaction order or rate constant. The model has been based on the angle between the kinetic vectors and on their norm ratio, which are readily calculated for any kinetic scheme. Evaluation of the proposed model has been carried out by detailed simulations of numerous experimental conditions and analysis by full PCR calculations (when applicable) or nonlinear least-squares fitting. An important conclusion is that analytical performance is determined to a large extent by the stability of the space spanned by the relevant component vectors (in addition to experimental noise and other factors). The quality of the analysis is governed by the angle between the kinetic vectors, while the norm ratio determines the error distribution between components. Optimum conditions for simultaneous kinetic analysis have been studied in several representative examples, regarding the timing of the kinetic monitoring and the effects of concentrations and of rate constant ratios, as well as several other factors of experimental relevance.

show abstract

“…Wavelength selection was chosen because of the numerous investigations in performing automatic selections (7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24). The proposed methods require complex computations and many do not assure selection of the global optimum wavelength set.…”

Section: Introductionmentioning

confidence: 99%

Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry

Kalivas¹,

Roberts²,

Sutter³

1989

Anal. Chem.

206

View full text Add to dashboard Cite

Selection of representative wavelength sets for monitoring in liquid chromatography with multichannel ultraviolet-visible detection

Cited by 12 publications

References 33 publications

Wavelength Selection for Simultaneous Spectroscopic Analysis. Experimental and Theoretical Study

Wavelength Selection for Simultaneous Spectroscopic Analysis. Experimental and Theoretical Study

Optimization Method for Simultaneous Kinetic Analysis

Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry

Contact Info

Product

Resources

About