Application of neural network calibrations to an halide ISE array

The Neural Network (NN) technique was applied to the calibration of an ion selective electrode (ISE) array comprising a bromide selective electrode, two chloride ISEs and one thiocyanate ISE. The measured samples were synthetic mixture solutions of chlorides and bromides in concentration ranges such that interference occurs. The NN method allowed to perform the calibration without estimating the coefficients of the Nikolskii-Eisenman theoretical relation. Only the determination of bromide was detailed. The results obtained using this method were better than those obtained using linear multivariate calibration methods.     

Data fusion in multivariate calibration transfer

We report the use of stacked partial least-squares regression and stacked dual-domain regression analysis with four commonly used techniques for calibration transfer to improve predictive performance from transferred multivariate calibration models. The predictive performance from three conventional calibration transfer methods, piecewise direct standardization (PDS), orthogonal signal correction (OSC) and model updating (MUP), requiring standards measured on both instruments, was significantly improved from data fusion either by stacking of wavelet scales or by stacking of spectral intervals, as demonstrated by transfer of calibrations developed on near-infrared spectra of synthetic gasoline. Stacking did not produce as significant an improvement for calibration transfer using a finite impulse response (FIR) filter, but application of SPLS regression to FIR-transferred spectra improves predictive performance of the transferred model.     

Response of the Iron Chalcogenide Glass Membrane Ion‐Selective Electrode in a Seawater Ligand Mimetic Calibration Buffer

As a continuation of recent mechanistic studies into the influence of seawater ligands on the surface chemistry of the iron chalcogenide glass membrane ion‐selective electrode (ISE), the present study has investigated the response of the iron(III) ISE in a seawater ligand mimetic system to examine its suitability as a calibration medium for the electroanalysis of raw or natural seawater. Significantly, dip method calibrations of the ISE in a mixture of salicylate, ethylene diamine tetraacetic acid (EDTA), ethylene diamine and minor amounts of dissolved iron(III) and copper(II) yielded the expected Nernstian response of 30 mV/decade according to the known ion‐exchange/electron transfer response mechanism of this ISE. Furthermore, ideal Nernstian response of the electrode is also obtained in a continuous flow analysis (CFA) mode, noting that this provides scope for using a hydrodynamic flow regime to minimize the electrode release of iron and the concomitant detection limit of the ISE. Ultimately, repetitive CFA analyses of free iron(III) in raw or natural seawater yielded a free iron(III) level commensurate with the expected inorganic and organic speciation of iron(III) in seawater.     

Spectrophotometric determination of organic dye mixtures by using multivariate calibration

The simultaneous determination of organic dye mixtures by using spectrophotometric methods is a difficult problem in analytical chemistry, due to spectral interferences. By using multivariate calibration methods such as partial least-squares regression (PLSR), it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration stage. In this study, the calibration model is based on absorption spectra in the 350-650-nm range for a set of 16 different mixtures of reactive red 195, reactive yellow 145 and reactive orange 122 dyes, and made the determination of the dye concentrations possible in a validation set with significantly greater accuracy than the conventional univariate calibration method. By using the developed model it was possible to monitor the decolorization kinetic of one dye (reactive orange 122), when the mixture of the three dyes was previously submitted to an ozonation process.     

Potentiometric determination of iron using a fluoride ion-selective electrode-the application of the Apple II-ISE intelligent ion analyzer

A new method for determining iron is based on both nonlinear regression calibration plots and parabolic interpolation using a fluoride ion-selective electrode (ISE) and the Apple II-ISE intelligent ion Analyzer developed by ourselves. The experimental conditions for determining iron are discussed. The appropriate acidity of the experimental solution is pH 3, controlled by total ionic strength adjustment buffer (TISAB) that is composed of glycine (aminoacetic acid), nitric acid and sodium nitrate. The suitable total concentration of fluoride is equal to the highest concentration of iron in the standard series. Because the mathematical model of the method coincides with the experimental data the Apple II-ISE intelligent ion Analyzer can perform data acquisition and data processing, and the performance of fluoride electrode is excellent, the new method for determination of iron is fast and accurate. This method has been used successfully in the determination of iron in mineral samples.     

Spectrophotometric determination of hydrocortisone, nystatin and oxytetracycline in synthetic and pharmaceutical preparations based on various univariate and multivariate methods

Two spectrophotometric methods are described and applied to resolve ternary mixtures of the corticosteroid hydrocortisone (HYD) and the antibiotics nystatin (NYS) and oxytetracycline (OXY). The simultaneous determination of these three compounds was firstly accomplished by a derivative method using the “ratio spectrum-zero crossing derivative” and then by multivariate methods partial least squares (PLS)-1, -2 and principal component regression (PCR). Multivariate calibration methods provide, specially PLS-2 in this case, a clear example of the high resolving powder of these techniques. The two described procedures do not require any separation step. Repeatability and reproducibility studies were achieved over two series of 10 standards for each compound showing no significant differences at 95% confidence level in the four spectrophotometric methods. A comparison of the derivative and multivariate calibration results obtained in pharmaceutical formulations was performed resulting in agreement of the values obtained and the results was confirm by a high-pressure liquid chromatography (HPLC) method.     

Simulation of high- and low-resolution mass spectra for assessment of calibration methods

Calibrating mixtures of residual gases in quadrupole mass spectrometry (QMS) can be difficult since low m/z ratios of molecular ions and their fragments result in overlap of signals especially in the lower mass regions. This causes problems in univariate calibration methods and encourages use of full spectral multivariate methods. Experimental assessment of regression methods has limitations since experimental sources of error can only be minimised and not entirely eliminated. A method of simulating full spectra at low and high resolution to accurate masses is described and these are then used for a calibration study of some popular linear regression methods [classical least squares regression (CLS), partial least squares (PLS), principal component regression (PCR)].     

Response of a copper(II) and iron(III) ion-selective electrode bielectrode array in saline media

A bielectrode array comprising a jalpaite membrane (i.e., Ag_1.5Cu_0.5S) copper(II) ion-selective electrode (ISE) and chalcogenide glass membrane (i.e., Fe_2.5(Se₆₀Ge₂₈Sb₁₂)_97.5) iron(III) ISE has been assembled by individually wiring each solid-state sensor into a single electrode body. Furthermore, a dual metal ion buffer calibration standard incorporating copper(II) and iron(III) coordinating ligands to regulate the levels of free copper(II) and iron(III) in the buffer has been developed to enable simultaneous calibration of the bielectrode ISE array. In this work, the bielectrode ISE array has been employed in the continuous flow analysis (CFA) of free copper(II) and iron(III) in seawater media. It is shown that the individual electrodes displayed Nernstian response in the metal ion buffer calibration standard over a wide dynamic range (viz., 10⁻¹⁵ to 10⁻⁵ M aCu²⁺ and 10⁻²¹ to 10⁻¹¹ M aFe³⁺), and the results of repetitive CFA analyses of free copper(II) and iron(III) in seawater are commensurate with the typical values found in coastal seawater samples. Clearly, the bielectrode ISE array may be used in the simultaneous analysis of free copper(II) and iron(III) in seawater without fear of cross-interference between the solid-state sensors.     

Multivariate Calibration,an Overview

Abstract

Numerous methods of multivariate calibration methods exist with ridge regression, principal component regression, and partial least squares being the most popular methods in analytical chemistry. This mini‐review overviews multivariate calibration and provides a common theme with respect to the bias/variance tradeoff (harmony) and the harmony/parsimony tradeoff for model selection. Other multivariate calibration considerations are briefly reviewed. A few applications are noted.     

Chemometric alternatives for resolution of classical analytical problems Spectrophotometric determination of lanthanide mixtures

The simultaneous determination of lanthanide family elements is one of the greatest problems in analytical chemistry, due to the close similarity of their chemical properties. Spectrophotometric methods are generally of limited use, due to the various mutual spectral interferences involved. By using multivariate calibration methods (partial least-squares regression, PLSR), it was possible to obtain a model that adjusts itself perfectly to the values of the mixture concentrations used in the calibration. The model used absorption spectra in the 290-800 nm range for a set of 20 different mixtures of Ce, Pr, Nd and Sm, and made possible the determination of Ce, Pr and Nd concentrations of a commercial rare-earth product, with significantly greater precision than the conventional univariate calibration method. Determination of the Sm concentrations was not possible, since its concentration was below the concentrations used in the model definition.     

Multicomponent determination of pesticides in vegetables by gas chromatography with mass spectrometric detection and multivariate calibration

Three multivariate calibration methods, partial least squares (PLS-1 and PLS-2) and principal component regression (PCR), were applied for the first time to the simultaneous determination of a mixture of six pesticides in vegetables samples by gas chromatography with mass spectrometric detection (GC-MS). PLS-1 method showed better prediction ability than PLS-2 and PCR methods. The GC-MS chromatograms obtained of vegetable samples spiked with the target pesticides were used to build the calibration matrix. The PLS-1 models were evaluated by predicting the concentrations of independent test samples. Also, the proposed models were successfully applied for the determination of these pesticides in vegetable samples after an extraction step with dichloromethane. By using the first derivative signals in PLS-1 models, simultaneous determination of the compounds was not improved.     

Multivariate calibration leverages and spectral F‐ratios via the filter factor representation

Diagnostics are fundamental to multivariate calibration (MC). Two common diagnostics are leverages and spectral F‐ratios and these have been formulated for many MC methods such as partial least square (PLS), principal component regression (PCR) and classical least squares (CLS). While these are some of the most common methods of calibration in analytical chemistry, ridge regression is also common place and yet spectral F‐ratios have not been developed for it. Noting that ridge regression is a form of Tikhonov regularization (TR) and using the unifying filter factor representation for MC, this paper develops the filter factor form of leverages and spectral F‐ratios. The approach is applied to a spectral data set to demonstrate computational speed‐up advantages and ease of implementation for the filter factor representation. Copyright © 2010 John Wiley & Sons, Ltd.     

Resolution of ternary mixtures of salicylic, salicyluric and gentisic acids by partial least squares and principal component regression: Optimization of the scanning path in the excitation-emission matrices

The resolution of ternary mixtures of salicylic, salicyluric and gentisic acids has been accomplished by partial least squares (PLS) and principal component regression (PCR) multivariate calibration. The total luminescence information of the compounds has been used to optimize the spectral data set to perform the calibration. A comparison between the predictive ability of the three multivariate calibration methods, PLS-1, PLS-2 and PCR, on three spectral data sets, excitation, emission and synchronous spectra, has been performed. The excitation spectrum has been the best scanning path for salicylic and salicyluric acid determinations, while the emission spectrum has been the best for the gentisic acid determination. The convenience of analysing the total luminescence spectrum information when using multivariate calibration methods on fluorescence data is demonstrated.     

Stability-indicating methods for the determination of disopyramide phosphate

Four methods were developed for the determination of intact disopyramide phosphate in the presence of its degradation product. In the first and second methods, third-derivative spectrophotometry and first derivative of the ratio spectra were used. For the third-derivative spectrophotometric method, the peak amplitude was measured at 272 nm, while for the derivative ratio spectrophotometric method, disopyramide phosphate was determined by measuring the peak amplitude at 248 and 273 nm. Both methods were used for the determination of disopyramide phosphate in the concentration range 12.5-87.5 microg/mL, with corresponding mean recovery 100.8 +/- 0.7% for the first method and 99.9 +/- 0.7% and 99.6 +/- 0.7% for the second method at 248 and 273 nm, respectively. In the third method, an ion selective electrode (ISE) was fabricated using phosphotungstic acid as an anionic exchanger, PVC as the polymer matrix, and dibutylsebacate as a plasticizer. The ISE was used for the determination of disopyramide phosphate in pure powder form in the concentration range 10(-2)-10(-5) M. The slope was found to be 58.5 (mV/decade), and the average recovery was 99.9 +/- 1.6%. The fourth method depended on the quantitative densitometric determination of the drug in concentration range of 0.25-2.5 microg/spot using silica gel 60 F245 plates and ethyl acetate-chloroform-ammonium hydroxide (85 + 10 + 5, v/v/v) as the mobile phase, with corresponding mean accuracy of 100.3 +/- 1.1%. The 4 proposed methods were found to be specific for disopyramide phosphate in presence of up to 80% of its degradation product for the spectrophotometric methods, 90% of its degradation for the densitometric method, and 40% for the ISE method. The 4 proposed procedures were successfully applied for the determination of disopyramide phosphate in Norpace capsules. Statistical comparison between the results obtained by these methods and the official method of the drug was done, and no significant differences were found.     

New methods applicable for calibration of indicator electrodes

The new methods applicable for calibration of indicator electrodes, based on standard addition and standard subtraction methods, are suggested. Some of the methods enable the slope of an indicator electrode and equivalence volume V_eq to be determined simultaneously from a single set of potentiometric titration data. Some other methods known hitherto were also taken into account. A new model, based on a standard addition method, applicable also in nonlinear range for the ISE slope (S) is suggested, and its applicability was confirmed experimentally in calibration of calcium ISE.     

Multivariate calibration techniques applied to the spectrophotometric analysis of one-to-four component systems

The UV spectrophotometric analysis of a multicomponent mixture containing paracetamol, caffeine, tripelenamine and salicylamide by using multivariate calibration methods, such as principal component regression (PCR) and partial least-squares regression (PLS), was described. The calibration set was based on 47 reference samples, consisting of quaternary, ternary, binary and single-component mixtures, with the aim to develop models able to predict the concentrations of unknown samples containing as many as one-to-four components. The calibration models were optimized by an appropriate selection of the number of factors as well as wavelength ranges to be used for building up the data matrix and excluding any information about the interfering excipients included in pharmaceutics. The PCR and PLS models were compared and their predictive performance was inferred by a successful application to the assays of synthetic mixtures and pharmaceutical formulations.     

Multivariate calibration standardization used for the reduction of standards needed for multivariate calibration in inductively coupled plasma mass spectrometry

Multivariate calibration methods such as partial least squares regression (PLS) are capable of eliminating spectroscopic interferences in inductively coupled plasma mass spectrometry. These methods often require a large number of standards for the calibration, which can be a drawback if a full recalibration is needed very often. This problem can be circumvented by using multivariate calibration standardization to adjust either the sample or the calibration model to match a given state of the instrument. Four standardization methods (two univariate methods, direct standardization, and inverse model standardization) have been investigated and compared with full and partial calibration. Direct standardization gave the best results. It allowed for up to 78% reduction of the number of standards needed in the daily routine. Inverse model standardization needed more standards to accomplish similar results, and the two univariate methods could not be used for the determination of Gd.     

Nonlinear Estimation of the Equilibrium Potential for a Solid‐State Lead Ion‐Selective Electrode

Nonlinear regression was applied to three empirical equations to model the response of a solid‐state lead ion‐selective electrode (ISE). One particular equation, previously reported to describe the response of a fluoride ISE, was found to also describe the response of a solid‐state lead ISE. Nonlinear regression was applied to the early portion of the response curve for the lead ISE and used to estimate the equilibrium potential for a range of test solutions.     

Multivariate versus univariate calibration for nonlinear chemiluminescence data: Application to chromium determination by luminol-hydrogen peroxide reaction

Multivariate calibration is tested as an alternative to model chromium(III) concentration versus chemiluminescence registers obtained from luminol-hydrogen peroxide reaction. The multivariate calibration approaches included have been: conventional linear methods (principal component regression (PCR) and partial least squares (PLS)), nonlinear methods (nonlinear variants and variants of locally weighted regression) and linear methods combined with variable selection performed in the original or in the transformed data (stepwise multiple linear regression procedure). Both the direct and inverse univariate approaches have been also tested.

The use of a double logarithmic transformation previous to the linear regression has been also evaluated. A new double logarithmic transformation previous to the linear regression is proposed in order to avoid the effect of the noise in the calibration model. Pre-processing, optimization and prediction ability of the multivariate calibration models has been studied at nine different experimental conditions including batch and FIA measurements. Box-plots, PCA and cluster analysis have been employed to test the prediction ability of the different models tested. Nonlinear PCR and nonlinear PLS provide the best results. Real samples have been analyzed and compared with the reference method. The results confirm the successful use of the proposed methodology.     

New validated liquid chromatographic and chemometrics-assisted UV spectroscopic methods for the determination of two multicomponent cough mixtures in syrup

Multivariate spectrophotometric calibration and liquid chromatographic (LC) methods were applied to the determination of 2 multicomponent mixtures containing diprophylline, guaiphenesin, methylparaben, and propylparaben (Mixture 1), or clobutinol, orciprenaline, saccharin sodium, and sodium benzoate (Mixture 2). For the multivariate spectrophotometric calibration methods, principal component regression (PCR) and partial least-squares regression (PLS-1), a calibration set of the mixtures consisting of the components of each mixture was prepared in 0.1 M HCl. Analytical figures of merit such as sensitivity, selectivity, limit of quantitation, and limit of detection were determined for both PLS-1 and PCR. The LC separation was achieved on a reversed-phase C18 analytical column by using isocratic elution with 20 mM potassium dihydrogen phosphate, pH 3.3-acetonitrile (55 + 45, v/v) as the mobile phase and UV detection at 260 and 220 nm for Mixture 1 and Mixture 2, respectively. The proposed methods were validated and successfully applied to the analysis of pharmaceutical formulations and laboratory-prepared mixtures containing the 2 multicomponent combinations.