Simultaneous determination of uranium(IV) and thorium(IV) ions with Arsenazo III by partial least squares method

A multivariate calibration method, Partial Least Squares Type 1 (PLS-1), is proposed for simultaneous spectrophotometric determination of uranium and thorium ions as their complexes with arsenazo III in hydrochloric acid medium. Several data characteristics are taking into account in order to minimize the optimum number of factors required for the construction of calibration model, while using various statistical criterions of selection. Finally, the evaluated calibration model is satisfactorily applied to determination of these ions in samples that resemble sulfuric acid leach solution obtained from a uranium ore.     

Kinetic spectrophotometric method for simultaneous determination of selenium and tellurium using partial least squares calibration

A kinetic-spectrophotometric method for the simultaneous determination of Se(IV) and Te(IV) is described. The method is based upon the catalytic effect of these cations on the reaction of toluidine blue with sulfide. Partial least squares calibration method was employed for the data manipulation and analysis. The concentrations were varied between 0.02-0.24 and 0.01-0.08 μg/ml for Se(IV) and Te(IV), respectively. Cross-validation method was used to select the optimum number of factors (NF). The root mean square errors of difference for selenium and tellurium were 1.2 and 1.7 μg/ml, respectively. Application of the method to artificial samples and several mixtures of standard solutions of Se(IV) and Te(IV) were performed and satisfactory results were obtained.     

beta-Correction as a preprocessing method for partial least squares in simultaneous determination of zinc and lead

An error analysis of predicted values using spectral correction matrix and partial least squares (PLS) modeling is applied for the determination of Zn²⁺ and Pb²⁺ with methylthymol blue (MTB) as a metallochromic indicator. The concentration ranges for Pb²⁺ and Zn²⁺ in standard solution sets are 0.5-5.2 and 0.1-2.5 μg ml⁻¹, respectively. The experimental calibration set was composed of 20 sample solutions using a random design for two component mixtures. The absorption spectra were recorded from 400 to 700 nm. The two wavelengths, which exert the minimum error in prediction of two metal ion concentrations, are chosen according to an error analysis of different pairs of wavelengths. The effect of the pH on the sensitivity in determination of Zn²⁺ and Pb²⁺ using MTB was studied in order to choose the optimum pH (pH=6) for determination. The values of root mean square difference (RMSD) for lead and zinc using β-correction partial least squares were 0.0977 and 0.1266, respectively. The effect of diverse ions and several experimental parameters were studied. The method was used for the determination of lead and zinc in alloy samples.     

Simultaneous determination of Sb(III) and Sb(V) by partial least squares regression

A method for simultaneous spectrophotometric determination of Sb(III) and Sb(V) using multivariate calibration method is proposed. This method is based on the development of the reaction between the analytes and pyrogallol red at pH 2.00. The selection of variables was studied. A series of synthetic solutions containing different concentrations of Sb(III) and Sb(V) were used to check the prediction ability of the partial least squares model. The calibration curves were linear over the range of 0.3-3.4 and 0.3-3.0 μg ml⁻¹ for Sb(III) and Sb(V), respectively. The detection limits were 0.177 and 0.200 μg ml⁻¹ for Sb(III) and Sb(V), respectively.     

Simultaneous determination of antimony(III) and antimony(V) by UV-vis spectroscopy and partial least squares method (PLS)

This paper describes a procedure for the speciation of antimony by UV-vis spectroscopy using pyrogallol as complexing agent. A partial least squares (PLS) regression was performed to resolve highly overlapping spectrophotometric signals obtained from mixtures of Sb(III) and Sb(V). The relative error in absolute value was less than 5% when concentrations of several mixtures were calculated. The minimum concentration determined was 3.96 × 10⁻⁵ mol dm⁻³ and 3.98 × 10⁻⁵ mol dm⁻³ for Sb(V) and Sb(III), respectively. The analysis of the possible effect of the presence of foreign ions in the solution was performed and the procedure was successfully applied to the speciation of antimony in pharmaceutical preparations and aqueous samples.     

Application of H-point standard addition method and partial least squares to the simultaneous kinetic-potentiometric determination of hydrazine and phenylhydrazine

Simultaneous determination of hydrazine (HZ) and phenylhydrazine (PHZ) by H-point standard addition method (HPSAM) and partial least squares (PLS) regression was carried out based on kinetic data from novel potentiometry methods. The rate of chloride ion production in the reaction of HZ and PHZ with N-chlorosuccinimide (NCS) was monitored by a chloride ion-selective electrode. The experimental data show the good ability of ion-selective electrodes (ISEs) as detectors not only for the direct determination of chloride ion but also for simultaneous kinetic-potentiometric analysis using HPSAM and PLS methods. The methods are based on the differences observed in the production rate of chloride ions. The results show that simultaneous determination of HZ and PHZ can be performed in concentration ranges of 0.5 - 20.0 and 0.8 - 25.0 microg mL(-1), respectively. The total relative standard error for applying the PLS method to 8 synthetic samples in the concentration ranges of 1.0 - 16.0 microg mL(-1) for HZ and 2.0 - 16.0 microg mL(-1) for PHZ was 3.96. In order for the selectivity of the method to be assessed, we evaluated the effects of certain foreign ions upon the reaction rate and assessed the selectivity of the method. Both methods (PLS and HPSAM) were evaluated using a set of synthetic sample mixtures and then applied for simultaneous determination of HZ and PHZ in water samples.     

Flow-injection chemiluminescence simultaneous determination of cobalt(II) and copper(II) using partial least squares calibration

A flow-injection chemiluminescence (CL) system is proposed for simultaneous determination of Co²⁺ and Cu²⁺ using partial least squares (PLS) calibration. This method is based on the fact that both Co²⁺ and Cu²⁺ catalyse the CL reaction of luminol-H₂O₂, and that their kinetic characteristics of Co²⁺ and Cu²⁺ are significantly different in the luminol-H₂O₂ system. The CL intensity was measured and recorder at different reaction times of luminol-H₂O₂Co²⁺Cu²⁺, and the obtained data were processed by the chemometric approach of partial least squares. The experimental calibration set was composed of 16 sample solutions using an orthogonal calibration design for two component mixtures. The proposed method offers the potential advantages of high sensitivity, simplicity and rapidity for Co²⁺ and Cu²⁺ determination, and was successfully applied to the simultaneous determination of both analytes in real water sample. The present paper demonstrated that the simultaneous determination of two metal ions without any prior separation has been possible using flow-injection CL system.     

Application of the spectral correction method and "neural networks" for simultaneous determination of V(V) and Al(III)

Simultaneous determination of V(V) and Al(III) was performed by application of neural networks when the calibration matrix was performed using β-correction spectra. Two reactions between V(V) and Al(III) and Alizarin Red S (ARS) as a ligand have been investigated and applied for the simultaneous spectrophotometric determination of these metal ions. The parameters controlling behavior of the system were investigated and optimum conditions selected. Feed-forward neural networks have been trained to quantify considered metal ions in mixtures under optimum conditions. Sigmoidal functions were used in the hidden and output layers. Determinations were made over the concentration range 0.10-7.80 μg ml⁻¹ of V(V) and 0.11-4.20 μg ml⁻¹ of Al(III). Applying this method satisfactorily to simultaneous determination of these metal ions in several synthetic solutions with total relative standard error less than 4.02% validated the proposed method.     

Orthogonal signal correction-partial least squares method for simultaneous spectrophotometric determination of cypermethrin and tetramethrin

The simultaneous determination of cypermethrin and tetramethrin mixtures by using spectrophotometric method is a difficult problem in analytical chemistry, due to spectral interferences. By multivariate calibration methods, such as partial least squares (PLS) regression, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Orthogonal signal correction (OSC) is a preprocessing technique used for removing the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 200-350 nm range for 25 different mixtures of cypermethrin and tetramethrin. Calibration matrices were containing 0.1-12.9 and 0.1-13.8 microg mL(-1) for cypermethrin and tetramethrin, respectively. The RMSEP for cypermethrin and tetramethrin with OSC and without OSC were 0.0884, 0.0614 and 0.2915, 0.2309, respectively. This procedure allows the simultaneous determination of cypermethrin and tetramethrin in synthetic and real samples good reliability of the determination was proved.     

Cloud point extraction and simultaneous spectrophotometric determination of V(V), Co(II) and Cu(II) ions in water samples by 5-Br-PADAP using partial least squares regression

In this work, a new method has been proposed to simultaneously determine V(V), Co(II) and Cu(II) ions from aqueous solution by spectrophotometry after cloud point extraction using partial least squares regression (PLS). The metal ions in 10 ml of aqueous solution (containing 0.2 M sodium acetate buffer solution, pH 3.5) were formed complexes with 2-(5-bromo-2-pyridylazo)-5-diethylaminophenol (5-Br-PADAP). Then, Triton X-114 (2 %, v/v) was added to the solution. By increasing the temperature of the solution up to 55 °C, a phase separation occurred. After centrifugation at 3,000 rpm for 10 min, the surfactant-rich phase was dissolved and diluted to 0.5 mL with ethanol. The metal ions were then determined using spectrophotometry. At these optimal extraction and operating conditions, linearity was obeyed in the range 7–300, 3–100 and 15–700 ng mL^?1 of V(V), Co(II) and Cu(II), with the detection limit of 2.2, 1.0 and 4.5 ng mL^?1, respectively. The relative predictive error for the simultaneous determination of 15 test samples of different concentrations of V(V), Co(II) and Cu(II) was 3.28, 3.64 and 4.04 %, respectively. The root mean square error of prediction for applying the PLS method to 15 synthetic samples in the linear ranges of these metal ions was 3.4, 1.6 and 18.1 ng mL^?1. The interference effect of some anions and cations was also tested. The proposed method has been applied successfully to the simultaneous determination of V(V), Co(II) and Cu(II) ions in real matrix samples with the recoveries of 96.75–104.80 %.     

Stacked partial least squares regression analysis for spectral calibration and prediction

Two novel algorithms which employ the idea of stacked generalization or stacked regression, stacked partial least squares (SPLS) and stacked moving‐window partial least squares (SMWPLS) are reported in the present paper. The new algorithms establish parallel, conventional PLS models based on all intervals of a set of spectra to take advantage of the information from the whole spectrum by incorporating parallel models in a way to emphasize intervals highly related to the target property. It is theoretically and experimentally illustrated that the predictive ability of these two stacked methods combining all subsets or intervals of the whole spectrum is never poorer than that of a PLS model based only on the best interval. These two stacking algorithms generate more parsimonious regression models with better predictive power than conventional PLS, and perform best when the spectral information is neither isolated to a single, small region, nor spread uniformly over the response. A simulation data set is employed in this work not only to demonstrate this improvement, but also to demonstrate that stacked regressions have the potential capability of predicting property information from an outlier spectrum in the prediction set. Moisture, oil, protein and starch in Cargill corn samples have been successfully predicted by these new algorithms, as well as hydroxyl number for different instruments of terpolymer samples including and excluding an outlier spectrum. Copyright © 2009 John Wiley & Sons, Ltd.     

Spectrophotometric simultaneous determination of cobalt, copper and nickel using nitroso-R-salt in alloys by partial least squares

Partial least squares modeling as a powerful multivariate statistical tool applied to spectrophotometric simultaneous determination of cobalt, copper, and nickel in aqueous solutions. The concentration range for cobalt, copper and nickel were 0.4-2.6, 0.6-3.4, 0.5-5.5 ppm, respectively. The experimental calibration set was composed with 36 sample solutions using a mixture design for three component mixtures. The absorption spectra were recorded from 470 to 600 nm. The effect of pH on the sensitivity and selectivity was studied according to net analyte signal (NAS). The values of root mean square difference (RMSD) for cobalt, copper and nickel using partial least squares (PLS) were 0.0192, 0.0263 and 0.0446 ppm, respectively. The effects of various cations and anions were investigated. The method was used to determination of cobalt, copper and nickel in two sample alloys based on copper, nickel and cobalt (known as cunico) and based on cobalt, nickel and iron (known as conife).     

Simultaneous spectrophotometric determination of Sn(II) and Sn(IV) by mean centering of ratio kinetic profiles and partial least squares methods

Two spectrophotometric methods are described for the simultaneous determination of binary mixtures of Sn(II) and Sn(IV) in water samples and fruit juice samples, without prior separation steps, using the mean centering of ratio kinetic profiles and partial least squares (PLS) methods. The methods are based on the difference in the rate of the reactions of Sn(II) and Sn(IV) with pyrocatechol violet at pH 4.0. The methods allow rapid and accurate determination of Sn(II) and Sn(IV). The analytical characteristics of the methods for the simultaneous determination of binary mixtures of Sn(II) and Sn(IV) were calculated. The results showed that the methods were capable to simultaneous determination of 0.1–1.80 mg L⁻¹ each of cations. The proposed methods were successfully applied to the simultaneous determination of Sn(II) and Sn(IV)in an orange juice sample.     

Gas-chromatographic fatty-acid fingerprints and partial least squares modeling as a basis for the simultaneous determination of edible oil mixtures

Partial least squares modeling and gas-chromatographic fatty-acid fingerprints are reported as a method for the simultaneous determination of cottonseed, olive, soybean and sunflower edible oil mixtures. In this work, two sets of three- and four-component combinations of oils were prepared, hydrolyzed and the obtained free fatty acids analyzed by gas chromatography (GC) without any further derivatization. The normalized percentages of the myristic (14:0), palmitic (16:0), palmitoleic (16:1), stearic (18:0), oleic (18:1), linoleic (18:2) and linolenic (18:3) acids were chromatographically measured in samples and used for constructing calibration matrix. The cross-validation method was used to select the number of factors and the proposed methods were validated by using two sets of synthetic oil mixture samples. The relative standard error for each oil in mixture samples was less than 10%. This approach allows determining possible adulteration in each of the four edible oils.     

Solid-phase UV spectroscopic multisensor for the simultaneous determination of caffeine, dimenhydrinate and acetaminophen by using partial least squares multicalibration

A straightforward flow-through multisensor was developed for the fast simultaneous determination of caffeine (CF), dimenhydrinate (DMH) and acetaminophen (AAP) based on the integration of their retention and UV detection. A diode array spectrophotometer was used to monitor the inherent UV full-spectra in the range 245-310 nm of the analytes retained on C(18) bonded phase beads packed in a flow cell, without requiring additional reagents or derivatization processes. The extensively overlapped spectra of the analytes retained on the solid support could be resolved by partial least squares (PLS) regression. After collecting the response of the multisensor, its active microzone was regenerated by using methanol as the eluting agent, leaving it ready for the next determination. The proposed multisensor has been satisfactorily applied for the analysis of synthetic and real samples with different nominal contents of these active principles.     

Spectrophotometric simultaneous determination of manganese(II) and iron(II) in pharmaceutical by orthogonal signal correction-partial least squares

The simultaneous determination of manganese(II) and iron(II) mixtures by using spectrophotometric methods is a difficult problem in analytical chemistry, due to spectral interferences. By multivariate calibration methods, such as partial least squares (PLS), it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. Orthogonal signal correction (OSC) is a preprocessing technique used to remove the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 450-600 nm range for 21 different mixtures of manganese(II) and iron(II). Calibration matrices were containing 0.05-1.2 and 0.1-2.3 microg mL(-1) Mn(II) and Fe(II), respectively. The RMSEP for manganese(II) and iron(II) with OSC and without OSC were 0.0316, 0.0291, and 0.0907, 0.115, respectively. This procedure allows the simultaneous determination of manganese(II) and iron(II) in synthetic and real matrix samples with good reliability of the determination.     

Simultaneous determination of uranium(VI) and thorium(IV) ions with carminic acid by the partial least squares (PLS-1 and PLS-2) methods

Two multivariate calibration methods, partial least squares types 1 and 2 (PLS-1 and PLS-2) have been applied to the simultaneous determination of U(VI) and Th(IV) ions as complexes with carminic acid by visible absorption spectrophotometry. The results obtained by application of different chemometric approaches are discussed. No significant advantages were found between the methods. The proposed methods were applied satisfactorily to the determination of these ions in synthetic solutions simulating sulfuric acid leach solutions obtained from uranium-thorium ores.     

Simultaneous kinetic spectrophotometric determination of cyanide and thiocyanate using the partial least squares (PLS) regression

The partial least squares (PLS-1) calibration model based on spectrophotometric measurement, for the simultaneous determination of CN⁻ and SCN⁻ ions is described. The method is based on the difference in the rate of the reaction between CN⁻ and SCN⁻ ions with chloramine-T in a pH 4.0 buffer solution and at 30 °C. The produced cyanogen chloride (CNCl) reacts with pyridine and the product condenses with barbituric acid and forms a final colored product. The absorption kinetic profiles of the solutions were monitored by measuring absorbance at 578 nm in the time range 20-180 s after initiation of the reaction with 2 s intervals. The experimental calibration matrix for partial least squares (PLS-1) calibration was designed with 31 samples. The cross-validation method was used for selecting the number of factors. The results showed that simultaneous determination could be performed in the range 10.0-900.0 and 50.0-1200.0 ng mL⁻¹ for CN⁻ and SCN⁻ ions, respectively. The proposed method was successfully applied to the simultaneous determination of cyanide and thiocyanate in water samples.     

Reflectance near-infrared spectroscopic method with a chemometric technique using partial least squares multivariate calibration for simultaneous determination of chondroitin, glucosamine, and ascorbic acid

A reflectance near-infrared (RNIR) spectroscopy method was developed for simultaneous determination of chondroitin (CH), glucosamine (GO), and ascorbic acid (AS) in capsule powder. A simple preparation of the sample was done by grinding, sieving, and compression of the powder sample for improving RNIR spectra. Partial least squares (PLS-1 and PLS-2) was successfully applied to quantify the three components in the studied mixture using information included in RNIR spectra in the 4240-9780 cm(-1) range. The calibration model was developed with the three drug concentrations ranging from 50 to 150% of the labeled amount. The calibration models using pure standards were evaluated by internal validation, cross-validation, and external validation using synthetic and pharmaceutical preparations. The proposed method was applied for analysis of two pharmaceutical products. Both pharmaceutical products had the same active principle and similar excipients, but with different nominal concentration values. The results of the proposed method were compared with the results of a pharmacopoeial method for the same pharmaceutical products. No significant differences between the results were found. The standard error of prediction was 0.004 for CH, 0.003 for GO, and 0.005 for AS. The correlation coefficient was 0.9998 for CH, 0.9999 for GO, and 0.9997 for AS. The highly accurate and precise RNIR method can be used for QC of pharmaceutical products.     

Mutual information-induced interval selection combined with kernel partial least squares for near-infrared spectral calibration

With the aim of developing a nonlinear tool for near-infrared spectral (NIRS) calibration, an applicable algorithm, called MIKPLS, is designed based on the combination of two different strategies, i.e. mutual information (MI) for interval selection and kernel partial least squares (KPLS) for modeling. Due to the ability of capturing linear and nonlinear dependencies between variables simultaneously, mutual information between each candidate variables and target is calculated and employed to induce a continuous wavelength interval, which is subsequently applied to build a parsimonious calibration model for future use by kernel partial least squares. Through the experiments on two datasets, it seems that mutual information (MI)-induced interval selection, followed by KPLS, forms a very simple and practical tool, allowing a prediction model to be constructed using a much-reduced set of neighboring variables, but without any loss of generalizations and with improved prediction performance instead.