Kinetic-spectrophotometric Data Research Articles

Mean Centered Kinetic—Spectrophotometric Data—Continuous Wavelet Transform for Simultaneous Determination of Dopamine and Uric Acid in Presence of Ascorbic Acid at Biological Samples

In the present study, a rapid, practical, selective and sensitive method was proposed for simultaneous determination of dopamine (DA) and uric acid (UA). Kinetic profiles of analytes were recorded and transformed by different mother wavelets. The contribution of ascorbic acid was neglected using mean centering of data before transformation. The concentrations range were 1.0–60.0 μmol L−1 and 7–40.0 μmol L−1, with detection limit of 0.06 and 0.30 μmol L−1 for uric acid and dopamine, respectively. The results of sym8 and db4 mother wavelets showed that proposed method creates a most selective and sensitive determination without using initial separation steps. The obtained results by CWT-sym8 and CWT-db4 were compared with partial least squares (PLS) results. The simultaneous quantitation of DA and UA with the proposed method was successfully applied in different urine and serum samples.

Closure constraint in multivariate curve resolution

AbstractMultivariate curve resolution techniques try to estimate physically and/or chemically meaningful profiles underlying a set of chemical or related measurements. However, the estimation of profiles is not generally unique and it is often complicated by intensity and rotational ambiguities. Constraints as further information of chemical entities can be imposed to reduce the extent of ambiguities. Not only a long list of constraints has been introduced but also some of them can be applied in different ways. Either investigating constraint effects on the extent of rotational ambiguity or how they can be applied during curve resolution can shed light on curve resolution studies. The motivation behind this contribution is to pave the way to a clarification about the closure constraint. Considering simulated equilibrium and kinetic spectrophotometric data sets, different approaches to closure implementation were applied to demonstrate the geometrical explanation of closure constraint and its effect on multivariate curve resolution‐alternating least squares results. Besides, the closure constraint is compared with normalization and it is proved that the closure constraint is a Borgen norm and has the same effect as other Borgen norms in multivariate curve resolution. Finally, to further examine the closure constraint, a real data set was investigated.

Determination of Nitrite in Food Samples by Kinetic Spectrophotometric Data and Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS)

Herein, a method for spectrophotometric determination of nitrite in food samples with complex matrices is developed. The method is based on the standard addition and collecting kinetic data of the reaction of nitrite with 4-amino-3-hydroxynaphthalene-1-sulfonic acid (AHNSA) and 1-naphthylamine. Standard additions were made based on the linear range of the method using the above reagents. Kinetic data of different standard additions were augmented and subsequently analyzed by multivariate curve resolution-alternating least squares (MCR-ALS) to achieve second-order advantage. The proposed method was applied to real samples, and 19.86, 19.68, 1.38, 2.50, and 4.00 mg kg−1 of nitrite was found in cheese, tomato paste, sausage, hamburger, and kielbasa, respectively. The results were validated by a standard method.

Determination of nitrite in food samples by second-order calibration of kinetic spectrophotometric data

A method for the determination of nitrite in soil and vegetable samples by UV-Vis spectroscopy was proposed. The kinetic UV-Vis data were collected during the reaction between nitrite and 4-amino-3-hydroxynaphthalene-1-sulfonic acid with concentration of 0.001 M and pH 1.6. Data were collected by standard addition method. Multivariate curve resolution-alternating least squares was employed to analyze data with non-negativity and three-way data structure constraints. The method can be used to solve matrix effect and unknown interferents in the determination of nitrite in complex samples. The proposed method was used to determine nitrite at low mg/L levels with satisfactory results in soil, lettuce, cabbage and cucumber samples.

Determination of Nitrite in Food Samples by sEcond-Order Calibration of Kinetic Spectrophotometric Data

Determination of Nitrite in Food Samples by sEcond-Order Calibration of Kinetic Spectrophotometric Data

Second-order advantage in determining Co (II) in real samples using kinetic-spectrophotometric data matrices and multivariate curve resolution-alternating least square approach

In the present study, multivariate curve resolution coupled to alternating least-squares (MCR-ALS) was used to analyze kinetic-spectroscopic second-order data. The purpose of the study was to achieve important sec ond-order advantage under the conditions of extreme spectral overlapping among sample components. The obtained experimental data indicated that MCR-ALS, unlike other second-order multivariate calibration algorithms, can conveniently handle the investigated analytical problem provided that matrix augmentation is implemented in the spectral mode instead of the usual kinetic mode. In this work, row-wise augmentation was used to break rank deficiency under conditions of extreme spectral overlapping among sample components. The approach was applied to determine Cobalt (II) based on its oxidation reaction with Fe (III) and 1, 10-phenantroline in micellar media. The results indicated good analytical performance toward the analyte despite the intense spectral overlapping and the presence of unexpected constituents in the test samples. The maximum and minimum band boundaries of feasible solutions corresponding to the species profiles were estimated by multivariate curve resolution. The results of the study indicated that unique solution can be practically obtained using MCR-ALS under the selection of suitable constraints such as trilinearity.

Mean centering of ratio spectra for dye degradation study in Fenton reaction

In this work, an application of mean centering of ratio spectra is proposed to the study of pollutant dyes degradation using Fenton reaction. Two-way kinetic-spectrophotometric data related to dye(s) mixtures degradation are divided into simulated kinetic profiles, mean centered and their ranks were monitored versus simulated dye degradation constant. For accurate dye degradation constant(s), the rank of resulted matrix will be reduced by one. By this search, all kinetic constants related to all included dyes are acquired. To find out which k values are related to the degradation of dye of interest, a preliminary deflation of data from its contribution is done and the procedure is repeated. By this search, the kinetic constant related to dye of interest will be omitted while others will be remained. The applicability of the proposed method was evaluated using model data. Finally, second-order kinetic-spectrophotometric data in the degradation of malachite green in the presence of crystal violet and methylene blue were analyzed by the proposed method as a real system.

Extraction of the contribution of kinetic profile for reaction of a chemical species in unknown matrices by standard addition method

A new and simple strategy is applied to resolve kinetic profile for the reaction of an analyte in unknown matrices, using standard addition method (SAM). The proposed method uses kinetic spectrophotometric data obtained by standard addition of analyte into unknown mixtures followed by the reaction of analyte with a proper reagent. The proposed method extracts kinetic profile for the reaction of an analyte by averaging the kinetic profiles obtained by subtraction of kinetic profiles after and before standard addition. The rate constant can be obtained using computational curve fitting. The performance of method was evaluated by using synthetic data as well as several experimental data sets. The proposed method can be applied to obtain kinetic profiles of the reactions in the presence of additive interference as well as multiplicative interferences. Hydroxylation reaction of diphenylcarbazide (DPCI) in the presence of diphenylcarbazone (DPCO) as a real system at various pHs was also studied by the present method. The rate constant and the order of the hydroxylation reaction were determined from extracted kinetic profiles.

Second-order advantage obtained from standard addition first-order instrumental data and multivariate curve resolution-alternating least squares. Calculation of the feasible bands of results

In order to achieve the second-order advantage, second-order data per sample is usually required, e.g., kinetic-spectrophotometric data. In this study, instead of monitoring the time evolution of spectra (and collecting the kinetic-spectrophotometric data) replicate spectra are used to build a virtual second order data. This data matrix (replicate mode×λ) is rank deficient. Augmentation of these data with standard addition data [or standard sample(s)] will break the rank deficiency, making the quantification of the analyte of interest possible. The MCR-ALS algorithm was applied for the resolution and quantitation of the analyte in both simulated and experimental data sets. In order to evaluate the rotational ambiguity in the retrieved solutions, the MCR-BANDS algorithm was employed. It has been shown that the reliability of the quantitative results significantly depends on the amount of spectral overlap in the spectral region of occurrence of the compound of interest and the remaining constituent(s).

Multivariate curve resolution-alternating least squares (MCR-ALS) and central composite experimental design for monitoring and optimization of simultaneous removal of some organic dyes

In this work, multivariate curve resolution-alternating least squares (MCR-ALS) has been applied to resolve and study the simultaneous degradation of three toxic organic dyes using Fenton reaction. Second-order kinetic-spectrophotometric data in the simultaneous degradation of malachite green, crystal violet and methylene blue were analyzed by MCR analysis to get their concentration profiles and calculate their degradation factors. The effect of three parameters (Fe2+, H2O2 concentration and initial pH) and their possible interaction in the simultaneous degradation of mentioned dyes were studied and optimized using experimental design and response surface method. Acquiring second-order data makes possible the analysis and study of the studied dyes in the gray systems which is termed as second-order advantage in the literatures. The prominent point of this work is the combination of second-order data and response surface methodology.

Determination of tartrazine in beverage samples by stopped-flow analysis and three-way multivariate calibration of non-linear kinetic-spectrophotometric data

The performance of MCR-ALS was studied in the modeling of non-linear kinetic-spectrophotometric data acquired by a stopped-flow system for the quantitation of tartrazine in the presence of brilliant blue and sunset yellow FCF as possible interferents.In the present work, MCR-ALS and U-PCA/RBL were firstly applied to remove the contribution of unexpected components not included in the calibration set. Secondly, a polynomial function was used to model the non-linear data obtained by the implementation of the algorithms. MCR-ALS was the only strategy that allowed the determination of tartrazine in test samples accurately. Therefore, it was applied for the analysis of tartrazine in beverage samples with minimum sample preparation and short analysis time. The proposed method was validated by comparison with a chromatographic procedure published in the literature. Mean recovery values between 98% and 100% and relative errors of prediction values between 4% and 9% were indicative of the good performance of the method.

A second-order standard addition method based on the data treatment by calculation of variation matrix of kinetic systems analyzed by MCR-ALS

A new method is proposed to resolve the kinetic-spectrophotometric data of multicomponent mixtures and determination of analyte(s) in the presence of unknown matrix. The method uses variation matrix data by shifting to another target, namely the reaction space. The variation matrix is obtained by subtracting the zero-point spectrum (e.g., first spectrum) from each spectrum at each time. This space shifting decreases the rank numbers to the numbers of reactions. Self-modeling curve resolution is used to resolve the variation matrices of kinetic-spectrophotometric data for mixtures of analytes. In addition, second-order standard addition method is used to remove the matrix effect(s) when analyze unknown samples. This means that, quantitative analysis can be performed by augmentation of the variation matrix of the unknown samples and standard added samples and, then, plotting standard addition calibration curve. The applicability of the proposed method is evaluated using model and real data for mixtures of analytes.

Estimation of the rate constants of second order reactions using mean centering of ratio spectra

A new application of the mean centering of ratio spectra method is proposed for estimation of the rate constants of second order reactions, using kinetic-spectrophotometric data. The method is based on the mean centering of the ratio spectra to obtain a kinetic profile of the product. Using computational fitting, the rate constant can be obtained without any ambiguity. An interesting feature of second-order reactions is that the number of steps in the reaction is less than the number of absorbing species, resulting in a rank-deficient response matrix. Through using row mean centering of ratio spectra, the pure response of the product of the reaction could be obtained, and thus an accurate estimation of rate constant would be possible. The applicability of the method was evaluated by using several model data. The reaction of 1,2-naphthoquinone-4-sulfonate sodium (NQS) and 3-nitroaniline (TNA) in ethanol as a real system was also studied applying the proposed method.

Rank annihilation factor analysis using mean centering of ratio spectra for kinetic–spectrophotometric analysis of unknown samples

In this work rank annihilation factor analysis (RAFA) using mean centering of ratio spectra was used to analyze the kinetic–spectrophotometric data. Annihilation of the contribution of one chemical component from the original data matrix is a general method in RAFA. However, sometimes, RAFA is not suitable for studying rank-deficient data such as kinetic–spectrophotometric measurements which involves closure rank deficiency. On the other hand, in order to apply RAFA for the determination of an analyte in an unknown sample, a standard two-way matrix of the analyte of interest with rank-one should generally be available. This is not usually attainable for kinetic–spectrophotometric monitoring of complexation reactions when both reactant and product are absorbing species. In these systems, the exact contribution of absorbing reagent should be eliminated from both unknown sample and standard calibration data matrix of analyte otherwise ordinary RAFA fails to give correct concentration of analyte of interest. Mean centering of ratio spectra using the spectrum of absorbing reagent as divisor can be used to eliminate the correct contribution of reagent for both sample data and standard calibration data of analyte. The obtained mean centering of ratio spectra matrix of sample and that of analyte of interested are full-rank and rank-one, respectively. Therefore the system can be analyzed by RAFA. The proposed method was investigated with simulated data at the first stage. The method was then applied in the analysis of experimental kinetic–spectrophotometric data of complexation reactions of Co(II), and Ni(II) with PAN in order to do multi-component determination of these ions in various real samples.

Different strategies for the direct determination of amoxicillin in human urine by second-order multivariate analysis of kinetic–spectrophotometric data

The kinetic evolution of UV–visible absorption spectra of amoxicillin in the presence of copper(II) ions has been processed by the second-order multivariate methods parallel factor analysis (PARAFAC) and also by a novel approach based on partial least-squares with residual bilinearization (PLS/RBL). The latter one is employed for the first time to evaluate kinetic–spectral information. The mechanism of the analyte metal-catalyzed hydrolysis involves a reaction intermediate and a final reaction product, both with spectra which may allow for the determination of amoxicillin in human urine, even in the presence of unsuspected sample components. This is possible thanks to the second-order advantage exploited by the employed chemometric algorithms, among which PARAFAC and PLS/RBL gave the best results. Amoxicillin was determined in a series of spiked and real urine samples, which allowed to perform, respectively, a recovery study and a comparison with the reference high-performance liquid chromatographic technique. The best figures of merit were obtained with PLS/RBL, namely sensitivity, 0.5 AU L mg −1 (AU = absorbance units), analytical sensitivity, 500 L mg −1 and limit of detection, 6 mg L −1. Relative advantages and disadvantages of the employed algorithms are discussed.

Application and comparison of two-rate and differential kinetic methods in simultaneous spectrophotometric determination of ascorbic acid and L-cysteine in pharmaceutical samples

Two methods for the simultaneous determination of ascorbic acid (Asc) and L-cysteine (Cys) from kinetic spectrophotometric data are described and compared. The first is the two-rate method (TRM), and the second, the differential kinetic method (DKM). Present in an excess amount, iron(III) is quantitatively reduced by Asc or Cys to iron(II) that, in turn, interacts with phenanthroline (Phen) to form a colored product, representing a Fe(II)-Phen complex that possesses a maximum absorbance at λmax = 510 nm. The first method is based on the measurement of reaction rates at two points in the course of successive reactions, and the second method is based on the difference in kinetics of the Asc and Cys oxidation reactions at different pH values. Both oxidation reactions have been studied by fitting the kinetic curves (absorbance versus time) to suitable reaction rate equations. It is established that the Cys + Fe(III) reaction obeys simple first-order kinetics, while the Asc + Fe(III) is a successive two-step process. Under the conditions studied, both Asc and Cys are determined in the 0.5–5.0 ppm range with satisfactory accuracy. The two methods under consideration have been successfully used for the analysis of model and real samples. The RMSEP values for the determination of Cys and Asc by the two kinetic methods (TRM, DKM) are 0.121, 0.120 and 0.131, 0.303 and the corresponding REP values are 5.15, 5.12% and 5.18, 11.98%, respectively.

Simultaneous determination of levodopa and benserazide by stopped-flow injection analysis and three-way multivariate calibration of kinetic-spectrophotometric data

The simultaneous determination of levodopa and benserazide in pharmaceutical formulations is described, based on the application of multidimensional partial least-squares regression to the kinetic-spectrophotometric data provided by diode-array detection within a stopped-flow injection method where analytes react with periodate. Flow injection parameters were adequately optimized. Accurate analysis is performed with no sample pre-treatment steps, and with minimum experimental effort. Satisfactory recovery results were obtained on a number of synthetic and commercial samples, in the latter case including the comparison with liquid chromatography measurements.

Modeling kinetic spectrophotometric data of aminophenol isomers by PARAFAC2

This paper describes an application of PARAFAC2 in the modeling of kinetic-spectrophotometric data. The data were obtained by spectrophotometric monitoring of the reaction between aminophenol isomers and NaNO 2 in acid solution. The data set of various samples produces a three-way data array. This reaction has the property that isomers in different proportions produce different kinetic profiles. Due this property, PARAFAC2 is suitable to model the system because it does not assume parallel proportional kinetic profiles. The results with PARAFAC2 were satisfactory, it being possible to recover the spectral and kinetic profiles, as well as the initial isomer concentrations with good accuracy.

Evaluation of classical and three-way multivariate calibration procedures in kinetic-spectrophotometric analysis

The bidimensional multivariate regression procedures: multiple linear regression (MLR), principal component regression (PCR), partial least squares regression (PLS) and continuum regression (CR), and several N-way methods such as N-way PLS (nPLS) and parallel factor analysis (PARAFAC) are tested as calibration methods for the kinetic-spectrophotometric determination of ternary mixtures in a pseudo first-order kinetic system. The different calibration procedures were first applied to computer simulated kinetic-spectrophotometric data where the effect of spectral overlap and the differences in the kinetic constants were evaluated at a low level of experimental noise. Later they were applied to the stopped-flow kinetic-spectrophotometric simultaneous resolution of Co(II), Ni(II) and Ga(III) using 4-(2-pyridylazo)resorcinol (PAR) as a chromogenic reagent. Accurate estimations of concentrations with relative standard errors of prediction of about 8% were obtained even though a high degree of spectral overlap and similar rate constants were present. The study of the influence of experimental noise on the 3-component system justifies the difference between the simulations and the experimental results for the different calibration procedures. PARAFAC and MLR did not allow the resolution of the proposed 3-component system. CR provided slightly better results than those obtained by PLS, PCR and nPLS.

Factors affecting the accuracy of multicomponent kinetic-spectrophotometric determinations based on multivariate calibration methods

The influence of experimental variables on the accuracy of multicomponent kinetic-spectrophotometric determinations using multivariate calibration techniques is reported. Kinetic and spectral angles are introduced and shown to be good descriptors of the quantity of analytical information present in kinetic-spectrophotometric data. The components of these descriptor angles are described. The effects of instrumental noise and rate constant fluctuation are contrasted. An equilibrium spectrophotometric determination of gallium(III) and nickel(II) is compared to a kinetic determination and a kinetic-spectrophotometric determination. The effect of changing experimental variables (e.g., pH and wavelength range) is discussed, and conclusions are drawn.