Multidetermination of thiamine HCl and pyridoxine HCl in their mixture using continuous daubechies and biorthogonal wavelet analysis

A new graphical method based on the one-dimensional wavelet transform (WT) was proposed and tested on mixture of thiamine hydrochloride (THI) and pyridoxine hydrochloride (PYR) in the presence of strongly overlapping signals. We selected from the data of the UV-VIS absorption spectra a signal consisting of 1150 points corresponding to the concentration range 8-32 mg ml⁻¹ for each vitamin and we subjected it to Daubechies8 (DAUB8) and Biorthogonal6.8 (BIOR6.8) wavelet transforms. Since the peaks of the transformed signals were bigger than original ones a zero crossing method was applied to obtain the calibration graphs. In addition, the validity of Beer-Lambert law was assumed for the transformed signals. An appropriate scale setting was choosing to obtain an alternative calibration for each method. Matlab 6.5 software was used for one-dimensional wavelet analysis and the basic concepts about wavelet method were given. The obtained results were successfully compared among each other as well as with those obtained by other literature methods. The method developed in this paper is rapid, easy to apply, not expensive and it is suitable for analyzing of the overlapping signals of compounds in their mixtures without any chemical pre-treatment.     

Chemometric methods for the simultaneous determination of some water-soluble vitamins

Two spectrophotometric methods, derivative and multivariate methods, were applied for the determination of binary, ternary, and quaternary mixtures of the water-soluble vitamins thiamine HCI (I), pyridoxine HCI (II), riboflavin (III), and cyanocobalamin (IV). The first method is divided into first derivative and first derivative of ratio spectra methods, and the second into classical least squares and principal components regression methods. Both methods are based on spectrophotometric measurements of the studied vitamins in 0.1 M HCl solution in the range of 200-500 nm for all components. The linear calibration curves were obtained from 2.5-90 microg/mL, and the correlation coefficients ranged from 0.9991 to 0.9999. These methods were applied for the analysis of the following mixtures: (I) and (II); (I), (II), and (III); (I), (II), and (IV); and (I), (II), (III), and (IV). The described methods were successfully applied for the determination of vitamin combinations in synthetic mixtures and dosage forms from different manufacturers. The recovery ranged from 96.1 +/- 1.2 to 101.2 +/- 1.0% for derivative methods and 97.0 +/- 0.5 to 101.9 +/- 1.3% for multivariate methods. The results of the developed methods were compared with those of reported methods, and gave good accuracy and precision.     

Efficient use of pure component and interferent spectra in multivariate calibration

Partial Least Squares (PLS) is by far the most popular regression method for building multivariate calibration models for spectroscopic data. However, the success of the conventional PLS approach depends on the availability of a ‘representative data set’ as the model needs to be trained for all expected variation at the prediction stage. When the concentration of the known interferents and their correlation with the analyte of interest change in a fashion which is not covered in the calibration set, the predictive performance of inverse calibration approaches such as conventional PLS can deteriorate. This underscores the need for calibration methods that are capable of building multivariate calibration models which can be robustified against the unexpected variation in the concentrations and the correlations of the known interferents in the test set. Several methods incorporating ‘a priori’ information such as pure component spectra of the analyte of interest and/or the known interferents have been proposed to build more robust calibration models. In the present study, four such calibration techniques have been benchmarked on two data sets with respect to their predictive ability and robustness: Net Analyte Preprocessing (NAP), Improved Direct Calibration (IDC), Science Based Calibration (SBC) and Augmented Classical Least Squares (ACLS) Calibration. For both data sets, the alternative calibration techniques were found to give good prediction performance even when the interferent structure in the test set was different from the one in the calibration set. The best results were obtained by the ACLS model incorporating both the pure component spectra of the analyte of interest and the interferents, resulting in a reduction of the RMSEP by a factor 3 compared to conventional PLS for the situation when the test set had a different interferent structure than the one in the calibration set.     

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.     

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.     

Integration of Commercial Screen‐printed Electrodes into a Voltammetric Electronic Tongue for the Analysis of Aminothiols

A voltammetric sensor array (or electronic tongue) is developed for the simultaneous quantification of cysteine, glutathione and homocysteine without need of previous separation. It is based on the integration of three commercial screen‐printed electrodes (gold curated at high and low temperature and carbon modified with carbon nanotubes). Linear sweep voltammograms measured simultaneously by all three sensors are processed by Partial Least Squares (PLS) regression and different variables selection algorithms such as Genetic Algorithm and interval‐Partial Least Squares. The method was applied to synthetic mixtures and successfully validated, with correlation coefficients of prediction (R_p²) of 0.9542, 0.9429 and 0.9589 for cysteine, glutathione, and homocysteine respectively.     

Simultaneous spectrophotometric determination of mercury and palladium with Thio-Michler's Ketone using partial least squares regression and orthogonal signal correction

A simple, novel and sensitive spectrophotometric method was described for simultaneous determination of mercury and palladium. The method is based on the complex formation of mercury and palladium with Thio-Michler's Ketone (TMK) at pH 3.5. All factors affecting on the sensitivity were optimized and the linear dynamic range for determination of mercury and palladium found. The simultaneous determination of mercury and palladium mixtures by using spectrophotometric method is a difficult problem, 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 for removing the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for PLS calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 360-660 nm range for 25 different mixtures of mercury and palladium. Calibration matrices were containing 0.025-1.60 and 0.05-0.50 microg mL(-1) of mercury and palladium, respectively. The RMSEP for mercury and palladium with OSC and without OSC were 0.013, 0.006 and 0.048, 0.030, respectively. This procedure allows the simultaneous determination of mercury and palladium in synthetic and real matrix samples good reliability of the determination.     

Comparison of Multicomponent Determination of Iprodione,Procymidone and Chlorothalonil by Partial Least Squares Modelling Using Spectrophotometric and High-Performance Liquid Chromatography Data

Abstract

A Partial Least Squares (PLS) calibration method was applied to the simultaneous determination of iprodione, procymidone and chlorothalonil in mixtures, by uv-vis absorption spectrophotometry and by high performance liquid chromatography (HPLC). Signals and first-derivative (¹D) signals were used to optimize the calibration matrices by the PLS-1 method. Quantitative results are presented for synthetic mixtures and for extracts from soil and groundwater samples. Significant improvements were achieved by using the PLS-1 method built with first-derivative chromatograms, in the determination of iprodione, procymidone and chlorothalonil in environmental samples.     

Spectrophotometric determination of ternary mixtures of thiamin, riboflavin and pyridoxal in pharmaceutical and human plasma by least-squares support vector machines.

Ternary mixtures of thiamin, riboflavin and pyridoxal have been simultaneously determined in synthetic and real samples by applications of spectrophotometric and least-squares support vector machines. The calibration graphs were linear in the ranges of 1.0 - 20.0, 1.0 - 10.0 and 1.0 - 20.0 microg ml(-1) with detection limits of 0.6, 0.5 and 0.7 microg ml(-1) for thiamin, riboflavin and pyridoxal, respectively. The experimental calibration matrix was designed with 21 mixtures of these chemicals. The concentrations were varied between calibration graph concentrations of vitamins. The simultaneous determination of these vitamin mixtures by using spectrophotometric methods is a difficult problem, due to spectral interferences. The partial least squares (PLS) modeling and least-squares support vector machines were used for the multivariate calibration of the spectrophotometric data. An excellent model was built using LS-SVM, with low prediction errors and superior performance in relation to PLS. The root mean square errors of prediction (RMSEP) for thiamin, riboflavin and pyridoxal with PLS and LS-SVM were 0.6926, 0.3755, 0.4322 and 0.0421, 0.0318, 0.0457, respectively. The proposed method was satisfactorily applied to the rapid simultaneous determination of thiamin, riboflavin and pyridoxal in commercial pharmaceutical preparations and human plasma samples.     

Determination of nebivolol hydrochloride and hydrochlorothiazide in tablets by first-order derivative spectrophotometry and liquid chromatography

Two simple and accurate methods for analysis of nebivolol hydrochloride (NEB) and hydrochlorothiazide (HCTZ) in their combined dosage forms were developed using first-order derivative spectrophotometry and reversed-phase liquid chromatography (LC). NEB and HCTZ in their combined dosage forms (tablets) were quantified using first-derivative responses at 294.6 and 334.6 nm in the spectra of their solutions in methanol. The calibration curves were linear in the concentration range of 8-40 microg/mL for NEB and 10-60 microg/mL for HCTZ. LC analysis was performed on a Phenomenex Gemini C18 column (250 x 4.6 mm id, 5 microm particle size) in the isocratic mode with 0.05 M potassium dihydrogen phosphate-acetonitrile-methanol (30 + 20 + 50, v/v/v; pH 4) mobile phase at a flow rate of 1 mL/min. Detection was made at 220 nm. Both of the drugs and the internal standard (ezetimibe) were well resolved with retention times of 5.1 min for NEB, 2.9 min for HCTZ, and 8.2 min for ezetimibe. The calibration curves were linear in the concentration range of 1-14 microg/mL for NEB and 0.3-28 microg/mL for HCTZ. Both methods were validated and found to be accurate, precise, and specific, and results were compared statistically. Developed methods were successfully applied for the estimation of NEB and HCTZ in their combined dosage forms.     

Determination of antihypertensive mixtures by use of a chemometrics-assisted spectrophotometric method

A simple multivariate calibration method for analysis of two types of hypotensive mixture is described. The mixtures are composed of chlorthalidone with atenolol or chlorthalidone with both amiloride hydrochloride and atenolol. The components of the mixtures result in substantial spectral overlap—between 87.5 and 91.0%. Resolution of the mixtures under investigation has been accomplished mainly by using CLS and PCR methods. The components in each mixture have been simultaneously determined in three commercial dosage forms with high accuracy and without interference from commonly encountered excipients and additives. Good recoveries were obtained with both synthetic mixtures and commercial tablets. The results obtained were compared with those from pharmacopeial methods and found to be in good agreement. The results obtained from CLS and PCR were also compared with those obtained from a ¹D spectrophotometric method.     

Estimation of pioglitazone hydrochloride and metformin hydrochloride in tablets by derivative spectrophotometry and liquid chromatographic methods

Two simple and accurate methods of analysis to determine pioglitazone hydrochloride (PIO) and mefformin hydrochloride (MET) in combined dosage forms were developed using second-derivative spectrophotometry and reversed-phase liquid chromatography (LC). PIO and MET in combined preparations (tablets) were quantified using the second-derivative responses at 227.55 nm for PIO and 257.25 nm for MET in spectra of their solutions in a mixture of methanol and acetonitrile (30 + 70). The calibration curves were linear [correlation coefficient (r) = 0.9984 for PIO and 0.9986 for MET] in the concentration range of 8-40 microg/mL for PIO and 4-12 microg/mL for MET. In the LC method, analysis was performed on a Hypersil ODS-C18 column with 5 microm particle size using the mobile phase acetonitrile-water-acetic acid (75 + 25 + 0.3), adjusted to pH 5.5 with liquor ammonia, at a flow rate of 0.5 mL/min. Measurement was made at a wavelength of 230 nm. Both the drugs were well resolved on the stationary phase, and the retention times were 8.5 min for PIO and 16.0 min for MET. The calibration curves were linear (r = 0.9933 for PIO and 0.9958 for MET) in the concentration range of 4-20 microg/mL for PIO and MET. Both methods were validated, and the results were compared statistically. They were found to be accurate, precise, and specific. The methods were successfully applied to the estimation of PIO and MET in combined tablet formulations.     

Simultaneous spectrophotometric determination of cobalt,copper and nickel using 1-（2-thiazolylazo）-2-naphthol by chemometrics methods

The simultaneous determination of cobalt, copper and nickel using 1-（2-thiazolylazo）-2-naphthol （first figure of this article） by 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 PLS calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 550-750-nm range for 21 different mixtures of cobalt, copper and nickel. Calibration matrices were formed from samples containing 0.05-1.05, 0.05-1.30 and 0.05-0.80 μg·mL^-1 for cobalt, copper and nickel, respectively. The root mean square error of prediction （RMSEP） for cobalt, copper and nickel with OSC and without OSC were 0.007, 0.008, 0.011 and 0.031,0.037, 0.032 μg· mL^-1, respectively. This procedure allows the simultaneous determination of cobalt, copper and nickel in synthetic and real samples and good reliability of the determination was proved.     

Comparison of different calibration methods for the determination by FT-NIR spectroscopy of the hydroxyl number in polyester resins

Different calibration methods have been applied for the determination of the Hydroxyl Number in polyester resins, namely Partial Least Squares (PLS), Principal Component Regression (PCR), Ordinary Least Squares with selection of the variables by genetic algorithm (OLS-GEN) and back-propagation Artificial Neural Networks (BP-ANN). The predictive ability of the regression models was estimated by splitting the dataset in training and test sets by application of the Kohonen self-organising maps. The linear methods (OLS-GEN, PLS and PCR) showed comparable results while artificial neural networks provided the best results both in fitting and prediction.     

Multicomponent determination of the pesticide naptalam and its metabolites in river water, by applying partial least squares calibration to the derivative spectrophotometric signals

A multivariate calibration method, partial least squares (types PLS-1 and PLS-2), was applied to the simultaneous determination of naptalam (N-(1-naphthyl) phthalamic acid) and its metabolites N-(1-naphthyl) phthalimide and 1-naphthylamine in mixtures by UV-visible absorption spectrophotometry. The absorption and first-derivative absorption spectra of mixtures were used to perform the optimization of the calibration matrices by the PLS method. Two different experimental designs for the three-component mixtures are assayed and the results are discussed. The proposed method with the derivative spectra was applied to the determination of these analytes in river water at the ppb level.     

Genetic programming as an analytical tool for non-linear dielectric spectroscopy.

By modelling the non-linear effects of membranous enzymes on an applied oscillating electromagnetic field using supervised multivariate analysis methods, Non-Linear Dielectric Spectroscopy (NLDS) has previously been shown to produce quantitative information that is indicative of the metabolic state of various organisms. The use of Genetic Programming (GP) for the multivariate analysis of NLDS data recorded from yeast fermentations is discussed, and GPs are compared with previous results using Partial Least Squares (PLS) and Artificial Neural Nets (NN). GP considerably outperforms these methods, both in terms of the precision of the predictions and their interpretability.     

Determination of origin and sugars of citrus fruits using genetic algorithm, correspondence analysis and partial least square combined with fiber optic NIR spectroscopy

The capacity to confirm the variety or origin and the estimation of sucrose, glucose, fructose of the citrus fruits are major interests of citrus juice industry. A rapid classification and quantification technique was developed and validated for simultaneous and nondestructive quantifying the sugar constituent's concentrations and the origin of citrus fruits using Fourier Transform Near-Infrared (FT-NIR) spectroscopy in conjunction with Artificial Neural Network (ANN) using genetic algorithm, Chemometrics and Correspondences Analysis (CA). To acquire good classification accuracy and to present a wide range of concentration of sucrose, glucose and fructose, we have collected 22 different varieties of citrus fruits from the market during the entire season of citruses. FT-NIR spectra were recorded in the NIR region from 1,100 to 2,500 nm using the fiber optic probe and three types of data analysis were performed. Chemometrics analysis using Partial Least Squares (PLS) was performed in order to determine the concentration of individual sugars. Artificial Neural Network analysis was performed for classification, origin or variety identification of citrus fruits using genetic algorithm. Correspondence analysis was performed in order to visualize the relationship between the citrus fruits. To compute a PLS model based upon the reference values and to validate the developed method, high performance liquid chromatography (HPLC) was performed. Spectral range and the number of PLS factors were optimized for the lowest standard error of calibration (SEC), prediction (SEP) and correlation coefficient (R(2)). The calibration model developed was able to assess the sucrose, glucose and fructose contents in unknown citrus fruit up to an R(2) value of 0.996-0.998. Numbers of factors from F1 to F10 were optimized for correspondence analysis for relationship visualization of citrus fruits based on the output values of genetic algorithm. ANN and CA analysis showed excellent classification of citrus according to the variety to which they belong and well-classified citrus according to their origin. The technique has potential in rapid determination of sugars content and to identify different varieties and origins of citrus in citrus juice industry.     

Spectrophotometric simultaneous determination of ceratine, creatinine, and uric acid in real samples by orthogonal signal correction–partial least squares regression

Abstract  This work describes a quantitative spectroscopic method for the analysis of ternary mixtures of ceratine (CER), creatinine (CRE), and uric acid (UA) using multivariate data models based upon ultraviolet spectroscopy. By multivariate calibration methods, such as partial least squares regression, it is possible to obtain a model adjusted to the concentration values of the mixtures used in the calibration range. In this study, the calibration model is based on absorption spectra in the 200–260 nm range for 36 different mixtures of CER, CRE, and UA. The unrelated information was removed by the orthogonal signal correction (OSC) method and the results were proved. Evaluation of the prediction errors for the prediction set reveals the OSC-treated data give substantially lower root mean square error of prediction (RMSEP) values than original data. The RMSEP for CER, CRE, and UA with OSC were 1.1686, 0.2195, and 0.3726, and without OSC were 1.9057, 0.3482, and 0.6164, respectively. This procedure allows the simultaneous determination of CER, CRE, and UA in synthetic and real samples. Graphical abstract        

Simultaneous determination of mebeverine hydrochloride and sulpiride using the first derivatives of ratio spectra and chemometric methods.

Two methods are described for the simultaneous determination of mebeverine hydrochloride (MB) and sulpiride (SU) in their combinations. The first method depends on the first derivative of the ratio spectra by measurement of the amplitudes at 263.7 and 234.9 nm for MB and SU, respectively. The linear ranges and detection limits are 4.0-40.0 and 0.72 microg/ml for MB and 1.0-10.0 and 0.34 microg/ml for SU. In the second case, a chemometric (classical least squares) method was developed. The concentration data matrices were obtained by using different concentrations of pure drugs in 0.1 M HCl. The absorbance data matrix corresponding to each concentration data matrix was obtained by the measurements of absorbances in the range 200-300 nm in their zero order spectra; then calibration was obtained by using the absorbance data matrix and the concentration data matrix for the prediction of the unknown concentrations of MB and SU in their mixture. The numerical values were calculated by using Matlab R12 version 6.0 and Origin 5.0 software. The procedures do not require any separation steps. These two methods were successfully applied for assaying the pharmaceutical formulation, of Colona tablets.     

Three different spectrophotometric methods manipulating ratio spectra for determination of binary mixture of Amlodipine and Atorvastatin

Three simple, specific, accurate and precise spectrophotometric methods manipulating ratio spectra are developed for the simultaneous determination of Amlodipine besylate (AM) and Atorvastatin calcium (AT) in tablet dosage forms. The first method is first derivative of the ratio spectra ((1)DD), the second is ratio subtraction and the third is the method of mean centering of ratio spectra. The calibration curve is linear over the concentration range of 3-40 and 8-32 μg/ml for AM and AT, respectively. These methods are tested by analyzing synthetic mixtures of the above drugs and they are applied to commercial pharmaceutical preparation of the subjected drugs. Standard deviation is <1.5 in the assay of raw materials and tablets. Methods are validated as per ICH guidelines and accuracy, precision, repeatability and robustness are found to be within the acceptable limit.