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 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.     

Spectrophotometric simultaneous determination of nitroaniline isomers by orthogonal signal correction-partial least squares

The simultaneous determination of nitroaniline isomer 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 for removes 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 200–500 nm range for 21 different mixtures of nitroaniline isomers. Calibration matrices were containing 1–21, 1–15 and 1–18 μg ml⁻¹ of m-nitroaniline, o-nitroaniline and p-nitroaniline, respectively. The RMSEP for m-nitroaniline, o-nitroaniline and p-nitroaniline with OSC and without OSC were 0.6567, 0.2692, and 0.3134, and 1.3818, 1.2181, and 0.3953, respectively. This procedure allows the simultaneous determination of nitroaniline isomers in real matrix samples and good reliability of the determination was proved.     

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.     

Kinetic spectrophotometric determination of trace amounts of palladium by whole kinetic curve and a fixed time method using resazurine sulfide reaction

The univariate and multivariate calibration methods were applied for the determination of trace amounts of palladium based on the catalytic effect on the reaction between resazurine and sulfide. The decrease in absorbance of resazurine at 602 nm over a fixed time is proportional to the concentration of palladium over the range of 10.0-160.0 ng mL(-1). The calibration matrix for partial least squares (PLS) regression was designed with 14 samples. 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 without loss of prediction ability using spectrophotometric method. The root mean square error of prediction (RMSEP) for palladium determination with fixed-time, PLS and OSC-PLS were 3.71, 2.84 and 0.68, respectively. This procedure allows the determination of palladium in synthetic and real samples with good reliability of the determination.     

A Partial Least-Squares Multivariate Calibration Method for the Simultaneous Spectrophotometric Determination of Spironolactone,Canrenone and Hydrochlorothiazide

Abstract

An application of a partial least squares calibration method for the simultaneous spectrophotometric determination of spironolactone, canrenone and hydrochlorothiazide is suggested. The use of the PLS for the multicomponent spectrophotometric determination is demonstrated on the analysis of several synthetic mixtures. It was shown that is possible to resolve complex mixtures of     

混合线性分析-分光光度法同时测定微量锌、镉、汞

提出了以2－（5－溴－2－吡啶偶氮）－5－二乙氨基酚为显色剂分光光度法同时测定锌、镉、汞的新方法。由于在可见区3种络合物的吸收光谱具有相似的特征和严重重叠,本文采用混合线性分析进行光谱分辨,各组分的纯光谱则用最小二乘法从校正集中求出。讨论了显色条件,波长选择,纯光谱的确定和吸光度加合性等因素对测定的影响。方法具有简单,快速,准确等优点。已成功地应用于混合试样中锌、镉、汞的同时测定,并与同条件下偏最小二乘法的计算结果进行了对比。     

Genetic Algorithm Applied to Selection of Wavelength in Partial Least Squares for Simultaneous Spectrophotometric Determination of Nitrophenol Isomers

Abstract

Ternary mixtures of nitrophenol isomers have been simultaneously determined in synthetic and real matrix by application of genetic algorithm and partial least squares model. All factors affecting the sensitivity were optimized and the linear dynamic range for determination of nitrophenol isomers found. The simultaneous determination of nitrophenol mixtures by using spectrophotometric methods is a difficult problem, due to spectral interferences. The partial least squares modeling was used for the multivariate calibration of the spectrophotometric data. A genetic algorithm is a suitable method for selecting wavelength for PLS calibration of mixtures with almost identical spectra without loss prediction capacity. The experimental calibration matrix was designed by measuring the absorbance over the range 300–520 nm for 21 samples of 1–20 µg mL^?1, 1–20 µg mL^?1, and 1–10 µg mL^?1 of m‐nitrophenol, o‐nitrophenol, and p‐nitrophenol, respectively. The root mean square error of prediction for m‐nitrophenol, o‐nitrophenol, and p‐nitrophenol with genetic algorithms and without genetic algorithms were 0.3732, 0.5997, 0.3181 and 0.7309, 0.9961, 1.0055, respectively. The proposed method was successfully applied for the determination of m‐nitrophenol, o‐nitrophenol, and p‐nitrophenol in synthetic and water samples.     

Genetic‐Algorithm‐Based Wavelength Selection in Multicomponent Spectrophotometric Determination by PLS: Application on Ascorbic Acid and Uric Acid Mixture

Genetic algorithm (GA) is a suitable method for selecting wavelengths for partial least squares (PLS) calibration of mixtures with almost identical spectra without loss of prediction capacity using the spectrophotometric method. In this study, the concentration model is based on absorption spectra in the range of 200‐320 nm for 25 different mixtures of ascorbic acid (AA) and uric acid (UA). The calibration curve was linear over the concentration range of 1‐15 and 2‐16 μg mL^?1 for ascorbic acid and uric acid, respectively. The root mean square deviation (RMSD) for ascorbic acid and uric acid with GA and without GA were 0.3071 and 0.3006, 0.3971 and 0.7063, respectively. The proposed method was successfully applied to the simultaneous determination of both analytes in human serum and urine samples.     

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        

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.     

Simultaneous determination of nifuroxazide and drotaverine hydrochloride in pharmaceutical preparations by bivariate and multivariate spectral analysis

The quantitative predictive abilities of the new and simple bivariate spectrophotometric method are compared with the results obtained by the use of multivariate calibration methods [the classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS)], using the information contained in the absorption spectra of the appropriate solutions. Mixtures of the two drugs Nifuroxazide (NIF) and Drotaverine hydrochloride (DRO) were resolved by application of the bivariate method. The different chemometric approaches were applied also with previous optimization of the calibration matrix, as they are useful in simultaneous inclusion of many spectral wavelengths. The results found by application of the bivariate, CLS, PCR and PLS methods for the simultaneous determinations of mixtures of both components containing 2-12microgml(-1) of NIF and 2-8microgml(-1) of DRO are reported. Both approaches were satisfactorily applied to the simultaneous determination of NIF and DRO in pure form and in pharmaceutical formulation. The results were in accordance with those given by the EVA Pharma reference spectrophotometric method.     

Genetic-algorithm-based wavelength selection in multicomponent spectrophotometric determination by PLS: application on copper and zinc mixture

Genetic algorithm (GA) is a suitable method for selecting wavelengths for PLS (partial least squares) calibration of mixtures with almost identical spectra without loss of prediction capacity using spectrophotometric method. The method is based on the development of the reaction between the analytes and Zincon at pH 9. A series of synthetic solution containing different concentrations of copper and zinc were used to check the prediction ability of the GA-PLS models. The RMSD for copper and zinc with GA and without GA were 0.0407 and 0.0865, 0.2147 and 0.3005, respectively. Calibration matrices were 0.05-1.8 and 0.05-1.5 μg ml⁻¹ for copper and zinc, respectively. This procedure allows the simultaneous determination of cited ions in natural, tap and waste waters good reliability of the determination was proved.     

人工神经网络紫外光度法同时测定甲基苯甲醛的三种同分异构体及其与偏最小二乘法的比较

同分异构体的同时测定一直是分析化学领域的热点和难点问题,本文将化学计量学中的多元校正方法,如偏最小二乘法和人工神经网络法与紫外分光光度法相结合,同时测定了紫外吸收光谱严重重叠的甲基苯甲醛的三种同分异构体混合体系中各组分的含量。确定了测定的最佳波长范围为230～304 nm;测得48个混合标样的吸光度值用于建立模型,其中,邻、间、对甲基苯甲醛的浓度范围分别为6.0～15.0、7.0～16.0和8.0～19.0 μg·mL-1。7个模拟样品作为监测集用于检验所建立模型的预测性能。本文还讨论了三种组分浓度比例对所建立模型预测性能的影响并确定了可以准确测定的浓度比例范围。所建立的方法用于模拟样品的测定,其回收率在84.00%与109.60%之间。与偏最小二乘法的测定结果比较,经成对t检验表明,两种方法对邻、间甲基苯甲醛测定结果无显著性差异;而对甲基苯甲醛的测定,人工神经网络法的测定结果优于偏最小二乘法。     

偏最小二乘法及主组分回归法用于药物组分的测定

本文研究了多元校准方法——偏最小二乘法(PLS)和主组份回归法(PCR)在药物多组份光度分析中的应用,获得了较满意的结果。而且在系列校准样品的实验设计、交叉证实法确定最佳因子数以及空缺组份体系的分析等方面进行了探讨。     

Combining orthogonal signal correction and wavelet packet transform with partial least squares to analyze overlapping spectra of three kinds of metal ions

A novel method named OSC-WPT-PLS approach based on partial least squares (PLS) regression with orthogonal signal correction (OSC) and wavelet packet transform (WPT) as pre-processed tools was proposed for the simultaneous spectrophotometric determination of Al(III), Mn(II) and Co(II). This method combines the ideas of OSC and WPT with PLS regression for enhancing the ability of extracting characteristic information and the quality of regression. OSC is used to remove information in the response matrix D by subtracting the structured noise that is orthogonal to the concentration matrix C. Wavelet packet transform was applied to perform data compression, to extract relevant information, and to eliminate noise and collinearity. PLS was applied for multivariate calibration and noise reduction by eliminating the less important latent variables. In this case, using trials, the kind of wavelet function, the decomposition level, the number of OSC components and the number of PLS factors for the OSC-WPT-PLS method were selected as Daubechies 4, 3, 2 and 3, respectively. A program (POSCWPTPLS) was designed to perform the simultaneous spectrophotometric determination of Al(III), Mn(II) and Co(II). The relative standard errors of prediction (RSEP) obtained for total elements using OSC-WPT-PLS, WPT-PLS and PLS were compared. Experimental results demonstrated that the OSC-WPT-PLS method had the best performance among the three methods and was successful even when there was severe overlap of spectra.     

Simultaneous determination of phenobarbital and phenytoin in tablet preparations by multivariate spectrophotometric calibration

The use of multivariate spectrophotometric calibration for the simultaneous determination of the active components of antiepileptic tablets is presented. The resolution of binary mixtures of phenobarbital and phenytoin has been accomplished by using partial least squares (PLS-1) regression analysis. Although the components show an important degree of spectral overlap, they have been simultaneously determined with high accuracy, with no interference from tablet excipients. A comparison is presented with the related multivariate method of classical least squares (CLS) analysis, which is shown to yield less reliable results due to the severe spectral overlap presented by the studied compounds. A statistical measure for the spectral overlap is proposed.     

Simultaneous kinetic spectrophotometric determination of Cu(II), Co(II) and Ni(II) using partial least squares (PLS) regression

A partial least squares (PLS-1) calibration model based on kinetic—spectrophotometric measurement, for the simultaneous determination of Cu(II), Ni(II) and Co(II) ions is described. The method was based on the difference in the rate of the reaction between Co(II), Ni(II) and Cu(II) ions with 1-(2-pyridylazo)2-naphthol in a pH 5.8 buffer solution and in micellar media at 25°C. The absorption kinetic profiles of the solutions were monitored by measuring the absorbance at 570 nm at 2 s intervals during the time range of 0–10 min after initiation of the reaction. The experimental calibration matrix for the partial least squares (PLS-1) model was designed with 30 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 0.1-2 μg mL⁻¹ for each cation. The proposed method was successfully applied to the simultaneous determination of Cu(II), Ni(II) and Co(II) ions in water and in synthetic alloy samples.      

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 minoxidil and tretinoin by the H-point standard addition method and partial least squares

A simple, sensitive and selective spectrophotometric method for simultaneous determination of tretinoin and minoxidil using partial least square (PLS) calibration and H-point standard addition method (HPSAM) is described. The results of the H-point standard addition method show that minoxidil and tretinoin can be determined simultaneously with the concentration ratio of tretinoin to minoxidil varying from 2: 1 to 1: 33 in mixed samples. A partial least squares multivariate calibration method for the analysis of binary mixtures of tretinoin and minoxidil was also developed. The total relative standard error for applying the PLS method to eleven synthetic samples in the concentration range of 0–10 μg mL⁻¹ tretinoin and 0–32 μg mL⁻¹ minoxidil was 2.59 %. Both proposed methods (PLS and HPSAM) were also successfully applied in the determination of tretinoin and minoxidil in several synthetic pharmaceutical solutions.