Principal Component‐Wavelet Neural Network as a Multivariate Calibration Method for Simultaneous Determination of Iron,Nickel, and Cobalt

Abstract

Principal component‐artificial neural network (PC‐ANN) and principal component‐wavelet neural network (PC‐WNN) are applied for simultaneous determination of iron(II), nickel(II), and cobalt(II). A simple and selective spectrophotometric method for simultaneous determination of iron(II), nickel(II), and cobalt(II) based on formation of their complexes with 1‐(2‐pyridylazo)‐2‐naphtol (PAN) in micellar media is described. Although the complexes of Fe(II), Ni(II), and Co(II) with reagent show a spectral overlap, they have been simultaneously determined by PC‐ANN and PC‐WNN. The results obtained by the two methods were compared and it was shown that in PC‐WNN, the convergence speed was faster and the root mean square error of prediction set was also smaller than PC‐ANN. Interference effects of common anions and cations were studied and the proposed method was also applied satisfactorily to the determination of Fe(II), Ni(II) and Co(II) in synthetic samples.     

Resolution of Differential Pulse Voltammetric Peaks Using Genetic Algorithm Based Variable Selection‐Partial Least Squares and Principal Component‐Artificial Neural Networks

Differential Pulse Voltammetry has been used for the simultaneous determination of cysteine, tyrosine and trptophan on the unmodified glassy carbon electrode. In the analysis of these analytes in the same samples, the main difficulty is the high degree of overlapping of voltammograms. The relationships between the currents and the concentrations are complex and highly nonlinear. The predictive ability of principal component regression (PCR), partial least squares regression (PLS), genetic algorithm‐partial least squares regression (GA‐PLS) and principal component‐artificial neural networks (PC‐ANNs) were examined for simultaneous determination of three amino acids. For a regression model, everything that could not help in constructing the model may be considered as noise without further specification. PC‐ANN and GA‐PLS use significant data and show superiority over other applied multivariate methods. The proposed method was also applied satisfactorily to determination of analytes in some synthetic samples.     

Simultaneous Kinetic‐Spectrophotometric Determination of Hydrazine and its Derivatives by Partial Least Squares and Principle Component Regression Methods

Simultaneous kinetic‐spectrophotometric determination of a ternary mixture of hydrazine (HZ) and its derivatives by principal component regression (PCR) and partial least squares (PLS) calibration is described. The methods were based on the difference observed in the reduction rate of iron(III) with HZ, thiosemicarbazide (TSCZ) and phenylhydrazine (PHZ) in the presence of 2,2′‐bipyridine (Bpy). The colored complex of [Fe(Bpy)₃]²⁺ was formed in sodium dodecyl sulfate (SDS) as micellar media, and then monitored at 520 nm. The results showed that simultaneous determination of HZ, TSCZ and PHZ could be performed in their concentration ranges of 1.0–70.0, 0.2–6.0 and 0.1–10.0 μg mL^?1, respectively. The root mean squares errors of prediction (RMSEP) of HZ, TSCZ and PHZ were 0.719, 0.164 and 0.105 (for PLS) 0.788, 0.166 and 0.993 (for PCR), respectively. Both methods (PCR and PLS) were validated using a set of synthetic sample mixtures and then applied for simultaneous determination of HZ, TSCZ and PHZ in water samples.     

Artificial neural networks for simultaneous spectrophotometric differential kinetic determination of Co(II) and V(IV)

A method for simultaneous analysis of V(IV) and Co(II) has been developed by using artificial neural network (ANN). This method is based on the difference of the chemical reaction rate of V(IV) and Co(II) with Fe(III) in the presence of chromogenic reagent, 1,10-phenanthroline. The reduced product of the reaction, Fe(II), can form a colored complex with 1,10-phenanthroline and make a visible spectrophotometric signal for indirect monitoring of the V(IV) and Co(II) concentrations. Feed forward neural networks have been trained to quantify considered metal ions in mixtures under optimum conditions. The networks were shown to be capable of correlating reduced spectral kinetic data using principal component analysis (PCA) of mixtures with individual metal ion. In this way an ANN containing three layers of nodes was trained. Sigmoidal and linear transfer functions were used in the hidden and output layers, respectively, to facilitate nonlinear calibration. Both V(IV) and Co(II) were analyzed in the concentration range of 0.1-4.0 μg ml⁻¹. The proposed method was also applied satisfactorily to the determination of considered metal ions in several synthetic and water samples.     

Application of Multivariate Calibration Methods for the Simultaneous Multiwavelength Spectrophotometric Determination of Fe(II), Cu(II), Zn(II), and Mn(II) in Mixtures

Abstract

A sensitive method for the simultaneous spectrophotometric determination of Fe(II), Cu(II), Zn(II), and Mn(II) in mixtures has been developed with the aid of multivariate calibration methods, such as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS). The method is based on the spectral differences of the analytes in their complexation reaction with 4‐(2‐pyridylazo)‐resorcinol (PAR) and the use of full spectra with wavelengths in the range of 300–600 nm. It was found that both the spectral positive and negative bands obtained against the PAR blank, are proportional to the concentration for each metal complex. The obtained linear calibration concentration ranges are 0.025–0.6, 0.05–0.8, 0.025–0.8, and 0.05–0.8 µg ml^?1 for Fe(II), Cu(II), Zn(II), and Mn(II), respectively, and the LODs for the four metal ions were found to be approximately 1–3×10^?2 µg ml^?1. The proposed method was applied to a verification set of synthetic mixtures of these four metal ions, with models built in three different wavelength ranges, i.e., 300–450, 450–600, and 300–600 nm, corresponding to the positive, negative bands and their combinations, respectively. It was shown that the PLS model for the 300–600 nm range gave the best results (RPE_T=6.9% and average recovery ～100%; cf. PCR: RPE_T=9.5% and average Recovery ～110%). This method was also successfully applied for the determination of the four metal ions in pharmaceutical preparations, chicken feedstuff, and water samples.     

Simultaneous spectrophotometric determination of iron, nickel and cobalt in micellar media by using direct orthogonal signal correction-partial least squares method

A very simple and selective spectrophotometric method for simultaneous determination of iron(II), nickel(II) and cobalt(II) based on formation of their complexes with 1-(2-pyridylazo)-2-naphtol (PAN) in micellar media is described. Although the complexes of Fe(II), Ni(II) and Co(II) with reagent show a spectral overlap, they have been simultaneously determined by partial least squares (PLS) with and without preprocessing step using direct orthogonal signal correction (DOSC). The linear range was 0.30-4.50 μg ml⁻¹ for Co(II), 0.20-3.00 μg ml⁻¹ for Ni(II) and 0.30-5.00 μg ml⁻¹ for Fe(II). The results obtained by the PLS and DOSC-PLS were statistically compared. Interference effects of common anions and cations were studied and the proposed method was also applied satisfactorily to the determination of Fe(II), Ni(II) and Co(II) in synthetic samples.     

同时测定合成样中铜钴镍钒含量的分光光度法--主成分回归法和偏最小二乘法比较

研究了主成分回归和偏最小二乘方法在多组分分光光度法分析中的应用,以５－Ｂｒ－ＰＡＤＡＰ（２〔５－溴－２－吡啶）－偶氮〕５－二乙氨基苯酚）为显色剂,ＯＰ（聚乙二醇辛基苯基醚）作为增溶增稳剂,在ｐＨ＝３．６的条件下,用主成分回归及偏最小二乘分光光度法同时测定了合成样中的铜、钴、镍、钒４组分含量,测定相对误差在－６．００％～４．００％之间。实验证明,对于加和性不好的体系偏最小二乘分光光度法要优于主成分回     

Simultaneous kinetic-spectrophotometric determination of carbidopa, levodopa and methyldopa in the presence of citrate with the aid of multivariate calibration and artificial neural networks

The kinetic methodology based on the difference of reaction rates, is based on the reaction between a common oxidizing agents such as tris(1,10-phenanthroline) and iron(III) complex (ferriin, [Fe (phen)₃]³⁺) in the presence of citrate and spectrophotometrically, monitoring the changes of absorbance at the maximum wavelength of 511 nm. Experimental conditions such as pH, reagents and citrate concentrations were optimized, and the data obtained from the experiments were processed by several chemometric approaches, such as artificial neural network (ANN) and partial least squares (PLS). A set of synthetic mixtures of carbidopa (CD), levodopa (LD) and methyldopa (MD) was evaluated and the results obtained by the applications of these chemometric approaches were discussed and compared. It was found that the back propagation artificial neural network (BP-ANN) method afforded better precision relatively than those of radial basis function artificial neural networks (RBF-ANN) and PLS. The proposed method was also applied satisfactorily to the determination of carbidopa, levodopa and methyldopa in real samples.     

主成分回归一紫外光度法同时测定盐酸西替利嗪和苯甲酸钠

提出了一种用紫外光度法同时测定盐酸西替利嗪和苯甲酸钠的方法.在pH 4.56的B-R缓冲溶液中对盐酸西替利嗪和苯甲酸钠两组分混合溶液进行吸光度测定,所得的重叠光谱数据用主成分回归法(PCR)和偏最小二乘法(PLS)等化学计量学方法进行处理,结果表明主成分回归(PCR)的预报误差最小.对实际样品进行测定,回收率为88.8...     

主成分回归-络合滴定法测定混合金属离子

提出了用络合滴定法测定混合金属离子.以汞膜电极为指示电极,银-氯化银电极为参比电极,以标准EDTA溶液滴定混合金属离子溶液.采集-系列指定电位点处滴定剂的体积,并以主成分回归法处理滴定数据.利用本文方法对铜、锌、铅、钻混合溶液进行了测定,结果满意.     

Spectrophotometric Simultaneous Determination of Amaranth,Ponceau 4R,Allura Red and Red 2G by Partial Least Squares and Principal Component Regression Multivariate Calibration

ABSTRACT

The multivariate calibration methods, partial least square regression type 1 (PLS 1) and principal component regression (PCR), were proposed for the simultaneous spectrophotometry determination of Amaranth (E-123), Ponceau 4R (E-124), Allura red (E-129) and Red 2G (E-128) in their mixtures. The parameters of the chemometric procedures were optimized and the proposed method was validated with synthetic samples and applied to analyze these dyes in spiked samples of beverages with satisfactory results.     

Simultaneous determination of composition of human urinary calculi by use of artificial neural networks

A new chemometric method, which uses artificial neural networks (ANN), is presented for determination of the composition of urinary calculi. The selected constituents were whewellite, weddellite, and uric acid from which approximately 40% of the urinary calculi obtained from Macedonia patients are composed. The results for the synthetic mixtures were better then those obtained by partial least squares (PLS) regression or by the principal component regression (PCR), because neural networks have better prediction capacity. The generalization abilities of the optimized neural networks were checked using the standard addition method on carefully selected real natural samples.     

FT‐IR Spectrophotometric Analysis of Chromium (Tris) Picolinate and its Pharmaceutical Formulations

Abstract

A Fourier transform infrared (FT‐IR) spectrometric method was developed for the rapid, direct measurement of chromium (tris) picolinate [Cr(pic)₃] in different pharmaceutical products. Conventional KBr potassium bromine spectra were compared for best determination of active substance in drug preparations. Lambert‐Beer's law and two chemometric approaches, partial least squares (PLS) and principal component regression (PCR+) methods, were used in data processing.     

Differential Kinetic Spectrophotometric Determination of Methamidophos and Fenitrothion in Water and Food Samples by Use of Chemometrics

A spectrophotometric method for simultaneous analysis of methamidophos and fenitrothion was proposed by application of chemometrics to the spectral kinetic data, which was based upon the difference in the inhibitory effect of the two pesticides on acetylcholinesterase (AChE) and the use of 5,5′‐dithiobis(2‐nitrobenzoic acid) (DTNB) as a chromogenic reagent for the thiocholine iodide (TChI) released from the acetylthiocholine iodide (ATChI) substrate. The absorbance of the chromogenic product was measured at 412 nm. The different experimental conditions affecting the development and stability of the chromogenic product were carefully studied and optimized. Linear calibration graphs were obtained in the concentration range of 0.5–7.5 ng·mL^?1 and 5–75 ng·mL^?1 for methamidophos and fenitrothion, respectively. Synthetic mixtures of the two pesticides were analysed, and the data obtained processed by chemometrics, such as partial least square (PLS), principal component regression (PCR), back propagation‐artificial neural network (BP‐ANN), radial basis function‐artificial neural network (RBF‐ANN) and principal component‐radial basis function‐artificial neural network (PC‐RBF‐ANN). The results show that the RBF‐ANN gives the lowest prediction errors of the five chemometric methods. Following the validation of the proposed method, it was applied to the determination of the pesticides in several commercial fruit and vegetable samples; and the standard addition method yielded satisfactory recoveries.     

Determination of rice type by 1H NMR spectroscopy in combination with different chemometric tools

A 400‐MHz ¹H nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis were used in the context of food surveillance to discriminate 46 authentic rice samples according to type. It was found that the optimal sample preparation consists of preparing aqueous rice extracts at pH 1.9. For the first time, the chemometric method independent component analysis (ICA) was applied to differentiate clusters of rice from the same type (Basmati, non‐Basmati long‐grain rice, and round‐grain rice) and, to a certain extent, their geographical origin. ICA was found to be superior to classical principal component analysis (PCA) regarding the verification of rice authenticity. The chemical shifts of the principal saccharides and acetic acid were found to be mostly responsible for the observed clustering. Among classification methods (linear discriminant analysis, factorial discriminant analysis, partial least squares discriminant analysis (PLS‐DA), soft independent modeling of class analogy, and ICA), PLS‐DA and ICA gave the best values of specificity (0.96 for both methods) and sensitivity (0.94 for PLS‐DA and 1.0 for ICA). Hence, NMR spectroscopy combined with chemometrics could be used as a screening method in the official control of rice samples. Copyright © 2013 John Wiley & Sons, Ltd.     

化学计量学-分光光度法同时测定饲料中的诺氟沙星、氧氟沙星和洛美沙星

在pH1.81的Britton-Robinson(B-R)缓冲溶液中对诺氟沙星、氧氟沙星和洛美沙星三组分混合溶液进行光度测定,所得的重叠光谱数据用经典最小二乘(CLS),主成分回归(PCR),偏最小二乘(PLS)和径向基人工神经网络(RBF-ANN)方法处理和分析,结果表明RBF-ANN对合成样中三种药物浓度的预报结果...     

Simultaneous kinetic determination of Fe(II) and Fe(III) based on their reactions with NQT4S in micellar media by using PLS and PCR methods

Simultaneous determination of Fe(II) and Fe(III) was studied using partial least squares regression (PLS) and principal component regression (PCR) methods. The models were based on the difference observed in the rates of the complex formation of iron in its two oxidation states with 1,2-naphthaquinone-2-thiosemicarbazone-4-sulphonic acid (NQT4S) at pH 4.0 in cetyltrimethylammoniumbromide (CTAB) as micellar media. The results showed that simultaneous determination of Fe(II) and Fe(III) could be performed in their concentration ranges of 0.10-2.10 and 0.25-2.25 μg/ml, respectively. The models used can proceed the data with low percent relative error of prediction (i.e. <5.5%). The procedure was successfully applied for the simultaneous determination of Fe(II) and Fe(III) in some environmental samples. The method would allow the transformation of the two oxidation states of iron to be monitored overtime in a water sample.     

Application of Multivariate Calibration Techniques to Simultaneous Spectrophotometric Determination of Copper and Iron Using 1‐(2‐Pyridylazo)‐2‐naphthol in AOT Micellar Solution

Multivariate calibration models (PCR and PLS) were developed for simultaneous determination of Fe(III) and Cu(II) with 1‐(2‐pyridylazo)‐2‐naphthol and AOT as chromogenic reagent and micellizing agent, respectively. In the presence of AOT the spectrum of Fe(III)‐PAN complex was shifted to higher wavelength and the overlapping with Cu‐PAN spectrum decreased. It seems that this anionic surfactant enters the structure of the Fe‐PAN complex to cause a shift in the absorption spectrum of it. The parameters controlling behavior of the systems were investigated and optimum conditions were selected. Sixteen ternary mixtures were selected as the calibration set. To select the number of factors in PCR and PLS algorithms, a cross validation method, leaving out one sample at a time, was employed. The calibration models were validated with 8 synthetic mixtures containing the metal ions in different proportions that were randomly designed. The best calibration model was obtained by using PLS regression. The method was successfully applied to simultaneous determination of copper and iron in biological samples.     

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。