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.     

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。     

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 Spectrophotometric Determination of Iron and Cobalt in Micellar Medium by Using a Principal Component Artificial Neural Network and Multivariate Calibration

A simple and reliable method for simultaneous spectrophotometric determination of iron(II) and cobalt(II) has been established. The method is based on complex formation with 1‐(2‐pyridylazo)‐2‐naphtol (PAN) in a micellar medium. Despite a spectral overlap, Fe²⁺ and Co²⁺ have been simultaneously determined with chemometric approaches involving principal component artificial neural network (PC‐ANN), principal component regression (PCR) and partial least squares (PLS). Various synthetic mixtures of iron and cobalt were assessed and the results obtained by the applications of these chemometric approaches were evaluated and compared. It was found that the PC‐ANN method afforded relatively better precision than that of PCR or PLS. The proposed method permits detection limits of 0.05 and 0.07 ng mL^?1 for Co and Fe, respectively. The influences of pH, ligand amount, solvent percentage and time on the absorbance were also investigated. The proposed method was also applied satisfactorily for the determination of Fe(II) and Co(II) in real and 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.     

Comparison of Different PLS Algorithms for Simultaneous Determination of Cd(II), Cu(II), Pb(II), and Zn(II) by Anodic Stripping Voltammetry at Bismuth Film Electrode

In this work we evaluated the use of different variable selection techniques combined with partial least‐squares regression (PLS) – genetic algorithm PLS (GA‐PLS), interval PLS (iPLS), and synergy interval PLS (siPLS) – in the simultaneous determination of Cd(II), Cu(II), Pb(II) and Zn(II) by anodic stripping voltammetry at a bismuth film. Generally, variable selection provided an improvement in prediction results when compared to full‐voltammogram PLS. The use of interval selection based algorithms have shown to be most adequate than the selection of discrete variables by GA. Excellent analytical performances were obtained despite the inherent complexity of the simultaneous determination.     

Multicomponent kinetic spectrophotometric determination of pefloxacin and norfloxacin in pharmaceutical preparations and human plasma samples with the aid of chemometrics

A spectrophotometric method for the simultaneous determination of the important pharmaceuticals, pefloxacin and its structurally similar metabolite, norfloxacin, is described for the first time. The analysis is based on the monitoring of a kinetic spectrophotometric reaction of the two analytes with potassium permanganate as the oxidant. The measurement of the reaction process followed the absorbance decrease of potassium permanganate at 526nm, and the accompanying increase of the product, potassium manganate, at 608nm. It was essential to use multivariate calibrations to overcome severe spectral overlaps and similarities in reaction kinetics. Calibration curves for the individual analytes showed linear relationships over the concentration ranges of 1.0-11.5mgL(-1) at 526 and 608nm for pefloxacin, and 0.15-1.8mgL(-1) at 526 and 608nm for norfloxacin. Various multivariate calibration models were applied, at the two analytical wavelengths, for the simultaneous prediction of the two analytes including classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), radial basis function-artificial neural network (RBF-ANN) and principal component-radial basis function-artificial neural network (PC-RBF-ANN). PLS and PC-RBF-ANN calibrations with the data collected at 526nm, were the preferred methods-%RPE(T) approximately 5, and LODs for pefloxacin and norfloxacin of 0.36 and 0.06mgL(-1), respectively. Then, the proposed method was applied successfully for the simultaneous determination of pefloxacin and norfloxacin present in pharmaceutical and human plasma samples. The results compared well with those from the alternative analysis by HPLC.     

Simultaneous Determination of Quercetin and Luteolin in Dried Flowers by Multivariate HPLC-ECD Calibration

Two calibration models, partial least squares (PLS) and principal component regression (PCR), were applied to the simultaneous determination of quercetin and luteolin by high performance liquid chromatography (HPLC) with electrochemical detection (ECD). The proposed methods were successfully applied to the analysis of dried flower samples. It was found that the relative standard errors of prediction (RSEP) for the validation set of PLS of quercetin and luteolin was 1.31 and 2.23%, and the RSEP of PCR was found to be 3.56 and 4.32%, respectively. Several dried flower samples were analysed and the recoveries were in the range of 95.9–103.3%.     

Regression with multiple regressor arrays

Extension of standard regression to the case of multiple regressor arrays is given via the Kronecker product. The method is illustrated using ordinary least squares regression (OLS) as well as the latent variable (LV) methods principal component regression (PCR) and partial least squares regression (PLS). Denoting the method applied to PLS as mrPLS, the latter was shown to explain as much or more variance for the first LV relative to the comparable L‐partial least squares regression (L‐PLS) model. The same relationship holds when mrPLS is compared to PLS or n‐way partial least squares (N‐PLS) and the response array is 2‐way or 3‐way, respectively, where the regressor array corresponding to the first mode of the response array is 2‐way and the second mode regressor array is an identity matrix. In a comparison with N‐PLS using fragrance data, mrPLS proved superior in a validation sense when model selection was used. Though the focus is on 2‐way regressor arrays, the method can be applied to n‐way regressors via N‐PLS. Copyright © 2007 John Wiley & Sons, Ltd.     

Multivariate calibration of spectral data using dual-domain regression analysis

To date, few efforts have been made to take simultaneous advantage of the local nature of spectral data in both the time and frequency domains in a single regression model. We describe here the use of a novel chemometrics algorithm using the wavelet transform. We call the algorithm dual-domain regression, as the regression step defines a weighted model in the time-domain based on the contributions of parallel, frequency-domain models made from wavelet coefficients reflecting different scales. In principle, any regression method can be used, and implementation of the algorithm using partial least squares regression and principal component regression are reported here. The performance of the models produced from the algorithm is generally superior to that of regular partial least squares (PLS) or principal component regression (PCR) models applied to data restricted to a single domain. Dual-domain PLS and PCR algorithms are applied to near infrared (NIR) spectral datasets of Cargill corn samples and sets of spectra collected on batch chemical reactions run in different reactors to illustrate the improved robustness of the modeling.     

Multicomponent Determination of Organophosphorus Pesticides in Grain Samples by Linear Sweep Stripping Voltammetry and Multivariate Calibration

Abstract

Organophosphorus pesticides, such as parathion methyl (PTM), fenitrothion (FT), parathion (PT), and isocarbophos (ICP), have sensitive but overlapped voltammetric peaks with peak potentials ?309, ?364, ?317, and ?480 mV, respectively, in Britton‐Robinson buffer of pH 4.8 by application of linear sweep stripping voltammetry (LSSV). In this work, two multivariate calibration methods, partial least squares (both PLS‐1 and PLS‐2), and principal component regression (PCR), were applied to quantitatively resolve the overlapping voltammogram of the mixtures of these four pesticides. The prediction results obtained from a set of independent test samples showed that PLS‐1 method performed better prediction ability than PLS‐2 and PCR methods. The proposed method was successfully applied to the determination of these four pesticides in grain samples after a pre‐extraction step with a solvent of acetone.     

Simultaneous Kinetic‐Potentiometric Determination of Hydrazine and Thiosemicarbazide by Partial Least Squares and Principle Component Regression Methods

Simultaneous determination of hydrazine (HZ) and thiosemicarbazide (TSC) by partial least squares (PLS) and principle component regression (PCR) was carried out based on kinetic data of novel potentiometry. The rate of chloride ion production in reaction of HZ and TSC with N‐chlorosuccinimide (NCS) was monitored by a chloride ion‐selective electrode. The experimental dada shows not only the good ability of ion‐selective electrodes (ISEs) as detectors for the direct determination of chloride ions but also for simultaneous kinetic‐potentiometric analysis using chemometrics methods. The methods are based on the difference observed in the production rate of chloride ions. The results show that simultaneous determination of HZ and TSC can be performed in their concentration ranges of 0.7‐20.0 and 0.5‐20.0 μg mL^?1, respectively. The total relative standard error for applying PLS and PCR methods to 9 synthetic samples in the concentration ranges of 0.8‐10 μg mL^?1 of TSC and 1.0‐12.0 μg mL^?1 of HZ was 4.62 and 4.98, respectively. The effects of certain foreign ions upon the reaction rate were determined for the assessment of the selectivity of the method. Both methods (PLS and PCR) were validated using a set of synthetic sample mixtures and then applied for simultaneous determination of HZ and TSC in water samples.     

Simultaneous spectrophotometric determination of phenanthridine, phenanthridinone and phenanthridine N-oxide using multivariate calibration methods

The multivariate calibration methods, partial least squares (PLS) and principle component regression (PCR) have been used to determine phenanthridine, phenanthridinone and phenanthridine N-oxide in spiked human plasma samples. Resolution of binary and ternary mixtures of analytes with minimum sample pre-treatment and without analyte separation has been successfully achieved analyzing the UV spectral data. The net analyte signal (NAS) concept was also used to calculate multivariate analytical figures of merit such as limit of detection, selectivity and sensitivity. The simultaneous determination of three analytes was possible by PLS and PCR processing of sample absorbance in the 210–355 nm region. Good recoveries were obtained for both synthetic mixtures and spiked human plasma samples.     

Near Infrared Spectral Similarity Combined with Variable Selection Method in the Quality Control of Flos Lonicerae: A Preliminary Study

This paper indicates the possibility to use near infrared (NIR) spectral similarity as a rapid method to estimate the quality of Flos Lonicerae. Variable selection together with modelling techniques is utilized to select representative variables that are used to calculate the similarity. NIR is used to build calibration models to predict the bacteriostatic activity of Flos Lonicerae. For the determination of the bacteriostatic activity, the in vitro experiment is used. Models are built for the Gram‐positive bacteria and also for the Gram‐negative bacteria. A genetic algorithm combined with partial least squares regression (GA‐PLS) is used to perform the calibration. The results of GA‐PLS models are compared to interval partial least squares (iPLS) models, full‐spectrum PLS and full‐spectrum principal component regression (PCR) models. Then, the variables in the two GA‐PLS models are combined and then used to calculate the NIR spectral similarity of samples. The similarity based on the characteristic variables and full spectrum is used for evaluating the fingerprints of Flos Lonicerae, respectively. The results show that the combination of variable selection method, modelling techniques and similarity analysis might be a powerful tool for quality control of traditional Chinese medicine (TCM).     

Simultaneous Voltammetric Determination of Three Herbicides in Food and Water Samples with the Aid of Chemometrics

Differential pulse stripping voltammetry method(DPSV) was applied to the determination of three herbicides,ametryn,cyanatryn,and dimethametryn.It was found that their voltammograms overlapped strongly,and it is difficult to determine these compounds individually from their mixtures.With the aid of chemometrics,classical least squares(CLS),principal component regression(PCR) and partial least squares(PLS),voltammogram resolution and quantitative analysis of the synthetic mixtures of the three compounds were successfully performed.The proposed method was also applied to the analysis of some real samples with satisfactory results.     

微分脉冲溶出伏安法结合化学计量学测定醚类除草剂

在pH=6.82的Britton-Robinson缓冲溶液中,采用循环伏安法和微分脉冲溶出伏安法对醚类除草剂甲羧除草醚(Bifenox)和三氟羧草醚(Acifluofen)的伏安行为进行了研究,发现吸附时间为50 s时此电化学体系达到平衡,而且微分脉冲溶出伏安法能给出较高的灵敏度,甲羧除草醚和三氟羧草醚分别在-685 mV和-700 mV处具有良好还原峰,但由于峰电位接近而谱峰重叠,很难分别测定.本文采用化学计量学方法来解析重叠峰并完成这两种除草剂的定量分析.甲羧除草醚和三氟羧草醚的测定线性范围分别为0.02～0.18 μg·5mL~(-1)和0.02～0.16 μg·5mL~(-1),检出限分别为0.0073 μg·5mL~(-1)和0.0068 μg·5mL~(-1).利用该方法对水样中的甲羧除草醚和三氟羧草醚进行直接测定,获得了较好的定量分析结果.     

Simultaneous kinetic spectrophotometric determination of cephalexin and trimethoprim in pharmaceutical preparation and human urine with the aid of chemometrics

A procedure for the simultaneous kinetic spectrophotometric determination of cephalexin and trimethoprim was described. It was based on the different reaction rate of oxidation of these compounds with yellow ammonium cerous （Ⅳ） sulfate in acidic medium and colorless cerous （Ⅲ） sulfate was produced. The overlapped kinetic data was quantitatively resolved by the use of chemometric methods, partial least squares （PLS）, principal component regression （PCR） and radial basis function-artificial neural network （RBF-ANN）. The proposed method was also applied to the simultaneous determination of cephalexin and trimethoprim in pharmaceutical preparation and human urine with satisfied results, which compared well with those obtained by HPLC.     

Comparison of Artificial Neural Networks with Partial Least Squares Regression for Simultaneous Determinations by ICP-AES

Simultaneous determination of several elements （U, Ta, Mn, Zr and W） with inductively coupled plasma atomic emission spectrometry （ICP-AES） in the presence of spectral interference was performed using chemometrics methods. True comparison between artificial neural network （ANN） and partial least squares regression （PLS） for simultaneous determination in different degrees of overlap was investigated. The emission spectra were recorded at uranium analytical line （263.553 nm） with a 0.06 nm spectral window by ICP-AES. Principal component analysis was applied to data and scores on 5 dominant principal components were subjected to ANN. A 5-5-5 （input, hidden and output neurons） network was used with linear transfer function after both hidden and output layers. The PI,S model was trained with five latent variables and 20 samples in calibration set. The relative errors of predictions （REP） in test set were 3.75% and 3.56% for ANN and PLS respectively.     

Simultaneous determination of three fluoroquinolones by linear sweep stripping voltammetry with the aid of chemometrics

A linear sweep stripping voltammetric (LSSV) method has been researched and developed for simultaneous quantitative determination of mixtures of three antibiotic drugs, ofloxacin, norfloxacin and ciprofloxacin. It relies on reductive reaction of the antibiotics at a mercury electrode in a Britton-Robinson buffer (pH 3.78). The voltammograms of these three compounds overlap strongly, and show non-linear character. Thus, it is difficult to analyse the compounds individually in their mixtures. In this work, chemometrics methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN) were applied for the simultaneous determination of these compounds. The prediction performance of the calibration models constructed on the basis of these methods was compared. It was shown that satisfactory quantitative results were obtained with the use of the RBF-ANN calibration model relative prediction error (RPE_T) of 8.1% and an average recovery of 101%. This method is able to accommodate non-linear data quite well. The proposed analytical method based on LSSV was applied for the analysis of ofloxacin, norfloxacin and ciprofloxacin antibiotics in bird feedstuffs and their spiked samples, as well as in eye drops with satisfactory results.     

偏最小二乘法—流动注射pH梯度技术用于同时测定铜和钴

以PAR作显色剂,用流动注射pH梯度技术测定多个不同pH下的吸光度,以偏最小二乘法建立校正模型并预测,对Cu~(2+)、Co~(2+)二元素进行了同时测定,其计算结果优于主成分回归及多元线性回归法。