Partial least-squares with residual bilinearization for the spectrofluorimetric determination of pesticides. A solution of the problems of inner-filter effects and matrix interferents

This paper demonstrates for the first time the power of a chemometric second-order algorithm for predicting, in a simple way and using spectrofluorimetric data, the concentration of analytes in the presence of both the inner-filter effect and unsuspected species. The simultaneous determination of the systemic fungicides carbendazim and thiabendazole was achieved and employed for the discussion of the scopes of the applied second-order chemometric tools: parallel factor analysis (PARAFAC) and partial least-squares with residual bilinearization (PLS/RBL). The chemometric study was performed using fluorescence excitation-emission matrices obtained after the extraction of the analytes over a C18-membrane surface. The ability of PLS/RBL to recognize and overcome the significant changes produced by thiabendazole in both the excitation and emission spectra of carbendazim is demonstrated. The high performance of the selected PLS/RBL method was established with the determination of both pesticides in artificial and real samples.     

Application of MATLAB package for the automation of the chemometric processing of spectrometric signals in the analysis of complex mixtures

We describe three types of automatic software for the chemometric processing of spectrometric data. The software was developed in the MATLAB working environment and includes data import, mathematical preprocessing, chemometric analysis, and generation of a report file. The software is designed to solve problems regarding identification of some components of multicomponent mixtures, determination of compounds with overlapping signals, and differentiation of samples by their spectral responses. To test the software, we present examples of spectrometric analyses of coffee, fruit juices, and alcoholic beverages using chemometric methods of independent component analysis (ICA) and partial least squares–discriminant analysis (PLS–DA). In particular, we simulated electronic absorption spectra for the identification of three artificial colors (E110, E102, and E122) in alcoholic beverages, NMR spectra for the simultaneous determination of five components (acetic acid, γ-aminobutyric acid, arginine, acetaldehyde, and proline) in orange juice without using reference standards, and NMR spectra of coffee samples to determine its varietal authenticity (Arabica or Robusta). The duration of automatic chemometric processing did not exceed 1 min per sample. The developed software can be optimized for other matrices and/or brands of spectrometers.     

Chemometric determination of naproxen sodium and pseudoephedrine hydrochloride in tablets by HPLC

A new chemometric determination by high-performance liquid chromatography (HPLC) with photodiode array (PDA) detection was implemented for the simultaneous determination of naproxen sodium and pseudoephedrine hydrochloride in tablets. Three chemometric calibration techniques, classical least squares (CLS), principle component regression (PCR) and partial least squares (PLS) were applied to the peak area at multiwavelength PDA detector responses. The combinations of HPLC with chemometric calibration techniques were called HPLC-CLS, HPLC-PCR and HPLC-PLS. For comparison purposes the HPLC method called the classic HPLC method was used to confirm the results obtained from combined HPLC-chemometric calibration techniques. A good chromatographic separation between two drugs with losartan potassium as an internal standard was achieved using a Waters Symmetry C18 Column 5 microm 4.6+/-250 mm and a mobile phase containing 0.2 M acetate buffer and acetonitrile (v/v, 40:60). The multiwavelength PDA detection was measured at five different wavelengths. The chromatograms were recorded as a training set in the mobile phase. Three HPLC-chemometric calibrations and the classic-HPLC method were used to test the synthetic mixtures of naproxen sodium and pseudoephedrine hydrochloride in the presence of the internal standard. The HPLC-chemometric approaches were applied to real samples containing drugs of interest. The experimental results obtained from HPLC-chemometric calibrations were compared with those obtained by a classic HPLC method.     

Measurement of the cumulative particle size distribution of microcrystalline cellulose using near infrared reflectance spectroscopy

The cumulative particle size distribution of microcrystalline cellulose, a widely used pharmaceutical excipient, was determined using near infrared (NIR) reflectance spectroscopy. Forward angle laser light scattering measurements were used to provide reference particle size values corresponding to different quantiles and then used to calibrate the NIR data. Two different chemometric methods, three wavelength multiple linear regression and principal components regression (three components), were compared. For each method, calibration equations were produced at each of eleven quantiles (5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 95%). NIR predicted cumulative frequency particle-size distributions were calculated for each of the calibration samples (n = 34) and for an independent test set (n = 23). The NIR procedure was able to predict those obtained via forward angle laser light scattering.     

Three-way Resolution of the Overlapping Ultrahigh-performance Liquid Spectrochromatograms for the Analysis of a Quaternary Mixture Using Parallel Factor Analysis

This paper presents a new application of three-way parallel factor analysis (3W-PARAFAC) model to the coeluting spectrochromatograms for the quantitative resolution of a quaternary mixture system consisting of paracetamol, propyphenazone, and caffeine with aspirin as an internal standard. Spectrochromatograms of calibration standards, validation sets, and unknown samples were recorded as a function of retention time and wavelength in the range of 0.0–2.5?min and 200–400?nm, respectively, using ultra-performance liquid chromatography with photodiode array detection (UPLC-PDA). Three-way UPLC-PDA data array X (retention time?×?wavelength?×?sample) was obtained from the data matrices of the spectrochromatograms. 3W-PARAFAC decomposition of three-way UPLC-PDA data array provided three loading matrices corresponding to chromatographic mode, spectral mode, and relative concentration mode. Quantitative estimation of paracetamol, propyphenazone, and caffeine in analyzed samples was accomplished using the relative concentration mode obtained by the deconvolution of the UPLC-PDA data set. The validity and ability of 3W-PARAFAC model were checked by analyzing independent test samples. It was observed from analyses that 3W-PARAFAC method has potential to uniquely resolve strongly overlapping peaks of analyzed compounds in a spectrochromatogram, which was obtained under experimental conditions consisting of the lower flow rate, short run time, and simple mobile phase composition. The proposed three-way chemometric approach was successfully applied to the simultaneous quantification of paracetamol, propyphenazone, and caffeine in tablets. Experiments showed that the determination results were in good agreement with label amount in commercial pharmaceutical preparation.     

Methodology of chemometric modeling of spectrometric signals in the analysis of complex samples

A generalized algorithm of the multivariate simulation of spectrometric data is considered for solving typical analytical problems, like the determination of the concentration of a particular analyte and the assignment of a sample to one of predefined classes. In particular, we considered preliminary data processing, exploratory analysis, optimization of a chemometric model, calculation of performance characteristics, transfer of the model to other spectrometers, and automation of chemometric processing for the routine analysis of samples. To illustrate the potential of the method, we selected a system of bovine and porcine heparin, mixtures of soy and sunflower lecithin, and a set of red and white wine samples as test samples. Partial least squares and discriminant analysis were used as chemometric methods. We used proton nuclear magnetic resonance (1H NMR) to record signals. Using the MATLAB environment, chemometric programs were developed for automated data processing in the context of problems under consideration and for the transfer of multivariate models to other spectrometers. Based on the results obtained, a methodology is proposed for the multivariate analysis of spectrometric data, which can be used in the analysis of various types of matrices and spectrometric signals.     

Direct coupling of a gas-liquid separator to an ion mobility spectrometer for the classification of different white wines using chemometrics tools

The potential of a vanguard technique as is the ion mobility spectrometry with ultraviolet ionization (UV-IMS) coupled to a continuous flow system (CFS) have been demonstrated in this work using a gas phase separator (GPS). This vanguard system (CFS-GPS-UV-IMS) has been used for the analysis of different types of white wines to obtain a characteristic profile for each type of wine and their posterior classification using different chemometric tools. Precision of the method was 3.1% expressed as relative standard deviation. A deep chemometric study was carried out for the classification of the four types of wines selected. The best classification performance was obtained by first reducing the data dimensionality by principal component analysis (PCA) followed by linear discriminant analysis (LDA) and finally using a k-nearest neighbour (kNN) classifier. The classification rate in an independent validation set was 92.0% classification rate value with confidence interval [89.0%, 95.0%] at 95% confidence level.The same white wines analyzed using CFS-GPS-UV-IMS were analyzed using gas chromatography with a flame detector (GC-FID) as conventional technique. The chromatographic method used for the determination of superior alcohols in wine samples shown in the Regulation CEE 1238/1992 was selected to carry out the analysis of the same samples set and later the classification using appropriate chemometrics tools. In this case, strategies PCA-LDA and kNN classifier were also used for the correct classification of the wine samples. This combination showed similar results to the ones obtained with the proposed method.     

Determination of phenol, resorcinol and hydroquinone in air samples by synchronous fluorescence using partial least-squares (PLS)

The determination of phenolic compounds is of great importance owing to their high toxicity. Some of them are present in tobacco smoke and it is important for their monitoring in air of closed room. A simple, rapid and sensitive method was developed for simultaneous determination of hydroquinone, resorcinol and phenol in this kind of samples. Synchronous fluorescence technique was used and the data were processed by using the partial least-squares (PLS) chemometric algorithm. The concentrations for experimental calibration matrix were varied between 0.02 and 0.2 mg L⁻¹ for hydroquinone, between 0.05 and 0.6 mg L⁻¹ for resorcinol and between 0.05 and 0.4 mg L⁻¹ for phenol in accordance with the national legislation. The cross-validation method was used to select the number of factors. To check the accuracy of the proposed method a recovery study on real samples was carried out.     

Spectrophotometric multicomponent determination of sunset yellow, tartrazine and allura red in soft drink powder by double divisor-ratio spectra derivative, inverse least-squares and principal component regression methods

Double divisor-ratio spectra derivative (graphical method), classical least-squares and principal component regression (two numerical methods) methods were developed for the spectrophotometric multicomponent analysis of soft drink powders and synthetic mixtures containing three colorants without any chemical separation. The graphical method is based on the use of derivative signals of the ratio spectra using double divisor. In this method, the linear determination ranges were 2-8 mug ml(-1) sunset yellow, 4-18 mug ml(-1) tartrazine and 2-8 mug ml(-1) allura red in 0.1 M HCl. In the numerical methods, a training set was randomly prepared by using 18 samples containing between 0 and 8 mug ml(-1) of sunset yellow, 0-18 mug ml(-1) of tartrazine and 0-8 mug ml(-1) of allura red. The chemometric calibrations were calculated by using the prepared training set and its absorbances at seven points (from 375.0 to 550.0 nm) in the spectral region 325-584 nm. The proposed methods were validated by using synthetic ternary mixtures and applied to the simultaneous determination of three colorants in soft drink powders. The obtained results were statistically compared with each other.     

Strategies for solving matrix effects in the analysis of sulfathiazole in honey samples using three-way photochemically induced fluorescence data

A widely employed compound for honey treatment, sulfathiazole (ST), was determined in commercial honey samples, employing a combination of photochemically induced fluorescence excitation-emission matrices (EEMs) and chemometric processing of the recorded second-order data. Parallel Factor Analysis (PARAFAC) and Self-Weighted Alternating Trilinear Decomposition (SWATLD) methods were used for calibration. An appropriately designed calibration with a set of standards composed of 18 samples, coupled to the use of the second-order advantage offered by the applied chemometric techniques, allowed quantitation of sulfathiazole in spiked commercial honey samples. No previous separation or sample pretreatment steps were required. The results were compared with other calibration methods such as N-PLS and PLS-1 that produced good results on synthetic samples but not on the investigated commercial honey samples.     

Second-order advantage with excitation–emission photoinduced fluorimetry for the determination of the antiepileptic carbamazepine in environmental waters

A photochemically induced fluorescence system combined with second-order chemometric analysis for the determination of the anticonvulsant carbamazepine (CBZ) is presented. CBZ is a widely used drug for the treatment of epilepsy and is included in the group of emerging contaminant present in the aquatic environment. CBZ is not fluorescent in solution but can be converted into a fluorescent compound through a photochemical reaction in a strong acid medium. The determination is carried out by measuring excitation–emission photoinduced fluorescence matrices of the products formed upon ultraviolet light irradiation in a laboratory-constructed reactor constituted by two simple 4 W germicidal tubes. Working conditions related to both the reaction medium and the photoreactor geometry are optimized by an experimental design. The developed approach enabled the determination of CBZ at trace levels without the necessity of applying separation steps, and in the presence of uncalibrated interferences which also display photoinduced fluorescence and may be potentially present in the investigated samples. Different second-order algorithms were tested and successful resolution was achieved using multivariate curve resolution-alternating least-squares (MCR-ALS). The study is employed for the discussion of the scopes and yields of each of the applied second-order chemometric tools. The quality of the proposed method is probed through the determination of the studied emerging pollutant in both environmental and drinking water samples. After a pre-concentration step on a C18 membrane using 50.0 mL of real water samples, a prediction relative error of 2% and limits of detection and quantification of 0.2 and 0.6 ng mL⁻¹ were respectively obtained.     

Interference-free determination of Sudan dyes in chilli foods using second-order calibration algorithms coupled with HPLC-DAD

This paper presents a new method for the determination of Sudan dyes contained in hot chilli samples. The method employs second-order calibration algorithms to handle the recorded data. The second-order calibration algorithms are based on the popular parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD) and self-weighted alternating trilinear decomposition (SWATLD), respectively. These chemometric methodologies have the second-order advantage, which is the ability to get accurate concentration estimates of interested analytes even in the presence of uncalibrated interfering components. The results on a set of spiked chilli test shows that low contents of Sudan I and Sudan II in complex chilli mixtures can be accurately determined using the new method. The sample preparation was based on solvent extraction, and internal standard was not required. Quantification was carried out with simple mobile phase.     

Micro-Raman spectroscopy of natural and synthetic indigo samples

In this work indigo samples from three different sources are studied by using Raman spectroscopy: the synthetic pigment and pigments from the woad (Isatis tinctoria) and the indigo plant (Indigofera tinctoria). 21 samples were obtained from 8 suppliers; for each sample 5 Raman spectra were recorded and used for further chemometrical analysis. Principal components analysis (PCA) was performed as data reduction method before applying hierarchical cluster analysis. Linear discriminant analysis (LDA) was implemented as a non-hierarchical supervised pattern recognition method to build a classification model. In order to avoid broad-shaped interferences from the fluorescence background, the influence of 1st and 2nd derivatives on the classification was studied by using cross-validation. Although chemically identical, it is shown that Raman spectroscopy in combination with suitable chemometric methods has the potential to discriminate between synthetic and natural indigo samples.     

Direct orthogonal signal correction as data pretreatment in the classification of clinical lots of creams from near infrared spectroscopy data

Direct orthogonal signal correction (DOSC) is applied to correct for major variance sources such as temperature effects, time influences and instrumental differences in near infrared (NIR) data. The samples analysed are creams containing different concentrations of an active drug. The final aim is to classify the samples according to their concentration of active compound. Having performed DOSC on the data, it is not necessary anymore to apply sophisticated chemometric techniques to correct for temperature or time effects and to attribute the samples to their respective concentration classes. Moreover, the application of DOSC on the NIR spectra recorded on two different instruments shows that this method can be considered as a valuable alternative for the standardisation in classification applications. Since the applied algorithm tends to overfit, in a second part of this paper, a comparison is made with an algorithm designed by Westerhuis, which should overcome this problem. Although the calibration set results show that the overfitting has been partially corrected for by the latter algorithm, the test set results did not improve significantly.     

Chemometric characterization of 5th century A.D. amphora-producing centres in the Mediterranean

The application of two chemometric techniques for data structure analysis (Ward's hierarchical clustering and Principal Components Analysis) has permitted the characterization of 5th century A.D. amphora-producing centres in the Mediterranean on the basis of X-ray fluorescence data on 66 amphora fragments. The chemometric study complements and reinforces the conclusions drawn from typological and archaeological analysis. Nineteen samples of unknown origin have been classified (using the SIMCA method) into the eight proposed classes of amphora production.     

Evaluation of feed-forward back propagation and radial basis function neural networks in simultaneous kinetic spectrophotometric determination of nitroaniline isomers

Mixtures of 2-, 3-, and 4-nitoroanilines, are simultaneously analyzed with spectrophotometry, based on their different kinetic properties. These nitroanilines react differentially with 1,2-naphtoquinone-4-sulphonate (NQS) at pH 7 in micellar medium to produce colored product. The differential kinetic spectra were monitored and recorded at 500 nm, and the data obtained from the experiments were processed by chemometric approaches, such as back-propagation neural networks (BPNNs), radial basis function neural networks (RBFNNs), and partial least squares (PLS). Experimental conditions were optimized and training the network was performed using principal components (PCs) of the original data. A set of synthetic mixtures of nitroanilines was evaluated and the results obtained by the application of these chemometric approaches were discussed and compared. The analytical performance of the models was characterized by relative standard errors. It was found that the artificial neural networks model affords relatively better results than PLS. The proposed method was applied to the determination of considered nitroanilines in water samples.     

Identification of heparin samples that contain impurities or contaminants by chemometric pattern recognition analysis of proton NMR spectral data

Chemometric analysis of a set of one-dimensional (1D) (1)H nuclear magnetic resonance (NMR) spectral data for heparin sodium active pharmaceutical ingredient (API) samples was employed to distinguish USP-grade heparin samples from those containing oversulfated chondroitin sulfate (OSCS) contaminant and/or unacceptable levels of dermatan sulfate (DS) impurity. Three chemometric pattern recognition approaches were implemented: classification and regression tree (CART), artificial neural network (ANN), and support vector machine (SVM). Heparin sodium samples from various manufacturers were analyzed in 2008 and 2009 by 1D (1)H NMR, strong anion-exchange high-performance liquid chromatography, and percent galactosamine in total hexosamine tests. Based on these data, the samples were divided into three groups: Heparin, DS ≤ 1.0% and OSCS = 0%; DS, DS > 1.0% and OSCS = 0%; and OSCS, OSCS > 0% with any content of DS. Three data sets corresponding to different chemical shift regions (1.95-2.20, 3.10-5.70, and 1.95-5.70 ppm) were evaluated. While all three chemometric approaches were able to effectively model the data in the 1.95-2.20 ppm region, SVM was found to substantially outperform CART and ANN for data in the 3.10-5.70 ppm region in terms of classification success rate. A 100% prediction rate was frequently achieved for discrimination between heparin and OSCS samples. The majority of classification errors between heparin and DS involved cases where the DS content was close to the 1.0% DS borderline between the two classes. When these borderline samples were removed, nearly perfect classification results were attained. Satisfactory results were achieved when the resulting models were challenged by test samples containing blends of heparin APIs spiked with non-, partially, or fully oversulfated chondroitin sulfate A, heparan sulfate, or DS at the 1.0%, 5.0%, and 10.0% (w/w) levels. This study demonstrated that the combination of 1D (1)H NMR spectroscopy with multivariate chemometric methods is a nonsubjective, statistics-based approach for heparin quality control and purity assessment that, once standardized, minimizes the need for expert analysts.     

On line photochemically induced excitation-emission-kinetic four-way data: analytical application for the determination of folic acid and its two main metabolites in serum by U-PLS and N-PLS/residual trilinearization (RTL) calibration

The determination of folic acid and its two main serum metabolites, 5-methyltetrahydrofolic acid and tetrahydrofolic acid, has been accomplished using four-way data modelled by the third-order multivariate calibration methods unfolded and N-dimensional partial least-squares (U-PLS and N-PLS), in combination with the separate procedure known as residual trilinearization (RTL). The four-way data were acquired by following the photochemical reaction of these compounds by on line irradiation with a UV lamp. The excitation-emission matrices (EEMs) were recorded as a function of the irradiation time, using a fast scanning spectrofluorimeter. The method achieves selectivity from the different rates at which the corresponding photoproducts of the folic acid derivatives are formed and degraded. Several N-dimensional chemometric algorithms were used and the method was applied to the determination of these compounds in serum samples. The best algorithms to perform the multivariate calibration were U-PLS and N-PLS in combination with the separate residual trilinearization procedure, achieving the second-order advantage. The approach allows minimizing or eliminating traditionally time-consuming sample pre-treatments and can facilitate quantifying an analyte in its native environment.     

Fast determination of ginsenosides in ginseng by high‐performance liquid chromatography with chemometric resolution

Ginseng is a well‐known traditional Chinese medicinal herb, and ginsenosides are its major active components. A method for the fast determination of ginsenosides in ginseng samples by high‐performance liquid chromatography was developed and used for the quantitative analysis of four ginsenosides in three different ginseng samples. In this method, instead of time‐consuming gradient elution, isocratic elution was used to speed up the analysis. Under strong isocratic elution, all the ginsenosides are eluted in 2.3 min. Although the measured signal is composed of overlapped peaks with the interferences and background, the signal of ginsenosides can be extracted by chemometric resolution. A non‐negative immune algorithm was employed to obtain the chromatographic information of the target components from the data. Compared with conventional chemometric approaches, the method can perform the extraction for one‐dimensional overlapping signals. The method was validated by the determination of four ginsenosides in three different ginseng samples. The recoveries of the spiked samples were in the range of 94.08–107.3%.     

Multivariate calibration applied to the time-resolved chemiluminescence for the simultaneous determination of morphine and its antagonist naloxone

A novel alternative for the simultaneous determination of compounds with similar structure is described, using the whole chemiluminescence-time profiles, acquired by the stopped-flow technique, in combination with mathematical treatments of multivariate calibration. The proposed method is based on the chemiluminescent oxidation of morphine and naloxone by their reaction with potassium permanganate in an acidic medium, using formaldehyde as co-factor. The whole chemiluminescence-time profiles, acquired using the stopped-flow technique in a continuous-flow system, allowed the use of the time-resolved chemiluminescence (CL) data in combination with multivariate calibration techniques, as partial least squares (PLS), for the quantitative determination of both opiate narcotics in binary mixtures.In order to achieve overcoat the additivity of the CL profiles and beside to obtain CL profiles for each drug the most separated as possible in the time, the optimum chemical conditions for the CL emission were investigated. The effect of common emission enhancers on the CL emission obtained in the oxidation reaction of these compounds in different acidic media was studied. The parameters selected were sulphuric acid 1.0 mol L⁻¹, permanganate 0.2 mmol L⁻¹ and formaldehyde 0.8 mol L⁻¹. A calibration set of standard samples was designed by combination of a factorial design, with three levels for each factor and a central composite design. Finally, with the aim of validating the chemometric proposed method, a prediction set of binary samples was prepared. Using the multivariate calibration method proposed, the analytes were determined in synthetic samples, obtaining recoveries of 97-109%.