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.     

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.     

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.     

Determination of Parathion‐methyl in Vegetables by Fluorescent‐Labeled Molecular Imprinted Polymer

A novel sensor for the determination of parathion‐methyl based on couple grafting of functional molecular imprinted polymers (MIPs) was fabricated which is developed by anchoring the MIP layer on surfaces of silica particles embedded CdSe quantum dots by surface imprinting technology. The synthesized molecular imprinted silica nanospheres (CdSe@SiO₂@MIP) allow a high selectivity and sensitivity of parathion‐methyl via fluorescence intensity decreasing when the MIP material rebinding the parathion‐methyl molecule. Compared with the MIP fabricated in traditional method, the template of parathion‐methyl was easier to remove from the CdSe@SiO₂@MIP imprinted material. Under optimal conditions, the fluorescence intensity of parathion‐methyl at the imprinted sensor was detected by spectrofluorophotometer. The relative fluorescence intensity of CdSe@SiO₂@MIP decreased linearly with the increasing concentration of parathion‐methyl ranging from 0.013 mg·kg⁻¹ to 2.63 mg·kg⁻¹ with a detection limit (3δ) of 0.004 mg·kg⁻¹ (S/N=3), which is lower than the MIP in tradition. The imprinted film sensor was applied to detect parathion‐methyl in vegetable samples without the interference of other organophosphate pesticides and showed a prosperous application in the field of food safety.     

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.     

Multicomponent determination of pesticides in vegetables by gas chromatography with mass spectrometric detection and multivariate calibration

Three multivariate calibration methods, partial least squares (PLS-1 and PLS-2) and principal component regression (PCR), were applied for the first time to the simultaneous determination of a mixture of six pesticides in vegetables samples by gas chromatography with mass spectrometric detection (GC-MS). PLS-1 method showed better prediction ability than PLS-2 and PCR methods. The GC-MS chromatograms obtained of vegetable samples spiked with the target pesticides were used to build the calibration matrix. The PLS-1 models were evaluated by predicting the concentrations of independent test samples. Also, the proposed models were successfully applied for the determination of these pesticides in vegetable samples after an extraction step with dichloromethane. By using the first derivative signals in PLS-1 models, simultaneous determination of the compounds was not improved.     

Simultaneous Determination of Mepyramine Maleate,Lidocaine Hydrochloride,and Dexpanthenol in Pharmaceutical Preparations by Partial Least‐Squares Multivariate Calibration

Abstract

A partial least‐squares calibration (PLS) method has been developed for simultaneous quantitative determination of mepyramine maleate (MAM), lidocaine hydrochloride (LIH), and dexpanthenol (DPA) in pharmaceutical preparations. The resolution of these mixtures has been accomplished by using partial least‐squares (PLS‐2) regression analysis of electronic absorption spectral data without prior separation or derivatization. The experimental calibration matrix was constructed with 27 samples. The concentration ranges considered were 2, 3, 4 µg mL^?1 for MAM, 2, 3, 4 µg mL^?1 for LIH, and 8, 10, 12 µg mL^?1 for DPA. The absorbances were recorded between 190 and 340 nm every 5 nm. The results show that PLS‐2 is a simple, rapid, and accurate method applied to the determination of these compounds in pharmaceuticals.     

Application of the molecularly imprinted solid-phase extraction to the organophosphate residues determination in strawberries

This study describe an analytical method employing gas chromatography (GC) using flame photometric detection that has been developed for the simultaneous determination of organophosphate pesticides (diazinon, disulfoton, parathion, chlorpyrifos and malathion) in strawberry samples. For this purpose, molecularly imprinted solid-phase extraction was applied as a sample preparation technique. The method was linear in the ranges from 0.10 to 1.00?μg?g^?1, for diazinon, disulfoton, parathion and chlorpyrifos, and 0.10 to 2.00?μg?g^?1 for malathion with r?>?0.99. The detection limits (LD) ranged from 0.02 to 0.05?μg?g^?1. Recovery studies yielded average recoveries in the range of 65.25 to 87.70?%. These results showed the potential of this technique for organophosphate residue monitoring in strawberry samples.     

Near-infrared spectroscopy quantitative determination of Pefloxacin mesylate concentration in pharmaceuticals by using partial least squares and principal component regression multivariate calibration

Pefloxacin mesylate, a broad-spectrum antibacterial fluoroquinolone, has been widely used in clinical practice. Therefore, it is very important to detect the concentration of Pefloxacin mesylate. In this research, the near-infrared spectroscopy (NIRS) has been applied to quantitatively analyze on 108 injection samples, which was divided into a calibration set containing 89 samples and a prediction set containing 19 samples randomly. In order to get a satisfying result, partial least square (PLS) regression and principal components regression (PCR) have been utilized to establish quantitative models. Also, the process of establishing the models, parameters of the models, and prediction results were discussed in detail. In the PLS regression, the values of the coefficient of determination (R²) and root mean square error of cross-validation (RMSECV) of PLS regression are 0.9263 and 0.00119, respectively. For comparison, though applying PCR method to get the values of R² and RMSECV we obtained are 0.9685 and 0.00108, respectively. And the values of the standard error of prediction set (SEP) of PLS and PCR models are 0.001480 and 0.001140. The result of the prediction set suggests that these two quantitative analysis models have excellent generalization ability and prediction precision. However, for this PFLX injection samples, the PCR quantitative analysis model achieved more accurate results than the PLS model. The experimental results showed that NIRS together with PCR method provide rapid and accurate quantitative analysis of PFLX injection samples. Moreover, this study supplied technical support for the further analysis of other injection samples in pharmaceuticals.     

Gold nanoparticles-carbon nanotubes modified sensor for electrochemical determination of organophosphate pesticides

An electrochemical sensor was developed for the detection of organophosphate pesticides based on electrodeposition of gold nanoparticles on a multi-walled carbon nanotubes modified glassy carbon electrode. Cyclic voltammetry was employed in the process of electrodeposition. Field emission scanning electron microscope and X-ray diffraction techniques were used for characterization of the composite. Organophosphate pesticides (e.g. parathion) were determined using linear scan voltammetry. A highly linear response to parathion in the concentration range from 6.0?×?10^?5 to 5.0?×?10^?7 M was observed, with a detection limit of 1.0?×?10^?7 M estimated at a signal-to-noise ratio of 3. The method has been applied to the analysis of parathion in real samples.     

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‐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 enzymatic kinetic determination of carbamate pesticides with the aid of chemometrics

A method for the simultaneous enzymatic kinetic determination of the pesticides, oxamyl, aldicarb and aminocarb in fruit, vegetables and water samples, has been researched and developed. It was based on enzymatic reaction kinetics and spectrophotometric measurements, and results were interpreted with the aid of chemometrics. The analytical method relies on the inhibitory effect of the 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 complex rate equation for the formation of the chromogenic product, P, was solved under certain experimental conditions, and this enabled the absorbance (A _p, at λ _max = 412 nm) from the mixtures of the three pesticide inhibitors to be directly related to their concentrations. The detection limits of the enzymatic kinetic spectrophotometric procedures for the determination of the oxamyl, aldicarb and aminocarb were 0.81, 2.13 and 1.25 ng mL^?1, respectively. Calibration models were constructed for principal component regression (PCR), partial least squares (PLS), and radial basis function-artificial neural network (RBF-ANN), and verified with synthetic samples of the three pesticides. The prediction performance of these models showed generally satisfactory results, and the RBF-ANN one performed slightly better than the other two (RPE_T = 7.59% and average %recovery = 99%). This model was then successfully applied to estimate the amounts of the three compounds in fruit, vegetables and water with satisfactory results.     

Molecularly imprinted nanoparticles-based electrochemical sensor for determination of ultratrace parathion in real samples

Molecularly imprinted polymer nanoparticles (nano-MIP), containing parathion selective sites, were synthesized by using suspension polymerization in silicon oil and then used for carbon paste electrode preparation. The obtained electrode was applied as an electrochemical sensor for parathion determination in different fruit and vegetable samples. Different factors including electrode composition, conditions of parathion extraction in the electrode and electrochemical measurement conditions were evaluated and then optimized by using various techniques of screening and response surface experimental designs. Electrode response to parathion (Res₁) and its selectivity for parathion (Res₂) were the desired responses. These responses were optimized simultaneously. After optimization, a sensor with high selectivity and picomolar detection limit were obtained. It was shown that the sensor response to parathion concentration was linear in the concentration range of 0.05 to 150?nmol?L^?1. The detection limit of designed sensor was calculated equal to 0.02?nmol?L^?1. The developed determination method was properly used for ultra-trace level assay of parathion in different fruit and cabbage samples.     

Application of H-Point standard addition method and multivariate calibration methods to the simultaneous kinetic-potentiometric determination of permanganate and dichromate

Simultaneous kinetic-potentiometric determination of binary mixture of permanganate (MnO₄ ^?) and dichromate (Cr₂O₇ ^2?) by H-point standard addition method (HPSAM), partial least squares (PLS) and principal component regression (PCR) is described. In this work, the difference between the rate of the oxidation reaction of Fe(II) to Fe(III) in the presence of MnO₄ ^? and Cr₂O₇ ^2? formed the basis of the method. The rate of the consumed fluoride ion for making the complex was detected by a fluoride ion selective electrode (FISE). The results show that the simultaneous determination of MnO₄ ^? and Cr₂O₇ ^2? could be conducted in their concentration ranges of 0.5?C10.0 and 0.1?C20.0 ??g ml^?1, respectively. The total relative standard error (RSE) for applying the PLS and PCR methods to 9 synthetic samples was 5.30 and 3.17, respectively in the concentration range of MnO₄ ^?, and 3.30 and 2.04, respectively, in the concentration range of Cr₂O₇ ^2?. In order for the selectivity of the method to be assessed, we evaluated the effects of certain foreign ions upon the reaction rate. The proposed methods (HPSAM, PLS and PCR) were evaluated using a set of synthetic sample mixtures and then applied to the simultaneous determination of MnO₄ ^? and Cr₂O₇ ^2? in different water samples.     

Evaluation of biodiesel-diesel blends quality using H NMR and chemometrics

In this work, the use of ¹H NMR spectroscopy and statistical approach to the evaluation of biodiesel-diesel blends quality is described. Forty-six mixtures of oil-diesel, biodiesel-diesel, and oil-biodiesel-diesel were analyzed by ¹H NMR and such data were employed to design four predictive models. Thirty-six mixtures were used in the calibration set and the others in the validation. The PCR and PLS models were evaluated through statistical parameters.Briefly, PLS and PCR models were suitable for the prediction of biodiesel and oil concentration in mineral diesel. Specially, in higher concentration the predicted values were quite similar to the real ones. This fact was evidenced by the low relative errors of high concentrated samples; this means that the prediction of low concentrated samples will probably show high deviation. Therefore, ¹H NMR-PLS and ¹H NMR-PCR methods are fairly useful for the quality control of biodiesel-diesel blends, particularly they are suitable for prediction of concentrations greater than 2%.     

Simultaneous Determination of Three Synthetic Glucocorticoids by Differential Pulse Stripping Voltammetry with the Aid of Chemometrics

Abstract

A novel voltammetric method for simultaneous determination of the glucocorticoid residues prednisone, prednisolone, and dexamethasone was developed. All three compounds were reduced at a mercury electrode in a Britton–Robinson buffer (pH 3.78), and well-defined voltammetric waves were observed. However, the voltammograms of these three compounds overlapped seriously and showed nonlinear character, and thus, it was difficult to analyze the compounds individually in their mixtures. In this work, two chemometrics methods, principal component regression (PCR) and partial least squares (PLS), were applied to resolve the overlapped voltammograms, and the calibration models were established for simultaneous determination of these compounds. Under the optimum experimental conditions, the limits of detection (LOD) were 5.6, 8.3, and 16.8 µg l^?1 for prednisone, prednisolone, and dexamethasone, respectively. The proposed method was also applied for the determination of these glucocorticoid residues in the rabbit plasma and human urine samples with satisfactory results.     

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.     

Spectrophotometric determination of metal ions in electroplating solutions in the presence of EDTA with the aid of multivariate calibration and artificial neural networks

Metal ions such as Co(II), Ni(II), Cu(II), Fe(III) and Cr(III), which are commonly present in electroplating baths at high concentrations, were analysed simultaneously by a spectrophotometric method modified by the inclusion of the ethylenediaminetetraacetate (EDTA) solution as a chromogenic reagent. The prediction of the metal ion concentrations was facilitated by the use of an orthogonal array design to build a calibration data set consisting of absorption spectra collected in the 370-760 nm range from solution mixtures containing the five metal ions earlier. With the aid of this data set, calibration models were built based on 10 different chemometrics methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), artificial neural networks (ANN) and others. These were tested with the use of a validation data set constructed from synthetic solutions of the five metal ions. The analytical performance of these chemometrics methods were characterized by relative prediction errors and recoveries (%). On the basis of these results, the computational methods were ranked according to their performances using the multi-criteria decision making procedures preference ranking organization method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA). PLS and PCR models applied to the spectral data matrix that used the first derivative pre-treatment were the preferred methods. They together with ANN-radial basis function (RBF) and PLS were applied for analysis of results from some typical industrial samples analysed by the EDTA-spectrophotometric method described. DPLS, DPCR and the ANN-RBF chemometrics methods performed particularly well especially when compared with some target values provided by industry.     

Ultrapreconcentration and determination of organophosphorus pesticides in water by solid‐phase extraction combined with dispersive liquid–liquid microextraction and high‐performance liquid chromatography

Solid‐phase extraction coupled with dispersive liquid–liquid microextraction was developed as an ultra‐preconcentration method for the determination of four organophosphorus pesticides (isocarbophos, parathion‐methyl, triazophos and fenitrothion) in water samples. The analytes considered in this study were rapidly extracted and concentrated from large volumes of aqueous solutions (100 mL) by solid‐phase extraction coupled with dispersive liquid–liquid microextraction and then analyzed using high performance liquid chromatography. Experimental variables including type and volume of elution solvent, volume and flow rate of sample solution, salt concentration, type and volume of extraction solvent and sample solution pH were investigated for the solid‐phase extraction coupled with dispersive liquid–liquid microextraction with these analytes, and the best results were obtained using methanol as eluent and ethylene chloride as extraction solvent. Under the optimal conditions, an exhaustive extraction for four analytes (recoveries >86.9%) and high enrichment factors were attained. The limits of detection were between 0.021 and 0.15 μg/L. The relative standard deviations for 0.5 μg/L of the pesticides in water were in the range of 1.9–6.8% (n = 5). The proposed strategy offered the advantages of simple operation, high enrichment factor and sensitivity and was successfully applied to the determination of four organophosphorus pesticides in water samples.