Aid Of Chemometrics Research Articles

A differential kinetic spectrophotometric method for determination of three sulphanilamide artificial sweeteners with the aid of chemometrics

A simple and sensitive spectrophotometric method for the simultaneous determination of acesulfame-K, sodium cyclamate and saccharin sodium sweeteners in foodstuff samples has been researched and developed. This analytical method relies on the different kinetic rates of the analytes in their oxidative reaction with KMnO 4 to produce the green manganate product in an alkaline solution. As the kinetic rates of acesulfame-K, sodium cyclamate and saccharin sodium were similar and their kinetic data seriously overlapped, chemometrics methods, such as partial least squares (PLS), principal component regression (PCR) and classical least squares (CLS), were applied to resolve the kinetic data. The results showed that the PLS prediction model performed somewhat better. The proposed method was then applied for the determination of the three sweeteners in foodstuff samples, and the results compared well with those obtained by the reference HPLC method.

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

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.

Simultaneous kinetic spectrophotometric determination of norfloxacin and rifampicin in pharmaceutical formulation and human urine samples by use of chemometrics approaches

A kinetic spectrophotometric method with aid of chemometrics is proposed for the simultaneous determination of norfloxacin and rifampicin in mixtures. The proposed method was applied for the simultaneous determination of these two compounds in pharmaceutical formulation and human urine samples, and the results obtained are similar to those obtained by high performance liquid chromatography.

Spectrometric and voltammetric studies of the interaction between quercetin and bovine serum albumin using warfarin as site marker with the aid of chemometrics

The interaction of quercetin, which is a bioflavonoid, with bovine serum albumin (BSA) was investigated under pseudo-physiological conditions by the application of UV–vis spectrometry, spectrofluorimetry and cyclic voltammetry (CV). These studies indicated a cooperative interaction between the quercetin–BSA complex and warfarin, which produced a ternary complex, quercetin–BSA–warfarin. It was found that both quercetin and warfarin were located in site I. However, the spectra of these three components overlapped and the chemometrics method – multivariate curve resolution-alternating least squares (MCR-ALS) was applied to resolve the spectra. The resolved spectra of quercetin–BSA and warfarin agreed well with their measured spectra, and importantly, the spectrum of the quercetin–BSA–warfarin complex was extracted. These results allowed the rationalization of the behaviour of the overlapping spectra. At lower concentrations ([warfarin] < 1 × 10 −5 mol L −1), most of the site marker reacted with the quercetin–BSA, but free warfarin was present at higher concentrations. Interestingly, the ratio between quercetin–BSA and warfarin was found to be 1:2, suggesting a quercetin–BSA–(warfarin) 2 complex, and the estimated equilibrium constant was 1.4 × 10 11 M −2. The results suggest that at low concentrations, warfarin binds at the high-affinity sites (HAS), while low-affinity binding sites (LAS) are occupied at higher concentrations.

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.

Fingerprint Analysis of Eucommia Bark by LC-DAD and LC-MS with the Aid of Chemometrics

Chromatographic fingerprints of 46 Eucommia Bark samples were obtained by liquid chromatography-diode array detector (LC-DAD). These samples were collected from eight provinces in China, with different geographical locations, and climates. Seven common LC peaks that could be used for fingerprinting this common popular traditional Chinese medicine were found, and six were identified as substituted resinols (4 compounds), geniposidic acid and chlorogenic acid by LC-MS. Principal components analysis (PCA) indicated that samples from the Sichuan, Hubei, Shanxi and Anhui—the SHSA provinces, clustered together. The other objects from the four provinces, Guizhou, Jiangxi, Gansu and Henan, were discriminated and widely scattered on the biplot in four province clusters. The SHSA provinces are geographically close together while the others are spread out. Thus, such results suggested that the composition of the Eucommia Bark samples was dependent on their geographic location and environment. In general, the basis for discrimination on the PCA biplot from the original 46 objects× 7 variables data matrix was the same as that for the SHSA subset (36 × 7 matrix). The seven marker compound loading vectors grouped into three sets: (1) three closely correlating substituted resinol compounds and chlorogenic acid; (2) the fourth resinol compound identified by the OCH3 substituent in the R4 position, and an unknown compound; and (3) the geniposidic acid, which was independent of the set 1 variables, and which negatively correlated with the set 2 ones above. These observations from the PCA biplot were supported by hierarchical cluster analysis, and indicated that Eucommia Bark preparations may be successfully compared with the use of the HPLC responses from the seven marker compounds and chemometric methods such as PCA and the complementary hierarchical cluster analysis (HCA).

Nondestructive determination of compound amoxicillin powder by NIR spectroscopy with the aid of chemometrics

Near-infrared (NIR) spectroscopy, in combination with chemometrics, enables nondestructive analysis of solid samples without time-consuming sample preparation methods. A new method for the nondestructive determination of compound amoxicillin powder drug via NIR spectroscopy combined with an improved neural network model based on principal component analysis (PCA) and radial basis function (RBF) neural networks is investigated. The PCA technique is applied to extraction relevant features from lots of spectra data in order to reduce the input variables of the RBF neural networks. Various optimum principal component analysis–radial basis function (PCA–RBF) network models based on conventional spectra and preprocessing spectra (standard normal variate (SNV) and multiplicative scatter correction (MSC)) have been established and compared. Principal component regression (PCR) and partial least squares (PLS) multivariate calibrations are also used, which are compared with PCA–RBF neural networks. Experiment results show that the proposed PCA–RBF method is more efficient than PCR and PLS multivariate calibrations. And the PCA–RBF approach with SNV preprocessing spectra is found to provide the best performance.

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 526 nm, and the accompanying increase of the product, potassium manganate, at 608 nm. 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 1.0–11.5 mg L −1 at 526 and 608 nm for pefloxacin, and 0.15–1.8 mg L −1 at 526 and 608 nm 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 526 nm, were the preferred methods—%RPE T ∼ 5, and LODs for pefloxacin and norfloxacin of 0.36 and 0.06 mg L −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.

Role of Carbon Nanotubes in Analytical Science

Analytical science has gone through several turning points, one of the most decisive of which was signaled by the development and massive use of instruments for analytical purposes. One other pivotal turning point was the inception of computer science, which not only enabled the automatic control of analytical systems but also facilitated the acquisition of vast amounts of data and their processing with the aid of chemometrics. Following the growing significance of automation and miniaturization in recent times, the early 21st century is witnessing the rise of nanotechnology as a new, increasingly important, revolutionary trend in science in general and analytical science in particular. The ability to exploit molecular interactions between analytes and nanoparticles has opened up new, challenging prospects in this area. Good proof of the interest aroused by nanoparticles is the large number of papers on their use in quantum dots, fullerene, aurum nanoparticles, or carbon nanotubes published in recent years.

Application of high performance liquid chromatography for the profiling of complex chemical mixtures with the aid of chemometrics

In this paper, chemometrics methods were applied to resolve the high performance liquid chromatography (HPLC) fingerprints of complex, many-component substances to compare samples from a batch from a given manufacturer, or from those of different producers. As an example of such complex substances, we used a common Chinese traditional medicine, Huoxiang Zhengqi Tincture (HZT) for this research. Twenty-one samples, each representing a separate HZT production batch from one of three manufacturers were analyzed by HPLC with the aid of a diode array detector (DAD). An Agilent Zorbax Eclipse XDB-C18 column with an Agilent Zorbax high pressure reliance cartridge guard-column were used. The mobile phase consisted of water (A) and methanol (B) with a gradient program of 25–65% (v/v, B) during 0–30 min, 65–55% (v/v, B) during 30–35 min and 55–100% (v/v, B) during 35–60 min (flow rate, 1.0 ml min −1; injection volume, 20 μl; and column temperature-ambient). The detection wavelength was adjusted for maximum sensitivity at different time periods. A peak area matrix with 21 objects × 14 HPLC variables was obtained by sampling each chromatogram at 14 common retention times. Similarities were then calculated to discriminate the batch-to-batch samples and also, a more informative multi-criteria decision making methodology (MCDM), PROMETHEE and GAIA, was applied to obtain more information from the chromatograms in order to rank and compare the complex HZT profiles. The results showed that with the MCDM analysis, it was possible to match and discriminate correctly the batch samples from the three different manufacturers. Fourier transform infrared (FT-IR) spectra taken from samples from several batches were compared by the common similarity method with the HPLC results. It was found that the FT-IR spectra did not discriminate the samples from the different batches.

Simultaneous enzymatic kinetic determination of pesticides, carbaryl and phoxim, with the aid of chemometrics

A sensitive and selective enzymatic kinetic method for the simultaneous determination of mixtures of carbaryl and phoxim pesticides was researched and developed. It was based 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 DTNB-thiocholine reaction was investigated by a spectrophotometric-kinetic approach. The complex rate equation for the formation of the chromogenic product, P, was solved under certain experimental conditions, which enabled the absorbance ( A P, at λ max = 412 nm) from the mixtures of the two pesticide inhibitors to be directly related to their concentrations provided the absorbance additivity was followed. The spectra were measured for mixtures of carbaryl and phoxim at different concentrations, and at t = 904 s, T = 35 °C, pH = 7.5, c ATChI = 0.14, and c AChE = 0.10 mg mL −1. The detection limits of the enzymatic kinetic spectrophotometric procedures for the determination of the carbaryl and phoxim were 4.7 and 0.59 μg L −1, respectively. Calibration models for chemometrics methods, such as principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural network (RBF-ANN) were constructed and verified with synthetic samples of the mixtures of the two pesticides. The best performing model was based on the RBF-ANN method yielding at approximately 10 ppb analyte concentrations, %RPE T (carbaryl = 5.2; phoxim = 6.5), %Recovery (approx.105%) and %RPE T (6.5). Various spiked town-water samples produced recoveries in the range of 98.8–103% for each pesticide.

Authentication of vegetable oils on the basis of their physico-chemical properties with the aid of chemometrics

In food production, reliable analytical methods for confirmation of purity or degree of spoilage are required by growers, food quality assessors, processors, and consumers. Seven parameters of physico-chemical properties, such as acid number, colority, density, refractive index, moisture and volatility, saponification value and peroxide value, were measured for quality and adulterated soybean, as well as quality and rancid rapeseed oils. Chemometrics methods were then applied for qualitative and quantitative discrimination and prediction of the oils by methods such exploratory principal component analysis (PCA), partial least squares (PLS), radial basis function-artificial neural networks (RBF-ANN), and multi-criteria decision making methods (MCDM), PROMETHEE and GAIA. In general, the soybean and rapeseed oils were discriminated by PCA, and the two spoilt oils behaved differently with the rancid rapeseed samples exhibiting more object scatter on the PC-scores plot, than the adulterated soybean oil. For the PLS and RBF-ANN prediction methods, suitable training models were devised, which were able to predict satisfactorily the category of the four different oil samples in the verification set. Rank ordering with the use of MCDM models indicated that the oil types can be discriminated on the PROMETHEE II scale. For the first time, it was demonstrated how ranking of oil objects with the use of PROMETHEE and GAIA could be utilized as a versatile indicator of quality performance of products on the basis of a standard selected by the stakeholder. In principle, this approach provides a very flexible method for assessment of product quality directly from the measured data.

Monitoring a commercial fermentation with proton nuclear magnetic resonance spectroscopy with the aid of chemometrics

Proton nuclear magnetic resonance spectroscopy (NMR) has shown the potential for being a valuable tool in monitoring a commercial fermentation. In this preliminary study, a suite of organic analytes including ethanol, fructose, glucose, methanol, glycerol, malic acid, tartaric acid, succinic acid, acetic acid and lactic acid were simultaneously determined during the fermentation. Data collection and analysis using chemometric algorithms aided the understanding of key processes including the effects of seeding a wine with bacteria for malo-lactic fermentation.

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.

A spectroscopic study of mechanochemically activated kaolinite with the aid of chemometrics

The study of kaolinite surfaces is of industrial importance. In this work we report the application of chemometrics to the study of modified kaolinite surfaces. DRIFT spectra of mechanochemically activated kaolinites (Kiralyhegy, Zettlitz, Szeg, and Birdwood) were analyzed using principal component analysis (PCA) and multicriteria decision making (MCDM) methods, PROMETHEE and GAIA. The clear discrimination of the Kiralyhegy spectral objects on the two PC scores plots (400–800 and 800–2030 cm −1) indicated the dominance of quartz. Importantly, no ordering of any spectral objects appeared to be related to grinding time in the PC plots of these spectral regions. Thus, neither the kaolinite nor the quartz, are systematically responsive to grinding time according to the spectral criteria investigated. The third spectral region (2600–3800 cm −1 OH vibrations), showed apparent systematic ordering of the Kiralyhegy and, to a lesser extent, Zettlitz spectral objects with grinding time. This was attributed to the effect of the natural quartz on the delamination of kaolinite and the accompanying phenomena (i.e., formation of kaolinite spheres and water). With the MCDM methods, it was shown that useful information on the basis of chemical composition, physical properties and grinding time can be obtained. For example, the effects of the minor chemical components (e.g., MgO, K 2O, etc.) indicated that the Birdwood kaolinite is arguably the most pure one analyzed. In another MCDM experiment, some support was obtained for the apparent trend with grinding time noted in the PC plot of the OH spectral region.

Simultaneous determination of three organophosphorus pesticides by differential pulse stripping voltammetry and chemometrics

A differential pulse stripping voltammetry method (DPSV) is proposed for the determination of parathion-methyl (PTM), fenitrothion (FT) and parathion (PT) at a hanging mercury drop electrode (HMDE). The voltammograms of these three compounds overlap strongly, and it is difficult to determine the compounds individually from their mixtures. Quantitative analysis for each of the pesticide compounds in a mixture has been investigated with the aid of chemometrics and the prediction performance of the different methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), Kalman filter (KF) and radial basis function-artificial neural networks (RBF-ANN), was compared. A set of synthetic mixtures of the three compounds was analysed by using the proposed methods, and it was found that the lowest relative prediction error (RPE) and satisfactory % recovery were achieved with the RBF-ANN procedure. The proposed method was also applied to several vegetable samples spiked with known amounts of the pesticides with satisfactory results.

Application of multivariate calibration and artificial neural networks to simultaneous kinetic-spectrophotometric determination of carbamate pesticides

A method for the simultaneous determination of the pesticides, carbofuran, isoprocarb and propoxur in fruit and vegetable samples has been investigated and developed. It is based on reaction kinetics and spectrophotometry, and results are interpreted with the aid of chemometrics. The analytical method relies on the differential rates of coupling reactions between the hydrolysis product of each carbamate and 4-aminophenol in the presence of potassium periodate in an alkaline solution. The optimized method was successfully tested by analyzing each of the carbamates independently, and linear calibration models are described. For the simultaneous determinations of the carbamates found in ternary mixtures, kinetic and spectral data were processed either by three-way data unfolding method or decomposed by trilinear modeling. Subsequently, 10 different RBF-ANN, PARAFAC and NPLS calibration models were constructed with the use of synthetic ternary mixtures of the three carbamates, and were validated with a separate set of mixtures. The performance of the calibration models was then ranked on the basis of several different figures of merit with the aid of the multi-criteria decision making approach, PROMETHEE and GAIA. RBF-ANN and PC-RBF-ANN were the best performing methods with %Relative Prediction Errors (RPE) in the 3–4% range and Recovery of about 97%. When compared with other recent studies, it was also noted that RBF-ANN has consistently outperformed the more common prediction methods such as PLS and PCR as well as BP-ANN. The successful RBF–ANN method was then applied for the determination of the three carbamate pesticides in purchased vegetable and fruit samples.

Vibrational spectroscopic investigation of Australian cotton cellulose fibres Part 1. A Fourier transform Raman study†

Seven types of raw naturally coloured and white cotton cellulose fibres were investigated by near-infrared excited Fourier transform Raman spectroscopy with the aid of chemometrics, namely principal component analysis (PCA). The PCA scores plot showed that PC2 discriminates the spectra of the naturally coloured cotton fibres and the white fibres. Further, it is also possible to differentiate some of the different types of white cotton fibres on this PC, and the PC2 scores appear to be related to the strength of the fibres.

Principal component analysis in fast atom bombardment‐mass spectrometry of triacylglycerols in edible oils

AbstractPositive‐ion fast atom bombardment‐mass spectrometry, withm‐nitrobenzyl alcohol as matrix and a methanolic sodium iodide (Nal) solution, was used to characterize edible oils by their triacylglycerol composition. Cationized triacylglycerols gave characteristic spectra for olive (57 samples), sunflower (9 samples), soybean (9 samples), corn (12 samples), and peanut (10 samples) oils. Relative abundance of [M + Na]+ ions showed relevant differences among the oils. The obtained data were analyzed with the aid of chemometrics by using principal component analysis (PCA) to evaluate the differentiation. Twelve variables were reduced to two principal components, accounting for 82% of the total variance. A two‐dimensional plot of 97 PCA scores allowed the separation of the edible oils. The analysis is both fast and reproducible.

Oil/oil correlation by aid of chemometrics : Øygard, K., O. Grahl-Nielsen and S. Ulvøen, 1984. Org. Geochem., 6:561–567

Oil/oil correlation by aid of chemometrics : Øygard, K., O. Grahl-Nielsen and S. Ulvøen, 1984. Org. Geochem., 6:561–567