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The polarographic waves of pyrazine and its methyl derivatives are seriously overlapping, so they cannot be determined individually by polarographic methods without a prior separation. In this paper, a chemometric approach, iterative target transformation factor analysis (ITTFA), is developed and applied to the determination of mixtures of pyrazines at trace level (2.0–9.0 × 10 −6 moll −1 ) by using differential pulse polarography (DPP) and a static mercury drop electrode (SMDE). Different from the general ITTFA method, only one-dimensional measurement data of n − 1 standards and an unknown were used in this work. It produced acceptable results with average recoveries in the 96–108% range and relative standard errors in the 3.4–9.5% range.

Two sets of cellulosic fabrics - one consisting of different types of dyed and undyed cellulose-based fabrics and the other of a cotton fabric sampled sequentially during its normal processing stages - were investigated by diffuse reflectance infrared Fourier transform spectroscopy. The band assignments were consistent with previous work, although in some instances visual differentiation of the spectra was very difficult. All spectra were qualitatively and quantitatively differentiated with the aid of chemometrics techniques, namely principal component analysis and soft independent modelling of class analogies and showed that discrimination on the basis of fabric dye, fabric type and textile processing can be achieved.

A set of natural cellulosic and regenerated fabrics was analysed by thermogravimetry (TG) and differential scanning calorimetry (DSC). The results were interpreted by chemometrics methods of data analysis, viz., principal component analysis (PCA) and SIMCA. PCA scores plots conveniently displayed the overall information from the TG and DSC data respectively, and the SIMCA classification analysis provided supporting quantitative information. The chemometrics analysis showed that both the TG and DSC data from the natural cellulosic fabrics clustered in a sequence: raw fabrics, linen, bleached fabrics and poplin. This sequence was related to the thermal degradation parameters of maximum weight loss rate and enthalpy of these fabrics.

A novel, simple and direct fluorescence method for analysis of complex substances and their potential substitutes has been researched and developed. Measurements involved excitation and emission (EEM) fluorescence spectra of powdered, complex, medicinal herbs, Cortex Phellodendri Chinensis (CPC) and the similar Cortex Phellodendri Amurensis (CPA); these substances were compared and discriminated from each other and the potentially adulterated samples (Caulis mahoniae (CM) and David poplar bark (DPB)). Different chemometrics methods were applied for resolution of the complex spectra, and the excitation spectra were found to be the most informative; only the rank-ordering PROMETHEE method was able to classify the samples with single ingredients (CPA, CPC, CM) or those with binary mixtures (CPA/CPC, CPA/CM, CPC/CM). Interestingly, it was essential to use the geometrical analysis for interactive aid (GAIA) display for a full understanding of the classification results. However, these two methods, like the other chemometrics models, were unable to classify composite spectral matrices consisting of data from samples of single ingredients and binary mixtures; this suggested that the excitation spectra of the different samples were very similar. However, the method is useful for classification of single-ingredient samples and, separately, their binary mixtures; it may also be applied for similar classification work with other complex substances.

A new modified electrode was constructed by the electro-polymerization of 7-[(2,4-dihydroxy-5-carboxybenzene)azo]-8-hydroxyquinoline-5-sulfonic acid (DHCBAQS) at a graphene-nafion modified glassy carbon electrode (GCE). The construction process was performed stepwise and at each step the electrochemical characteristics were investigated particularly with respect to the oxidation of the three noxious analytes, 2-nitroaniline (2-NA), 3-nitroaniline (3-NA), 4-nitroaniline (4-NA); the electrode treated with the fluorescence reagent DHCBAQS performed best. At this electrode, the differential pulse voltammetry peak currents of the three isomers increased linearly with their concentrations in the range of 0.05-0.60 μg mL(-1), respectively, and their corresponding limits of detection (LODs) were all about 0.022 μg mL(-1). Furthermore, satisfactory results were obtained when this electrode was applied for the simultaneous quantitative analysis of the nitroaniline isomer mixtures by Principal component regression (PCR) and Partial least squares (PLS) as calibration methods (relative prediction error (PRE(T)) - 9.04% and 9.23%) and average recoveries (101.0% and 101.7%), respectively. The above novel poly-DHCBAQS/graphene-nafion/GCE was successfully employed for the simultaneous analysis of the three noxious nitroaniline isomers in water and sewage samples.

Electrochemical behavior of nitrofurazone (NFZ) was investigated with the use of cyclic voltammetry (CV) and differential pulse voltammetry (DPV) methods. The pH-dependence of NFZ was studied at a glassy carbon electrode (GCE) in ethanol/Britton–Robinson buffer (30:70), and short-lived nitro-radicals were generated by the reduction of NFZ at high pHs (>7.0). In the presence of DNA, the DPV peak current of NFZ decreased and the peak potential shifted negatively, which indicated that there was an electrostatic interaction between NFZ and DNA. An electrochemical dsDNA/GCE biosensor was prepared to study the DNA damage produced in the presence NFZ; this process was followed with the use of the Co(phen) 3 2+ electroactive probe. Also, the oxidation peaks of guanosine (750 mV) and adenosine (980 mV) indicated that DNA damage was related directly to the nitro-radicals. Experiments demonstrated that DNA damage occurred via two different steps while NFZ was metabolized and nitro-radicals were produced. Novel work with AFM on the NFZ/DNA interaction supported the suggestion that in vivo , the nitro-radicals were more cytotoxic than the NFZ molecules. A linear DPV calibration plot was obtained for NFZ analysis at a modified dsDNA/GCE (concentration range: 2.50×10 −6 –3.75×10 −5 mol L −1 ; limit of detection: 8.0×10 −7 mol L −1 ), and NFZ was determined successfully in pharmaceutical samples.

An electrochemical method involving a gold nanoparticle modified glassy carbon electrode (AuNPs/GCE) was researched and developed for the simultaneous analysis of three β(2)-agonists, ractopamine (RAC), salbutamol (SAL) and clenbuterol (CLB). The three analytes were electrocatalytically oxidized at the AuNP/GCE, which enhanced the oxidation peak current and influenced the shift of the oxidation potentials to lower values in comparison with the analysis involving only the GCE. The differential pulse stripping voltammetry (DPSV) voltammograms from the drug mixture produced complex, overlapping profiles, and chemometrics methods were applied for calibration modeling. The peak currents associated with RAC, SAL and CLB measurements were linear as a function of their concentrations (ranges within 0.005-0.150 μg mL(-1)); the detection limits for RAC, SAL and CLB were 2.4, 5.8 and 2.6 ng mL(-1), respectively. It was shown that satisfactory quantitative results were obtained with the use of the MVC1 package of chemometrics methods e.g. the PLS1 calibration model produced a relative prediction error (RPE(T)) of 7.0% and an average recovery of 97.6%. The above AuNP/GCE was successfully employed for the simultaneous analysis of RAC, SAL and CLB in pork meat, liver and pig feed samples.

Authentication of traditional Chinese medicines (TCMs) has become important because they can be adulterated with relatively cheap herbal medicines similar in appearance. Detection of such adulterated samples is needed because their presence is likely to reduce the pharmacological potency of the original TCM and, in the worst cases, the samples may be harmful. The aim of this study was to develop a rapid near-infrared spectroscopy (NIRS) analytical method which was supported by multi-variate calibration, e.g. partial least squares regression (PLSR) and radial basis function artificial neural networks (RBF-ANN), in order to quantify the TCM and the adulterants. In this work, Cynanchum stauntonii (CS), a commonly used TCM, in mixtures with one or two adulterants — two morphological types of TCM, Cynanchum atrati (CA) and Cynanchum paniculati (CP), were determined using NIR reflectance spectroscopy. The three sample sets, CS adulterated with CA or CP, and CS with both CA and CP, were measured in the range of 800–2500 nm. Both PLSR and RBF-ANN calibration models provided satisfactory results, even at an adulteration level of 5 mass %, but the RBF-ANN models with better root mean square error of prediction (RMSEP) values for CS, CA, and CP arguably performed better. Consequently, this work demonstrates that the NIR method of sampling complex mixtures of similar substances such as CS adulterated by CA and/or CP is capable of producing data suitable for the quantitative analysis of mixtures consisting of the original TCM adulterated by one or two similar substances, provided the spectral data are interrogated by multi-variate methods of data analysis such as PLS or RBF-ANN.

"Catalytic damage" occurs in cotton fabrics during hydrogen peroxide bleaching. The model for catalytic damage proposed previously by Meyer, Kokot, Weber, and Zürcher is compared with a laboratory simulation of cotton cellulose damage produced using electrogenerated oxygen species at metal electrodes. Additional electrochemical information is provided to support the previously proposed mechanism of the damage of a cotton poplin. Diffuse reflectance infrared spectroscopy and chemometrics are used for relative qualitative and quantitative interpretation of the damage.

Treating cotton fabrics with electrogenerated oxygen at a Pt anode provides a lab oratory method for simulating the "catalytic damage" phenomenon. Samples of cotton voile were treated in this manner using different current and temperature conditions to damage the fabric. Diffuse reflectance infrared spectra of a series of these samples treated at 80°C were then analyzed using fuzzy clustering, an unsupervised classification method. The resulting classes were assigned a number (0 to 4) nominally indicating the extent of fabric damage as measured by this spectroscopic technique. This series of spectra together with the damage class numbers was then used to construct a cali bration set by principal components regression. The calibration was successfully val idated with a similar set of samples and also used to predict the relative fabric damage on other oxidatively affected voile samples.

A sensitive kinetic spectrophotometric method was developed for the determination of four flavor enhancers—maltol, ethyl maltol, vanillin, and ethyl vanillin—in food samples. The method was based on the reduction of iron(III) by the four analytes in a sulfuric acid medium (0.012 mol/L), and the subsequent interaction of iron(II) with hexacyanoferrate(III) to form the strongly colored Prussian blue complex, which exhibited an absorption maximum at 800 nm. The optimized method had linear calibrations over the concentration ranges of 0.2–2.8 mg/L for maltol, ethyl maltol, and vanillin, as well as 0.2–1.8 mg/L for ethyl vanillin; the corresponding detection limits were 0.07, 0.07, 0.06, and 0.06 mg/L, respectively. Calibration models were constructed from the original and frst-derivative spectral data with the use of partial least-squares (PLS) and principal component regression chemometrics methods. Ultimately, the proposed analytical procedure was successively applied for the determination of the four compounds in commercial food samples with the use of a PLS calibration based on the frst-derivative spectral data. The results were comparable with those from a reference HPLC method.

Road dust contain potentially toxic pollutants originating from a range of anthropogenic sources common to urban land uses and soil inputs from surrounding areas. The research study analysed the mineralogy and morphology of dust samples from road surfaces from different land uses and background soil samples to characterise the relative source contributions to road dust. The road dust consist primarily of soil derived minerals (60%) with quartz averaging 40-50% and remainder being clay forming minerals of albite, microcline, chlorite and muscovite originating from surrounding soils. About 2% was organic matter primarily originating from plant matter. Potentially toxic pollutants represented about 30% of the build-up. These pollutants consist of brake and tire wear, combustion emissions and fly ash from asphalt. Heavy metals such as Zn, Cu, Pb, Ni, Cr and Cd primarily originate from vehicular traffic while Fe, Al and Mn primarily originate from surrounding soils. The research study confirmed the significant contribution of vehicular traffic to dust deposited on urban road surfaces.

A rapid kinetic method for the simultaneous determination of levodopa, dopamine, and dobutamine was examined and developed. It was based on a consecutive reaction of a reduction of Cu(II) to Cu(I) by catecholamines, followed by the complexation of Cu(I) with neocuproine to form a yellow product in an acetic acid-acetate buffer. Spectrophotometric data were recorded at 453 nm (wavelength at the yellow complex absorption maximum) for 300 s. Linear calibrations were obtained in the concentration ranges of (0.08–1.44) × 10−5 mol L−1, (0.08–1.44) × 10−5 mol L−1, and (0.16–1.44) × 10−5 mol L−1 for levodopa, dopamine, and dobutamine, respectively. A variety of multivariate calibration models was developed for simultaneous analysis of the three analytes; while most models produced satisfactory prediction results for synthetic samples, the hybrid linear analysis method was arguably the best-performing (relative prediction error, RPET = 6.6 %). The proposed method was applied to an analysis of spiked rabbit serum samples and the results showed good agreement with the high performance liquid chromatography measurements.

The interaction of salbutamol (Sal), an animal growth promoter, with DNA was investigated by differential pulse voltammetry (DPV), cyclic voltammetry (CV), and fluorescence spectroscopy. An irreversible reduction was observed from the cyclic voltammograms, and the reaction mechanism involved a one-electron change irreversible oxidation. In the presence of DNA, the DPV peak current decreased and the Sal peak shifted to higher potentials, indicating that Sal interacted with DNA to form an intercalation Sal-DNA complex. In addition, reaction binding parameters were extracted from the DPV data with the use of the multivariate curve resolution-alternating least squares (MCR-ALS) method; the binding constant and ratio were found to be (2.0±0.5)×10(5) M(-1) and 1:1, respectively. Quantitative voltammetric analysis of Sal was performed in the concentration range of 3.02×10(-6) to 1.23×10(-4) molL(-1), and it was found that the detection limit was 5.11×10(-7) molL(-1) in the presence of 1.00×10(-6) molL(-1) DNA. The method was applied for the determination of Sal in spiked urine and human serum samples, and the calibration was successfully verified.

A study of the polarization of copper and mild steel electrodes in the absence and presence of cotton fabric in an alkaline environment has been carried out. In each case passive film formation on the metal substrate is followed by the OER reaction. For those experiments in which the electrodes were in loose contact with the fabric, exhaustion of OH− ion in the solution between the metal substrate and the fabric resulted in a decrease in the rate of the OER. This can be attributed to a change in mechanism from that in an alkaline to that in an acid environment. The interaction of the electrogenerated O2 with the cotton cellulose leads to degradation of the latter; this is comparable to the “catalytic damage” observed during H2O2 bleaching of cellulose. The increased damage observed to the fabric compared to when the O2 is generated on Pt supports the role of both Cu and Fe as catalysts for the O2 cellulose reaction.

Two sets of cotton fabrics—one consisting of different types of fabric and the other of a fabric sampled sequentially during its normal processing stages—were investigated by DRIFT spectroscopy. The band assignments were consistent with previous work but, in general, the spectra could not be differentiated on visual examination. However, they were successfully qualitatively and quantitatively distinguished with the use of chemometrics; a chemical basis for fabric clustering was also indicated. This approach is a significant improvement on previously reported work with KBr disk IR sampling.

Hole formation in cotton fabrics similar to that observed during the peroxide bleaching process and known as "catalytic damage" may be produced by exposing the fabric to an electrochemical process involving generation of oxygen at platinum anodes. A morphological study of an electrochemically damaged poplin fabric is de scribed. Several morphological fiber changes are identified, including crack formation consistent with granular and spiral splittings. A qualitative model is proposed high lighting a possible sequence of morphological changes that occur during oxidation and culminate in fiber rupture.

The application of four chemometrics procedures viz., principal components analysis, SIMCA, multicriteria decision-making routines PROMETHEE and GAIA, and fuzzy clustering, was investigated for the selection of a suitable microwave digestion method for sediment and rock samples. The NBS 2704 SRM and a secondary rock standard were acid digested by 15 different methods and the digests analysed for six metals, Cu, Pb, Ni, Cr, Co and Zn. The four chemometrics approaches produced consistent results and provided similar information about the data structure (outliers, groupings, trends). Only the PROMETHEE procedure gave the ranking information necessary for the selection of a suitable digestion method. This method was based on the HF-HNO3 acid composition of the digest mixture.

DRIFT spectra were collected from dye mixtures extracted from small yarn samples taken from several areas of a worn test garment. Raw and pretreated data matrices were interpreted with the use of chemometrics (PCA, SIMCA, fuzzy clustering). This approach showed that spectra cluster and match according to their sampling area on the test textile. The DRIFT results provide detailed information that is not available from the application of the usual techniques (e.g., TLC) with such samples and therefore should be of use in forensics or similar work where comparisons of unknown, small dye mixtures are required.

Catalytic damage observed during normal hydrogen peroxide bleaching of cotton fabric can be duplicated in experiments in which a cotton fabric, loosely wrapped about a platinum anode, comes in contact with electro-generated oxygen. Polarization of the anode up to +4000 mV(SSE) in an alkaline environment results in the formation of Pt(II) and Pt(IV) oxides followed by evolution of O 2 . Due to rapid exhaustion of OH − ion (the source of the O 2 ) the pH at the Pt/fabric interface drops from approx. 11 to 3. The polarization curve reveals the formation of a peak and this behaviour is explained in terms of a change in the mechanism of the OER from that in an alkaline environment to one in an acid medium.

The polarograms of mixtures of the cocoa flavor compounds, pyrazines, consist of overlapping peaks. This generally precludes the direct analysis of these compunds without prior separation. In this paper, polarographic conditions for the analysis of up to four component mixtures of pyrazines present at trace levels (150 ppb-1 ppm) were investigated using differential pulse polarography (DPP) at a static mercury drop electrode (SMDE). A series of pyrazine mixtures were analyzed at pH 4.8 (phosphate/citric acid buffer) and the results were interpreted using partial least squares (PLS), principal component regression (PCR), and multiple linear regression (MLR) chemometric routines. In each case an orthogonally designed training set was used to facilitate predictions. The PLS and the PCR models produced acceptable results with recoveries, in general, being in the 97–104% range and RSD in the 4–10% range depending on the nature and complexity of the mixture analyzed.

Principal component analysis (PCA) and the multicriteria decision making methods, PROMETHEE and GAIA, were used to select a suitable microwave digestion method for metal analysis of soil samples. When the residuals matrix derived from the Cu, Pb, Co, Mn and Zn analyses of 18 different digests of the NBS 2704 SRM, was subjected to PCA and PROMETHEE ranking, two prefered methods were isolated. This PROMETHEE ranking together with the microwave oven settings and digest acid composition were then used as variables. The corresponding data matrix was subjected to PROMETHEE analysis coupled with the visualisation technique, GAIA. This illustrated the relationship between the different practical variables and method perfromance leading to the selection of the most suitable digestion method.

This paper presents the outcomes of a research project, which focused on developing a set of surrogate parameters to evaluate urban stormwater quality using simulated rainfall. Use of surrogate parameters has the potential to enhance the rapid generation of urban stormwater quality data based on on-site measurements and thereby reduce resource intensive laboratory analysis. The samples collected from rainfall simulations were tested for a range of physico-chemical parameters which are key indicators of nutrients, solids and organic matter. The analysis revealed that [total dissolved solids (TDS) and dissolved organic carbon (DOC)]; [total solids (TS) and total organic carbon (TOC)]; [turbidity (TTU)]; [electrical conductivity (EC)]; [TTU and EC] as appropriate surrogate parameters for dissolved total nitrogen (DTN), total phosphorus (TP), total suspended solids (TSS), TDS and TS respectively. Relationships obtained for DTN-TDS, DTN-DOC, and TP-TS demonstrated good portability potential. The portability of the relationship developed for TP and TOC was found to be unsatisfactory. The relationship developed for TDS-EC and TS-EC also demonstrated poor portability.

The binding interaction of Alpinetin (APT) with bovine serum albumin (BSA) was studied by fluorescence, UV–visible and synchronous fluorescence spectroscopy (SFS) under simulated physiological conditions. The measured complex spectra were resolved by multivariate curve resolution-alternating least squares (MCR-ALS), yielding a host of data and information, which otherwise would have been impossible to obtain. The extracted profiles corresponded to the spectra of the single species in the APT/BSA mixture. In addition, the presence of the APT–BSA complex was demonstrated, and it was shown that the associated quenching of the fluorescence from the BSA protein resulted from the formation of APT–BSA complex via a static mechanism. The binding constant ( K a(ave) = 2.34 × 10 6 L mol −1 ) and the number of sites ( n = 1) were obtained by fluorescence methods as were the thermodynamic parameters (Δ H 0 , Δ S 0 and Δ G 0 ). This work suggested that the principal binding between APT to BSA was facilitated by hydrophobic interactions. The thermodynamic parameters for APT were compared to those from the structurally similar Chrysin and Wogonin molecules. It appeared that the entropy parameters were relatively more affected by the small structural changes. SFS from the interaction of BSA and APT showed that the ligand affected the conformation of BSA. The competitive interaction of APT and site makers with BSA indicated site I as the binding area of APT in BSA.

A rapid NIR method for the determination of octane number of reformate samples of Australian refined motor gasoline is described. Results of predictions using calibration sets based on ASTM full blends and actual reformate samples are presented. Interpretation of spectral data using principal component analysis facilitates the selection of a suitable analytical spectral range and demonstrates that the reformate samples may be distinguished on the basis of the geographical origins of the parent crude oils. The described method forms a basis for practical application and is a possible alternative to the standard CFR engine test method.

The interaction between fluoroquinolones (FQs), ofloxacin and enrofloxacin, and bovine serum albumin (BSA) was investigated by fluorescence and UV–vis spectroscopy. It was demonstrated that the fluorescence quenching of BSA by FQ is a result of the formation of the FQ–BSA complex stabilized, in the main, by hydrogen bonds and van der Waals forces. The Stern–Volmer quenching constant, K SV , and the corresponding thermodynamic parameters, Δ H , Δ S and Δ G , were estimated. The distance, r , between the donor, BSA, and the acceptor, FQ, was estimated from fluorescence resonance energy transfer (FRET). The effect of FQ on the conformation of BSA was analyzed with the aid of UV–vis absorbance spectra and synchronous fluorescence spectroscopy. Spectral analysis showed that the two FQs affected the conformation of the BSA but in a different manner. Thus, with ofloxacin, the polarity around the tryptophan residues decreased and the hydrophobicity increased, while for enrofloxacin, the opposite effect was observed.

This review explores the question whether chemometrics methods enhance the performance of electroanalytical methods. Electroanalysis has long benefited from the well-established techniques such as potentiometric titrations, polarography and voltammetry, and the more novel ones such as electronic tongues and noses, which have enlarged the scope of applications. The electroanalytical methods have been improved with the application of chemometrics for simultaneous quantitative prediction of analytes or qualitative resolution of complex overlapping responses. Typical methods include partial least squares (PLS), artificial neural networks (ANNs), and multiple curve resolution methods (MCR-ALS, N-PLS and PARAFAC). This review aims to provide the practising analyst with a broad guide to electroanalytical applications supported by chemometrics. In this context, after a general consideration of the use of a number of electroanalytical techniques with the aid of chemometrics methods, several overviews follow with each one focusing on an important field of application such as food, pharmaceuticals, pesticides and the environment. The growth of chemometrics in conjunction with electronic tongue and nose sensors is highlighted, and this is followed by an overview of the use of chemometrics for the resolution of complicated profiles for qualitative identification of analytes, especially with the use of the MCR-ALS methodology. Finally, the performance of electroanalytical methods is compared with that of some spectrophotometric procedures on the basis of figures-of-merit. This showed that electroanalytical methods can perform as well as the spectrophotometric ones. PLS-1 appears to be the method of practical choice if the %relative prediction error of approximately +/-10% is acceptable.

The binding interaction of the pesticide Isoprocarb and its degradation product, sodium 2-isopropylphenate, with bovine serum albumin (BSA) was studied by spectrofluorimetry under simulated physiological conditions. Both Isoprocarb and sodium 2-isopropylphenate quenched the intrinsic fluorescence of BSA. This quenching proceeded via a static mechanism. The thermodynamic parameters (DeltaH(o), DeltaS(o) and DeltaG(o)) obtained from the fluorescence data measured at two different temperatures showed that the binding of Isoprocarb to BSA involved hydrogen bonds and that of sodium 2-isopropylphenate to BSA involved hydrophobic and electrostatic interactions. Synchronous fluorescence spectroscopy of the interaction of BSA with either Isoprocarb or sodium 2-isopropylphenate showed that the molecular structure of the BSA was changed significantly, which is consistent with the known toxicity of the pesticide, i.e., the protein is denatured. The sodium 2-isopropylphenate, was estimated to be about 4-5 times more toxic than its parent, Isoprocarb. Synchronous fluorescence spectroscopy and the resolution of the three-way excitation-emission fluorescence spectra by the PARAFAC method extracted the relative concentration profiles of BSA, Isoprocab and sodium 2-isopropylphenate as a function of the added sodium 2-isopropylphenate. These profiles showed that the degradation product, sodium 2-isopropylphenate, displaced the pesticide in a competitive reaction with the BSA protein.

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) approximately 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.

A differential kinetic spectrophotometric method was researched and developed for the simultaneous determination of iron and aluminium in food samples. It was based on the direct reaction kinetics and spectrophotometry of these two metal ions with Chrome Azurol S (CAS) in ethylenediamine–hydrochloric acid buffer (pH 6.3). The results were interpreted with the use of chemometrics. The kinetic runs and the visible spectra of the complex formation reaction were studied between 540 and 750 nm every 30 s over a total period of 285 s. A set of synthetic metal mixture samples was used to build calibrations models. These were based on the spectral and kinetic two-way data matrices, which were processed separately by the radial basis function-artificial neural network (global RBF-ANN) method. The prediction performance of these models was poorer than that from the combined kinetic-spectral three-way array, which was similarly processed by the same method (% relative prediction error (RPET) = 5.6). These results demonstrate that improved predictions can be obtained from the data array, which has more information, and that appropriate chemometrics methods can enhance analytical performance of simple techniques such as spectrophotometry. Other chemometrics models were then applied: N-way partial least squares (NPLS), parallel factor analysis (PARAFAC), back propagation-artificial neural network (BP-ANN), single radial basis function-artificial neural network (RBF-ANN), and principal component neural network (PC-RBF-ANN). There was no substantial difference between the methods with the overall %RPET range being 5.0–5.8. These two values corresponded to the NPLS and BP-ANN models, respectively. The proposed method was applied for the determination of iron and aluminium in some commercial food samples with satisfactory results.

Organo-clays synthesised by the ion exchange of sodium in Wyoming Na-montmorillonite (SWy-2-MMT) with three surfactants: (a) octadecyltrimethylammonium bromide (ODTMA), formula C(21)H(46)NBr; (b) dodecyldimethylammonium bromide (DDDMA), formula C(22)H(48)BrN; and (c) di(hydrogenated tallow)dimethylammonium chloride were tested for hydrocarbon adsorption. Using diesel, hydraulic oil, and engine oil an evaluation was made of the effectiveness of the sorbent materials for a range of hydrocarbon products that are likely to be involved in land-based oil spills. It was found that the hydrocarbon sorption capacity of the organo-clays depended upon the materials and surfactants used in the organo-clay synthesis. Greater adsorption was obtained if the surfactant contained two or more hydrocarbon long chains. Extensive utilisation of chemometrics principally with the aid of MCDM methods, produced models which consistently ranked the organo-clays well above any of the competitors including commercial benchmark materials. Thus, the use of organo-clays for cleaning up oil spills is feasible due to its many desirable properties such as high hydrocarbon sorption and retention capacities, hydrophobicity. The negative effects of the use of organo-clays for oil-spill cleanup are the cost, the biodegradability, and recyclability of the organo-clays.

The binding of trazodone hydrochloride (TZH), an antidepressant drug, to bovine serum albumin (BSA) has been investigated by fluorescence spectroscopic analysis. The fluorescence emission of BSA (λem=350 nm) was quenched by TZH while that of this ligand was enhanced (λem=443 nm). The spectral behavior was consistent with the static quenching mechanism, and the apparent binding constant, K a (1.05×104 l mol−1) as well as binding site number, n (∼1), were estimated. Thermodynamic parameters obtained from the measured data at different temperatures showed that the binding of TZH to BSA involved predominantly hydrophobic interactions as well as smaller contributions from electrostatic forces. Phenylbutazone and ibuprofen were utilized as competitive markers for sites I and II, respectively, in the interaction of TZH with BSA. This competitive displacement procedure indicated that the likely binding was site I, i.e., subdomain IIA, and this was supported by the observation that up to 50% of this site ...

The interaction of quercetin-Cu(II) complex with calf thymus DNA was investigated with the use of Neutral Red (NR) dye as a spectral probe by the application of UV-vis spectrophotometry, cyclic voltammetry and synchronous fluorescence spectroscopy. The results showed that both quercetin-Cu(II) complex and the NR molecule can intercalate into the double helix of the DNA. The 2:1 quercetin:Cu(II) complex (estimated binding constant = 2.85 x 10(9)) is stabilized by intercalation in the DNA (binding constant, K[quercetin-Cu(II)-DNA] = (1.82 +/- 0.20) x 10(5) M-1), and displaces the NR dye from the NR-DNA complex in a competitive reaction. Cyclic voltammetry studies confirm the intercalation reaction and show that the ratio (K-R/K-O) of binding constants for the reduced and oxidized forms of the metal complex is 2.05. Furthermore, the alternative least squares (ALS) method was applied to resolve a complex two-way array of the absorption spectra data. This yielded the equilibrium concentration profiles of each component in the reaction (NR, NR-DNA and quercetin-Cu(II)) as well as the corresponding pure spectra. The extracted profiles showed that at equilibrium the [NR-DNA] and [NR] trends decreased and increased symmetrically, respectively, with approximately linear behaviour being observed below 10 x 10(-6) mol L-1 of the added quercetin-Cu2+ complex. Thereafter, these trends converged asymptotically. The free [quercetin-Cu(II)] trend-line at equilibrium was linear over the whole range of the complex added. It was possible to estimate the approximate value of the equilibrium constant of the exchange process (approximately 5 x 10(-1)) involving the intercalation of the quercetin-Cu(II) complex. It was also found that about 35% of the bound complex was unaccounted by the intercalation reaction, presumably being stabilized at an alternative site. (c) 2006 Elsevier B.V. All rights reserved.

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.

Constant wavelength synchronous fluorescence spectroscopy (CW-SFS), UV-visible absorption spectroscopy, and cyclic and differential pulse voltammetry were applied to investigate the competitive interaction of DNA with the bis(1,10-phenanthroline)copper(II) complex cation ([Cu(phen)(2)](2+)) and a fluorescence probe, neutral red dye (NR), in a tris-hydrogen chloride buffer (pH 7.4). The results show that both the [Cu(phen)(2)](2+)and the NR molecules can intercalate competitively into the DNA double-helix structure. The cyclic voltammetry method showed that both anodic and cathodic currents of [Cu(phen)(2)](2+) decreased on addition of the DNA and the intercalated [Cu(phen)(2)](2+)-DNA complex formed (beta = (4.14 +/- 0.24) x 10(3)). CW-SFS measurements were facilitated by the use of the three-way resolution of the CW-SFS for NR, [Cu(phen)(2)](2+), and NR-DNA. The important constant wavelength (CW) interval, Deltalambda, was shown to vary considerably when optimized (135, 58, and 98 nm for NR, NR-DNA, and [Cu(phen)(2)](2+), respectively). This approach clearly avoided the errors that otherwise would have arisen from the common assumption that Deltalambda is constant. Furthermore, a chemometrics approach, parallel factor analysis (PARAFAC), was applied to resolve the measured three-way CW-SFS data, and the results provided simultaneously the concentration information for the three reaction components, NR, [Cu(phen)(2)](2+), and NR-DNA, for the system at each equilibrium point. The PARAFAC analysis indicated that the intercalation of the [Cu(phen)(2)](2+) molecule into the DNA proceeds by exchanging with the NR probe and can be attributed to two parallel reactions. Comprehensive information was readily obtained; the replacement of the intercalated NR commenced immediately on introduction of [Cu(phen)(2)](2+), approximately 50% of NR was replaced by [Cu(phen)(2)](2+) at a concentration of 0.45 x 10(-5) mol L(-1), and nearly all of the NR was replaced at a [Cu(phen)(2)](2+) concentration of 2.50 x 10(-5) mol L(-1). This work has the potential to improve extraction of information from the fluorescence intercalator displacement (FID) assay.

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.

The name ‘chemometrics’ was first used by Svante Wold in a Swedish journal. In general, it refers to a chemical discipline that focuses on maximizing the extraction of information from data and experimental measurements with the aid of mathematical, computational, and logic methods. The data or information collected are submitted for analysis by one or more methods of chemometrics typically associated with pattern recognition, classification, or prediction.

Polypyrrole was electrochemically deposited onto cotton fabrics with the aid of a water-soluble adhesive. The conductivity and surface structure of the resultant polymer were studied, showing a templated dendritic growth on the surface of the cotton fabric. The mechanism for templated growth is discussed.

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(2)O, 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.

In this study, we have shown with the use of UV-vis spectrophotometry and the constant wavelength synchronous fluorescence spectroscopy (CW-SFS) techniques that the pharmaceutical drug, chlorpromazine hydrochloride (CPZ), intercalates into the deoxyribonucleic acid (DNA) double helix by partial exchange with the Neutral Red (NR) molecular probe. We have also demonstrated that with the use of three-way data plots, it is clear that it is important to have well-defined methodology for the selection of the important CW-SFS method parameter, Deltalambda. Ad hoc selection of this parameter, or even that based on experience, can readily lead to serious errors, which subsequently can be transferred to the interpretation of results. The said three-way plots provide a straightforward diagrammatic method, which improves the selection process of a satisfactory value for Deltalambda. Finally, we used PARAFAC modeling to resolve the complex three-way CW-SFS data, which provided simultaneously the concentration information for the three reaction components, NR, CPZ and NR-DNA, for the system at equilibrium. This PARAFAC analysis indicated that the intercalation of the CPZ molecule into the DNA proceeds by exchanging with the NR probe, and can be attributed to two parallel reactions.

This paper reports the first application of the multicriteria decision making methods, PROMETHEE and GAIA, to indoor and outdoor air quality data. Fourteen residential houses in a suburb of Brisbane, Australia were investigated for 21 air quality-influencing criteria, which included the characteristics of the houses as well as the concentrations of volatile organic compounds, fungi, bacteria, submicrometer, and supermicrometer particles in their indoor and outdoor air samples. Ranking information necessary to select one house in preference to all others and to assess the parameters influencing the differentiation of the houses was found with the aid of PROMETHEE and GAIA. There was no correlation between the rank order of each house and the health complaints of its occupants. Patterns in GAIA plots show that indoor air quality in these houses is strongly dependent on the characteristics of the houses (construction material, distance of the house from a major road, and the presence of an in-built garage). Marked similarities were observed in the patterns obtained when GAIA and factor analysis were applied to the data. This underscores the potential of PROMETHEE and GAIA to provide information that can assist source apportionment and elucidation of effective remedial measures for indoor air pollution.

Light green copper(II)-wool samples prepared under conditions of pH < 5 have been treated for short periods at about pH 11.5. The color changes and the electron spin resonance spectra of these new samples are described. All observations are con sistent with the metal ion being transferred from the carboxylate binding sites of the light green complex to new ones involving nitrogen donor groups.

An efficient method for the analysis of hydroquinone at trace levels in water samples has been developed in the form of a fluorescent probe based on graphene quantum dots (GQDs). The analytical variable, fluorescence quenching, was generated from the formation of benzoquinone intermediates, which formed during the catalytic oxidation of hydroquinone by horseradish peroxidase (HRP). In general, the reaction mechanism involved hydroquinone, as an electron acceptor, which affected the surface state of GQDs via an electron transfer effect. The water-soluble GQDs were directly prepared by the pyrolysis of citric acid and with the use of the mentioned hybrid enzyme system, the detection limit for hydroquinone was as low as 8.4 × 10−8 M. Furthermore, this analysis was almost unaffected by other phenol and quinine compounds, such as phenol, resorcinol and other quinines, and therefore, the developed GQD method produced satisfactory results for the analysis of hydroquinone in several different lake water samples.

A rapid FT-i.r. method for the determination of the flexible volatility index (FVI) of one of the major blending components (light catalytic naphtha, LCN) of Australian refined motor gasoline is presented. LCN spectra were collected in the 6000 − 1550 cm −1 range using a CaF 2 cell. With the aid of property correlation spectra, the 1700 − 1550 cm −1 region was chosen for use in analysis. A standard set was prepared from typical LCN samples. This calibration set together with the unknown samples was subjected to principal component analysis for the prediction of the FVI. The predicted results were found to be in good agreement with those obtained by the standard method [ R 2 = 0.977; standard error of estimate, SEE (FT-i.r.) = 2.65; cf. SEE (Std) = 3.0].

The versatility of FTIR spectrometry was explored by considering a variety of samples drawn from industrial applications, materials science and biomedical research. These samples included polymeric insulators, bauxite ore, clay, human hair and human skin. A range of sampling techniques suitable for these samples is discussed, in particular FTIR microscopy, FTIR emission spectroscopy, attenuated total reflectance and photoacoustic FTIR spectrometry. The power of modern data processing techniques, particularly multivariate analysis, to extract useful information from spectral data is also illustrated.

Cotton fabrics may be oxidatively bleached and damaged by electro-generated species at metal electrodes. Such fabrics were investigated by DRIFT spectroscopy. The spectra agree well with the literature, although spectra from differently damaged fabrics cannot be readily distinguished. Spectral discrimination is facilitated by principal components analysis, and the electrochemical parameters which control the fabric damage can be successfully predicted by PC regression.

Two different sets of processed cotton fabrics were investigated by FT-IR and FT-Raman spectroscopy. The chemometric technique of principal component analysis, was applied to the IR and Raman spectra from each fabric series in an attempt to discriminate between the various processing stages. The results indicate that a combination of the two techniques and chemometrics adequately discriminates between cotton samples from each processing stage.

A woollen fabric sample has been oxidized by electro-generated oxygen species produced at a platinum electrode. This treatment produced three visually discoloured or bleached regions. The areas of the fabric that were located close to the electrode surface showed dark brown discoloration. On either side of this region, bleaching of the wool was apparent to various degrees. Fabric well removed from the electrode appeared unaffected by the treatment, and was used as a reference. Such samples were analysed by the complementary techniques of FT-IR and FT-Raman spectroscopy, and the pattern recognition method of principal components analysis (PCA). The samples were successfully separated into three groups on the basis of the levels of known oxidation intermediates from cystine and other readily oxidizable amino-acid residues present in wool-keratin.

Standard chemical methods of analysis for marker alkaloids and flavonoids such as rutin, apigenin, quercetin, kaempferol, and leonurine were insufficient to discriminate the geographical origins of the complex Herba leonuri (HL) samples. This led to the research and development of a novel, quantitative HPLC fingerprint method for the simultaneous analysis of the content of important markers present in the HL samples. Seven HPLC peaks were selected and a structure was assigned to five. Fifty-six HL samples collected from three provinces, Anhui, Hubei, and Jiangxi, were analyzed by the above HPLC method and the resulting 56 × 7 matrix of the HPLC fingerprints and the seven marker compounds was submitted to principal component analysis (PCA) with consequent discrimination of the HL samples according to their geographical origins; interestingly, it was found that the highly correlated L6 (kaempferol) and L7 (apigenin) loadings were independent of the other five marker compound loadings (L1–L5). In addition, the L6 and L7 variables were related only to the Jiangxi group, while the L1–L5 loadings were associated with Jiangxi and Anhui; the Hubei cluster was not directly related to any loading. For quantitative analysis, the least squares-support vector machine (LS-SVM) calibration model was able to predict 94.4% of the samples correctly.