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Interaction of isoprenaline (ISO) with calf-thymus DNA was studied by spectroscopic and electrochemical methods. The behavior of ISO was investigated at a glassy carbon electrode (GCE) by cyclic voltammetry (CV) and differential pulse stripping voltammetry (DPSV); ISO was oxidized and an irreversible oxidation peak was observed. The binding constant K and the stoichiometric coefficient m of ISO with DNA were evaluated. Also, with the addition of DNA, hyperchromicity of the UV-vis absorption spectra of ISO was noted, while the fluorescence intensity decreased significantly. Multivariate curve resolution-alternating least squares (MCR-ALS) chemometrics method was applied to resolve the combined spectroscopic data matrix, which was obtained by the UV-vis and fluorescence methods. Pure spectra of ISO, DNA and ISO-DNA complex, and their concentration profiles were then successfully obtained. The results indicated that the ISO molecule intercalated into the base-pairs of DNA, and the complex of ISO-DNA was formed.

High performance liquid chromatography with diode array detector (HPLC-DAD) was employed for the chromatographic fingerprint analysis and characterization of Rhizoma Curcumae, a traditional Chinese medicine (TCM). Genetic algorithm-partial least squares (GA-PLS) were applied for feature variables selection based on the 11 common peaks. Then, two chemometrics pattern recognition methods, principal component analysis (PCA) and K-nearest neighbor (KNN), were applied to investigate the mean chromatograms of Rhizoma Curcumae samples, which were obtained from four different provinces with two different processing methods. It was found that these samples can be successfully compared and distinguished according to their origin and processing methods. The results indicated that the proposed method could be efficiently used to control the quality of Rhizoma Curcumae samples and providing a reference method for chemical pattern recognition for other TCMs.

The interaction of 10-hydroxycamptothecine (HCPT) with DNA under pseudo-physiological conditions (Tris-HCl buffer of pH 7.4), using ethidium bromide (EB) dye as a probe, was investigated with the use of spectrofluorimetry, UV-vis spectrometry and viscosity measurement. The binding constant and binding number for HCPT with DNA were evaluated as (7.1 ± 0.5) × 104 M-1 and 1.1, respectively, by multivariate curve resolution-alternating least squares (MCR-ALS). Moreover, parallel factor analysis (PARAFAC) was applied to resolve the three-way fluorescence data obtained from the interaction system, and the concentration information for the three components of the system at equilibrium was simultaneously obtained. It was found that there was a cooperative interaction between the HCPT-DNA complex and EB, which produced a ternary complex of HCPT-DNA-EB. © 2011 Elsevier B.V.

A novel kinetic spectrophotometric method was developed for determination of pyrocatechol, resorcin, hydroquinone and phenol based on their inhibitory effect on the oxidation of Rhodamine B (RhB) in acid medium at pH=3.0. A linear relationship was observed between the inhibitory effect and the concentrations of the compounds. The absorbance associated with the kinetic reactions was monitored at the maximum wavelength of 557nm. The effects of different parameters such as pH, concentration of RhB and KBrO(3), and temperature of the reaction were investigated and optimum conditions were established. The linear ranges were 0.22-3.30, 0.108-0.828, 0.36-3.96 and 1.52-19.76μg mL(-1) for pyrocatechol, resorcin, hydroquinone and phenol, respectively, and their corresponding detection limits were 0.15, 0.044, 0.16 and 0.60μg mL(-1). The measured data were processed by several chemometrics methods, such as principal component regression (PCR), partial least squares (PLS) and artificial neural network (ANN), and a set of synthetic mixtures of these compounds was used to verify the established models. It was found that the prediction ability of PLS, PCR and RBF-ANN was similar, however, the RBF-ANN model did perform somewhat better than the other methods. The proposed method was also applied satisfactorily for the simultaneous determination of pyrocatechol, resorcin, hydroquinone and phenol in real water samples.

A novel differential pulse voltammetry method (DPV) was researched and developed for the simultaneous determination of Pendimethalin, Dinoseb and sodium 5-nitroguaiacolate (5NG) with the aid of chemometrics. The voltammograms of these three compounds overlapped significantly, and to facilitate the simultaneous determination of the three analytes, chemometrics methods were applied. These included classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN). A separately prepared verification data set was used to confirm the calibrations, which were built from the original and first derivative data matrices of the voltammograms. On the basis relative prediction errors and recoveries of the analytes, the RBF-ANN and the DPLS (D - first derivative spectra) models performed best and are particularly recommended for application. The DPLS calibration model was applied satisfactorily for the prediction of the three analytes from market vegetables and lake water samples.

An NIR spectroscopic method was researched and developed for the analysis of potato crisps (chips) chosen as an example of a common, cheap but complex product. Four similar types of the ‘original flavour’ potato chips from different manufacturers were analysed by NIR spectroscopy; as well, the quality parameters — fat, moisture, acid and peroxide values of the extracted oil were predicted. Principal component analysis (PCA) of the NIR data displayed the clustering of objects with respect to the type of chips. NIR spectra were rank-ordered with the use of the sparingly applied multiple criteria decision making (MCDM) ranking methods, PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluation) and GAIA (Geometrical Analysis for Interactive Aid), and a comprehensive quantitative description of the data was obtained. The four traditional parameters were predicted on the basis of the NIR spectra; the performance of the Partial Least Squares (PLS), and Kernel Partial Least Squares (KPLS) calibrations was compared with those from Least Squares-Support Vector Machines (LS-SVM) method. The LS-SVM calibrations, which model better data linearity and non-linearity, successfully predicted all four parameters. This work has demonstrated that NIR methodology with the use of chemometrics can describe comprehensively qualitative and quantitative properties of complex, processed substances as illustrated by the potato chips example, and indicated that this approach may be applied to other similar complex samples.

The new simple, cost effective and well performing differential pulse stripping voltammetry method for the simultaneous determination of antibiotics – oxytetracycline, tetracycline and chlorotetracycline was researched and developed. It depends on the reduction of these compounds at a hanging mercury drop electrode. The samples were extracted from (i) spiked animal feed, and (ii) fresh fish muscle dosed with the drugs. The voltammograms from the drug mixture produced complex, overlapping profiles, and chemometrics methods were applied for calibration modelling. The analytical linear ranges were within 0.02–0.18 μg mL −1 and the corresponding LODs were 3–5 μg L −1 for the three analytes. These values compare well with those from the HPLC and fluorescence methods in the literature. The % relative prediction errors from the verification trials were between 4% and 9% with % Recoveries being 103–107. Also, the % Recoveries of the antibiotics from animal feeds as measured by the new method were comparable with those from the HPLC analysis (85%), i.e. the method is highly competitive, especially as a screening approach.

Interaction of chlorotetracycline (CTC) with bovine serum albumin (BSA) was investigated under simulated physiological conditions by spectroscopy with the aid of multivariate curve resolution-alternating least squares (MCR-ALS). Eosin Y was selected as an alternative site I marker on the BSA to study the above molecular interaction. The binding of Eosin Y and CTC to BSA showed that CTC was displaced from CTC-BSA complex by Eosin Y, and Eosin Y-BSA complex was formed. However, the recorded fluorescence spectra of Eosin Y and Eosin Y-BSA overlapped and MCR-ALS was applied to resolve the two-way fluorescence spectra. From the resolved equilibrium concentration profiles, it was observed that Eosin Y competed with CTC in the binding process with BSA; it was also shown that the binding site of CTC on BSA was site I, and this was further confirmed by the fluorescence polarization method. Compared with some common site I markers for BSA, the fluorescence and UV-vis spectral shapes of the Eosin Y-BSA complex were quite different from that of Eosin Y, and this feature facilitated the investigation of the small molecule-BSA interaction.

Zeolite-based technology can provide a cost effective solution for stormwater treatment for the removal of toxic heavy metals under increasing demand of safe water from alternative sources. This paper reviews the currently available knowledge relating to the effect of properties of zeolites such as pore size, surface area and Si:Al ratio and the physico-chemical conditions of the system such as pH, temperature, initial metal concentration and zeolite concentration on heavy metal removal performance. The primary aims are, to consolidate available knowledge and identify knowledge gaps. It was established that an in-depth understanding of operational issues such as, diffusion of metal ions into the zeolite pore structure, pore clogging, zeolite surface coverage by particulates in stormwater as well as the effect of pH on stormwater quality in the presence of zeolites is essential for developing a zeolite-based technology for the treatment of polluted stormwater. The optimum zeolite concentration to treat typical volumes of stormwater and initial heavy metal concentrations in stormwater should also be considered as operational issues in this regard. Additionally, leaching of aluminium and sodium ions from the zeolite structure to solution were identified as key issues requiring further research in the effort to develop cost effective solutions for the removal of heavy metals from stormwater.

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE, and GAIA. Initial analyses established high, low, and moderate traffic scenarios as well as low, low to moderate, moderate, high, and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up, while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75 μm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 -300 μm, whereas metal concentrations in finer size range of1-75 μm were not affected. As practical implications, solids1 μm and organic matter from 1 -300 μm can be targeted for removal of Ni, Cu, Pb, Cd, Cr, and Zn from build-up, while organic matter from1 -300 μm can be targeted for removal of Cd, Cr, Pb, and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

This paper describes a kinetic spectrophotometric method for simultaneous determination of three cephalosporin antibiotics, cephradine, cefaclor and cefixime, with the aid of chemometrics. The method relies on their oxidation with KMnO4 to produce green manganate with different kinetic rates in alkaline medium. The proposed method was successfully applied to a pharmacokinetic study of three cephalosporin antibiotics in rabbit plasma via intravenous injections. The results indicated that the amount of cephradine, cefaclor and cefixime were reduced rapidly in rabbit blood, showing clear dose-dependency and the half-life of cefixime (160 min) was longer than those of cephradine (60 min) and cefaclor (60 min).

Interaction of a steroid drug, Ractopamine (RAC), and DNA was investigated by electroanalysis-differential pulse and cyclic voltammetry (DPV and CV), and UV-vis and fluorescence spectroscopy. DPV showed that RAC intercalated with DNA, and CV indicated that the reaction mechanism of RAC and dsDNA involved irreversible oxidation with the loss of two H+ and a transfer of two electrons. Reaction binding parameters were obtained. Pure spectra of RAC, DNA and the RAC-DNA complex, and their concentrations were extracted by multivariate curve resolution-alternating least squares method (MCR-ALS). Concentration profiles indicated quantitatively the course of the reaction.

To investigate the interaction between Ractopamine (RAC), an animal growth promoter, and bovine serum albumin (BSA), three spectroscopic approaches (fluorescence, UV–vis and FT-IR) and three different experiments (two mole-ratio and a Job's methods) were used to monitor the biological kinetic interaction procedure. The Stern–Volmer quenching constants K SV , the binding constants K a , and the number of binding sites n at 298, 301 and 304 K were evaluated by molecular spectroscopic approaches. The values of enthalpy (−13.47 kJ mol −1 ) and entropy (78.39 J mol −1 K −1 ) in the reaction indicated that RAC bound to BSA mainly by electrostatic and hydrophobic interaction. The site markers competitive experiments indicated that the binding of RAC to BSA primarily took place in site I. The spectra data matrix was further investigated with multivariate curve resolution-alternating least squares (MCR-ALS), and the concentration profiles and the pure spectra for three species (BSA, RAC and RAC-BSA) existed in the kinetic interaction procedure, as well as the apparent equilibrium constants, were obtained.

Raw and roasted Semen Cassiae seeds, a complex traditional Chinese medicine (TCM), are used as examples to research and develop a method of classification analysis based on measurements of Fourier transform infrared (FT-IR) spectral fingerprints. Eighty samples of the TCM were measured in the mid-infrared range, 400–2000 cm−1(KBr pellets), and the complex overlapping spectra were submitted for interpretation to a principal component analysis least squares support vector machine (PC-LS-SVM), kernel principal component analysis least squares support vector machine (KPC-LS-SVM), and radial basis function artificial neural networks (RBF-ANN). The LS-SVM models were developed with an RBF kernel function and a grid search technique. Training models were constructed with the use of raw and first-derivative spectra and these were then verified by another data set containing both raw and roasted spectral objects. It was demonstrated that the first-derivative data set produced the best separation of the spectral objects. In general, satisfactory analytical performance was obtained with the PC-LS-SVM, KPC-LS-SVM, and RBF-ANN training models and with the classification of the verification spectral objects. With regard to chemometrics modeling, the performance of KPC-LS-SVM was somewhat more economical than that of the PC-LS-SVM model. It would appear that the latter relatively simple model would be sufficient for application to most small to medium sized FT-IR fingerprint data sets, but with larger matrices the more complex models, such as the RBF-ANN and KPC-LS-SVM, may be more advantageous on a computational basis.

This work aimed to classify the categories (produced by different processes) and brands (obtained from different geographical origins) of Chinese soy sauces. Nine variables of physico-chemical properties (density, pH, dry matter, ashes, electric conductivity, amino nitrogen, salt, viscosity and total acidity) of 53 soy sauce samples were measured. The measured data was submitted to such pattern recognition as cluster analysis (CA), principal component analysis (PCA), discrimination partial least squares (DPLS), linear discrimination analysis (LDA) and K-nearest neighbor (KNN) to evaluate the data patterns and the possibility of differentiating Chinese soy sauces between different categories and brands. Two clusters corresponding to the two categories were obtained, and each cluster was divided into three subsets corresponding to three brands by the CA method. The variables for LDA and KNN were selected by the Fisher F-ratio approach. The prediction ability of all classifiers was evaluated by cross-validation. For the three supervised discrimination analyses, LDA and KNN gave 100% predications according to the sample category and brand.

This article discusses the outcomes of a research project on nutrients build-up on urban road surfaces. Nutrient build-up was investigated on road sites belonging to residential, industrial and commercial land use. Collected build-up samples were separated into five particle size ranges and were tested for total nitrogen (TN), total phosphorus (TP) and sub species of nutrients, namely, NO2-, NO3-, TKN and PO4(3-). Multivariate analytical techniques were used to analyse the data and to develop detailed understanding on buildup. Data analysis revealed that the solids loads on urban road surfaces are highly influenced by factors such as land use, antecedent dry period and traffic volume. However, the nutrient build-up process was found to be independent of the type of land use. It was solely dependent on the particle size of solids build-up. Most of the nutrients were associated with the particle size range150 microm. Therefore, the removal of particles below 150 microm from road surfaces is of importance for the removal of nitrogen and phosphorus from road surface solids build-up. It is also important to consider the difference in the composition of nitrogen and phosphorus build-up in the context of designing effective stormwater quality mitigation strategies.

This overview focuses on the application of chemometrics techniques to the investigation of soils contaminated by polycyclic aromatic hydrocarbons (PAHs) and metals, because these two important and very diverse groups of pollutants are ubiquitous in soils. We highlight the salient features of studies carried out in the microenvironments and recreational environments of humans in the context of the multivariate statistical techniques available across the boundaries of disciplines used in soil studies. We pay particular attention to techniques employed in the geosciences that may be effectively utilized for environmental soil studies. We also discuss classical multivariate approaches that may be used in isolation or as complementary methods to these. Chemometrics techniques widely applied in atmospheric studies for identifying sources of pollutants or for determining the importance of contributions of contaminant sources to a particular site have seen little use in soil studies, but they may be employed effectively in such investigations. Suitable programs are also available for suggesting measures of mitigation in cases of soil contamination, and we also consider these. Specific techniques reviewed include: • pattern-recognition techniques [e.g., Principal Components Analysis (PCA), Fuzzy Clustering (FC) and Cluster Analysis (CA); • geostatistical tools [e.g., variograms, Geographical Information Systems (GISs), contour mapping and kriging]; and, • source-identification and contribution-estimation methods [e.g., Positive Matrix Factorization (PMF), and PCA on Absolute Principal Component Scores (PCA/APCS)]. Mitigating measures to limit or to eliminate pollutant sources may be suggested through the use of ranking analysis and multi-criteria decision-making methods (MCDMs), mainly represented in this review by studies employing the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) and its associated graphic output, Geometrical Analysis for Interactive Aid (GAIA).

High performance liquid chromatographic (HPLC) fingerprints of Cassia seed, a traditional Chinese medicine (TCM), were developed by means of the chromatograms at two wavelengths of 238 and 282 nm. Then, the two data sets were combined into one matrix. The application of principal component analysis (PCA) for this data matrix showed that the samples were clustered into four groups in accordance with the plant sources and preparation procedures. Furthermore, partial least squares (PLS), back propagation artificial neural network (BP-ANN), and radial basis function artificial neural network (RBF-ANN) were effectively applied to predict the category of the four different samples in the test set.

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.

Photochemistry has made significant contributions to our understanding of many important natural processes as well as the scientific discoveries of the man-made world. The measurements from such studies are often complex and may require advanced data interpretation with the use of multivariate or chemometrics methods. In general, such methods have been applied successfully for data display, classification, multivariate curve resolution and prediction in analytical chemistry, environmental chemistry, engineering, medical research and industry. However, in photochemistry, by comparison, applications of such multivariate approaches were found to be less frequent although a variety of methods have been used, especially with spectroscopic photochemical applications. The methods include Principal Component Analysis (PCA; data display), Partial Least Squares (PLS; prediction), Artificial Neural Networks (ANN; prediction) and several models for multivariate curve resolution related to Parallel Factor Analysis (PARAFAC; decomposition of complex responses). Applications of such methods are discussed in this overview and typical examples include photodegradation of herbicides, prediction of antibiotics in human fluids (fluorescence spectroscopy), non-destructive in- and on-line monitoring (near infrared spectroscopy) and fast-time resolution of spectroscopic signals from photochemical reactions. It is also quite clear from the literature that the scope of spectroscopic photochemistry was enhanced by the application of chemometrics. To highlight and encourage further applications of chemometrics in photochemistry, several additional chemometrics approaches are discussed using data collected by the authors. The use of a PCA biplot is illustrated with an analysis of a matrix containing data on the performance of photocatalysts developed for water splitting and hydrogen production. In addition, the applications of the Multi-Criteria Decision Making (MCDM) ranking methods and Fuzzy Clustering are demonstrated with an analysis of water quality data matrix. Other examples of topics include the application of simultaneous kinetic spectroscopic methods for prediction of pesticides, and the use of response fingerprinting approach for classification of medicinal preparations. In general, the overview endeavours to emphasise the advantages of chemometrics’ interpretation of multivariate photochemical data, and an Appendix of references and summaries of common and less usual chemometrics methods noted in this work, is provided.

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 a...

Films found on the windows of residential buildings have been studied. The main aim of the paper was to assess the roles of the films in the accumulation of potentially toxic chemicals in residential buildings. Thus the elemental and polycyclic aromatic hydrocarbon compositions of the surface films from the glass windows of eighteen residential buildings were examined. The presence of sample amounts of inorganic elements (4.0–1.2 × 106 μg m−2) and polycyclic aromatic hydrocarbons in the films (BDL - 620.1 ng m−2) has implications for human exposure and the fate of pollutants in the urban environment. To facilitate the interpretation of the results, data matrices consisting of the chemical composition of the films and the building characteristics were subjected to multivariate data analysis methods, and these revealed that the accumulation of the chemicals was strongly dependent on building characteristics such as the type of glass used for the window, the distance from a major road, age of the building, distance from an industrial activity, number of smokers in the building and frequency of cooking in the buildings. Thus, building characteristics which minimize the accumulation of pollutants on the surface films need to be encouraged.

The binding interaction of the terazosin hydrochloride and prazosin hydrochloride with bovine serum albumin (BSA) was studied by spectrofluorimetry. Both of these two compounds quenched the fluorescence of BSA. The thermodynamic parameters (ΔH 0, ΔS 0 and ΔG 0) obtained from the fluorescence data measured at two different temperatures showed that the binding of terazosin hydrochloride to BSA involved hydrogen bonds and that of prazosin hydrochloride to BSA involved hydrophobic and electrostatic interactions. In this work, the competitive interaction of the terazosin hydrochloride and prazosin hydrochloride with BSA was studied by three-way excitation-emission fluorescence with the aid of parallel factor analysis (PARAFAC).

A procedure for the simultaneous kinetic spectrophotometric determination of aminocarb and carbaryl in vegetable and water samples was described. The method was based on the differential oxidation rate of aminocarb and carbaryl when they were reacted with the oxidant, potassium ferricyanide (K 3 Fe(CN) 6 ), in an appropriate alkaline medium. Both species were instantly oxidized, and resulted in a decrease of ferricyanide concentration. This anion has a maximum spectral absorbance at about 420 nm. Under the optimum experimental conditions, the linear ranges were 0.05–0.6 mg L −1 and 0.1–1.2 mg L −1 for aminocarb and carbaryl, respectively. The kinetic data collected were processed by chemometrics methods, such as classical least squares (CLS), partial least squares (PLS), principal components 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). These methods were applied for the prediction of the two carbamate pesticides. The results showed that the PLS and PC-RBF-ANN calibration models gave the lowest prediction errors. The proposed method was successfully applied to the simultaneous determination of aminocarb and carbaryl in vegetable and water samples, and satisfactory results were obtained.

Naturally occurring macromolecules present at the epicuticular wax/stalk tissue interface of sugarcane were investigated using near infrared spectroscopy (NIRS). Investigations of water, cellulose, and wax-cellulose interrelationships were possible using NIRS methods, where in the past many different techniques have been required. The sugarcane complex interface was used as an example of typical phenomena found at plant leaf/stalk interfaces. This detailed study showed that sugarcane cultivars exhibit spectral differences in the CH(n), water OH, and cellulose OH regions, reflecting the presence of epicuticular wax, epidermis, and ground tissue. Spectrally complex water bands (5276 cm(-1) and 7500-6000 cm(-1)) were investigated via freeze-drying experiments which revealed sequentially a complex band substructure (7500-6000 cm(-1)), a developing weak H-bonding system ( approximately 7301 cm(-1)), and strong H-bonding ( approximately 7062 cm(-1)) assigned to water-cellulose interactions. Principal component analysis techniques clarified complex band trends that developed during the desorption experiment. Bands from wax-free stalk were minimized in the 4327-4080 cm(-1) region (C--H(n) vibrational modes associated with long chain fatty compounds), while bands from the stalk tissue (particularly lignin and moisture) became more pronounced. This work is a comprehensive guide to similar studies by scientists involved in a variety of plant and fiber research fields. (c) 2009 Wiley Periodicals, Inc. Biopolymers 91: 642-651, 2009.This article was originally published online as an accepted preprint. The "Published Online" date corresponds to the preprint version. You can request a copy of the preprint by emailing the Biopolymers editorial office at biopolymers@wiley.com.

Multi-wavelength fingerprints of Cassia seed, a traditional Chinese medicine (TCM), were collected by high-performance liquid chromatography (HPLC) at two wavelengths with the use of diode array detection. The two data sets of chromatograms were combined by the data fusion-based method. This data set of fingerprints was compared separately with the two data sets collected at each of the two wavelengths. It was demonstrated with the use of principal component analysis (PCA), that multi-wavelength fingerprints provided a much improved representation of the differences in the samples. Thereafter, the multi-wavelength fingerprint data set was submitted for classification to a suite of chemometrics methods viz. fuzzy clustering (FC), SIMCA and the rank ordering MCDM PROMETHEE and GAIA. Each method highlighted different properties of the data matrix according to the fingerprints from different types of Cassia seeds. In general, the PROMETHEE and GAIA MCDM methods provided the most comprehensive information for matching and discrimination of the fingerprints, and appeared to be best suited for quality assurance purposes for these and similar types of sample.

This paper describes a simple and sensitive kinetic spectrophotometric method for the simultaneous determination of Amaranth, Ponceau 4R, Sunset Yellow, Tartrazine and Brilliant Blue in mixtures with the aid of chemometrics. The method involved two coupled reactions, viz. the reduction of iron(III) by the analytes to iron(II) in sodium acetate/hydrochloric acid solution (pH 1.71) and the chromogenic reaction between iron(II) and hexacyanoferrate(III) ions to yield a Prussian blue peak at 760 nm. The spectral data were recorded over the 500-1000 nm wavelength range every 2s for 600 s. The kinetic data were collected at 760 nm and 600 s, and linear calibration models were satisfactorily constructed for each of the dyes with detection limits in the range of 0.04-0.50 mg L(-1). Multivariate calibration models for kinetic data were established and verified for methods such as the Iterative target transform factor analysis (ITTFA), principal component regression (PCR), partial least squares (PLS), and principal component-radial basis function-artificial neural network (PC-RBF-ANN) with and without wavelet packet transform (WPT) pre-treatment. The PC-RBF-ANN with WPT calibration performed somewhat better than others on the basis of the %RPE(T) (approximately 9) and %Recovery parameters (approximately 108), although the effect of the WPT pre-treatment was marginal (approximately 0.5% RPE(T)). The proposed method was applied for the simultaneous determination of the five colorants in foodstuff samples, and the results were comparable with those from a reference HPLC method.

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 KMnO4 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.

This paper demonstrates how inferential measurements or indirect methods using near-infrared (NIR) methodology and chemometrics can be used to predict sugarcane clonal performance. Fiji leaf gall resistance is used in this study as an example. Fiji leaf gall is one of Australia's most serious sugarcane diseases, representing a significant problem in almost half of the total area under production. Traditional rating of sugarcane clones for resistance/susceptibility is difficult and expensive because of the nature of field-based methods and variable infection levels of the trials. Thus, the aim of this work was to investigate the potential of NIR spectroscopy as an alternative means to rate clones from direct measurement of sugarcane leaf spectra and to examine its ability to successfully predict traditional resistance ratings using a calibration model based on a chemometrics method such as partial least squares (PLS). A scanning electron microscopy (SEM) study of the leaf substrate was undertaken to elucidate the nature of the NIR sample site. In addition, an NIR study of freeze-dried sugarcane leaf samples resolved the heavily overlapping O–H bands present in the NIR spectrum due to water/cellulose interaction. A significant decrease in the spectral intensity between 5205 and 5393 cm−1 was observed and a similar decrease was noted in the OH stretching overtone (7114 cm−1) with an accompanying shift to lower wavenumbers. PLS modeling based on traditional ratings as the dependent variable and the corresponding NIR spectra showed satisfactory results with standard error of validation (SEV) and standard error of prediction (SEP) values being 0.98 ( R2 = 0.97) and 1.20 ( R2 = 0.88), respectively. This methodology has now been recommended for more extensive field trials.

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]

A method for determination of lactose in food samples by Osteryoung square wave voltammetry (OSWV) was developed. It was based on the nucleophilic addition reaction between lactose and aqua ammonia. The carbonyl group of lactose can be changed into imido group, and this increases the electrochemical activity in reduction and the sensitivity. The optimal condition for the nucleophilic addition reaction was investigated and it was found that in NH4Cl–NH3 buffer of pH 10.1, the linear range between the peak current and the concentration of lactose was 0.6–8.4 mg L−1, and the detection limits was 0.44 mg L−1. The proposed method was applied to the determination of lactose in food samples and satisfactory results were obtained.

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 r...

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.

A fast and accurate procedure has been researched and developed for the simultaneous determination of maltol and ethyl maltol, based on their reaction with iron(III) in the presence of o-phenanthroline in sulfuric acid medium. This reaction was the basis for an indirect kinetic spectrophotometric method, which followed the development of the pink ferroin product (λmax = 524 nm). The kinetic data were collected in the 370–900 nm range over 0–30 s. The optimized method indicates that individual analytes followed Beer’s law in the concentration range of 4.0–76.0 mg L−1 for both maltol and ethyl maltol. The LOD values of 1.6 mg L−1 for maltol and 1.4 mg L−1 for ethyl maltol agree well with those obtained by the alternative high performance liquid chromatography with ultraviolet detection (HPLC-UV). Three chemometrics methods, principal component regression (PCR), partial least squares (PLS) and principal component analysis–radial basis function–artificial neural networks (PC–RBF–ANN), were used to resolve the measured data with small kinetic differences between the two analytes as reflected by the development of the pink ferroin product. All three performed satisfactorily in the case of the synthetic verification samples, and in their application for the prediction of the analytes in several food products. The figures of merit for the analytes based on the multivariate models agreed well with those from the alternative HPLC-UV method involving the same samples.

Thermogravimetric analysis and differential scanning calorimetry have been applied to determine the adsorption of oil on selected adsorbates: sand, organo-clay and raw cotton. Thermal analysis provides evidence for the interaction and physical adsorption of the diesel oil on the adsorbates. Sand adsorbed diesel to around 33% by mass through weak physical interactions and appeared to fractionate the diesel components. The organo-clays more strongly adsorbed the diesel as evidenced by higher thermal decomposition temperatures. Differential scanning calorimetry (DSC) shows a strong interaction between the organo-clay and the diesel oil. Diesel is effectively adsorbed on organo-clay through adsorption and partitioning and is not removed from the organo-clay until significantly higher temperatures. Cotton displayed a very high adsorption/absorption capacity. A shift in the peak at 110°C (compared with pure diesel at 90°C) suggests an interaction between the diesel compounds and the cotton fibres as diesel is being retained at higher temperatures and more energy is required to evaporate the diesel. DSC was used to determine the strength of the diesel adsorption on the sand, organo-clay and cotton. The use of adsorbent materials to adsorb oil from oil spills is of great significance in modern society. One method of proving the effectiveness of an adsorbent material is through thermoanalytical techniques.

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).

Synchronous fluorescence spectroscopy (SFS) was applied for the investigation of interactions of the antibiotic, tetracycline (TC), with DNA in the presence of aluminium ions Al3+. The study was facilitated by the use of the Methylene Blue (MB) dye probe, and the interpretation of the spectral data with the aid of the chemometrics method, parallel factor analysis (PARAFAC). Three-way synchronous fluorescence analysis extracted the important optimum constant wavelength differences, deltalambda, and showed that for the TC-Al3+-DNA, TC-Al3+ and MB dye systems, the associated deltalambda values were different (deltalambda=80, 75 and 30 nm, respectively). Subsequent PARAFAC analysis demonstrated the extraction of the equilibrium concentration profiles for the TC-Al3+, TC-Al3+-DNA and MB probe systems. This information is unobtainable by conventional means of data interpretation. The results indicated that the MB dye interacted with the TC-Al3+-DNA surface complex, presumably via a reaction intermediate, TC-Al3+-DNA-MB, leading to the displacement of the TC-Al3+ by the incoming MB dye probe.

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 0-30min, 65-55% (v/v, B) during 30-35min and 55-100% (v/v, B) during 35-60min (flow rate, 1.0mlmin(-1); injection volume, 20mul; and column temperature-ambient). The detection wavelength was adjusted for maximum sensitivity at different time periods. A peak area matrix with 21objectsx14HPLC 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.

The need to find the most efficient material for the clean-up of oil/fuel spills both at sea and on land is of extreme importance. Generally, this requires material selection based upon the adsorption properties of selected sorbent materials such as sand, swelling clays, organo-clays and cotton fibres. These adsorption properties are a function of the surface characterisation where hydrophobic and oleophilic properties are essential. From BET analysis, the adsorption isotherm of the selected materials was Types II and IV in the IUPAC classification scheme. The main adsorption mechanism for these sorbents occurred on the external surface of the material in the pores or capillaries. ESEM studies indicate that cotton capillaries contribute significantly to the adsorption process of oil. In addition, the presence of surface wax on cotton–cellulose fibre facilitated the uptake by: (a) providing a relatively hydrophobic surface for sorption of organics; and (b) providing a low surface energy environment for the capillaries to aid in oil transport. Cotton fibre was observed to have several key properties such as hydrophobicity, good affinity for hydrocarbons, rapid adsorption on contact, and high adsorption and retention through interfibre capillaries. This research provides the basis for selection of cotton–cellulose fibres compared to common and other novel alternatives such as sand and organo-clays, respectively.

This paper demonstrates the crucial role of chemometrics in facilitating the knowledge transfer of a laboratory derived rating for sugarcane clonal performance (based on GC measurements) towards a rapid near infrared (NIR) spectroscopic methodology for at-field screening applications. NIR sugarcane stalk spectra were collected from 65 sugarcane clones, which were obtained from two widely different geographical regions. An exploratory principal component analysis (PCA) of an NIR spectral data matrix of the sugarcane clones showed a clear trend along PCI similar to that found from the GC measurements, with the resistant clone (Q90) being well discriminated from the susceptible one (NCo310). Biplots related the NIR spectral frequencies with the spectral objects. Cellulose and lignin bands (4248 and 4406 cm(-1) respectively) were associated with the well performing clones and epicuticular wax bands (4346 and 5781 cm(-1)) with the poorly performing ones. Several partial least squares (PLS) regression models were constructed from the spectral objects, and satisfactorily predicted the traditional sugarcane performance ratings (SEP range +/-0.7-0.9 traditional units for the verification data, and the Measured versus Predicted R-2 range 0.880-0.910). In addition, the stalk spectra were investigated with the use of multicriteria decision-making methods, PROMETHEE and GAIA. This demonstrated that the spectral objects could be ranked on the basis of the NIR information alone, and that this rank order was in agreement with traditionally determined ratings. Thus, the performance of sugarcane clones could be assessed from molecular information as from the earlier laboratory GC measurements, and therefore, can be obtained completely independently of any conventional nominal ratings scales. (C) 2006 Elsevier B.V. All rights reserved.

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...

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.

Summary Physico-chemical properties of surface water and groundwater samples from some developing countries have been subjected to multivariate analyses by the non-parametric multi-criteria decision-making methods, PROMETHEE and GAIA. Complete ranking information necessary to select one source of water in preference to all others was obtained, and this enabled relationships between the physico-chemical properties and water quality to be assessed. Thus, the ranking of the quality of the water bodies was found to be strongly dependent on the total dissolved solid, phosphate, sulfate, ammonia–nitrogen, calcium, iron, chloride, magnesium, zinc, nitrate and fluoride contents of the waters. However, potassium, manganese and zinc composition showed the least influence in differentiating the water bodies. To model and predict the water quality influencing parameters, partial least squares analyses were carried out on a matrix made up of the results of water quality assessment studies carried out in Nigeria, Papua New Guinea, Egypt, Thailand and India/Pakistan. The results showed that the total dissolved solid, calcium, sulfate, sodium and chloride contents can be used to predict a wide range of physico-chemical characteristics of water. The potential implications of these observations on the financial and opportunity costs associated with elaborate water quality monitoring are discussed.

The presence of the pesticide ethion was determined using an electroanalytical method, i.e. , linear sweep stripping voltammetry at a hanging mercury drop electrode in the Britton-Robbinson buffer with pH = 8.36, based on its reduction peak observed at - 690 mV following its alkaline hydrolysis. The experimental parameters, namely, the preconcentration potential, the preconcentration time, and the scan rate were investigated and - 300 mV ( vs. Ag/AgCl), 270 s, and 100 mV/s were selected as the optimal values, respectively. The linear relationship between the peak current and the concentration was found to be in the range of 0.02-0.16 mg/L, with a detection limit of 0.0087 mg/L. The proposed method was applied to the determination of ethion in spiked vegetable and fruit samples via a preextraction with anhydrous ethanol.

A novel 3D nano-flower-like Cu/multi-layer molybdenum disulfide composite (CuNFs/MoS2) modified glassy carbon electrode (GCE) has been successfully constructed. It was a highly sensitive and selective non-enzymatic hydrogen peroxide (H2O2) and glucose biosensor. The morphology of the obtained CuNFs-MoS2 nano-particles was investigated with the use of a scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDS). The physicochemical properties of the modified electrode were characterized at each of the construction stages with the use of an electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) techniques. The new sensor combined the advantages of MoS2 and CuNFs, and exhibited high electro-catalytic activity toward H2O2 and glucose. Quantitative analysis of H2O2 and glucose was carried out with the use of the amperometric i-t method. Linear ranges were obtained between 0.04-1.88 μM and 1.88-35.6 μM for H2O2 and 1-20 μM and 20-70 μM for glucose, and their corresponding limits of detection (LOD) were 0.021 μM and 0.32 μM. This novel sensor was successfully applied for the quantitative analysis of H2O2 in tap water and glucose in human serum samples.

Alzheimer’s disease (AD) is one of the most common age-associated pathologies, which inevitably leads to dementia and death. The aggregation of β-amyloid (Aβ) peptides on plaques in brain tissue is strongly associated with AD. The possible link between aluminum and AD still remains controversial. In this work, the aggregation of Aβ40 induced by Al(III) was investigated with the use of the fluorescence quenching method, UV–visible and circular dichroism spectroscopies as well as the atomic force microscopy technique. The results demonstrated that Al(III) induced the transformation of the initial random coil structure to the β-sheet configuration in the Aβ40 peptides. These structural changes facilitated the aggregation of Aβ40. Also, the binding constant was calculated with the use of the multivariate curve resolution-alternating least squares (MCR-ALS) chemometrics method. Keywords: Alzheimer’s disease, β-Amyloid peptides, Spectroscopy, Chemometrics

The Chinese yam ( Dioscorea opposita) is a basic food in Asia and especially China. Consequently, an uncomplicated, reliable method should be available for the analysis of the quality and origin of the yams. Thus, near-infrared (NIR) and mid-infrared (mid-IR) spectroscopic methods were developed to discriminate among Chinese yam samples collected from four geographical regions. The yam samples were analyzed also for total sugar, polysaccharides, and flavonoids. These three analytes were used to compare the performance of the analytical methods. Overlapping spectra were resolved using chemometrics methods. Such spectra were compared qualitatively using principal component analysis (PCA) and quantitatively using partial least squares (PLS) and least squares-support vector machine (LS-SVM) models. We discriminated among the four sets of yam data using PCA, and the NIR data performed somewhat better than the mid-IR data. We constructed the PLS and LS-SVM calibration models for the prediction of the three key variables, and the LS-SVM model produced better results. Also, the NIR prediction model produced better outcomes than the mid-IR prediction model. Thus, both infrared (IR) techniques performed well for the analysis of the three key analytes, and the samples were qualitatively discriminated according to their provinces of origin. Both techniques may be recommended for the analysis of Chinese yams, although the NIR technique would be preferred.

Studies of kaolinite surfaces are of industrial importance. One useful method for studying the changes in kaolinite surface properties is to apply chemometric analyses to the kaolinite surface infrared spectra. A comparison is made between the mechanochemical activation of Kiralyhegy kaolinites with significant amounts of natural quartz and the mechanochemical activation of Zettlitz kaolinite with added quartz. Diffuse reflectance infrared Fourier transform (DRIFT) spectra were analyzed using principal component analysis (PCA) and multi-criteria decision making (MCDM) methods, the preference ranking organization method for enrichment evaluations (PROMETHEE) and geometrical analysis for interactive assistance (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). The mechanochemical activation of kaolinite and quartz, through dry grinding, results in changes to the surface structure. Different grinding times were adopted to study the rate of destruction of the kaolinite and quartz structures. This relationship (i.e., grinding time) was classified using PROMETHEE and GAIA methodology.

Molecular interactions between microcrystalline cellulose (MCC) and water were investigated by attenuated total reflection infrared (ATR/IR) spectroscopy. Moisture-content-dependent IR spectra during a drying process of wet MCC were measured. In order to distinguish overlapping O–H stretching bands arising from both cellulose and water, principal component analysis (PCA) and, generalized two-dimensional correlation spectroscopy (2DCOS) and second derivative analysis were applied to the obtained spectra. Four typical drying stages were clearly separated by PCA, and spectral variations in each stage were analyzed by 2DCOS. In the drying time range of 0–41 min, a decrease in the broad band around 3390 cm−1 was observed, indicating that bulk water was evaporated. In the drying time range of 49–195 min, decreases in the bands at 3412, 3344 and 3286 cm−1 assigned to the O6H6cdots, three dots, centeredO3′ interchain hydrogen bonds (H-bonds), the O3H3cdots, three dots, centeredO5 intrachain H-bonds and the H-bonds in Iβ phase in MCC, respectively, were observed. The result of the second derivative analysis suggests that water molecules mainly interact with the O6H6cdots, three dots, centeredO3′ interchain H-bonds. Thus, the H-bonding network in MCC is stabilized by H-bonds between OH groups constructing O6H6cdots, three dots, centeredO3′ interchain H-bonds and water, and the removal of the water molecules induces changes in the H-bonding network in MCC.

The interactions of salicylic acid (SL) and two different site markers (warfarin for site I and ibuprofen for site II) with bovine serum albumin (BSA) in pH 7.4 Tris–HCl buffer have been investigated with the use of spectrofluorimetry. An equilibrium solution of BSA and SA was titrated separately with the two markers. This initial work showed that the binding of SL with BSA could be quite complex, and that there was probably a competitive interaction occurring between ibuprofen and SL. However, the spectral results were difficult to interpret clearly for the interaction of warfarin and SL in similar circumstances. To extract more information from the resolution of fluorescence excitation-emission spectra, the contour plots of the fluorescence spectra indicated that the optimal excitation wavelengths for BSA, SL, warfarin and ibuprofen were different, and were found to be at 278, 295, 306 and 218 nm, respectively. The spectral information was arranged into three-way excitation-emission fluorescence matrix (EEM) stack arrays, and was submitted for analysis by the parallel factor analysis (PARAFAC) algorithm. Firstly, it was demonstrated that the estimated excitation and emission spectral responses for SL, BSA and the site markers, warfarin and ibuprofen, agreed well with the measured spectra. Then, the interpretation of the plots of simultaneously extracted (by PARAFAC) equilibrium concentrations for the above four reactants, showed that: (i) the SL primarily appears to bind in site I but at a different location from the high-affinity binding site (HAS) for warfarin, and the interaction partially overlaps with the low-affinity binding site (LAS) for warfarin. (ii) The SL may have two LAS—one in site II where the HAS for ibuprofen is located, and the other in site I at the LAS for ibuprofen. Thus, application of the PARAFAC method for the study of competitive interaction of SL and BSA with the aid of two different site markers has extracted information unobtainable by traditional methods such as the Scatchard plot, and provided useful means of data visualization.