Removal of major interference sources in aqueous near-infrared spectroscopy techniques

This work describes a hybrid procedure for eliminating major interference sources in aqueous near-infrared (NIR) spectra, that include aqueous influence, noise, and systemic variations irrelevant to concentration. The scheme consists of two parts: extension of wavelet prism (WPe) and orthogonal signal correction (OSC). First, WPe is employed to remove variations due to aqueous absorbance and noise; then OSC is applied to remove systemic spectral variations irrelevant to concentration. Although water possesses strong absorption bands that overshadow and overlap the absorption bands of analytes, along with noise and systematic interference, successful calibration models can be generated by employing the method proposed here. We show that the elimination of major interference sources from the aqueous NIR spectra results in a substantial improvement in the precision of prediction, and reduces the required number of PLS components in the model. In addition, the strategy proposed here can be applied to various analytical data for quantitative purposes as well.     

Paradigms and paradoxes: patterns and estimation of the entropy of formation of aqueous hydrogen containing mono and polynuclear oxyanions

“Simple” energetic patterns, where simple means the use of parameters derived only from the stoichiometry of these species, are relatively rarely discussed in the literature. In addition, entropy studies have been dominated by derivation of the absolute quantity S° rather than the entropy of formation (TΔ_f S ^o). Relationships between the entropy of formation and different parameters such as negative value of the charge of the species, the number of oxygen atoms, the natural logarithm of the molecular weight, the total number of atoms and the number of central atoms that are gases were recently discussed by us for aqueous polynuclear oxyanions. As shown here hydrogen containing anions do not follow this pattern. In this study, new approaches for the estimation of the entropy of formation of aqueous hydrogen containing mono and polynuclear oxyanions are suggested, evaluated and recommended.     

The state of conservation of painted surfaces in the presence of accelerated ageing processes monitored by use of FT-Raman spectroscopy and multivariate control charts

A new method has been developed for monitoring the degradation of paintings. Two inorganic pigments (ultramarine blue and red ochre) were blended with linseed oil and spread on canvas. Each canvas was subjected to simulated accelerated ageing in the presence of typical degradation agents (UV radiation and acidic solution). Periodically the painted surfaces were analysed by FT-Raman, to investigate the status of the surface. The data obtained were analysed by principal component analysis (PCA). Finally the Shewhart and cumulative sum control charts based on the relevant principal components (PC) and the so called scores monitoring and residuals tracking (SMART) charts were built. The method based on the use of PC to describe the process was found to enable identification of the presence of relevant modification occurring on the surface of the samples studied.Electronic supplementary material Supplementary material is available for this article at     

Multivariate optimisation of the experimental conditions for determination of three methylxanthines by reversed-phase high-performance liquid chromatography

Caffeine (1,3,7-trimethylxanthine), theobromine (3,7-dimethylxanthine) and theophylline (1,3-dimethylxanthine) are the most important naturally occurring methylxanthines. Caffeine is a constituent of coffee and other beverage and included in many medicines. Theobromine and theophylline are formed as metabolites of caffeine in humans, and are also present in tea, cocoa and chocolate products.

In order to improve the chromatographic resolution (R_s) with a good analysis time, experimental designs were applied for multivariate optimisation of the experimental conditions of an isocratic reversed-phase high-performance liquid chromatographic (RP-HPLC) method used for the simultaneous determination of caffeine, theobromine and theophylline. The optimisation process was carried out in two steps using full three-level factorial designs. The factors optimised were: flow rate and mobile phase composition. Optimal conditions for the separation of the three methylxanthines were obtained using a mixture of water/ethanol/acetic acid (75:24:1%, v/v/v) as mobile phase and a flow rate of 1.0 mL min⁻¹. The RP-HPLC/UV method was validated in terms of limit of detection (LOD), limit of quantitation (LOQ), linearity, recovery and the precision, calculated as relative standard deviation (R.S.D.). In these conditions, the LOD was 0.10 μg L⁻¹ for caffeine, 0.07 μg L⁻¹ for theobromine and 0.06 μg L⁻¹ for theophylline. The proposed method is fast, requires no extraction step or derivatization and was suitable for quantification of these methylxanthines in coffee, tea and human urine samples.     

Simultaneous spectrophotometric determination of ethinylestradiol and levonorgestrel by partial least squares and principal component regression multivariate calibration

Two spectrophotometric methods for the determination of Ethinylestradiol (ETE) and Levonorgestrel (LEV) by using the multivariate calibration technique of partial least square (PLS) and principal component regression (PCR) are presented. In this study the PLS and PCR are successfully applied to quantify both hormones using the information contained in the absorption spectra of appropriate solutions. In order to do this, a calibration set of standard samples composed of different mixtures of both compounds has been designed. The results found by application of the PLS and PCR methods to the simultaneous determination of mixtures, containing 4–11 μg ml⁻¹ of ETE and 2–23 μg ml⁻¹ of LEV, are reported. Five different oral contraceptives were analyzed and the results were very similar to that obtained by a reference liquid Chromatographic method.     

Multivariate calibration techniques applied to the spectrophotometric analysis of one-to-four component systems

The UV spectrophotometric analysis of a multicomponent mixture containing paracetamol, caffeine, tripelenamine and salicylamide by using multivariate calibration methods, such as principal component regression (PCR) and partial least-squares regression (PLS), was described. The calibration set was based on 47 reference samples, consisting of quaternary, ternary, binary and single-component mixtures, with the aim to develop models able to predict the concentrations of unknown samples containing as many as one-to-four components. The calibration models were optimized by an appropriate selection of the number of factors as well as wavelength ranges to be used for building up the data matrix and excluding any information about the interfering excipients included in pharmaceutics. The PCR and PLS models were compared and their predictive performance was inferred by a successful application to the assays of synthetic mixtures and pharmaceutical formulations.     

Multivariate monitoring of soybean oil ethanolysis by FTIR

In this work, an analytical procedure was developed to monitor the ethanolysis of degummed soybean oil (DSO) using Fourier-transformed mid-infrared spectroscopy (FTIR) and methods of multivariate analysis such as principal component analysis (PCA) and partial least squares regression (PLS). The triglycerides (reagents) and ethyl esters (products) involved in ethanolysis were shown to have similar FTIR spectra. However, when the FTIR spectra derived from seven standard mixtures of triolein and ethyl oleate were treated by PCA at the region that represents the CO stretching vibration of ester groups (1700-1800 cm⁻¹), only two principal components (PC) were shown to capture 99.95% of the total spectral variance (92.37% for the former and 7.58% for the latter PC). This observation supported the development of a multivariate calibration model that was based on the PLS regression of the FTIR data. The prevision capability of this model was measured against 40 reaction aliquots whose ester content was previously determined by size exclusion chromatography. Only small discrepancies were observed when the two experimental data sets were treated by linear regression (R²=0.9837) and these deviations were attributed to the occurrence of non-modeled transient species in the reaction mixture (reaction intermediates), particularly at short reaction times. Therefore, the FTIR/PLS model was shown to be a fast and accurate method to predict reaction yields and to follow the in situ kinetics of soybean oil ethanolysis.     

Explorative data analysis of two-dimensional electrophoresis gels

Methods for classification of two-dimensional (2-DE) electrophoresis gels based on multivariate data analysis are demonstrated. Two-dimensional gels of ten wheat varieties are analyzed and it is demonstrated how to classify the wheat varieties in two qualities and a method for initial screening of gels is presented. First, an approach is demonstrated in which no prior knowledge of the separated proteins is used. Alignment of the gels followed by a simple transformation of data makes it possible to analyze the gels in an automated explorative manner by principal component analysis, to determine if the gels should be further analyzed. A more detailed approach is done by analyzing spot volume lists by principal components analysis and partial least square regression. The use of spot volume data offers a mean to investigate the spot pattern and link the classified protein patterns to distinct spots on the gels for further investigation. The explorative approach in analysis of 2-D gels makes it possible, in a fast and convenient way, to screen many gels in order to determine the protein patterns that form clusters and could be selected for further examination.     

Simultaneous determination of albumin and immunoglobulin G with fluorescence spectroscopy and multivariate calibration

A method is proposed for the simultaneous determination of albumin and immunoglobulin G (IgG1) with fluorescence spectroscopy and multivariate calibration with partial least squares regression (PLS). The influence of some instrumental parameters were investigated with two experimental designs comprising 19 and 11 experiments, respectively. The investigated parameters were excitation and emission slit, detection voltage and scan rate. When a suitable instrumental setting had been found, a minor calibration and test set were analysed and evaluated. Thereafter, a larger calibration of albumin and IgG1 was made out of 26 samples (0-42 μg ml⁻¹ albumin and 0-12.7 μg ml⁻¹ IgG1). This calibration was validated with a test set consisting of 14 samples in the same concentration range. The precision of the method was estimated by analysing two test set samples for six times each. The scan modes tested were emission scan and synchronous scan Δ60 nm. The results showed that the method could be used for determination of albumin and IgG1 (albumin, root mean square error of prediction (RMSEP) <2, relative standard error of prediction (RSEP) <6% and IgG1, RMSEP <1, RSEP <8%) in spite of the overlapping fluorescence of the two compounds. The estimated precision was relative standard deviation (R.S.D.) <1.7%. The method was finally applied for the analysis of some sample fractions from an albumin standard used in affinity chromatography.     

Study of reaction processes by in-line near-infrared spectroscopy in combination with multivariate curve resolution: Esterification of myristic acid with isopropanol

The acid-catalysed esterification of myristic acid with isopropanol was studied by using near-infrared spectroscopy (NIR) in combination with soft-modeling curve resolution (MCR) methodology with a view to establishing the effect of experimental variables on the reaction kinetics. The reaction was conducted at temperatures above the boiling point of the alcohol, with continuous addition of an isopropanol/water mixture to the reactor. Spectral and concentration profiles were determined by applying soft-modeling curve resolution methodology to a column-wise augmented data matrix containing the spectra for the pure components. MCR profiles were compared with reference values and found to depart from then by less than 3% as %RSE for concentrations and to exhibit correlation above 0.999 for spectra.The reaction kinetics as estimated from the concentration profiles was found to be pseudo-first-order. Also, the pseudo-first-order rate constant was found to depend on the flow-rate of the isopropanol/water mixture and its water content; although the constant decreased with increase in the proportion of water, a content of ca. 15% could be used without important retarding effects on the kinetics. The proposed NIR-MCR method allows the rate constant and the influence of the initial water content to be determined with a view to minimizing consumption of the raw materials and optimizing the experimental conditions.