Second- and third-order multivariate calibration: data, algorithms and applications

Application of excitation-emission matrix fluorescence combined with second-order calibration algorithm for the determination of five polycyclic aromatic hydrocarbons simultaneously in drinking

Direct determination of five polycyclic aromatic hydrocarbons including fluorene, anthracene, phenanthrene, pyrene and fluoranthene was accomplished by excitation-emission matrix fluorescence coupled with chemometric methods based on an alternating trilinear decomposition (ATLD) algorithm. A uniform design and orthogonal design are proposed for the creation of the calibration set. Results showed that no significant difference in the recoveries for each of the PAHs was observed. Thus, both of the designs can be used for the calibration set. In addition, some statistical parameters and figures of merit, such as average recovery, root-mean-square error of prediction, sensitivity, and selectivity were investigated to evalute the performance of the proposed method. The results showed that fluoranthene was the most selective, whereas fluorene was more sensitive than any other compound. This method was also employed for the determination of samples of drinking water spiked with all these PAHs. It can be observed that the results were not as satisfying as those in synthetic samples due to the negative effects of humic acid or fulvic acid in drinking water.

Simple in situ monitoring of a complex catalytic reaction network at high pressure by attenuated total reflection Fourier transform infrared spectroscopy

Attenuated total reflection (ATR) Fourier transform infrared (FT-IR) in situ measurements were performed during the catalytic hydrogenation of acetophenone under high pressure (5.0 MPa). The catalyst used was a suspension of rhodium nanoparticles in an ionic liquid. At the highest temperature used (80 degrees C), the selectivity of the hydrogenation to 1-phenylethanol dropped from 80% in the beginning of the reaction, when acetylcyclohexane was the main side product, to less than 50% after a few hours of experiment because of the consecutive hydrogenation of 1-phenylethanol to ethylcyclohexane. The evolution of the concentrations of reactant and products was quantified using flawless spectra of pure components with a classical least squares (CLS) multivariate method applied to several ranges of the mid-infrared spectra. The only variable parameters of the analysis are the concentrations of each component themselves and the baseline shift of the spectrum during the reaction. The advantage of using multivariate analysis over the analysis of a single vibrational band, as well as the limitations of this type of spectral analysis, are discussed.

Interference-free determination of and in plant samples using excitation-emission matrix fluorescence based on oxidationderivatization coupled with second-order calibration methods

A sensitive excitation-emission fluorescence method with a second-order calibration strategy is proposed to simultaneously determine abscisic acid (ABA) and gibberellin (GA) contents in extracts of leaves and buds of ginkgo. The methodology is based on the alternating normalization-weighed error (ANWE) and the parallel factor analysis (PARAFAC) algorithms, which make it possible that the ABA and GA concentration can be attained in extract of plants even in the presence of unknown interference from potential interfering matrix contaminants introduced during the simple pretreatment procedure. Satisfactory recoveries were obtained although the excitation and emission profiles of the analytes were heavily overlapped with each other and the background in the extracts. The limits of detection obtained for GA and ABA in leaf samples were 9.6 and 6.9 ng mL-1, respectively, which were in the concentration range (from hundreds to several ng g-1) for GA and ABA in leaves in different periods. Furthermore, in order to investigate the performance of the developed method, some statistical parameters and figures of merit of ANWE and PARAFAC are evaluated. The method proposed lights a new avenue to determine quantitatively phytohormones in extracts of plants with a simple pretreatment procedure, and may hold potential to be extended as a promising alternative for more practical applications in plant growth processes.

Fluorescence as a potential monitoring tool for recycled water systems: a review

A rapid, highly sensitive and selective detector is urgently required to detect contamination events in recycled water systems - for example, cross-connection events in dual reticulation pipes that recycle advanced treated sewage effluent - as existing technologies, including total organic carbon and conductivity monitoring, cannot always provide the sensitivity required. Fluorescence spectroscopy has been suggested as a potential monitoring tool given its high sensitivity and selectivity. A review of recent literature demonstrates that by monitoring the fluorescence of dissolved organic matter (DOM), the ratios of humic-like (Peak C) and protein-like (Peak T) fluorescence peaks can be used to identify trace sewage contamination in river waters and estuaries, a situation analogous to contamination detection in recycled water systems. Additionally, strong correlations have been shown between Peak T and biochemical oxygen demand (BOD) in rivers, which is indicative of water impacted by microbial activity and therefore of sewage impacted systems. Hence, this review concludes that the sensitive detection of contamination events in recycled water systems may be achieved by monitoring Peak T and/or Peak C fluorescence. However, in such systems, effluent is treated to a high standard resulting in much lower DOM concentrations and the impact of these advanced treatment processes on Peaks T and C fluorescence is largely unknown and requires investigation. This review has highlighted that further work is also required to determine (a) the stability and distinctiveness of recycled water fluorescence in relation to the treatment processes utilised, (b) the impact of matrix effects, particularly the impact of oxidation, (c) calibration issues for online monitoring, and (d) the advanced data analytical techniques required, if any, to improve detection of contamination events.

Determination of indole-3-acetic acid in soil using excitation-emission matrix fluorescence with trilinear decomposition-based calibration methods

Indole-3-acetic acid (IAA) is a phytohormone of the auxin group and is capable of coordinating the overall processes of plant growth and development. IAA is active in the very low concentration range. Therefore, it is important to quantify IAA in the low concentration range in complex system. In this work, a new spectrofluorometric method for the direct determination of IAA in soil is proposed and discussed. It combines the fluorescence excitation-emission matrices (EEMs) with second-order calibration methods based on the alternating trilinear decomposition (ATLD) algorithm and the self-weighed alternating trilinear decomposition (SWATLD) algorithm. These methodologies fully exploit the second-order advantage of the three-way fluorescence data, allowing the analyte concentrations to be quantified even in the presence of unknown fluorescent interferents. IAA recoveries in soil were determined as 100.6 +/- 3.0 and 96.9 +/- 1.1% with ATLD and SWATLD, respectively. The limits of detection obtained were 17.6 and 4.6 ng mL(-1), and the limits of quantification were 52.9 and 13.9 ng mL(-1) with ATLD and SWATLD, respectively.

Nonlinear four-way kinetic-excitation-emission fluorescence data processed by a variant of parallel factor analysis and by a neural network model achieving the second-order advantage: malonaldehyde determination in olive oil samples

Four-way data were obtained by recording the kinetic evolution of excitation-emission fluorescence matrices for the product of the Hantzsch reaction between the analyte malonaldehyde and methylamine. The reaction product, 1,4-disubstituted-1,4-dihydropyridine-3,5-dicarbaldehyde, is a highly fluorescent compound. The nonlinear nature of the kinetic fluorescence data has been demonstrated, and therefore the four-way data were processed with parallel factor analysis combined with a nonlinear pseudounivariate regression, based on a quadratic polynomial fit, and also with a recently introduced neural network methodology, based on the combination of unfolded principal component analysis, residual trilinearization, and radial basis functions. The applied chemometric strategies are not only able to adequately model the nonlinear data but also to successfully determine malonaldehyde in olive oil samples. This is possible since the experimentally recorded four-way data, modeled with the above-mentioned advanced chemometric approaches, permit the achievement of the second-order advantage. This allows us to predict the analyte concentration in a complex background, in spite of the nonlinear behavior and in the presence of uncalibrated interferences. The present work is a new example of the use of higher-order data for the resolution of a complex nonlinear system, successfully employed in the context of food chemical analysis.