On line photochemically induced excitation–emission-kinetic four-way data

Four- and five-way excitation-emission luminescence-based data acquisition and modeling for analytical applications. A review

The latest advances in both theory and experimental procedures on third-order/four-way and fourth-order/five-way calibration methods are discussed. This report is focused on excitation-emission (fluorescence and phosphorescence) matrices generation, employing different variables as the third data mode (time retention in chromatography, pH gradient, fluorescence/phosphorescence lifetime, kinetics, or other chemical treatments). Fully capitalizing on the second-order advantage, it has been possible to develop appealing analytical applications in spite of the complexity of the data. Extraction of the significant chemical information about the system under study as well as the individual abundance of the contributing constituents after proper higher-order data decomposition has allowed to analytical researchers performing quantitative analysis of complex samples. The experimental works reported up to the present are introduced and discussed in order to illustrate concepts. Throughout this work, the analytical benefits achieved by modeling third- and fourth-order data are exposed, attempting to contribute to the ongoing debate in the chemometric community regarding the existence and the true nature of the third-order advantage.

Comparison of three-way and four-way calibration for the real-time quantitative analysis of drug hydrolysis in complex dynamic samples by excitation-emission matrix fluorescence

Multiway calibration in combination with spectroscopic technique is an attractive tool for online or real-time monitoring of target analyte(s) in complex samples. However, how to choose a suitable multiway calibration method for the resolution of spectroscopic-kinetic data is a troubling problem in practical application. In this work, for the first time, three-way and four-way fluorescence-kinetic data arrays were generated during the real-time monitoring of the hydrolysis of irinotecan (CPT-11) in human plasma by excitation-emission matrix fluorescence. Alternating normalization-weighted error (ANWE) and alternating penalty trilinear decomposition (APTLD) were used as three-way calibration for the decomposition of the three-way kinetic data array, whereas alternating weighted residual constraint quadrilinear decomposition (AWRCQLD) and alternating penalty quadrilinear decomposition (APQLD) were applied as four-way calibration to the four-way kinetic data array. The quantitative results of the two kinds of calibration models were fully compared from the perspective of predicted real-time concentrations, spiked recoveries of initial concentration, and analytical figures of merit. The comparison study demonstrated that both three-way and four-way calibration models could achieve real-time quantitative analysis of the hydrolysis of CPT-11 in human plasma under certain conditions. However, it was also found that both of them possess some critical advantages and shortcomings during the process of dynamic analysis. The conclusions obtained in this paper can provide some helpful guidance for the reasonable selection of multiway calibration models to achieve the real-time quantitative analysis of target analyte(s) in complex dynamic systems.

Standard addition method based on four-way PARAFAC decomposition to solve the matrix interferences in the determination of carbamate pesticides in lettuce using excitation-emission fluorescence data

The simultaneous determination of two carbamate pesticides (carbaryl and carbendazim) and of the degradation product of carbaryl (1-naphthol) in iceberg lettuce was achieved by means of PARAFAC decomposition and excitation-emission fluorescence matrices. A standard addition method for a calibration based on four-way data was applied using different dilutions of the extract from iceberg lettuce as a fourth way that provided the enough variation of the matrix to carry out the four-way analysis. A high fluorescent overlapping existed between the three analytes and the fluorophores of the matrix. The identification of two fluorescent matrix constituents through the four-way model enabled to know the matrix contribution in each dilution of the extract. This contribution was subtracted from the previous signals and a subsequent three-way analysis was carried out with the tensors corresponding to each dilution. The PARAFAC decomposition of these resulting tensors showed a CORCONDIA index equal to 99%. For the identification of the analytes, the correlation between the PARAFAC spectral loadings and the reference spectra has been used. The trueness of the method, in the concentration range studied, was guaranteed because there was neither constant nor proportional bias according to the appropriate hypothesis tests. The best recovery percentages were obtained with the data from the most diluted extract, being the results: 127.6% for carbaryl, 125.55% for carbendazim and 87.6% for 1-naphthol. When the solvent calibration was performed, the decision limit (CCα) and the capability of detection (CCβ) values, in x0=0, were 2.21 and 4.38 μg L(-1) for carbaryl, 4.87 and 9.64 μg L(-1) for carbendazim; and 3.22 and 6.38 μg L(-1) for 1-naphthol, respectively, for probabilities of false positive and false negative fixed at 0.05. However, these values were 5.30 and 10.49 μg L(-1) for carbaryl, 18.05 and 35.73 μg L(-1) for carbendazim; and 1.92 and 3.79 μg L(-1) for 1-naphthol, respectively, when the matrix-matched calibration using the most diluted extract was carried out in the recovery study.

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.