Simultaneous determination of plant growth regulators in environmental samples using chemometrics-assisted excitation–emission matrix fluorescence: Experimental study on the prediction quality of second-order calibration method

Impact of diverse background interferences on the alternating trilinear decomposition modeling of excitation-emission matrix fluorescence data acquired from different sample sources

Alternating trilinear decomposition (ATLD) method enables the qualitative and quantitative analysis of excitation-emission matrix fluorescence (EEMF) data acquired from complex samples. However, the impact of diverse background interferences from different sample sources on the performances of ATLD method has never been lucubrated. In this work, simulated and real EEMF data sets from different sample sources with diverse background interferences were collected and subjected to ATLD analysis. The performances of ATLD modeling individual and global EEMF data sets were comprehensively compared in terms of the resolved spectral profiles and quantitative results. It was found that ATLD method can use the same set of calibration samples to resolve and quantify multiple components of interest in multiple complex systems with diverse background interferences, regardless of individual or global modeling. The results revealed that the qualitative and quantitative results provided by ATLD method were affected neither by diversity of background interferences nor by data merging as long as the acquired EEMF data sets conform to the trilinear component model. This property of ATLD method can enrich the "second-order advantage", i.e. the term "unknown interferences" in the concept of "second-order advantage" refers to not only constant background interferences but also diverse background interferences, which will be certain to further expand the practicality of ATLD method in complex sample analysis, especially in the field of fluorescence spectroscopy.

Determination of adulterated gasoline using fluorescence emission-excitation matrices and multivariate calibration

Methanol gasoline, known as a new energy, has a certain degree of damage to automobile. The aim of this work was to identify and quantify the methanol in methanol gasoline using three-dimensional fluorescence spectroscopy technique combined with second order chemometric methods. Parallel factor analysis (PARAFAC) and self-weighted alternating trilinear decomposition (SWATLD) methods were used to analyse artificial samples. However, the obtained results by PARAFAC were not satisfactory. On the other hand, excellent prediction results were obtained when SWATLD model was applied, with recovery rate between 98.7 and 102.8%, and between 97.4 and 101.9% for two and three factor respectively. In order to verify the accuracy of the method, four real samples were predicted using SWATLD model with RMSEP between 0.1 μg/mL and 0.23 μg/mL.

Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants

Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

Chemometrics-assisted determination of amiloride and triamterene in biological fluids with overlapped peaks and unknown interferences

Background: Amiloride (AMI) and triamterene (TRI) are both potassium-saving diuretics, which are ordinarily used as doping to enhance the performance of athletes in sports. For the similar structures and complex matrices existence, chromatography and extraction are commonly employed to realize the determination of AMI and TRI in biological fluids, which are very time-consuming and laborious. Results: A novel method is presented to simultaneous interference-free determination of AMI and TRI in complex biological fluids samples using excitation–emission matrix fluorescence coupled with second-order calibration method based on alternating normalization-weight error algorithm. Conclusion: The proposed method can obtain accurate qualitative and quantitative information of the analytes, even in the presence of the interference from complex biological fluids, which requires few prior purification and separation procedures.

Simultaneous determination of 2-naphthoxyacetic acid and indole-3-acetic acid by first derivation synchronous fluorescence spectroscopy

A simple, rapid, sensitive and selective method for simultaneously determining 2-naphthoxyacetic acid (BNOA) and Indole-3-Acetic Acid (IAA) in mixtures has been developed using derivation synchronous fluorescence spectroscopy based on their synchronous fluorescence. The synchronous fluorescence spectra were obtained with Δλ=100 nm in a pH 8.5 NaH2PO4-NaOH buffer solution, and the detected wavelengths of quantitative analysis were set at 239 nm for BNOA and 293 nm for IAA respectively. The over lapped fluorescence spectra were well separated by the synchronous derivative method. Under optimized conditions, the limits of detection (LOD) were 0.003 μg/mL for BNOA and 0.012 μg/mL for IAA. This method is simple and expeditious, and it has been successfully applied to the determination of 2-naphthoxyacetic acid and indole-3-acetic acid in fruit juice samples with satisfactory results. The samples were only filtrated through a 0.45 μm membrane filter, which was free from the tedious separation procedures. The obtaining recoveries were in the range of 83.88-87.43% for BNOA and 80.76-86.68% for IAA, and the relative standard deviations were all less than 5.0%. Statistical comparison of the results with high performance liquid chromatography Mass Spectrometry (HPLC-MS) method revealed good agreement and proved that there were no significant difference in the accuracy and precision between these two methods.