Three-Way Multivariate Calibration Procedures Applied To High-Performance Liquid Chromatography Coupled with Fast-Scanning Fluorescence Spectrometry Detection. Determination of Polycyclic Aromatic Hydrocarbons in Water Samples

Combination of Liquid Chromatography with Multivariate Curve Resolution-Alternating Least-Squares (MCR-ALS) in the Quantitation of Polycyclic Aromatic Hydrocarbons Present in Paprika Samples

This work presents a strategy for quantitating polycyclic aromatic hydrocarbons (PAHs) in smoked paprika samples. For this, a liquid chromatographic method with fluorimetric detection (HPLC-FLD) was optimized. To resolve some interference co-eluting with the target analytes, the second-order multivariate curve resolution-alternating least-squares (MCR-ALS) algorithm has been employed combined with this liquid chromatographic method. Among the eight PAHs quantified (fluorene, phenanthrene, anthracene, pyrene, chrysene, benzo[a]anthracene, benzo[b]fluoranthene, and benzo[a]pyrene) by HPLC-FLD, only in the case of fluorene, pyrene, and benzo[b]fluoranthene was it necessary to apply the second-order algorithm for their resolution. Limits of detection and quantitation were between 0.015 and 0.45 mg/kg and between 0.15 and 1.5 mg/kg, respectively. Good recovery results (>80%) for paprika were obtained via the complete extraction procedure, consisting of an extraction from the matrix and the cleanup of the extract by means of silica cartridges. Higher concentrations of chrysene, benzo[a]anthracene, benzo[b]fluoranthene, and benzo[a]pyrene were found in the paprika samples, with respect to the maximal amounts allowed for other spices that are under European Regulation (EU) N° 2015/1933.

Coupled vectors resolution method for chemometric calibration with three-way data

A new second-order calibration procedure, the coupled vectors resolution (COVER) method, has been developed. The objective of the method is to seek a couple of vectors that minimize a least-squares criterion. With the knowledge indispensable for quantitation, the method yields direct solutions to various cases of second-order calibration. Moreover, it allows a statistically plausible way to make use of multisample information. In the case of multiple calibration samples, the method uses the calibration samples to resolve the profiles of the analytes in each order, and then calculates the concentrations of the analytes. This offers the advantage that unknown mixtures newly collected can be predicted in a direct manner. In the case of one calibration sample, the method provides an effective way to utilize the information of spectral profiles of the analytes. Results of simulated experiments and a real analytical example show that the proposed method produces acceptable performance in profile resolution and concentration estimation.

Quantitative determination in chromatographic analysis based on n-way calibration strategies

Chemometric techniques for calibration with three-way signals are sufficiently developed for their use in routine analysis. The advantage of the second order property (the possibility of quantifying an analyte in the presence of interferents) together with the guarantee of the uniqueness of the decomposition, what means to extract the signal corresponding only to the analyte of interest, make these calibration techniques especially useful for the quantification and identification of analytes in complex samples. This has a particular interest in the identification and quantification of banned substances or substances with a specified maximum limit. The paper describes the theory of the calibration methodology in relation to the signal order and then focuses the analysis on the three-way techniques commonly used in calibration: n-way partial least squares, multivariate curve resolution and parallel factor analysis. The figures of merit needed for the accreditation of analytical methods are analyzed from the viewpoint of n-way calibrations in chromatography.

Simple, sensitive and on-line fluorescence monitoring of photodegradation of phenol and 2-naphthol

A simple molecular fluorescence spectrometer based on a hand-held CCD spectrometer was constructed for on-line monitoring of the photodegradation of pollutants. A high-pressure Hg vapour lamp was used for the UV photodegradation and simultaneously for the fluorescence excitation. Phenol and 2-naphthol were selected as the targets for this preliminary study. Using peak fluorescence, figures of merit for monitoring these two hydroxybenzene were obtained. Degradation efficiencies with different homogeneous photocatalyst systems were investigated, including UV only, UV/H(2)O(2) and UV/Fe(3+) degradation systems. The kinetics modelling showed that their photodegradation fitted the Langmuir-Hinshelwood model. Results showed that the proposed method is potentially applicable to both on-line real-time monitoring and field analysis.

Excitation-emission matrix fluorescence spectroscopy in conjunction with multiway analysis for PAH detection in complex matrices

A field portable, single exposure excitation-emission matrix (EEM) fluorometer has been constructed and used in conjunction with parallel factor analysis (PARAFAC) to determine the sub part per billion (ppb) concentrations of several aqueous polycyclic aromatic hydrocarbons (PAHs), such as benzo(k)fluoranthene and benzo(a)pyrene, in various matrices including aqueous motor oil extract and asphalt leachate. Multiway methods like PARAFAC are essential to resolve the analyte signature from the ubiquitous background in environmental samples. With multiway data and PARAFAC analysis it is shown that reliable concentration determinations can be achieved with minimal standards in spite of the large convoluting fluorescence background signal. Thus, rapid fieldable EEM analyses may prove to be a good screening method for tracking pollutants and prioritizing sampling and analysis by more complete but time consuming and labor intensive EPA methods.

Determination of Daunomycin in Human Plasma and Urine by Using an Interference-free Analysis of Excitation-Emission Matrix Fluorescence Data with Second-Order Calibration

Daunorubicin (DNR) is a significant antineoplastic antibiotic, which is usually applied to a chemotherapy of acute lymphatic and myelogenous leukaemia. Unfortunately, cardiotoxicity research in animals has indicated that DNR is cardiotoxic. Therefore, it is important to quantify DNR in biological fluids. A new algorithm, the alternating fitting residue (AFR) method, and the traditional parallel factor analysis (PARAFAC) have been utilized to directly determine DNR in human plasma and urine. These methodologies fully exploit the second-order advantage of the employed three-way fluorescence data, allowing the analyte concentrations to be quantified even in the presence of unknown fluorescent interferents. Furthermore, in contrast to PARAFAC, more satisfactory results were gained with AFR.

Evaluation of partial least-squares with second-order advantage for the multi-way spectroscopic analysis of complex biological samples in the presence of analyte–background interactions

The combination of unfolded partial least-squares (U-PLS) with residual bilinearization (RBL) has not been properly exploited to process experimental second-order spectroscopic information, although it is able to achieve the important second-order advantage. Among other desirable properties, the technique can handle incomplete calibration information, i.e., when only certain analyte concentrations are known in the training set. It can also cope with analyte spectral changes from sample to sample, due to its latent variable structure. In this work, U-PLS/RBL has been successfully applied to experimental fluorescence excitation-emission matrix data aimed at the quantitation of analytes in complex samples: these were the antibiotic tetracycline and the anti-inflammatory salicylate, in both cases in the presence of human serum, where significant analyte-background interactions occur. The interactions of the analyte with the serum proteins modify their spectral fluorescence properties, making it necessary to employ training sets of samples where the biological background is present, possibly causing analyte spectral changes from sample to sample. The predictive ability of the studied model has been compared with that of parallel factor analysis (PARAFAC), as regards test samples containing different sera, and also other pharmaceuticals which could act as potential interferents.

Computing Sensitivity and Selectivity in Parallel Factor Analysis and Related Multiway Techniques: The Need for Further Developments in Net Analyte Signal Theory

Sensitivity and selectivity are important figures of merit in multiway analysis, regularly employed for comparison of the analytical performance of methods and for experimental design and planning. They are especially interesting in the second-order advantage scenario, where the latter property allows for the analysis of samples with a complex background, permitting analyte determination even in the presence of unsuspected interferences. Since no general theory exists for estimating the multiway sensitivity, Monte Carlo numerical calculations have been developed for estimating variance inflation factors, as a convenient way of assessing both sensitivity and selectivity parameters for the popular parallel factor (PARAFAC) analysis and also for related multiway techniques. When the second-order advantage is achieved, the existing expressions derived from net analyte signal theory are only able to adequately cover cases where a single analyte is calibrated using second-order instrumental data. However, they fail for certain multianalyte cases, or when third-order data are employed, calling for an extension of net analyte theory. The results have strong implications in the planning of multiway analytical experiments.

Second-Order Advantage Achieved with Four-Way Fluorescence Excitation−Emission−Kinetic Data Processed by Parallel Factor Analysis and Trilinear Least-Squares. Determination of Methotrexate and Leucovorin in Human Urine

Four-way fluorescence data recorded by following the kinetic evolution of excitation-emission fluorescence matrices (EEMs) have been analyzed by parallel factor analysis and trilinear least-squares algorithms. These methodologies exploit the second-order advantage of the studied data, allowing analyte concentrations to be estimated even in the presence of an uncalibrated fluorescent background. They were applied to the simultaneous determination of the components of the anticancer combination of methotrexate and leucovorin in human urine samples. Both analytes were converted into highly fluorescent compounds by oxidation with potassium permanganate, and the kinetics of the reaction was continuously monitored by recording full EEM of the samples at different reaction times. A commercial fast scanning spectrofluorometer has been used for the first time to measure the four-way EEM kinetic data. The rapid scanning instrument allows the acquisition of a complete EEM in 12 s at a wavelength scanning speed of 24 000 nm/min. The emission spectra were recorded from 335 to 490 nm at 5-nm intervals, exciting from 255 to 315 nm at 6-nm intervals. Ten successive EEMs were measured at 72-s intervals, to follow the fluorescence kinetic evolution of the mixture components. Good recoveries were obtained in synthetic binary samples and also in spiked urine samples. The excitation, emission, and kinetic time profiles recovered by both chemometric techniques are in good agreement with experimental observations.

An improved trilinear decomposition algorithm based on a Lagrange operator

An improved trilinear decomposition algorithm based on a Lagrange operator (LO) is developed in this paper, which introduces a Lagrange operator and penalty terms in the loss function to improve the performance of the algorithm. Compared to the traditional parallel factor (PARAFAC) algorithm, the algorithm not only may converge much faster, but also overcome the sensibility to estimate the number of components. A set of simulated and measured excitation/emission fluorescence data were treated by both the proposed and traditional PARAFAC algorithm to compare their efficiencies. The analytical results obtained with real chemical system containing aspirin and its metabolic products show that the trilinear decomposition methodology is a promising tool to obtain spectral and composition information from mixtures without chemical separation.

Fast-scanning fluorescence spectroscopy as a detection system in liquid chromatography for confirmatory analysis of flumequine and oxolinic acid

Oxolinic acid and flumequine were analysed by reversed-phase liquid chromatography after extraction from the sample matrix with dichloromethane and partitioning with NaOH. The detection system consisted of a fast-scanning fluorescence detector, which provides the full spectra of the eluting peaks and can thus be used to confirm the identity of analytes. Determination was performed by partial least squares (PLS) and three-way PLS over the three-dimensional data, i.e. fluorescence intensity versus retention time and excitation wavelength. In both cases, similar results, with prediction errors around 4%, were obtained. The method was successfully applied to the analysis of salmon, pork and chicken muscle spiked up to 300 ng g(-1).

Three-way analysis of fluorescence spectra of polycyclic aromatic hydrocarbons with quenching by nitromethane

The application of trilinear decomposition (TLD) to the analysis of fluorescence excitation-emission matrices of mixtures of polycyclic aromatic hydrocarbons (PAHs) is described. The variables constituting the third-order tensor are excitation wavelength, emission wavelength, and concentration of a fluorescence quencher (nitromethane). The addition of a quencher to PAH mixtures selectively reduces the fluorescence intensity of mixture components according to the Stern-Volmer equation. TLD allows the three-way matrix to be decomposed to give unique solutions for the excitation spectrum, emission spectrum, and quenching profiles for each component. The availability of spectra and calculated Stern-Volmer constants can aid in the identification of unknown components. Preprocessing of the data to correct for Rayleigh/Raman scatter and primary absorption by the quencher is necessary. Both three-component (anthracene, pyrene, 1-methylpyrene) and four-component (fluoranthene, anthracene, pyrene, 2,3-benzofluorene) synthetic mixtures are successfully resolved by TLD using quencher concentrations up to 100 mM. Results are compared using both alternating least-squares and direct trilinear decomposition algorithms. The reproducibility of extracted Stern-Volmer constants is determined from replicate experiments. To illustrate the application of TLD to a real sample, a chromatographic cut from the analysis of a light gas oil sample was used. Analysis of the TLD extracted spectra and quenching constants suggests the presence of three classes of polycyclic aromatic hydrocarbons consistent with data from a second dimension of chromatography and mass spectrometry.

Determination of naphthalenesulfonates in water by on-line ion-pair solid-phase extraction and ion-pair liquid chromatography with fast-scanning fluorescence detection

A fast analytical method for quantifying a mixture of 12 naphthalenesulfonates and naphthalenedisulfonates has been developed. This method consists of on-line ion-pair solid-phase extraction with PLRP-s sorbent and ion-pair liquid-chromatography using fast-scanning fluorescence spectrometer as a detection system and multivariate calibration. As complete separation is unnecessary, the compounds were analysed in isocratic conditions and the chromatographic analysis took only 25 min. Three-way partial least-squares (PLS) was used to carry out multivariate calibration for spiked tap water. In these conditions, quantification limits were between 0.01 and 3 microg x l(-1). Repeatability was also evaluated and relative standard deviations (n=3) were between 0.5 and 4, depending on the compound. Finally, spiked tap and Ebro river waters were analysed to evaluate prediction capability of the method.

Reversed-phase liquid chromatographic separation of complex samples by optimizing temperature and gradient time II. Two-run assay procedures

By optimizing column temperature T and gradient time tG, complex samples can often be separated by means of reversed-phase high-performance liquid chromatography (RP-LC). Conclusions reached in Part I suggest that the complete separation of such samples will be difficult, however, when more than 15-20 components are present in the sample. An alternative approach is to carry out two separations with different conditions (T, tG) in each run. The combination of results from these two runs then allows the total analysis of the sample, providing that every sample component is adequately resolved in one run or the other. Examples of this approach, carried out by means of computer simulation, are shown here for several samples of varying complexity. Also considered is the ability of a single separation where T and tG are optimized to enable the separation and analysis of one or more individual sample components from complex mixtures (e.g., drugs in animal plasma), including the resolution of isomeric compounds from each other.