Partial least-squares with residual bilinearization for the spectrofluorimetric determination of pesticides. A solution of the problems of inner-filter effects and matrix interferents

The advantages behind the efforts of performing higher-order calibration methods - A case study

BACKGROUND

Across numerous investigations delved into second- and higher-order data, an undoubted finding emerges: models based on such data can effectively exploit the second-order advantage. However, whether further benefits can be achieved by modeling data of higher dimensions remains a subject of inquiry. In this regard, a prevailing question emerges in third-order data-based applications regarding the fundamental need to increase the data dimension and, hence, the data analysis complexity. This study aims to provide meaningful evidence to support the advantages inherent in employing third-order calibration methods despite the associated efforts, such as instrumentation and data analysis complexity.

RESULTS

This study compares the analytical performance achieved using a third-order calibration method with those obtained from most of the possible second-order calibration approaches derived from the same dataset. This work delves into the structural properties of the data, modeling limitations, and analytical characteristics associated with each model. Additionally, it includes a comprehensive statistical comparison of the models based on their recovery performance. First, the outcomes demonstrate the importance of capitalizing on all available chemical information and harnessing the full potential of data to maximize its benefits. Moreover, the results provide evidence that asserts the fact that third-order calibration methods bring the opportunity to increase the number of analytes that can be simultaneously determined, notwithstanding the need for more tedious experimental protocols, specialized instrumentation (sometimes), and quite complex data analysis.

SIGNIFICANCE

this research marks the first extensive comparison of third-order data calibration models with possible second-order calibration methods. Moreover, this work pioneers the incorporation of highly challenging non-multilinear data. The advancements detailed in this study emphasize the advantages of third-order data acquisition, notwithstanding the need for more tedious experimental protocols, specialized instrumentation (sometimes), and quite complex data analysis.

A micellar-enhanced fluorescence photoinduced four-way calibration method for the determination of multiclass pesticides in lemon juice

In this work, a four-way multivariate calibration method for the simultaneous determination of four pesticides - carbendazim (CBZ), thiabendazole (TBZ), pirimiphos-methyl (PMM), and clothianidin (CLT) - in lemon juice is presented. Third-order data were acquired by registering the photoinduced fluorescence of the analytes as excitation-emission matrices at different times of UV-light irradiation, in the presence of organized media (direct micelles) as fluorescence enhancers. The optimal experimental conditions (pH 11.5 and 32 mmol L-1 hexadecyltrimethylammonium chloride surfactant) were determined through a central composite design using the response surface methodology. The analytes were individually calibrated, except for TBZ and CBZ due to the inner filter effect of TBZ on CBZ. Test samples containing all analytes and imidacloprid (as potential interference) were analysed. PARAFAC was utilized to evaluate both the trilinearity and quadrilinearity of the third-order data and four-way arrays, respectively. PMM was successfully determined with quadrilinear PARAFAC decomposition, whereas CLT, TBZ, and CBZ were satisfactorily modelled using U-PLS/RTL due to the loss of quadrilinearity caused by different phenomena. The profitable applicability of the analytical method in the CBZ, TBZ, PMM, and CLT determination in lemon juice samples was demonstrated, achieving limits of detection below the maximum residue levels reported by the European Commission, and mean recoveries at 90 ± 5%.

Chromatographic Applications in the Multi-Way Calibration Field

In this review, recent advances and applications using multi-way calibration protocols based on the processing of multi-dimensional chromatographic data are discussed. We first describe the various modes in which multi-way chromatographic data sets can be generated, including some important characteristics that should be taken into account for the selection of an adequate data processing model. We then discuss the different manners in which the collected instrumental data can be arranged, and the most usually applied models and algorithms for the decomposition of the data arrays. The latter activity leads to the estimation of surrogate variables (scores), useful for analyte quantitation in the presence of uncalibrated interferences, achieving the second-order advantage. Recent experimental reports based on multi-way liquid and gas chromatographic data are then reviewed. Finally, analytical figures of merit that should always accompany quantitative calibration reports are described.

Green approach for simultaneous determination of multi-pesticide residue in environmental water samples using excitation-emission matrix fluorescence and multivariate calibration

Pesticides are among the most widespread organic contaminants in aquatic environments. In this work, a new green fluorescence application was proposed for the simultaneous determination of four widely employed pesticides in environmental water samples. To overcome the highly overlapped spectra within the analytes, and with the tissue matrix interferences in complex solutions, we have used the multivariate calibration methods such as parallel factor analysis (PARAFAC) and unfolded partial least squares coupled to residual bilinearization (U-PLS/RBL). These four pesticides can be identified simultaneously, and the correlation coefficients between resolved and actual spectra are all above 0.95. The second-order advantage allowed the determination of four pesticides at the ng mL^-1 level, even in the presence of humic acid (HA). The best results were obtained with the limits of detection of 1.72-18.69 for Carbendazim (CBZ), 0.30-5.19 for carbaryl (CAR), 0.35-6.32 for chlorothalonil (CHL), and 4.92-29.96 for tsumacide (TSU) (ng mL^-1), which can fully meet the quantitative detection and analysis requirements of trace pesticides in water samples. The real water sample of Bohai Seawater was used to check the performance of this approach in practical applications, which have achieved good prediction results of U-PLS/RBL. This study demonstrated the proposed method is rapid, accurate, sensitive, low detection limit, and environmentally friendly to determinate multi-pesticide residues in environmental water samples.

Simultaneous Determination of Pesticides in Fruits by Using Second-Order Fluorescence Data Resolved by Unfolded Partial Least-Squares Coupled to Residual Bilinearization

In the present work, a chemometric-assisted spectrofluorimetric method has been developed for the simultaneous determination of natural fluorescent pesticides, carbaryl, carbendazim, and thiabendazole, in orange and banana. Only a simple extraction with methanol was required as sample pretreatment. Emission-excitation fluorescence matrices were obtained and resolved by using a second-order multivariate calibration method based on unfolded partial least-squares combined with residual bilinearization (U-PLS/RBL) for achieving “second-order advantage.” In this way, pesticides were determined in fruits even in the presence of inner filter effects, background interactions, strong spectral overlapping, and unexpected components. U-PLS can cope with effects that cause trilinearity loss such as, inner filter effects, including background in the calibration set; meanwhile, RBL allows to resolve the presence of unexpected components. The extraction technique was validated against a commonly applied technique based on the use of ethyl acetate and sodium sulfate. Besides, results obtained for real samples were statistically compared with those obtained by using HPLC. LODs of 0.038, 0.054, and 0.018 mg·kg−1 and 0.044, 0.072, and 0.020 mg·kg−1 were obtained for carbaryl, carbendazim, and thiabendazole in banana and orange samples, respectively; values were in accordance with the MRLs (Maximum Residue Limits) established by different official control organizations such as National Food Safety and Quality Service (SENASA), Codex Alimentarius (based on Food and Agriculture Organization (FAO) of the United Nations and World Health Organization (WHO), and Environmental Protection Agency (EPA).

The multi-resolution capability of Tchebichef moments and its applications to the analysis of fluorescence excitation-emission spectra

Fluorescence spectroscopy with an excitation-emission matrix (EEM) is a fast and inexpensive technique and has been applied to the detection of a very wide range of analytes. However, serious scattering and overlapping signals hinder the applications of EEM spectra. In this contribution, the multi-resolution capability of Tchebichef moments was investigated in depth and applied to the analysis of two EEM data sets (data set 1 consisted of valine-tyrosine-valine, tryptophan-glycine and phenylalanine, and data set 2 included vitamin B1, vitamin B2 and vitamin B6) for the first time. By means of the Tchebichef moments with different orders, the different information in the EEM spectra can be represented. It is owing to this multi-resolution capability that the overlapping problem was solved, and the information of chemicals and scatterings were separated. The obtained results demonstrated that the Tchebichef moment method is very effective, which provides a promising tool for the analysis of EEM spectra. It is expected that the applications of Tchebichef moment method could be developed and extended in complex systems such as biological fluids, food, environment and others to deal with the practical problems (overlapped peaks, unknown interferences, baseline drifts, and so on) with other spectra.

Accurate anisotropy recovery from fluorophore mixtures using Multivariate Curve Resolution (MCR)

Anisotropy resolved multidimensional emission spectroscopy (ARMES) provides valuable insights into multi-fluorophore systems like proteins that have complex overlapping emission bands. The method combines multidimensional fluorescence, anisotropy, and chemometrics to facilitate the differentiation of fluorophores with very similar emission properties. Here, we address the critical issue of standardizing the chemometric methods required to accurately extract spectral and anisotropy information from fluorophore mixtures using two standard sample sets: perylene in glycerol, and a mixture of Erythrosin B and Phloxine B with overlapping emission but different anisotropies. We show for the first time how to accurately model component anisotropy using Multivariate Curve Resolution (MCR) from data collected using total synchronous fluorescence scan (TSFS) and Excitation Emission Matrix (EEM) measurement methods. These datasets were selected to avoid the presence of inner filter effects (IFE) or Förster resonance energy transfer (FRET) that would depolarize fluorescence emission or reduce data tri-linearity. This allowed the non-trilinear TSFS data to yield accurate component anisotropy data once modelled using the correct data augmentation strategy, however, the EEM data proved to be more accurate once optimal constraints (non-negativity and correspondence among species) were employed. For perylene (S₂) and Phloxine B which both have very weak anisotropy (<0.06), while the spectral recovery was excellent, the modelled anisotropy values were reasonably accurate (±20% of the real value) because of large relative noise contributions. However, for perylene (S₁) and Erythrosin B which have large (>0.2) anisotropies, bilinear and trilinear EEM models built using a total tri-linearity constraint, yielded solutions without any rotational ambiguities and very accurate (±4% of real value) anisotropy values. These sample systems thus provide simple and robust test systems for validating the spectral measurement and chemometric data analysis elements of ARMES.

Simultaneous determination of binary solution of triphenylmethane dyes in complex matrices onto magnetic amino-rich SWCNT using second-order calibration method

This study suggested a new method for simultaneous quantification of two dyes in complex matrices using second-order data by spectrophotometry. Second-order data was generated simply without any expensive instrument using two independent variables including wavelength and the monotonic addition of sodium dodecyl sulfate. Solid-phase extraction (SPE) based on amino-rich magnetic single-walled carbon nanotube as an adsorbent was employed prior to second-order data generation. SPE optimization was performed by Box-Behnken design, and parameters and their interaction which were dependent on the simultaneous extraction of dyes were examined. Competitive Langmuir and Freundlich isotherms for a binary system and individual dyes could all represent the equilibrium data well. The second-order data was processed by parallel factor analysis (PARAFAC and PARAFAC2) and multivariate curve resolution-alternating least squares (MCR-ALS). Figures of merit of the model including a limit of detection of 3.0 and 2.5 ng mL^-1 for crystal violet and malachite green, respectively, were estimated using the MCR-ALS method. The combination of the second-order calibration and SPE presents an easy and versatile method for determination of the mixture of two dyes in the presence of uncalibrated interferences in environmental water, synthetic, and fish samples with the recoveries of 94-104.

A road map for multi-way calibration models

A road map is proposed for the selection of a multi-way calibration model according to the data properties.

Supervised neural computing solutions for fluorescence identification of benzimidazole fungicides. Data and decision fusion strategies

Benzimidazole fungicides (BFs) are a type of pesticide of high environmental interest characterized by a heavy fluorescence spectral overlap which complicates its detection in mixtures. In this paper, we present a computational study based on supervised neural networks for a multi-label classification problem. Specifically, backpropagation networks (BPNs) with data fusion and ensemble schemes are used for the simultaneous resolution of difficult multi-fungicide mixtures. We designed, optimized and compared simple BPNs, BPNs with data fusion and BPNs ensembles. The information environment used is made up of synchronous and conventional BF fluorescence spectra. The mixture spectra are not used in the training nor the validation stage. This study allows us to determine the convenience of fusioning the labels of carbendazim and benomyl for the identification of BFs in complex multi-fungicide mixtures.

Luminescence sensors applied to water analysis of organic pollutants--an update

The development of chemical sensors for environmental analysis based on fluorescence, phosphorescence and chemiluminescence signals continues to be a dynamic topic within the sensor field. This review covers the fundamentals of this type of sensors, and an update on recent works devoted to quantifying organic pollutants in environmental waters, focusing on advances since about 2005. Among the wide variety of these contaminants, special attention has been paid polycyclic aromatic hydrocarbons, pesticides, explosives and emerging organic pollutants. The potential of coupling optical sensors with multivariate calibration methods in order to improve the selectivity is also discussed.

Simultaneous flow-injection solid-phase fluorometric determination of thiabendazole and metsulfuron methyl using photochemical derivatization

A flow-through optosensor implemented with photochemically induced fluorescence (PIF) is reported for the simultaneous determination of thiabendazole (TBZ) and metsulfuron methyl (MET). TBZ is determined by measuring its native fluorescence once retained on the solid support filling the flow-cell of a FI-system. On the other hand, a strongly fluorescent photoproduct from MET is generated on-line in micellar medium by UV irradiation and monitored in a similar way to TBZ. MET photoproduct and TBZ are separated by placing in the flow-system a minicolumn, filled with C(18) silica gel, which allows their sequential arrival to the detection area. The sorption of the species on the solid support in the detection area provides a noticeable improvement in sensitivity and selectivity when comparing with their determination in homogeneous solution. The detection limits and RSDs for TBZ and MET are 2.5 and 3.3 ng ml(-1) and 1.1 and 2.4%, respectively. The method is successfully applied to environmental water samples.

Environmental water samples analysis of pesticides by means of chemometrics combined with fluorimetric multioptosensing

A single flow-through optosensor spectrofluorimetric system is proposed for the resolution of mixtures of three pesticides, alpha-naphthol, o-phenylphenol and thiabendazole, at microg l(-1) levels using a partial least-squares (PLS) calibration approach. The sensor was developed in conjunction with a monochannel flow-injection analysis system with fluorimetric detection using C18 silicagel as an active sorbent substrate in the flow cell. By using 20% methanol-water (v:v) solution as carrier solution, the multisensor responds linearly in the measuring range without requiring additional reagents or derivatization. First derivative emission spectra of the corresponding analytes recorded during the process of retention-elution were used to provide multivariate data. The different kinetic on the retention process of the analytes on the sensing zone allows the selection of a time matrix for each analyte providing best results in the PLS approach. Accurate prediction results were obtained for the three analytes with RMSEP values of 1.86%, 3.34% and 0.50% were obtained for alpha-naphthol, o-phenylphenol and thiabendazole respectively. In the analysis of environmental waters samples, a mean recovery of 103% was obtained.

Second-Order Advantage Achieved by Unfolded-Partial Least-Squares/Residual Bilinearization Modeling of Excitation−Emission Fluorescence Data Presenting Inner Filter Effects

A second-order multivariate calibration approach, based on a combination of unfolded-partial least-squares with residual bilinearization (U-PLS/RBL), has been applied to fluorescence excitation-emission matrix data for multicomponent mixtures showing inner filter effects. The employed chemometric algorithm is the most successful one regarding the prediction of analyte concentrations when significant inner filter effects occur, even in the presence of unexpected sample components, which require strict adherence to the second-order advantage. Results for simulated fluorescence excitation-emission data are described, in comparison with the classical approach based on parallel factor analysis and other second-order algorithms, including generalized rank annihilation, bilinear least squares combined with residual bilinearization and multivariate curve resolution-alternating leastsquares. A set of experimental data was also studied, in which calibration was performed with fluorescence excitation-emission matrices for samples containing mixtures of chrysene (the analyte of interest) and benzopyrene (which produced strong inner filter effect across the useful wavelength range). Prediction was made on validation samples with a qualitative composition similar to the calibration set, and also on test samples containing an unexpected component (pyrene). In this latter case, U-PLS/RBL showed a unique success for the analysis of the calibrated component chrysene, achieving the useful second-order advantage.