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

Using multilinear regressions developed from excitation-emission matrices to estimate the wastewater content in urban streams impacted by sanitary sewer leaks and overflows

Failing sewer infrastructure introduces unknown quantities of raw wastewater into urban streams, raising human and ecological health concerns. To address this problem, we developed multilinear regressions that relate fluorescent dissolved organic matter to wastewater content. The models were constructed with the area-normalized regional volumes of excitation-emission matrices measured for mixtures of deionized water, surface water from a wastewater-impacted stream, wastewater from a sanitary sewer adjacent to the stream, and Suwannee River natural organic matter. The best performing multilinear regression had a standard error of 0.55 % wastewater. A matrix-matched calibration was used to internally validate the approach and confirm the wastewater content of select samples. The multilinear model was externally validated through (i) comparison to concentrations of contaminants of emerging concern in surface water and wastewater and (ii) extension to samples from previous campaigns that employed alternative wastewater indicators. Using the validated model, we estimated an average wastewater content of 2.4 ± 4.0 % in 165 samples collected from 14 locations in the Gwynns Falls watershed (USA) between April 2019 and April 2023. The maximum wastewater content was 35 % at a site where sanitary sewer leaks and overflows have been previously documented. The reported approach represents a cost-effective and scalable technique to estimate wastewater content in urban streams through analysis of fluorescent dissolved organic matter.

Development of 2D and 3D front face fluorescence spectroscopy for monitoring ultrasound treatment in the removal of pesticides residues from fresh lettuces at the laboratory and pilot scales

Pesticide residues in vegetables are potentially toxic components to humans and can cause serious health problems. To remove pesticide residues from fresh agricultural products and improve consumer food safety, various pesticide removal methods have been investigated over the past decades. In this study, the effectiveness of laboratory and pilot scale ultrasonic cleaning on the removal of boscalid and pyraclostrobin residues from lettuce was examined. 2D fluorescence spectroscopy, 3D fluorescence spectroscopy represented by excitation-emission matrix (EEM), and parallel factor analysis (PARAFAC) were used to characterize and discriminate the fluorescence signatures of these pesticides in the cleaning water to determine the effectiveness of the ultrasonic cleaning method as a function of the level of pesticide removal. The 2D fluorescence results showed that the rate of removal of boscalid by ultrasonics at the laboratory scale increased with the cleaning time. The ultrasonic treatment showed a higher cleaning efficiency compared to only soaking in distilled water for 10 min. The same trends were observed at the pilot scale. The EEM also showed differences in the concentration of pesticides removed by ultrasonication between the different parts of the lettuce, the concentration was higher in the upper part than the lower part. This study showed that ultrasonication is an effective technique for the removal of pesticide residues on lettuce, and it also showed the significant potential of fluorescence spectroscopy coupled with PARAFAC for the discrimination and characterization of pesticides.

Notifications on Pesticide Residues in the Rapid Alert System for Food and Feed (RASFF)

Pesticides are commonly used to protect plants against various pests and to preserve crops, but their residues can be harmful for human health. They are the third most widely reported hazard category in the European Rapid Alert System for Food and Feed (RASFF). The purpose of the study was to identify the most frequently notified pesticides in the RASFF in 1981–2020, considering: year, notification type, product category, origin country, notifying country, notification basis, distribution status and action taken. The data from the RASFF database was processed using: filtering, transposition, pivot tables and then subjected to cluster analysis: joining (tree clustering) and two-way joining methods. Pesticides were most commonly reported in fruits and vegetables and herbs and spices following border controls and rejections. The products usually came from India or Turkey and were not placed on the market or were not distributed and then destroyed. The effectiveness of the European Union border posts in terms of hazards detection and mutual information is important from the point of view of protecting the internal market and ensuring public health. It is also necessary to increase the awareness of pesticide users through training and the activity of control authorities in the use of pesticides.

Simultaneous determination of carbendazim and chlorothalonil pesticide residues in peanut oil using excitation-emission matrix fluorescence coupled with three-way calibration method

A novel fluorescence application for simultaneous determination of two common fungicide pesticides (carbendazim and chlorothalonil) in peanut oil is presented. Using the strategy of combining excitation-emission matrix (EEM) fluorescence with three-way calibration methods, the proposed approach successfully achieved quantitative analysis of carbendazim and chlorothalonil pesticide residues in peanut oil, even with highly overlapped spectra. It needs little preparation, using "mathematical separation" instead of "analytical separation" to achieve concentration prediction of target analytes in complex systems. Each analyte was performed using fluorescence spectroscopy after instrument spectral correction and scatter removal. Then the data were modeled with two three-way calibration algorithms, including alternating trilinear decomposition (ATLD) and alternating penalty trilinear decomposition (APTLD). The results indicated that APTLD performed slightly better than ATLD for this system. The carbendazim and chlorothalonil can be recognized simultaneously with the correlation coefficients all above 0.96 between resolved spectra and actual spectra. Satisfactory results have been achieved with the average recoveries (mean ± standard deviation) of carbendazim and chlorothalonil being 100.2 ± 6.7% and 99.7 ± 6.7%, respectively. Moreover, as for carbendazim and chlorothalonil, the sensitivity (SENs) are 1.50 × 10² and 3.80 × 10² mL ng^-1, the limits of detection (LODs) are 11 ng mL^-1 and 4.3 ng mL^-1, the limit of quantitation (LOQ) are 33.33 ng mL^-1 and 13.03 ng mL^-1, respectively. The above results demonstrated that the proposed method is sensitive, fast and accurate for direct quantitative analysis of multiple pesticide residues in complex matrix such as that of peanut oil.

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 several third-order correction algorithms applied to fluorescence excitation-emission-sample data array: Interference-free determination of polycyclic aromatic hydrocarbons in water pollution

Interference-free determination of polycyclic aromatic hydrocarbons (PAHs) in water pollution is proposed based on third-order correction algorithms with quadrilinear component modeling applied to the constructed four way fluorescence excitation-emission-sample data array with higher accuracy and better predictive ability than second-order (three-dimension) correction. Alternating weighted residue constraint quadrilinear decomposition (AWRCQLD), quadrilinear parallel factor analysis (4-PARAFAC), alternate penalty quadrilinear decomposition (APQLD) and alternate penalty trilinear decomposition (APTLD) are applied to acenaphthene (ANA), naphthalene (NAP) and fluorene (FLU) respectively. Fulvic acid affects PAHs determination seriously in real-world situation, so it is simulated as an interfering agent. Excitation-emission fluorescence matrixes (EEMs) of PAHs are measured at different volumes of fulvic acid simulated different interference conditions, to construct a four-way data array. After the four-way spectra data is analyzed by AWRCQLD, 4-PARAFAC, and APQLD, three-way EEMs analyzed by APTLD, results show that, on the one hand, PAHs can be measured more accurately with four-way data combined with third-order calibration than lower-order. On the other hand, AWRCQLD algorithm can reflect the superiority of third-order advantage better with higher recovery rate and smaller root mean square error, than other third-order or second-order correction algorithms.

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).

Four-dimensional data coupled to alternating weighted residue constraint quadrilinear decomposition model applied to environmental analysis: Determination of polycyclic aromatic hydrocarbons

Qualitative and quantitative analysis of polycyclic aromatic hydrocarbons (PAHs) was carried out by three-dimensional fluorescence spectroscopy combining with Alternating Weighted Residue Constraint Quadrilinear Decomposition (AWRCQLD). The experimental subjects were acenaphthene (ANA) and naphthalene (NAP). Firstly, in order to solve the redundant information of the three-dimensional fluorescence spectral data, the wavelet transform was used to compress data in preprocessing. Then, the four-dimensional data was constructed by using the excitation-emission fluorescence spectra of different concentration PAHs. The sample data was obtained from three solvents that are methanol, ethanol and Ultra-pure water. The four-dimensional spectral data was analyzed by AWRCQLD, then the recovery rate of PAHs was obtained from the three solvents and compared respectively. On one hand, the results showed that PAHs can be measured more accurately by the high-order data, and the recovery rate was higher. On the other hand, the results presented that AWRCQLD can better reflect the superiority of four-dimensional algorithm than the second-order calibration and other third-order calibration algorithms. The recovery rate of ANA was 96.5%~103.3% and the root mean square error of prediction was 0.04μgL^-1. The recovery rate of NAP was 96.7%~115.7% and the root mean square error of prediction was 0.06μgL^-1.

Determination of hydrogen sulfide and hydrogen peroxide in complex samples of milk and urine by spectroscopic standard addition data and chemometrics methods

Spectroscopic data of standard additions were collected and used to calculate the spectrum of the unknown interferent(s) based on the net analyte signal.

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.

Front-face fluorescence spectroscopy combined with second-order multivariate algorithms for the quantification of polyphenols in red wine samples

The potential of front-face fluorescence spectroscopy combined with second-order chemometric methods was investigated for the quantification of the main polyphenols present in wine samples. Parallel factor analysis (PARAFAC) and unfolded-partial least squares coupled to residual bilinearization (U-PLS/RBL) were assessed for the quantification of catechin, epicatechin, quercetin, resveratrol, caffeic acid, gallic acid, p-coumaric acid, and vanillic acid in red wines. Excitation-emission matrices of different red wine samples, without pretreatment, were obtained in front-face mode, recording emission between 290 and 450 nm, exciting between 240 and 290 nm, for the analysis of epicatechin, catechin, caffeic acid, gallic acid, and vanillic acid; and excitation and emission between 300-360 and 330-400nm, respectively, for the analysis of resveratrol. U-PLS/RBL algorithm provided the best results and this methodology was validated by an optimized liquid chromatographic coupled to diode array and fluorimetric detectors procedure, obtaining a very good correlation for vanillic acid, caffeic acid, epicatechin and resveratrol.