One-step purification/extraction method to access glyphosate, glufosinate, and their metabolites in natural waters

Basic research for identification and classification of organophosphorus pesticides in water based on ultraviolet-visible spectroscopy information

In this study, the goal was to develop a method for detecting and classifying organophosphorus pesticides (OPPs) in bodies of water. Sixty-five samples with different concentrations were prepared for each of the organophosphorus pesticides, namely chlorpyrifos, acephate, parathion-methyl, trichlorphon, dichlorvos, profenofos, malathion, dimethoate, fenthion, and phoxim, respectively. Firstly, the spectral data of all the samples was obtained using a UV-visible spectrometer. Secondly, five preprocessing methods, six manifold learning methods, and five machine learning algorithms were utilized to build detection models for identifying OPPs in water bodies. The findings indicate that the accuracy of machine learning models trained on data preprocessed using convolutional smoothing + first-order derivatives (SG + FD) outperforms that of models trained on data preprocessed using other methods. The backpropagation neural network (BPNN) model exhibited the highest accuracy rate at 99.95%, followed by the support vector machine (SVM) and convolutional neural network (CNN) models, both at 99.92%. The extreme learning machine (ELM) and K-nearest neighbors (KNN) models demonstrated accuracy rates of 99.84% and 99.81%, respectively. Following the application of a manifold learning algorithm to the full-wavelength data set for the purpose of dimensionality reduction, the data was then visualized in the first three dimensions. The results demonstrate that the t-distributed domain embedding (t-SNE) algorithm is superior, exhibiting dense clustering of similar clusters and clear classification of dissimilar ones. SG + FD-t-SNE-SVM ranks highest among the feature extraction models in terms of performance. The feature extraction dimension was set to 4, and the average classification accuracy was 99.98%, which slightly improved the prediction performance over the full-wavelength model. As shown in this study, the ultraviolet-visible (UV-visible) spectroscopy system combined with the t-SNE and SVM algorithms can effectively identify and classify OPPs in waterbodies.

Synthesis of weak cation exchange/C18 bifunctional magnetic polymers for pretreatment and determination of glufosinate and its two metabolites in plasma samples

This study focuses on the purification and detection of glufosinate (GLUF) and its metabolites N-acetyl GLUF and MPP in plasma samples. A Dikma Polyamino HILIC column was used for the effective retention and separation of GLUF and its metabolites, and the innovative addition of a low concentration of ammonium fluoride solution to the mobile phase effectively improved the detection sensitivity of the target analytes. Monodisperse core-shell weak cation exchange (WCX)/C18 bifunctional magnetic polymer composites (Fe3O4@WCX/C18) were prepared in a controllable manner, and their morphology and composition were fully characterized. The Fe3O4@WCX/C18 microspheres were used as a magnetic solid-phase extraction (MSPE) adsorbent for the sample purification and detection of GLUF and its metabolites in plasma samples combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS). The purification conditions of Fe3O4@WCX/C18 microspheres for GLUF and its metabolites in spiked plasma samples were optimized to achieve the best MSPE efficiency. The purification mechanisms of the target analytes in plasma samples include electrostatic attraction and hydrophobic interactions. Furthermore, the effect of the molar ratio of the two functional monomers 4-VBA and 1-octadecene in the adsorbent was optimized and it shows that the bifunctional components WCX/C18 have a synergistic effect on the determination of GLUF and its metabolites in plasma samples. In addition, the present study compared the purification performance of the Fe3O4@WCX/C18 microsphere-based MSPE method with that of the commercial Oasis WCX SPE method, and the results showed that the Fe3O4@WCX/C18 microsphere-based MSPE method established in this work had a stronger ability to remove matrix interferences. Under optimal purification conditions, the recoveries of GLUF and its metabolites in plasma were 87.6-111 % with relative standard deviations (RSDs) ranging from 0.2 % to 4.8 %. The limits of detection (LODs, S/N≥3) and limits of quantification (LOQs, S/N≥10) were 0.10-0.18 μg/L and 0.30-0.54 μg/L, respectively. The MSPE-LC-MS/MS method developed in this study is fast, simple, accurate and sensitive and can be used to confirm GLUF intoxication based not only on the detection of the GLUF prototype but also on the detection of its two metabolites.

Validation and Application of UPLC-MS/MS Method to Analysis of Glyphosate and its Metabolites in Water

A method was developed to determine glyphosate and their metabolites in water. The widespread use of this herbicide in agricultural activities worldwide, despite the reported adverse effects on both the environment and health, is a cause for concern and makes it necessary to monitor its presence through a method that guarantees the determination at trace levels. A direct extraction of the analytes with phosphate buffer was performed with subsequent derivatization with 9-fluorenylmethyl chloroformate. The quantification was determined by Ultra Performance Liquid Chromatography-tandem mass spectrometer. The method was validated through the following parameters: selectivity, detection and quantification limits, linearity, accuracy, precision and uncertainty. The average recoveries ranged between 94.08 and 103.31%. Additionally, detection limits from 0.396 to 0.433 μg/L, and the quantification limit was 5.0 μg/L for all the analytes evaluated. In terms of linearity and precision, the results obtained were in the ranges considered adequate (R2 ≥ 0.99 and CV ≤ 20%), the estimated expanded uncertainty was 12.95, 11.15 and 13.83% for glyphosate, aminomethylphosphonic acid and glufosinate, respectively. This method was successfully applied for the determination of the target analytes in irrigation water samples, detecting concentrations of aminomethylphosphonic acid over limit detection for some sampling sites.

Development and inter-laboratory validation of analytical methods for glufosinate and its two metabolites in foods of plant origin

Glufosinate is widely used to control various weeds. Glufosinate and its main metabolites have become the focus of attention because of their high water solubility and persistence in aquatic systems. Quantification of the agrochemical product and its metabolite residues is essential for the safety of agricultural products. In this study, a highly specific, simple method was developed to directly determine glufosinate and its metabolite residues in 21 plant origin foods by liquid chromatography with tandem mass spectrometry (LC-MS/MS), and it was validated on 11 foods in five laboratories. Finally, the repeatability limit, reproducibility limit, and uncertainty of the method were calculated based on these validated data and used to support the more accurate detection results. Four different chromatographic columns were used to analyze three target compounds, and the anionic polar pesticide column showed the optimum separation and peak shape. Composition of the mobile phase, extraction solvent, and the clean-up procedure were optimized. The developed method was validated on 21 plant origin foods. The average recoveries were 74-115% for all matrices. The validation results of five laboratories showed this method had a good repeatability (RSDr < 9.5%) and reproducibility (RSDR < 18.9%). The method validation parameters met the requirements of guidance established by the European Union (EU) and China for pesticide residue analysis. This methodology can be used for a routine monitoring that performs well for glufosinate and its metabolite residues.

Investigation of the performance of activated carbon cloth to remove glyphosate, glufosinate, aminomethylphosphonic acid and bialaphos from aqueous solutions by adsorption/electrosorption

The present study investigates the removal of glyphosate, glufosinate, aminomethylphosphonic acid and bialaphos herbicides from their 5 × 10^-5 M aqueous solutions onto activated carbon cloth by adsorption and electrosorption. Analysis of these highly polar herbicides was achieved by UV-visible absorbance measurements, after derivatization with 9-fluorenylmethyloxycarbonyl chloride. The limit of quantification values of glyphosate, glufosinate, aminomethylphosphonic acid and bialaphos were 1.06 × 10^-6 mol L^-1, 1.38 × 10^-6 mol L^-1, 1.32 × 10^-6 mol L^-1 and 1.08 × 10^-6 mol L^-1, respectively. Glyphosate, glufosinate, aminomethylphosphonic acid and bialaphos were removed from their aqueous solutions with higher efficiencies by means of electrosorption (78.2%, 94.9%, 82.3% and 97%, respectively) than of open-circuit adsorption (42.5%, 22%, 6.9% and 81.8%, respectively). Experimental kinetic data were fitted to pseudo-first order and pseudo-second order kinetic models. It was determined that pseudo-second order kinetic model represents experimental data better with satisfactory coefficient of determination, r² (> 0.985) and normalized percent deviation, P (< 5.15) values. Adsorption isotherm data were treated according to Freundlich and Langmuir isotherm models. Based on the r² (> 0.98) and P (< 5.9) values, it was found that experimental data well fitted to Freundlich isotherm model. Adsorption capacities of activated carbon cloth for glyphosate, glufosinate, aminomethylphosphonic acid and bialaphos, expressed in terms of Freundlich constant, were calculated as 20.31, 118.73, 239.33 and 30.68 mmol g^-1, respectively. The results show that the studied ACC can be used in home/business water treatment systems as an adsorbent due to its high adsorption capacity.

A Novel Fluorescent Sensor Based on Aptamer and qPCR for Determination of Glyphosate in Tap Water

Glyphosate (GLYP) is a broad-spectrum, nonselective, organic phosphine postemergence herbicide registered for many food and nonfood fields. Herein, we developed a biosensor (Mbs@dsDNA) based on carboxylated modified magnetic beads incubated with NH2-polyA and then hybridized with polyT-glyphosate aptamer and complementary DNA. Afterwards, a quantitative detection method based on qPCR was established. When the glyphosate aptamer on Mbs@dsDNA specifically recognizes glyphosate, complementary DNA is released and then enters the qPCR signal amplification process. The linear range of the method was 0.6 μmol/L−30 mmol/L and the detection limit was set at 0.6 μmol/L. The recoveries in tap water ranged from 103.4 to 104.9% and the relative standard deviations (RSDs) were <1%. The aptamer proposed in this study has good potential for recognizing glyphosate. The detection method combined with qPCR might have good application prospects in detecting and supervising other pesticide residues.

Evaluation of pesticide pollution in the Gualeguay Basin: An extensive agriculture area in Argentina

The current agricultural production model was established in the 1990s based on the use of genetically modified organisms and agrochemicals, mainly pesticides. Despite pesticide spread and prevalence, data on the associated concentrations in surface watercourses are comparatively scarce. The aim of this work was to evaluate to what extent the >20 years of agricultural activity with the use of pesticides has impacted on the Gualeguay-River basin, with respect to the different stream orders: the tributary streams and main channel. Thirteen sites within the lower Gualeguay basin were sampled once every season (autumn, winter, spring, and summer) in 2017-2018. The samples were analyzed by gas chromatography time-of-flight mass-spectrometry (GC-TOF-MS) and ultraperformance liquid chromatography tandem mass-spectrometry (UPLC-MS/MS). The most frequently detected pesticide was glyphosate along with its metabolite (aminomethyl)phosphonic acid (AMPA), at 82 % and 71 % of surface water samples and 97 % and 92 % of bottom sediments, respectively; followed by atrazine in 73 % of the water samples. The concentrations of these compounds, each in their respective matrices, did not present sufficient statistically significant differences for differentiating a tributary stream from the main channel. Regardless of glyphosate's affinity for the suspended particulate and bottom sediments, over the entire basin the soluble fraction contributed on average to >80 % of the total concentration in surface water. Despite not being so frequently detected, certain insecticides, mostly deltamethrin, were likewise detected at concentrations above their water-quality guidelines for the protection of aquatic life, even in samples from the main channel. Upon comparison of the pesticide profiles of extensive- and horticultural-production systems in the country, atrazine emerged as a prime candidate to be used as a tracer of extensive agriculture contamination in the environment. Further research is required to establish to what degree pesticides used in agriculture and mobilized by watercourses have an impact on their associated wetland ecosystems.

Determination of Glyphosate, Glufosinate, and Their Major Metabolites in Tea Infusions by Dual-Channel Capillary Electrophoresis following Solid-Phase Extraction

In this study, two analytical procedures were developed and validated using dual-channel capillary electrophoresis-coupled contactless conductivity detection (CE-C4D) followed by solid-phase extraction (SPE) for simultaneous determination of glyphosate (GLYP), glufosinate (GLUF), and their two major metabolites, aminomethylphosphonic acid (AMPA) and 3-(methylphosphinico) propionic acid (MPPA), respectively, in a popular beverage such as tea infusions. GLYP, GLUF, and AMPA were analyzed in the first channel using background electrolyte (BGE) of 1 mM histidine (His) adjusted to pH 2.75 by acetic acid (Ace). In contrast, MPPA was quantified in the second channel with a BGE of 30 mM His adjusted to pH 6.7 by 3-(N-morpholino) propanesulfonic acid (MOPS) and 10 µM of cetyltrimethylammonium bromide (CTAB). In addition, the samples of tea infusions were treated using SPE with 10 mL of 0.5 mM HCl in methanol as eluent. At the optimized conditions, the method detection limit (MDL) of GLYP, GLUF, AMPA, and MPPA is 0.80, 1.56, 0.56, and 0.54 μg/l, respectively. The methods were then applied to analyze four target compounds in 16 samples of tea infusions. GLYP was found in two infusion samples of oolong tea with concentrations ranging from 5.34 to 10.74 µg/L, and GLUF was recognized in three samples of green tea infusion in the range of 45.1-53.9 µg/L.