Investigation of neonicotinoid pesticides in Slovenian honey by LC-MS/MS

Determination of twelve neonicotinoid pesticides in chili using an improved QuEChERS method with UPLC-Q-TOF/MS

In this study, a QuEChERS method based on citrate was developed and utilized for the analysis of twelve neonicotinoid pesticides in fresh red chilies, fresh green chilies, and dried chilies, coupled with ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-Q-TOF/MS). In the sample preparation, acetonitrile containing 1% formic acid was used as the extraction solvent. Anhydrous sodium sulfate replaced the traditional anhydrous magnesium sulfate for water removal, effectively eliminating the issues of salt caking. Graphitized carbon black, octadecyl silica, and primary secondary amine were used as cleaning agents. The method showed good sensitivity, with the limits of quantification below 0.03 mg/kg for fresh chilies and below 0.15 mg/kg for dried chilies. Values of matrix effects ranged from -19.5% to 8.4%, and the recovery was 86.9% - 105.2%. The analytical method provided an effective tool for the high throughput detection of neonicotinoid pesticide residues in multiple chili matrices.

Dihydroxyl modified UiO-66 as dispersive solid-phase extraction sorbent coupled with ultra-high performance liquid chromatography tandem mass spectrometry for detection of neonicotinoid insecticides

The extensive usage of neonicotinoid insecticides (NIs) has raised many concerns about their potential harm to environment and human health. Thus, it is of great importance to develop an efficient and reliable method to determine NIs in food samples. In this work, three Zr4+-based metal-organic frameworks functionalized with various numbers of hydroxyl groups were fabricated with a facile one-pot solvothermal method. Among them, dihydroxy modified UiO-66 (UiO-66-(OH)2) exhibited best adsorption performance towards five target NIs. Then, a sensitive and efficient method for detection of NIs from vegetable and fruit samples was established based on dispersive solid phase extraction (dSPE) with UiO-66-(OH)2 as adsorbent coupled with ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS). Key parameters affecting the dSPE procedure including amounts of adsorbent, adsorption time, eluent solvents and desorption time were investigated. Under the optimal conditions, rapid adsorption of NIs within five minutes was achieved due to the high affinity of UiO-66-(OH)2 towards NIs. The developed method exhibited high sensitivity with limits of detection (LODs) varied from 0.003 to 0.03 ng/mL and wide linearity range over 3-4 orders of magnitude from 0.01 to 500 ng/mL. Furthermore, the established method was applied for determining trace NIs from complex matrices with recoveries ranging from 74.6 to 99.6 % and 77.0-106.8 % for pear and tomato samples, respectively. The results indicate the potential of UiO-66-(OH)2 for efficient enrichment of trace NIs from complex matrices.

Application and Progress of Machine Learning in Pesticide Hazard and Risk Assessment

Long-term exposure to pesticides is associated with the incidence of cancer. With the exponential increase in the number of new pesticides being synthesized, it becomes more and more important to evaluate the toxicity of pesticides by means of simulated calculations. Based on existing data, machine learning methods can train and model the predictions of the effects of novel pesticides, which have limited available data. Combined with other technologies, this can aid the synthesis of new pesticides with specific active structures, detect pesticide residues, and identify their tolerable exposure levels. This article mainly discusses support vector machines, linear discriminant analysis, decision trees, partial least squares, and algorithms based on feedforward neural networks in machine learning. It is envisaged that this article will provide scientists and users with a better understanding of machine learning and its application prospects in pesticide toxicity assessment.

Detection of neonicotinoids in agricultural products using magnetic molecularly imprinted polymers-surface enhanced Raman spectroscopy

In this paper, magnetic molecularly imprinted polymers-surface-enhanced Raman spectroscopy (MMIPs-SERS) for rapidly analyzing acetamiprid and thiacloprid in agricultural products has been firstly developed. The magnetic imprinted polymers were obtained by polymerizing the imprinted layers on the surface of magnetic nanoparticles. The polymers were detailed characterized by using series of analytical techniques, and their adsorption and recognition performance were validated by adsorption tests. The results showed that the magnetic molecularly imprinted polymers possessed typically core-shell structure and exhibited class-specific recognition, fast adsorption saturation (only 1 min), and good magnetic separation performance towards targets. The adsorption and desorption conditions for MMIPs-SERS detection system were carefully investigated. Under optimum conditions, the good linear detection range of 1∼20 μg/g with LODs of 23.7-68.8 ng/g for acetamiprid and thiacloprid in peach and pear samples was obtained. Through the reusable and spiked experiments, the developed MMIPs-SERS method based on Au NPs as enhanced substrate was validated to be highly sensitive, accurate, efficient and applicable in analyzing neonicotinoids from pear and peach samples. This study provided a rapid and simple detection method for neonicotinoids with effective separation and detection properties based on the synergistic effect of imprinted polymers and SERS. More importantly, this developed method have good application potential in rapid analyzing field for neonicotinoids due to the amazing rapid adsorption time for extracting targets from complex food matrix (only 1 min).

Design of hydroxyl-functionalized nanoporous organic polymer with tunable hydrophilic-hydrophobic surface for solid phase extraction of neonicotinoid insecticides

As being widely used insecticides, neonicotinoid residues are toxic and harmful to human health and aquatic ecosystems. Thus, the sensitive monitoring of neonicotinoids in water and food samples is highly desirable to reduce their risks to humans. Herein, four novel hydroxyl-functionalized nanoporous organic frameworks (OH-NOP1, OH-NOP2, OH-NOP3 and OH-NOP4) with tunable hydrophilic-hydrophobic surface have been designed and fabricated for the first time by employing luteolin as monomer and 4,4'-bis(chloromethyl)-1,1'-biphenyl as crosslinker at the molar ratio of 3:1, 1:1, 1:3 and 1:6, respectively. When the molar ratio of luteolin to crosslinker was 1:3, OH-NOP3 was obtained and it presented the highest affinity with excellent adsorption performance towards the studied neonicotinoids. The adsorption mechanism was proposed to be the strong hydrogen bond, polar interaction, Lewis acid-base interaction and pore adsorption between OH-NOP3 and neonicotinoids. Then, utilizing OH-NOP3 as sorbent for solid phase extraction cartridges, an effective method for extraction and preconcentration of neonicotinoids followed by high performance liquid chromatography analysis has been developed for quantitative detection of neonicotinoids from water and edible fungi. The method provided good linearity over the range of 0.06-100.0 ng mL^-1 for lake water, 1.5-100.0 ng g^-1 for pleurotus eryngii and sea-shroom. Low detection limit (at the signal to noise ratio of 3) was achieved in the range of 0.02-0.08 ng mL^-1 for water, 0.50-0.60 ng g^-1 for pleurotus eryngii and 0.50-0.80 ng g^-1 for sea-shroom, while the limit of quantification was 0.06-0.25 ng mL^-1, 1.50-1.80 ng g^-1 and 1.50-2.50 ng g^-1, respectively. Satisfactory method recoveries (85.1-112%) were obtained, with relative standard deviations below 8.2%. This study offered a new strategy for designing efficient sorbents to adsorb or remove organic pollutants based on the structure and properties of substrates.

Neonicotinoid Analysis in Sunflower (Helianthus annuus) Honey Samples Collected around Tekirdag in Turkey

In recent years, the widespread use of neonicotinoids in agricultural areas has caused environmental pollution due to its lower toxicity to mammals. Honey bees, which are considered as biological indicators of environmental pollution, can carry these pollutants to the hives. Forager bees returning from sunflower crops that have been treated with neonicotinoids treated sunflower fields cause residue accumulation in the hives, which reason colony-level adverse effects. This study analyses neonicotinoid residues in sunflower (Helianthus annuus) honey sampled by beekeepers from Tekirdag province. Honey samples have been subjected to liquid-liquid extraction methods before liquid chromatography-mass spectrometry (LC-MS/MS). The method validation was carried out to fulfill all the necessary requirements of procedures SANCO/12571/2013. Accuracy was in the range of 93.63–108.56%, for recovery in the range of 63.04–103.19%, and for precision in the range 6.03–12.77%. Detection and quantification limits were determined according to the maximum residue limits of each analyte. No neonicotinoid residues were found above the maximum residue limit in the sunflower honey samples analysed.

Chronic larval exposure to thiacloprid impairs honeybee antennal selectivity, learning and memory performances

The use of agricultural neonicotinoid insecticides has sub-lethal chronic effects on bees that are more prevalent than acute toxicity. Among these insecticides, thiacloprid, a commonly used compound with low toxicity, has attracted significant attention due to its potential impact on the olfactory and learning abilities of honeybees. The effect of sub-lethal larval exposure to thiacloprid on the antennal activity of adult honeybees (Apis mellifera L.) is not yet fully understood. To address this knowledge gap, laboratory-based experiments were conducted in which honeybee larvae were administered thiacloprid (0.5 mg/L and 1.0 mg/L). Using electroantennography (EAG), the impacts of thiacloprid exposure on the antennal selectivity to common floral volatiles were evaluated. Additionally, the effects of sub-lethal exposure on odor-related learning and memory were also assessed. The results of this study reveal, for the first time, that sub-lethal larval exposure to thiacloprid decreased honeybee antenna EAG responses to floral scents, leading to increased olfactory selectivity in the high-dose (1.0 mg/L) group compared to the control group (0 mg/L vs. 1.0 mg/L: p = 0.042). The results also suggest that thiacloprid negatively affected odor-associated paired learning acquisition, as well as medium-term (1 h) (0 mg/L vs. 1.0 mg/L: p = 0.019) and long-term memory (24 h) (0 mg/L vs. 1.0 mg/L: p = 0.037) in adult honeybees. EAG amplitudes were dramatically reduced following R-linalool paired olfactory training (0 mg/L vs. 1.0 mg/L: p = 0.001; 0 mg/L vs. 0.5 mg/L: p = 0.027), while antennal activities only differed significantly in the control between paired and unpaired groups. Our results indicated that exposure to sub-lethal concentrations of thiacloprid may affect olfactory perception and learning and memory behaviors in honeybees. These findings have important implications for the safe use of agrochemicals in the environment.

A comprehensive review on the pretreatment and detection methods of neonicotinoid insecticides in food and environmental samples

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The metabolism and residue status of neonicotinoids were briefly summarized in this work.

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Sample pretreatment techniques for the analysis of neonicotinoids were critically discussed.

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The commonly used detection methods for neonicotinoids residues were also pointed out.

In recent years, the residues of neonicotinoid insecticide in food and environmental samples have attracted extensive attention. Neonicotinoids have many adverse effects on human health, such as cancer, chronic disease, birth defects, and infertility. They have substantial toxicity to some non-target organisms (especially bees). Hence, monitoring the residues of neonicotinoid insecticides in foodstuffs is necessary to guarantee public health and ecological stability. This review aims to summarize and assess the metabolic features, residue status, sample pretreatment methods (solid-phase extraction (SPE), Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS), and some novel pretreatment methods), and detection methods (instrument detection, immunoassay, and some innovative detection methods) for neonicotinoid insecticide residues in food and environmental samples. This review provides detailed references and discussion for the analysis of neonicotinoid insecticide residues, which can effectively promote the establishment of innovative detection methods for neonicotinoid insecticide residues.

Development of magnetic solid phase extraction using magnetic amphiphilic polymer for sensitive analysis of multi-pesticides residue in honey

A sensitive and time-saving method for the determination of multi-pesticide residues in honey was developed using magnetic solid phase extraction (MSPE) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). Magnetic polymer (N-vinyl pyrrolidone-divinyl benzene) (MVP-DB) was fabricated and employed as the adsorbent for extraction and enrichment of multi-pesticide residues in honey. MVP-DB contains lipophilic benzene ring, divinyl group, and hydrophilic pyrrolidone group. The good hydrophilic and hydrophobic structure of MVP-DB not only ensures sufficient dispersion in honey samples, but also enhances the ability to enrich target analytes. The predominant factors affecting the recoveries of analytes were systematically investigated, affording a rapid and highly efficient MSPE method. Under the optimal conditions, the method was verified, including the recovery, precision, linearity, sensitivity, and matrix effects. The results displayed that these pesticides showed good linearity in the range of 2-250 µg L^-1. The MLOQs were 0.5 µg kg^-1. The recoveries of pesticides in honey at the pre-spiked concentrations of 0.5-25 µg kg^-1 were 61.6%-112% with RSDs less than 18.2%. Hence, the developed method displayed good application prospect for the determination of multi-pesticide residues in honey samples.

Facile synthesis of uniform spherical covalent organic frameworks for determination of neonicotinoid insecticides

A uniform spherical structure covalent organic framework (TAPA-BPDA-COF) was prepared by a facile method at room temperature with tris(4-aminophenyl)amine (TAPA) and 4,4'-biphenyldicarboxaldehyde (BPDA) as building blocks. Based on the solid phase extraction with the TAPA-BPDA-COF as the sorbent and high performance liquid chromatography-diode array detection, a sensitive analytical method was established for the determination of four neonicotinoid insecticides from water and honey samples. Under the optimum conditions, good linear response for the quantification of the analytes was achieved in the range of 0.3-50.0 ng mL^-1 for water samples and in the range of 8.0-500.0 ng g^-1 for honey samples. The method recoveries fell in the range of 80.0-121.9% with RSDs less than 7.6%. The limits of detection at the signal to noise ratio of 3 were measured to be in the range of 0.08-0.12 ng mL^-1 for water samples and 2.6-3.3 ng g^-1 for honey samples, depending on compounds.

Optical Screening Methods for Pesticide Residue Detection in Food Matrices: Advances and Emerging Analytical Trends

Pesticides have been extensively used in agriculture to protect crops and enhance their yields, indicating the need to monitor for their toxic residues in foodstuff. To achieve that, chromatographic methods coupled to mass spectrometry is the common analytical approach, combining low limits of detection, wide linear ranges, and high accuracy. However, these methods are also quite expensive, time-consuming, and require highly skilled personnel, indicating the need to seek for alternatives providing simple, low-cost, rapid, and on-site results. In this study, we critically review the available screening methods for pesticide residues on the basis of optical detection during the period 2016-2020. Optical biosensors are commonly miniaturized analytical platforms introducing the point-of-care (POC) era in the field. Various optical detection principles have been utilized, namely, colorimetry, fluorescence (FL), surface plasmon resonance (SPR), and surface enhanced Raman spectroscopy (SERS). Nanomaterials can significantly enhance optical detection performance and handheld platforms, for example, handheld SERS devices can revolutionize testing. The hyphenation of optical assays to smartphones is also underlined as it enables unprecedented features such as one-click results using smartphone apps or online result communication. All in all, despite being in an early stage facing several challenges, i.e., long sample preparation protocols or interphone variation results, such POC diagnostics pave a new road into the food safety field in which analysis cost will be reduced and a more intensive testing will be achieved.

Determination of Neonicotinoid Pesticides in Propolis with Liquid Chromatography Coupled to Tandem Mass Spectrometry

In this study, a method was developed for the determination of five neonicotinoid pesticides (acetamiprid, clothianidin, imidacloprid, thiacloprid, and thiamethoxam) in propolis. Two sample preparation methods were tested: solid-phase extraction and the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method. The identities of analytes were confirmed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the selected reaction monitoring mode. Solid-phase extraction resulted in cleaner extracts; therefore, the SPE-LC-MS/MS method was validated according to the SANTE protocol in triplicate at two spiking levels (10 ng/g and 50 ng/g). The average recoveries of analytes ranged from 61% to 101%, except for clothianidin (10-20%). The LOD ranged from 0.2 ng/g to 4.4 ng/g, whereas the LOQ was in the range of 0.8 ng/g-14.7 ng/g. In order to compensate for the matrix effect, matrix-matched calibration was used. Good accuracy (relative error: 1.9-10.4%) and good linearity (R² > 0.991) were obtained for all compounds. The optimised method was applied to 30 samples: 18 raw propolis and 12 ethanol tinctures. Acetamiprid, imidacloprid, and thiacloprid were detectable in seven samples but were still below the LOQ. This study is the first to report the determination of several neonicotinoid residues in propolis.

Simultaneous determination of acetamiprid and 6-chloronicotinic acid in environmental samples by using ion chromatography hyphenated to online photoinduced fluorescence detector

This study aims to introduce a simple, sensitive, and cost-effective method for the simultaneous determination of acetamiprid and its main metabolite 6-chloronicotinic acid in environmental samples by using a nonsuppressed ion chromatography hyphenated with an online postcolumn photoinduced fluorescence detection system. The fluorescence detector wavelengths λ_ex /λ_em  = 257/382 nm was set for up to 6.0 min for acetamiprid, while λ_ex /λ_em  = 231/370 nm programmed for 6-chloronicotinic acid for the rest of the analysis time. Both samples were treated by applying miniaturized quick, easy, cheap, effective, rugged, and safe method before the separation of analytes on an IonPac^® AS11-HC column by pumping 40 mM NaOH having minuscule content of acetonitrile (5%, v/v) as an eluent. Both intrinsically nonfluorescent analytes were turned-on by online postcolumn photoinduced derivatization, avoiding the need for complex chemical derivatization or addition of a postcolumn extra pump. The developed method was appraised for the analysis of environmental samples, exhibiting excellent linearity (0.050-10 μg/mL) with a correlation coefficient greater than 0.9993 for both analytes. Whereas, obtained limit of detection (0.025-0.0072 μg/mL), recoveries (98.02-116.00%), and inter- and intraday precision (≤3.02 %) were satisfactory for both compounds in environmental samples.