Pesticide Molecules Research Articles

Improved Ensemble Model for Insecticide Recognition by Incorporating Insect Toxicity Data.

Pesticide molecules, such as insecticides, play a critical role in modern agricultural production. Traditional pesticide development methods are often inefficient and expensive, while data-driven artificial intelligence (AI) techniques have emerged as a useful tool to facilitate drug discovery. However, currently available commercial pesticide data is limited, which makes the trained models unsatisfactory in terms of performance and generalization. From a domain knowledge perspective, insect toxicity data were incorporated to improve the insecticide recognition of AI models. Compared to the models trained with the original data set, the new models performed better in the external validation, and their generalization was more desirable. In addition, by integrating different types of individual models, we obtained an ensemble model with better performance. Based on this, an online platform was developed to provide researchers with free access to insecticide screening (https://dpai.ccnu.edu.cn/InsectiVS/). Finally, two potential insecticide molecules with insecticidal activity against Plutella xylostella were successfully identified in a real-world scenario. In conclusion, this idea connects the fields of AI and agricultural chemistry and is expected to have wide application in pesticide research.

Analysis, Quantification and Identification of Pesticides from Lettuce in Ouagadougou City (Burkina Faso)

In Burkina Faso, chemical inputs are used massively in market gardening to increase the yields. The misuse of these chemicals is responsible of contamination of market garden products, leading to the rapid rotting of vegetables. The objective of this study was to determine the pesticides in chemical inputs applied on vegetables produced in Ouagadougou City. To do this, lettuce has been sampled from producers in three sites (Tanghin, Boulmiougou and Kossodo) and pesticides amounts have been analyzed using Gas Chromatography coupled with mass spectrometry. Chemical analyses have carried out on three lettuce samples and the extraction of chemical input residues was done according to QuEChERS (Quick Easy Cheap Effective Rugged and Safe) method. Results revealed the presence of six (06) pesticide molecules (chlordimeform, quintozene, lindane, cypermethrin, α-cypermethrin, δ-deltamethrin) in Boulmiougou sample, four (04) molecules (methomyl, cypermethrin, α-cypermethrin, δ-deltamethrin) in Kossodo sample and three (03) molecules (cypermethrin, α-cypermethrin, δ-deltamethrin) in Tanghin sample. In this regard, analysis of pesticide amount revealed that the quantity of molecules was acceptable for the consumer, but these pesticides could contribute to the rapid rotting of our vegetables which generates economic and social losses for the country.

Design and synthesis aldehydes-thiourea and thiazolyl hydrazine derivatives as promising antifungal agents against Monilinia fructicola.

Fungal diseases present a significant threat to global agriculture, necessitating the development of new, safe, and effective fungicides. Existing fungicides face resistance and health risks, prompting the synthesis of novel compounds. Researchers have synthesized aldehyde-based thiourea and thiazolyl hydrazine derivatives, evaluating their antifungal activities to identify impactful pesticide molecules. The results showed that most of the compounds had broad-spectrum antifungal activity against six plant pathogenic fungi and four post-harvest fungi. Notably, compound LN18 showed the best antifungal activity against Monilinia fructicola with a half-maximal effective concentration (EC50) of 0.17 μg mL-1, which was better than the commercial fungicide natamycin. A structure-activity relationship (SAR) study showed that the presence of unsaturated double bonds in the structure and the length of the carbon chain were the main factors affecting antifungal activity. The presence of unsaturated double bonds and an increase in the length of the carbon chain greatly improved inhibitory activity against the tested pathogens. The preliminary mechanism study showed that LN18 could damage the integrity of the mycelial plasma membrane, leading to leakage of intracellular nucleic acid and protein. LN18 also induced an increase in the intracellular reactive oxygen species level to exert its antifungal effects. In addition, compound LN18 had a stronger antifungal effect in vivo, and better phytotoxicity than natamycin, indicating broad application prospects in agriculture. Aldehydes-thiourea and thiazolyl hydrazine derivatives demonstrate remarkable antifungal efficacy against plant pathogenic and post-harvest fungi, offering a promising avenue for commercialization as highly efficacious, cost-effective and safe antifungal agents. © 2024 Society of Chemical Industry.

Adsorption behavior of nano polyethylene for bensulfuron-methyl in an aqueous environment

Agricultural plastic film, which is widely used to maintain heat and moisture during agricultural production, could gradually degrade into micro- and nano-scale polyethylene plastic fragments when not properly treated. The polyethylene plastic fragments, with ideal properties to carry hydrophobic compounds, interact with pesticide molecules, forming co-exposed residues that persist in the environment. In this work, a small and representative nano-polyethylene particle (PE-NPs, 500 nm) were selected as the adsorption carrier, and bensulfuron-methyl, a commonly used herbicide for crops (e.g. rice and wheat) covered under agricultural plastic films, was chosen as the target analyte to investigate their adsorption behavior. The adsorption equilibrium time of bensulfuron-methyl on PE-NPs increases(6–12 h) with the increase of plastic dosage(500 mg/L-2000 mg/L). The adsorption capacity showed an increasing and then decreasing trend as the dosage of plastic increased, with the highest value achieved at around 500 mg/L. The adsorption behavior was influenced by environmental factors, for example, adsorption was significantly inhibited at pH=9.0 or NaCl concentrations above 0.05 mg/g or dissolved organic matter (oxalic acid) concentrations above 10 mg/L. In addition, The adsorption of bensulfuron-methyl aligned relatively close with pseudo-secondary kinetics and the Freundlich model, suggesting that surface adsorption, intraparticle diffusion, and mass transfer might play a role in the process of non-uniform multilayer adsorption. The adsorption thermodynamics experiment indicated that the adsorption process was spontaneous, heat-absorbing, and mainly physisorption.

Hydroxyl functionalized hexagonal boron nitride quantum dots as nanozyme for pesticides sensing through dual colorimetric and fluorometric platform: A combined experimental and theoretical study

The Hydroxyl-functionalized hexagonal boron nitride quantum dots (h-BN QDs) were synthesized using a hydrothermal technique in a water medium, exhibiting stability in water for over 90 days. The present study demonstrates two simple fluorescence and colorimetric techniques for sensing organophosphorus (OP) and organochloride (OC) pesticides (atrazine, simazine and chlorpyrifos) in an aqueous medium using hydroxyl-functionalized h-BN QDs. The sensing capability of h-BN QDs for these pesticides was determined to be in the range of 5–10 µM using both techniques. The hydroxyl groups on the surface of the QDs enhanced dispersibility and enabled peroxidase-like catalytic activity in acidic conditions. The radical generation using hydroxyl-functionalized h-BN QDs in the presence of H2O2 upon 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) oxidation plays a significant role in the peroxidase reaction. The hydrogen bonding and π-π interactions between the pesticide molecules and ABTS can enhance the pesticide sensing performance. The limit of detection (LOD) using ABTS for atrazine, simazine, and chlorpyrifos was 6.11, 6.56, and 2.47 µM, respectively. Fluorescence sensing, based on a turn ON/OFF mechanism, demonstrated high specificity and sensitivity with LODs of 5.59, 6.45, and 8.08 µM for the same pesticides. The DFT studies revealed non-covalent bonding, such as hydrogen bonding, π-π interactions between the pesticides and the h-BN QDs, indicating binding affinities and stabilization energies of the complexes which can detect pesticides effectively. Atrazine exhibited higher binding affinity towards h-BN QDs, followed by simazine and chlorpyrifos. The h-BN QDs provide a new insight into bonding with pesticides, enhancing the peroxidase mimetic and fluorescence activity.

High-performance metal-organic frameworks for efficient adsorption, controlled release, and membrane separation of organophosphate pesticides

Metal-organic frameworks (MOFs) are considered good choices for the absorption, separation, and release of various substances. The rapid increase in the number of MOFs being produced makes it impractical to conduct experimental research to identify the most promising candidates in these areas. Therefore, computational screening has emerged as a robust approach. We employed this approach to identify the most efficient MOFs for the removal, separation, and controlled release of organophosphorus pesticides, including diazinon, chlorpyrifos, and chlorpyrifos-methyl. From a database of approximately 14,000 MOFs, 584 MOFs with the largest cavity diameters were used in the screening process to evaluate promising candidates for each pesticide. Monte Carlo simulations were used to estimate the pesticide uptake capacities and isosteric heats of the selected MOFs. The structural properties of MOFs were correlated with their adsorption capacities and isosteric heats. Computational screening identified 325, 330, and 450 MOFs as potential absorbents and carriers for diazinon, chlorpyrifos-methyl, and chlorpyrifos, respectively. Additionally, it proposed 235, 254, and 135 MOFs as membranes for the effective separation of these organophosphorus pesticides. The reactivity of the pesticides was explored using quantum mechanics calculations. Molecular dynamics simulations of the top three MOFs with high uptake capacities for each pesticide were performed and analyzed to understand the interactions between the MOF, pesticide, and water molecules. The solvation-free energies of the pesticides were calculated for various solvents to identify the most effective solvent for desorbing pesticides from the MOFs, thereby enabling MOF regeneration.

Application of Difluoromethyl Isosteres in the Design of Pesticide Active Molecules.

Difluoromethyl (CF2H) groups have been found in many listed pesticides due to their unique physical and chemical properties and outstanding biological activity. In pesticide molecules, compared with the drastic changes brought by trifluoromethyl, difluoromethyl usually moderately regulates the metabolic stability, lipophilicity, bioavailability, and binding affinity of compounds. Therefore, difluoromethylation has become an effective means to modify the biological activity of pesticide molecules. This paper reviews the representative literatures and patents containing difluoromethyl groups in the past 10 years, and introduces the research progress. The aim is to provide an effective reference value for the study of difluoromethyl in pesticides.

A novel HCR-CRISPR/Cas12a immunosensor for the sensitive detection of pesticide residues in animal-derived foods

Pesticides are widely used in the cultivation and breeding of agricultural products. However, pesticide residue monitoring has focused mainly on fruits and vegetables and has not focused on animal-derived foods. Therefore, a novel approach for determining pesticide residues in animal-derived food products via an immunosensor based on a chain hybridization reaction (HCR) with CRISPR/Cas12a is presented. Triazophos pesticide was used as a research object. This method establishes a competitive immunoreaction system in which OVA-hapten is encapsulated on the surface of the enzyme label plate, competing with pesticide molecules bound to antibodies on the surface of the nanogold composite probe. Integrating the immunoreaction with two signal amplification mechanisms, HCR and CRISPR/Cas12a, ensures heightened method sensitivity while maintaining enhanced convenience and speed. The method's detection range spans from 0.01 to 50 ng/mL, with a remarkably low detection limit of 0.013 ng/mL. Moreover, in practical sample applications, the assay exhibited a robust correlation with GC‒MS. This approach uniquely offers real-time, cost-effective, and onsite data, providing a more comprehensive and timely foundation for establishing standards on pesticide residues in animal-derived foods, bolstering food safety surveillance, and upholding public health. Moreover, the proposed HCR-CRISPR/Cas12a immunosensor effectively improved the sensitivity and accuracy of pesticides detection, offering a promising and versatile platform for food safety detection.

Comparison of pesticide contamination between captive-reared and wild grey partridges: insights into environmental exposure disparities.

Pesticide contamination is often cited as a key factor in the global decline of farmland birds. However, the majority of studies on pesticide exposure in non-target fauna are not representative of what happens in nature because they are limited to artificial conditions. The aim of this study was to define and compare, for the first time, pesticide contamination in grey partridges (Perdix perdix) from two different contexts, i.e., captivity vs. the wild. Blood samples taken from 35 captive and 54 wild partridges in 2021-2022 were analysed for 94 pesticides most commonly used in French agriculture. Captive partridges had 29 molecules detected in their blood (12 herbicides, 14 fungicides, and three insecticides) compared to wild partridges, which had 50 molecules (13 herbicides, 23 fungicides, and 14 insecticides). Of these pesticide compounds found in individuals, 26 were banned. Captive partridges had significantly fewer pesticide molecules than wild partridges, with one to 14 pesticides per captive individual and 8 to 20 pesticides per wild individual. Nineteen molecules were common to both groups, with concentrations up to three times higher in wild partridges than in captive partridges. Our results thus show multiple exposures for most of our individuals, especially in wild partridges, which can lead to cocktail effects, which are never considered. Furthermore, the difference in contamination between the wild and captive partridges reflects the multiple routes of contamination in nature, in particular, due to the use of a wide range of habitats by wild partridges.

Removal of tricyclazole residues from water by sorption on metal organic frameworks (MOFs): A theoretical insight of the experimental data

All over the world, there are stringent regulations in place concerning the acceptable amount of pesticide residues in various food commodities, including cereals. The majority of the water tainted with pesticides comes from agricultural drainage, making it imperative that this water be cleansed of any lingering traces of the chemicals. The presence of unacceptable levels of pesticides residues is another issue hindering India's ability to export Basmati rice and other commodities. Tricyclazole, a fungicide has been found in rice in recent years, leading to the rejection of a number of bulk consignments. Therefore, three metal organic frameworks (MOFs) viz., MIL-53(Al), Fe-BTC, and ZIF-8, based on three different metal ions (aluminium, iron, and zinc) and three different organic "struts" were investigated for the removal of TRCZ from water. Interestingly, TRCZ was found to be selective towards both metal ions and linkers. The maximum adsorption capacities of TRCZ onto MIL-53(Al), Fe-BTC and ZIF-8 were 980.0, 896.7 and 904.6 μg g−1 (@1 ppm aqueous solution), respectively. Adsorption followed pseudo-second-order kinetics and best fit the Sips isotherm. The adsorption of TRCZ molecules onto the surface of the MOFs were confirmed using Fourier Transform infrared (FTIR) and X-Ray Diffraction (XRD) spectroscopy. MIL-53(Al) showed the best regeneration capacity (> 90 % efficiency after the 4th cycle). The adsorption of pesticide molecules onto MOF surfaces was studied (in vacuo and in aqueous) circumstances using Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) simulations revealing the prime competitive role of water molecules aided by π-π stacking and π-lone pair interactions during adsorption. Metal organic frameworks have the potential to replace costly commercial activated carbons in the future to treat pesticide-contaminated water.

Synergetic studies on the thermochemical activation and polyaniline integration on the adsorption properties of natural coal for chlorpyrifos pesticide: steric and energetic studies

Three types of synthetic coal-derived adsorbents were characterized as potential enhanced structurers during the removal of chlorpyrifos pesticide. The raw coal (CA) was activated into porous graphitic carbon (AC), and both CA and AC were blended with polyaniline polymers (PANI/CA and PANI/AC) forming two advanced composites. The adsorption performances of the modified structures in comparison with CA were evaluated based on both the steric and energetic parameters of the applied advanced isotherm model (the monolayer model of one energy). The uptake performances reflected higher capacities for the PANI hybridized form (235.8 mg/g (PANI/CA) and 309.75 mg/g (PANI/AC) as compared to AC (156.9 mg/g) and raw coal (135.8 mg/g). This signifies the impact of activation step and PANI blending on the surface and textural properties of coal. The steric investigation determined the saturation of the coal surface with extra active sites after the activation step (Nm(AC) = 62.05 mg/g) and the PANI integration (Nm(PANI/CA) = 113.5 mg/g and Nm(PANI/AC) = 169.7 mg/g) as compared to raw coal (Nm(CA) = 39.6 mg/g). This illustrated the reported uptake efficiencies of the modified samples, which can be attributed to the enhancement in the surface area and the incorporation of additional chemical groups. The results also reflect that each site can be loaded with 3–4 molecules of chlorpyrifos, which are arranged vertically and adsorbed by multi-molecular mechanisms. The energetic studies (< 40 kJ/mol) suggested the physical uptake of pesticide molecules by dipole bonding and hydrogen bonding processes. The thermodynamic functions donate the exothermic properties of 47reactions that occur spontaneously.

Resin bound gold nanocomposites assisted SE/ATR-FTIR spectroscopy for detection of pymetrozine insecticide in vegetable samples

The goal of this work was to assess the competence of organic hydrophobic resin bound gold nanocomposites (OH/R-AuNCs) for detection of pymetrozine insecticide from vegetable samples employing surface-enhanced/attenuated total reflectance-Fourier transform infrared (SE/ATR-FTIR) spectroscopy. The adsorption isotherm models, including the Langmuir, Freundlich and Temkin, are tested to reveal the interactive behaviour between the OH/R-AuNCs and pesticide. The adsorption occurs principally by London–Van der Waals dispersion interactions and hydrogen bonding interactions between the surface of OH/R-AuNCs materials and the hydrophobic part of pesticide molecule. The characteristic absorption band obtained at 3019.94 cm−1 was utilized for the quantitative analysis of pymetrozine insecticide in vegetable samples. The method was found to be accurate and precise, with mean recovery values in the range of 94.5–110 %, correlation coefficient of 0.992 %, and detection limit of 2.65 μg mL−1. The adsorption efficiency of the designed OH/R-AuNCs significantly influences the SE/ATR-FTIR response of the pymetrozine around 90 %. The optimized and validated method was applied to determine the residual concentrations of the pymetrozine that had been applied to vegetable samples.

Synergetic studies on the nitrogen functionalization and polyaniline hybridization on the uptake performances of acephate pesticides by raw coal: Steric and energetic studies

Three forms of modified coal-based adsorbents were developed and characterized as potential enhanced structurers during the removal of acephate pesticide. The raw coal (CA) was oxidized by nitric acid, forming nitrogen functionalized coal (N.CA), and both CA and N.CA were hybridized with polyaniline polymers (PANI/CA and PANI/N.CA). The adsorption performances of the modified structures in comparison with CA were evaluated based on both the steric and energetic parameters of the applied advanced isotherm model (the monolayer model of one energy). The uptake performances reflected higher capacities for the PANI hybridized form (261.9 mg/g (PANI/CA) and 316.6 mg/g (PANI/N.CA) as compared to N.CA (232.3 mg/g) and raw coal (201.2 mg/g). This signifies the impact of nitrogen functionalization and PANI hybridization on the surface properties of coal. The steric investigation determined the saturation of the coal surface with extra active sites after the nitric acid treatment (Nm (N.CA) = 103.5 mg/g) and the PANI hybridization (Nm (PANI/CA) = 119.07 mg/g and Nm (PANI/N.CA) = 146.4 mg/g) as compared to raw coal (Nm (CA) = 81.9 mg/g). This illustrated the reported uptake efficiencies of the modified samples, which can be attributed to the enhancement in the surface area (5.4 m2/g (CA), 18.3 m2/g (N.CA), 27.7 m2/g (PANI/CA), and 36.2 m2/g (PANI/N.CA)) and the incorporation of additional chemical groups (NO, C-N, and N-H). The results also reflect that each site can be loaded with three molecules of acephate, which are arranged vertically and adsorbed by multi-molecular mechanisms. The energetic studies (<40 kJ/mol) suggested the physical uptake of pesticide molecules by dipole bonding and hydrogen bonding processes. The thermodynamic functions reflect the exothermic properties of reactions that occur spontaneously.

Bulk or supported tungstophosphates? Antioxidant and antimicrobial activities following pesticide removal

The study evaluates caesium, potassium, silver, and zinc tungstophosphates synthesized in bulk and Y zeolite-supported forms through a two-step process. Spectral investigation reveals the impact of cation size on tungstophosphates formation. The large cations form ion-ion interaction with the Keggin ion, while smaller cations form hydrogen bonds between the cation hydration sphere and terminal oxygens in the Keggin ion. Supported salts formation proceeds without Keggin ion distortion. Zeta potential showed the absence of particle aggregation for caesium and potassium tungstophosphate. Nicosulfuron removal by the supported salt exhibits enhanced retention, with the exception observed for zinc tungstophosphate suggesting a decomposition mechanism. Antimicrobial evaluations reveal silver salt's potency, especially in zeolite-supported form, emphasizing the role of zeolite support. In the presence of pesticide molecules, the antimicrobial activity of salts lowers, with the exception seen for fungus strain. The antioxidant assessments demonstrate superior inhibition for insoluble bulk salts, with caesium tungstophosphate exhibiting the highest inhibition, while supported silver salt enhances bulk salt performance. The presence of pesticides affects both antimicrobial and antioxidant activities, while a complex relationship with radical scavenging ability in bulk and supported salts is independent of their pesticide adsorption capacities. The study broadens the range of the versatile applications of tungstophosphates, highlighting their specific interactions with pesticides and their impact on bioactivity and environmental remediation.

A color-changed fluorescence sensor for pesticide triclopyr 2-butoxyethyl ester based on naphthalimide Schiff-base

Triclopyr 2-butoxyethyl ester is a usual pesticide, however, its excessive use might pose risks to environmental safety. The rapid, simple and in-situ detecting method for triclopyr 2-butoxyethyl ester is of great importance but rarely reported. In this work, the first fluorescent sensor for triclopyr 2-butoxyethyl ester was developed based on a derivative of n-butyl-1,8-naphthimide Schiff-base (NSB). NSB is a typical AIE molecule with good green fluorescence in DMSO-H2O (5:95). The green fluorescence of NSB was transferred into strong blue fluorescence on sensing triclopyr 2-butoxyethyl ester. The high selective detection of NSB for triclopyr 2-butoxyethyl ester was observed among 26 kinds of normal metallic ions and pesticide molecules. The detecting limitation was as low as 2.89 × 10−7 M. The sensing mechanism was confirmed as 1:1 stoichiometric ratio based on the multiple hydrogen bonding and hydrophobic interactions. NSB was applied on sensing triclopyr 2-butoxyethyl ester in real samples of wheat seedlings, sugarcane and broadleaf weedane and water samples, suggesting the excellent application potential on simple, rapid and in-situ detection of triclopyr 2-butoxyethyl ester in daily environments.

Effective extraction of pyrethroid pesticides from cabbages using Fe3O4@NU-1000 and adsorption mechanism: An experimental and theoretical study

In this paper, a magnetic zirconium-based MOFs (Fe3O4@NU-1000) with good water stability was prepared for effective extraction of pyrethroid pesticides from vegetables. Characterization results showed Fe3O4@NU-1000 has a high specific surface area (435.34 m2·g−1) and a large pore size (4.88 nm), which provides abundant adsorption sites for pesticides molecules. Fe3O4@NU-1000 can achieve rapid magnetic separation from solution within 1 min, greatly reducing the extraction time of pyrethroid pesticides. The results of adsorption kinetics and isotherms showed that the adsorption process of pyrethroid pesticides on Fe3O4@NU-1000 was monolayer adsorption and physisorption. The maximum adsorption capacities of Fe3O4@NU-1000 for beta-cyfluthrin, lambda-cyhalothrin, permethrin, and bifenthrin were up to 1159.11, 1194.16, 1151.48, and 1181.74 mg·g−1, respectively. Molecular dynamics simulations showed that adsorption is driven by hydrophobic interaction. Van der Waals forces and hydrogen bonding accelerate pesticide molecules to approach the surface, and π–π interactions enable stable adsorption of pesticide molecules within the triangular and hexagonal micropores of NU-1000. DFT calculations confirmed that pesticide molecules predominantly adsorb stably within the pores of Fe3O4@NU-1000 through π–π interactions, with additional contributions from CH3–π and Cl–π interactions. Finally, a simple and sensitive method was established for the determination of pyrethroid pesticides in cabbage samples using Fe3O4@NU-1000 based magnetic solid-phase extraction and high-performance liquid chromatography. It provided low limit of detection (0.0011–0.0058 μg·mL−1), a wide linear range (1–25 μg·mL−1), and satisfactory recoveries (81.35–98.64 %), which can achieve effective extraction and trace detection. This study provides a magnetic MOFs material for extraction of pesticides and reveals its adsorptive mechanism at molecular level, which is helpful for rational design of more pretreatment materials for pesticides detection in complex food matrices.

Plasmonic AgNPs reinforced flexible hydrogel Surface-Enhanced Raman scattering (SERS) sensor for in-situ detection of curved samples

In-situ detection of analytes on curved surfaces is a persistent and great challenge in the application of SERS technique. A hydrogel-based flexible SERS substrate demonstrates a unique charm for providing close contact to the real-sample surface but limited by its weak enhancement capability in the quantitative analysis. Herein, we report a reinforced hydrogel by reduction of plasmonic silver nanoparticles (AgNPs) on a PNIPAM membrane with the aid of polyvinylpyrrolidone (PVP) surfactant. The modification of AgNPs on PNIPAM endows the AgNPs/PNIPAM composite hydrogel with good mechanical properties and reinforced swelling property. Moreover, the AgNPs/PNIPAM hydrogel-based SERS sensor exhibits an enhanced SERS sensitivity as well as improved signal uniformity (RSD ＜10 %), and the detection concentration for pesticide molecules can be down to 10-9 M. Due to the fingerprint feature of SERS, multicomponent detection of pesticide mixtures was readily realized. In addition, the flexible AgNPs/PNIPAM hydrogel was successfully applied to the curved apple surface for SERS detection. Notably, it is capable of achieving qualitative and quantitative analyses of different pesticides, which has lower analytical concentrations than European Union (EU) standards, indicating the potential applications in rapid in-situ pesticide analysis.

Laser-based synthesis of silver nanoparticles embedded in cellulose paper for catalytic reduction of azo dyes and SERS sensing of pesticides

In this study, highly reactive bare silver nanoparticles (Ag NPs) are synthesized using the Pulsed Laser Ablation in Liquid (PLAL) technique. Ag NPs are then coated on the filter paper using the dip coating method. This process converts filter paper into a versatile substrate for catalysis and surface-enhanced Raman Spectroscopy (SERS) based sensing. The successful synthesis of spherical Ag NPs and their effective embedding into the filter paper was confirmed using UV–visible absorption spectroscopy, scanning electron microscopy (SEM), and Energy Dispersive x-ray analysis (EDX). SEM images revealed that the Ag NPs were embedded in the filter paper and attached to the cellulose fibers. The use of Ag NPs embedded filter paper as a catalyst substrate for the reduction of both cationic and anionic dyes demonstrated that higher concentrations of Ag NPs on the filter paper resulted in a faster reduction. In particular, filter paper impregnated with 52 μg of Ag NPs demonstrated a complete reduction of methylene blue and methyl orange in less than a minute and 4 min, respectively. To demonstrate the practical sensing capability of the Ag NPs embedded filter paper, it was utilized as a SERS substrate. This enabled the detection of trace levels of Rhodamine 6G (R6G) and the pesticide molecule chlorpyrifos, demonstrating its potential real-world applications.

Metalorganic Polyhedra Polyoxometalate Hybrid Salts for Tandem Photooxidative‐Hydrolytic Pesticide Detoxification

AbstractThe extensive use of pesticides to ensure global food production presents significant threats to both human health and the environment. In this study, the photochemical, redox, and acid‐base properties of Zr‐metal‐organic polyhedra (Zr‐MOP) and polyoxometalates (POM) are utilized to fabricate functional hybrid salts, denoted as [Zr‐MOP][POM], designed for pesticide detoxification. Upon light irradiation, [Zr‐MOP][POM] salts generate a charge‐separated state with oxidizing properties. This activated state selectively photooxidizes highly toxic and persistent fenamiphos into fenamiphos sulfoxide and subsequently hydrolytically breaks down it into non‐toxic 3‐methyl‐4‐(methylsulfinyl)phenol and phosphate components. The hydrolytic degradation of fenamiphos is facilitated by the reduced basicity of the 3‐methyl‐4‐(methylsulfinyl)phenolate residue (ΔpKb = ‐2.4) in the photooxidized form of the pesticide molecule. Furthermore, the hybrid salts demonstrate efficacy in the breakdown of multicomponent pesticide mixtures such as fenamiphos and methylparaoxon.

Using honey bee flight activity data and a deep learning model as a toxicovigilance tool

Automatic monitoring devices placed at the entrances of honey bee hives have facilitated the detection of various sublethal effects related to pesticide exposure, such as homing failure and reduced flight activity. These devices have further demonstrated that different neurotoxic pesticide molecules produce similar sublethal impacts on flight activity. The detection of these effects was conducted a posteriori, following the recording of flight activity data. This study introduces a method using an artificial intelligence model, specifically a recurrent neural network, to detect the sublethal effects of pesticides in real-time based on honey bee flight activity. This model was trained on a flight activity dataset comprising 42,092 flight records from 1107 control and 1689 pesticide-exposed bees. The model was able to classify honey bees as healthy or pesticide-exposed based on the number of flights and minutes spent foraging per day. The model was the least accurate (68.46%) when only five days of records per bee were used for training. However, the highest classification accuracy of 99%, a Cohen Kappa of 0.9766, a precision of 0.99, a recall of 0.99, and an F1-score of 0.99 was achieved with the model trained on 25 days of activity data, signifying near-perfect classification ability. These results underscore the highly predictive performance of AI models for toxicovigilance and highlight the potential of our approach for real-time and cost-effective monitoring of risks due to exposure to neurotoxic pesticide in honey bee populations.