Pesticides In Agricultural Products Research Articles

Selective colorimetric detection of carbosulfan based on its hydrolysis behavior and Ti3C2/AuPt nanozyme

BackgroundCarbosulfan (CBS) is a widely used carbamate pesticide in agricultural production, its easy decomposition into hypertoxic carbofuran poses serious threats to human health and food safety. Therefore, sensitive and accurate detection of CBS is of significant importance. Conventional chromatography-based techniques require expensive instruments and complicated sample pretreatment, limiting their application for fast detection. Current electrochemical and colorimetric methods for detection of pesticides based on the cascade catalytic reactions between acetylcholinesterase (AChE) and nanozymes, which exhibit inferior selectivity. Hence, selective, sensitive and fast detection of CBS is still challenging. ResultsIn this work, an AChE-free colorimetric method was proposed for selective detection of CBS based on its unique hydrolysis behavior and nanozyme. Ti3C2 nanosheets/AuPt nanoparticles (Ti3C2/AuPt NPs) with enhanced peroxidase-like activity were prepared via one-step self-reduction reaction. CBS can be hydrolyzed under acidic condition and produce -SH moieties, which could bond to Pt atoms of Ti3C2/AuPt NPs and shield the active sites of nanozyme, resulting in decreased catalytic activity. Based on the inhibitory effect on the peroxidase-like activity of Ti3C2/AuPt NPs, a colorimetric method was proposed for direct detection of CBS. Under optimal conditions, the method showed wide linear range (0.5 ng mL−1-5 μg mL−1), low limit of detection (0.342 nM), good selectivity and anti-interference ability. The feasibility of this method for practical use was confirmed by analysis of CBS in real lake water samples. SignificanceThis work proposed a simple colorimetric method for selective and fast detection of CBS, which avoided employing AChE and cascade catalytic reactions, significantly lowering the detection cost and improving detection efficiency. The method showed great potential for accurate detection of CBS in actual samples, and provided a new avenue for developing nanozyme-based colorimetric method for detection of other pesticide residues.

Highly sensitive colorimetric method for the detection of organophosphorus pesticides based on H2O2 etching of silver-coated gold nanostars

The residues of organophosphorus pesticides in agricultural production and soil constitute a significant threat to both human health and ecosystems, underscoring the critical importance of developing effective detection methods for these pesticides. Here, we introduce an innovative method for detecting trichlorfon that integrates hydrogen peroxide (H2O2)-induced etching of silver-coated gold nanostars (AuNS@Ag) with an enzymatic reaction cascade. By precisely controlling the thickness of the silver layer and the morphology of the gold nanoparticle core, we enhance the sensitivity of the H2O2 etching process. In this detection system, acetylcholinesterase (AChE) catalyzes the hydrolysis of acetylcholine chloride (ACh) into choline, which is then oxidized by choline oxidase (ChOx) to produce H2O2. The generated H2O2 subsequently etches the silver layer of AuNS@Ag, leading to a pronounced red-shift in the localized surface plasmon resonance (LSPR) wavelength, from 590 nm to 735 nm. However, the presence of trichlorfon inhibits the activity of AChE, resulting in a reduced production of H2O2 and a subsequent attenuation of the LSPR wavelength shift. Under optimized experimental conditions, this method enables the linear detection of trichlorfon within a concentration range of 0.1–5.0 μg mL−1 and has been successfully applied to detect trichlorfon in cabbage and tap water samples, showcasing its promising potential in food safety and environmental monitoring.

Biodegradation of imidacloprid and diuron by Simplicillium sp. QHSH-33

Imidacloprid (IMI) and diuron (DIU) are widely used pesticides in agricultural production. However, their excessive use and high residues have caused harm to the ecological environment and human health. Microbial remediation as an efficient and low-toxic method has become a research hotspot for controlling environmental pollutants. A fungus QHSH-33, identified as Simplicillium sp., has the ability to degrade neonicotinoids IMI and phenylurea DIU. When QHSH-33 and pesticide were co-cultured in liquid medium for 7 days, the degradation rates of IMI and DIU by QHSH-33 in simulated field soil microenvironment were 50.19 % and 70.57 %, respectively. Through HPLC-MS analysis, it was found that the degradation of IMI mainly involved nitro reduction, hydroxylation and other reactions. Three degradation pathways and eight degradation products were identified, among which two metabolites were obtained by microbial transformation of IMI for the first time. The degradation of DIU mainly involved demethylation and dehalogenation reactions, and two degradation pathways and four degradation products were identified, one of which was a new degradation product of DIU. Toxicity assessment demonstrated that most of the degradation products might be considerably less harmful than IMI and DIU. Whole genome sequencing of QHSH-33 revealed a genome size of 33.2 Mbp with 11,707 genes. The genome of QHSH-33 was annotated by KEGG to reveal 128 genes related to exogenous degradation and metabolism. After local blast with reported IMI and DIU degrading enzymes, seven IMI-degrading related genes and seven DIU-degrading related genes were identified in the QHSH-33 genome. The results of this study will help to expand our knowledge on the microbial decomposition metabolism of IMI and DIU, and provide new insights into the degradation mechanism of IMI and DIU in soil and pure culture system, laying a foundation for QHSH-33 strain applied to the removal, biotransformation or detoxification of IMI and DIU.

Flexible SERS chips for rapid on-site detection of tricyclazole pesticide in agricultural products.

A flexible, ultrasensitive, and practical SERS chip is presented based on a paper/f-TiO2/Ag structure. The chip enhances the self-assembly of Ag nanoparticles on a cellulose fiber matrix, facilitated by smart functionalized TiO2 nanomaterials (f-TiO2). This design enables superior detection of the hazardous pesticide tricyclazole (TCZ) on crops using an advanced, simple, and efficient analytical method.Despite its straightforward fabrication process via a solvent immersion method, the intrinsic smart surface properties of the TiO2 bridging material -both hydrophilic and hydrophobic-enable the uniform and dense self-assembly of hydrophilic Ag nanoparticles (NPs) on the cellulose fiber paper substrate. This innovative design provides superior sensing efficiency for TCZ molecules with a detection limit reaching 2.1 × 10-9M, a remarkable improvement compared to Paper/Ag substrates lacking f-TiO2 nanomaterials, which register at 10-5M. This flexible SERS substrate also exhibits very high reliability as indicated by its excellent reproducibility and repeatability with relative standard deviations (RSD) of only 5.93% and 4.73%, respectively. Characterized by flexibility and a water-attractive yet non-soluble surface, the flexible Paper/f-TiO2/Ag chips offer the convenience of direct immersion into the analytical sample, facilitating seamless target molecule collection while circumventing interference signals. Termed the "dip and dry" technique, its advantages in field analysis are indisputable, boasting in situ deployment, simplicity, and high efficiency, while minimizing interference signals to negligible levels. Through the application of this advanced technique, we have successfully detected TCZ in two high-value crops, ST25 rice and dragon fruit, achieving excellent recovery values ranging from 90 to 128%. This underscores its immense potential in ensuring food quality and safety. As a proof of concept, flexible Paper/f-TiO2/Ag SERS chips, with a simple fabrication process, advanced analytical technique, and superior sensing efficiency, bring SERS one step closer to field applications beyond the laboratory.

LC-MS/MS and GC-MS/MS Cross-Checking Analysis Method for 426 Pesticide Residues in Agricultural Products: A Method Validation and Measurement of Uncertainty.

A method was developed to analyze residual pesticides in various vegetables using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS). A method can analyze over 200 individual compounds, selectively separate peaks within 30 min, and meet various criteria such as those by the Codex Alimentarius Commission (CODEX). Most compounds showed recovery rates between 70 and 120%, and a relative standard deviation was within 20%. Measurement uncertainty, considering various influencing factors such as instrument precision, method sensitivity, experimental conditions, sample handling, and analytical procedures, was meticulously calculated. The expanded uncertainties of cross-checking 33 available pesticides ranged from 10.1 to 26.2 μg/kg at a confidence level of approximately 95%. Risk assessment of detected pesticides in agricultural products indicated a safety range of 0.00003-2.87240%. The developed method effectively analyzes diverse compounds simultaneously, contributing to agricultural product safety.

A case of oral chloropicrin poisoning

Chloropicrin is a commonly used pesticide in agricultural production. The clinical manifestations of oral poisoning patients are complex, and the lesions involve multiple organs. At present, the specific pathogenic mechanism of such poisoning is not clear, and the treatment experience is insufficient, so there are certain difficulties in clinical diagnosis, treatment and treatment. In this paper, the data of a patient with oral chloropicrin poisoning treated in Yidu Central Hospital of Weifang City in April 2023 were summarized. The patient was admitted to our hospital for treatment in time, and his condition improved after Hemopurification, methylene blue reduction, organ support, infection prevention as well as other symptomatic support. Oral chlorophenol can cause lung damage, skin and mucous membrane damage, and may have certain effects on the nervous system and kidney. Early intervention, especially blood purification, is effective.

Dual-Mode Fluorescent/Intelligent Lateral Flow Immunoassay Based on Machine Learning Algorithm for Ultrasensitive Analysis of Chloroacetamide Herbicides.

Given the harmful effect of pesticide residues, it is essential to develop portable and accurate biosensors for the analysis of pesticides in agricultural products. In this paper, we demonstrated a dual-mode fluorescent/intelligent (DM-f/DM-i) lateral flow immunoassay (LFIA) for chloroacetamide herbicides, which utilized horseradish peroxidase-IgG conjugated time-resolved fluorescent nanoparticle probes as both a signal label and amplification tool. With the newly developed LFIA in the DM-f mode, the limits of detection (LODs) were 0.08 ng/mL of acetochlor, 0.29 ng/mL of metolachlor, 0.51 ng/mL of Propisochlor, and 0.13 ng/mL of their mixture. In the DM-i mode, machine learning (ML) algorithms were used for image segmentation, feature extraction, and correlation analysis to obtain multivariate fitted equations, which had high reliability in the regression model with R2 of 0.95 in the range of 2 × 102-2 × 105 pg/mL. Importantly, the practical applicability was successfully validated by determining chloroacetamide herbicides in the corn sample with good recovery rates (85.4 to 109.3%) that correlate well with the regression model. The newly developed dual-mode LFIA with reduced detection time (12 min) holds great potential for pesticide monitoring in equipment-limited environments using a portable test strip reader and laboratory conditions using ML algorithms.

Permethrin exposure impacts zebrafish lipid metabolism via the KRAS-PPAR-GLUT signaling pathway, which is mediated by oxidative stress

Permethrin (Per) is a widely used and frequently detected pyrethroid pesticide in agricultural products and the environment. It may pose potential toxicity to non-target organisms. Per has been reported to affect lipid homeostasis, although the mechanism is undefined. This study aims to explore the characteristic transcriptomic profiles and clarify the underlying signaling pathways of Per-induced lipid metabolism disorder in zebrafish liver. The results showed that environmental exposure to Per caused changes in the liver index, histopathology, and oxidative stress in zebrafish. Moreover, transcriptome results showed that Per heavily altered the pathways involved in metabolism, the immune system, and the endocrine system. We conducted a more in-depth analysis of the genes associated with lipid metabolism. Our findings revealed that exposure to Per led to a disruption in lipid metabolism by activating the KRAS-PPAR-GLUT signaling pathways through oxidative stress. The disruption of lipid homeostasis caused by exposure to Per may also contribute to obesity, hepatitis, and other diseases. The results may provide new insights for the risk of Permethrin to aquatic organisms and new horizons for the pathogenesis of hepatotoxicity.

Automated identification of pesticide mixtures via machine learning analysis of TLC-SERS spectra

Identification of components in pesticide mixtures has been a major challenge in spectral analysis. In this paper, we assembled monolayer Ag nanoparticles on Thin-layer chromatography (TLC) plates to prepare TLC-Ag substrates with mixture separation and surface-enhanced Raman scattering (SERS) detection. Spectral scans were performed along the longitudinal direction of the TLC-Ag substrate to generate SERS spectra of all target analytes on the TLC plate. Convolutional neural network classification and spectral angle similarity machine learning algorithms were used to identify pesticide information from the TLC-SERS spectra. It was shown that the proposed automated spectral analysis method successfully classified five categories, including four pesticides (thiram, triadimefon, benzimidazole, thiamethoxam) as well as a blank TLC-Ag data control. The location of each pesticide on the TLC plate was determined by the intersection of the information curves of the two algorithms with 100 % accuracy. Therefore, this method is expected to help regulators understand the residues of mixed pesticides in agricultural products and reduce the potential risk of agricultural products to human health and the environment.

CdTe@ZnS quantum dots for rapid detection of organophosphorus pesticide in agricultural products

Organophosphorus pesticides (OPPs) constitute the most widely employed class of pesticides. However, the prevalent use of OPPs, while advantageous, raises concerns due to their toxicity, posing serious threats to food safety. Chemical sensors utilizing quantum dots (QDs) demonstrate promising applications in rapidly detecting OPPs residues, thereby facilitating efficient inspection of agricultural products. In this study, we employ an aqueous synthesis approach to prepare low toxic CdTe@ZnS QDs with stable fluorescence properties. To mitigate the risk of imprecise measurements stemming from the inherent susceptibility of fluorescence to quenching, we have adopted the principle of fluorescence resonance energy transfer (FRET) for the construction of the turn-on quantum dot sensor. With a detection limit for chlorpyrifos as low as 10 ppb (10 μg/L), the QDs sensor exhibits notable resistance to interference from various pesticides. Application of this system to detect organophosphorothioate pesticides in apples produced results consistent with those obtained from high-performance liquid chromatography (HPLC) detection, affirming the promising application prospects of this sensing system for the rapid detection of OPPs residues.

Simultaneous Analysis of 272 Pesticides in Agricultural Products by the QuEChERS Method and Gas Chromatography with Tandem Mass Spectrometry.

The aim of this study is to develop a rapid and accurate method for simultaneous analysis of multi-residue pesticides and conduct pesticide monitoring in agricultural products produced by the production and distribution stage in Korea. The representative agricultural products were selected as brown rice, soybean, potato, mandarin, and green pepper and developed using gas chromatography with tandem mass (GC-MS/MS) for the analysis of 272 pesticide residues. The experimental samples were extracted by the QuEChERS-EN method and then cleaned up by using d-SPE, including MgSO4 and primary secondary amine (PSA) sorbents. The established method was validated in accordance with Codex CAC-GL/40, and the limit of quantitation (LOQ) was determined to be 0.01 mg/kg. A total of 243 pesticides satisfied the guidelines in five samples at three levels with values of 60 to 120% (recovery) and ≤45% (coefficient of variation, CV). The remaining 29 pesticides did not satisfy the guidelines, and these pesticides are expected to be used as a screening method for the routine inspection of agricultural products. As a result of analyzing 223 agricultural products in South Korea by applying the simultaneous analysis method, none of the detected levels in the samples exceeded the standard values based on maximum residue limits (MRLs). The developed method in this study will be used to inspect residual pesticides in agricultural products, and it is anticipated to contribute to the distribution of safe agricultural products to consumers.

Fabrication of a label-free electrochemical immunosensor by functionalized nanofiber membrane for the ultrasensitive detection of quinalphos

The accumulation of quinalphos pesticide in agricultural products have detrimental effects to human body and environment, hence, an efficient and sensitive detection approach is desirable. In this study, a label-free electrochemical immunosensor based on the directly immobilizing nanobody onto functionalized polyvinyl alcohol/gelatin-gold nanoparticles nanofiber membrane (PVA/G-AuNPs NFM) was fabricated. First, a homogeneous PVA/G-AuNPs NFM with multiple-porosity structure and appropriate hydrophilicity was prepared. Then, the electrochemical immunosensor was assembled and under the optimized conditions, the prepared biosensor exhibited good detection performance towards quinalphos with the linear range and limit of detection being 0.06–1000 ng/mL and 50.74 pg/mL (S/N = 3), respectively. Moreover, the sensor presented good specificity, regenerability and stability, maintaining more than 90% activity after 5 times of regeneration and about 90% activity after 6 weeks of storage. Finally, the average recoveries of quinalphos from food samples were 89.68%–110.88% with the coefficient of variation being 1.65%–7.81%, showing good correlation with UPLC-MS/MS (R2 = 0.9859), indicating the accuracy of the proposed electrochemical immunosensor assay. Overall, the label-free electrochemical immunosensor presents a novel approach for the rapid and sensitive detection of quinalphos and other pesticide residues.

MiR-2b-3p Downregulated PxTrypsin-9 Expression in the Larval Midgut to Decrease Cry1Ac Susceptibility of the Diamondback Moth, Plutella xylostella (L.).

Crystal (Cry) toxins, produced by Bacillus thuringiensis, are widely used as effective biological pesticides in agricultural production. However, insects always quickly evolve adaptations against Cry toxins within a few generations. In this study, we focused on the Cry1Ac protoxin activated by protease. Our results identified PxTrypsin-9 as a trypsin gene that plays a key role in Cry1Ac virulence in Plutella xylostella larvae. In addition, P. xylostella miR-2b-3p, a member of the micoRNA-2 (miR-2) family, was significantly upregulated by Cry1Ac protoxin and targeted to PxTrypsin-9 downregulated its expression. The mRNA level of PxTrypsin-9, regulated by miR-2b-3p, revealed an increased tolerance of P. xylostella larvae to Cry1Ac at the post-transcriptional level. Considering that miR-2b and trypsin genes are widely distributed in various pest species, our study provides the basis for further investigation of the roles of miRNAs in the regulation of the resistance to Cry1Ac and other insecticides.

Development of an Analytical Method of Nereistoxin and Nereistoxin-related Pesticides in Agricultural Products by LC-MS/MS

Development of an Analytical Method of Nereistoxin and Nereistoxin-related Pesticides in Agricultural Products by LC-MS/MS

Cerium Dioxide-NRs/ Tungsten Disulfide-Quantum Dots Functionalized W-Shaped WaveFlex Biosensor for Rapid Detection of Paraoxon Pesticide in Agricultural Products

Cerium Dioxide-NRs/ Tungsten Disulfide-Quantum Dots Functionalized W-Shaped WaveFlex Biosensor for Rapid Detection of Paraoxon Pesticide in Agricultural Products

A Safety Survey for Residual Pesticides in Agricultural Products in Meal-kits

A Safety Survey for Residual Pesticides in Agricultural Products in Meal-kits

Exploring Various Photochemical Processes in Optical Sensing of Pesticides by Luminescent Nanomaterials: A Concise Discussion on Challenges and Recent Advancements.

Food safety is a burning global issue in this present era. The prevalence of harmful food additives and contaminants in everyday food is a significant cause for concern as they can adversely affect human health. More particularly, among the different food contaminants, the use of excessive pesticides in agricultural products is severely hazardous. So, the optical detection of residual pesticides is an effective strategy to counter the hazardous effect and ensure food safety. In this perspective, nanomaterials have played a leading role in defending the open threat against food safety instigated by the reckless use of pesticides. Now, nanomaterial-based optical detection of pesticides has reached full pace and needs an inclusive discussion. This Review covers the advancement of photoprocess-based optical detection of pesticides categorically using nanomaterials. Here, we have thoroughly dissected the photoprocesses (aggregation and aggregation-induced emission (AIE), charge transfer and intramolecular charge transfer (ICT), electron transfer and photoinduced electron transfer (PET), fluorescence resonance energy transfer (FRET), hydrogen bonding, and inner filter effect) and categorically demarcated their significant role in the optical detection of pesticides by luminescent nanomaterials over the last few years.

Rapid detection of residual chlorpyrifos and pyrimethanil on fruit surface by surface-enhanced Raman spectroscopy integrated with deep learning approach

Chlorpyrifos and pyrimethanil are widely used insecticides/fungicides in agriculture. The residual pesticides/fungicides remaining in fruits and vegetables may do harm to human health if they are taken without notice by the customers. Therefore, it is important to develop methods and tools for the rapid detection of pesticides/fungicides in fruits and vegetables, which are highly demanded in the current markets. Surface-enhanced Raman spectroscopy (SERS) can achieve trace chemical detection, while it is still a challenge to apply SERS for the detection and identification of mixed pesticides/fungicides. In this work, we tried to combine SERS technique and deep learning spectral analysis for the determination of mixed chlorpyrifos and pyrimethanil on the surface of fruits including apples and strawberries. Especially, the multi-channel convolutional neural networks-gate recurrent unit (MC-CNN-GRU) classification model was used to extract sequence and spatial information in the spectra, so that the accuracy of the optimized classification model could reach 99% even when the mixture ratio of pesticide/fungicide varied considerably. This work therefore demonstrates an effective application of using SERS combined deep learning approach in the rapid detection and identification of different mixed pesticides in agricultural products.

Evolving community structure in the international pesticide trade networks

The statistical properties of the international trade networks of all commodities as a whole have been extensively studied. However, the international trade networks of individual commodities often behave differently. Due to the importance of pesticides in agricultural production and food security, we investigated the evolving community structure in the international pesticide trade networks (iPTNs) of five categories from 2007 to 2018. We reveal that the community structures in the undirected and directed iPTNs exhibit regional patterns. However, the regional patterns are very different for undirected and directed networks and for different categories of pesticides. Moreover, the community structure is more stable in the directed iPTNs than in the undirected iPTNs. We also extract the intrinsic community blocks for the directed international trade networks of each pesticide category. It is found that the largest intrinsic community block is the most stable, appears in every pesticide category, and contains important economies (Belgium, Germany, Spain, France, the United Kingdom, Italy, the Netherlands, and Portugal) in Europe. Other important and stable intrinsic community blocks are Canada and the United States in North America, Argentina and Brazil in South America, and Australia and New Zealand in Oceania. These results suggest that, in the international trade of pesticides, geographic distance and the complementarity of important and adjacent economies are significant factors.

Impacts of Agricultural Pesticide Contamination: An Integrated Risk Assessment of Rural Communities of Eswatini.

Marked reductions in mean annual rainfall associated with climate change in Eswatini in Southern Africa have encouraged the recycling of irrigation water and the increased use of pesticides in agricultural production, raising concerns about potential ecological and health risks due to long-term exposure to pesticide residues in soil and irrigation water. This probabilistic integrated risk assessment used liquid chromatography with tandem mass spectrometry to analyze the concentrations of four commonly used agricultural pesticides (ametryn, atrazine, pendimethalin, and 2,4-dichlorophenoxyacetic acid (2,4-D)) in irrigation water and topsoil samples from farmlands in Eswatini to assess potential ecological and health risks due to exposure. The concentrations of these pesticides ranged from undetectable to 0.104 µg/L in irrigation water and from undetectable to 2.70 µg/g in soil. The probabilistic multi-pathway and multi-route risk assessments conducted revealed hazard indices exceeding 1.0 for all age groups for ametryn and atrazine, suggesting that the daily consumption of recycled irrigation water and produce from the fields in this area may pose considerable health risks. The indices pertaining to ecological risks had values less than 0.1. Adaptation measures are recommended to efficiently manage pesticide use in agriculture, and further research will ensure that agriculture can adapt to climate change and that the general public and ecosystem are protected.