A method for the rapid determination of pesticides coupling thin-layer chromatography and enzyme inhibition principles

Self-powered photoelectrochemical sensor based on molecularly imprinted polymer-coupled CBFO photocathode and Ag2S/SnS2 photoanode for ultrasensitive dimethoate sensing

Dimethoate (DIM) is one of the most extensively applied organophosphorus pesticides (OPs), which is used to boost farm productivity due to its high insecticidal efficacy. However, the excessive use of DIM can result in the extensive contamination of soil, groundwater and food. Monitoring of DIM in environmental and food samples is crucial in view of its potential health risks and environmental hazards from excessive residues. The expensive equipment and complex operations for current detection methods greatly limit their practical applications. Herein, a self-powered photoelectrochemical (PEC) sensing platform based on Ag2S/SnS2 photoanode, iron-doped cobalt borate (CBFO) photocathode, and molecularly imprinted polymers (MIPs) was proposed for the detection of DIM. The molecularly imprinted polymers at CBFO photocathode endow the self-powered PEC sensor with high selectivity. The Ag2S/SnS2 photoanode enhances the efficient of electron transfer between the photoanode and photocathode, contributing to the high sensitivity of PEC sensor. The self-powered molecularly imprinted PEC sensor exhibits outstanding sensitivity and selectivity for DIM at concentrations from 1 × 10-2 to 1 × 105 nM with a detection limit of 5.9 pM. Excellent recoveries (95.4 ± 2.6 %, 98.4 ± 2.3 %, 106.3 ± 3.3 %) were achieved in spiked crown pear samples, indicating that the molecularly imprinted PEC sensor is capable of detecting DIM in real samples. This research provides a novel simple, fast, highly selective and sensitive self-powered molecularly imprinted photoelectrochemical sensing platform for detection of DIM. The fabricated PEC sensor offers a promising candidate for the detection method of organophosphorus pesticides residues, which is of great significance for the fields of food safety and environmental protection.

De novo synthesis of a novel hapten and development of a monoclonal antibody-based immunoassay for the detection of dichlorvos and trichlorfon

The absence of high-affinity antibodies has hindered the development of satisfactory immunoassays for dichlorvos (DDVP) and trichlorfon (TCP), two highly toxic organophosphorus pesticides. Herein, the de novo synthesis of a novel anti-DDVP hapten was introduced. Subsequently, a specific anti-DDVP monoclonal antibody (Mab) was produced with satisfying affinity to DDVP (IC50: 12.4 ng mL-1). This Mab was highly specific to DDVP, and TCP could readily convert into DDVP under mild alkaline conditions. Leveraging this insight, an indirect competitive ELISA was successfully developed for simultaneous detection of DDVP and TCP. The limit of detection in rice, cabbage and apple for DDVP /TCP was found to be 12.1/14.6 μg kg-1, 7.3/8.8 μg kg-1 and 6.9/8.3 μg kg-1, respectively. This study not only provides an effective strategy for producing a high-quality anti-DDVP Mab but also affords a reliable and cost-effective tool suitable for high-throughput detection of DDVP and TCP in food samples.

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.

Nanobodies-based colloidal gold immunochromatographic assay for specific detection of parathion

Parathion is one of organophosphorus pesticide, which has been prohibited in agricultural products due to its high toxicity to human beings. However, there are still abuse cases for profit in agricultural production. Hence, we established nanobodies-based colloidal gold immunochromatographic assay (GICA) in which nanobodies (Nbs) as an excellent recognition element, greatly improving the stability and sensitivity of ICA. Under the optimal conditions, the developed Nbs-based GICA showed a cut-off value of 50 ng/mL for visual judgment and a half-inhibitory concentration (IC50) of 2.39 ng/mL for quantitative detection. The limit of detection (LOD) was as low as 0.15 ng/mL which was significantly 50-fold higher sensitivity than the commercial mAb-ICA. Additionally, this method exhibited good recoveries for the detection of cabbage, cucumber, and orange samples and excellent correlation with the UPLC-MS/MS method. The results showed that this method developed in this work based on nanobody can be used in practical detection of parathion in foods and nanobody is novel prospective antibody resource for immunoassays of chemical contaminants.

Pesticide residue detection technology for herbal medicine: current status, challenges, and prospects

The domains of cancer therapy, disease prevention, and health care greatly benefit from the use of herbal medicine. Herbal medicine has become the mainstay of developing characteristic agriculture in the planting area increasing year by year. One of the most significant factors in affecting the quality of herbal medicines is the pesticide residue problem caused by pesticide abuse during the cultivation of herbal medicines. It is urgent to solve the problem of detecting pesticide residues in herbal medicines efficiently and rapidly. In this review, we provide a comprehensive description of the various methods used for pesticide residue testing, including optical detection, the enzyme inhibition rate method, molecular detection methods, enzyme immunoassays, lateral immunochromatographic, nanoparticle-based detection methods, colorimetric immunosensor, chemiluminescence immunosensor, smartphone-based immunosensor, etc. On this basis, we systematically analyze the mechanisms and some of the findings of the above detection strategies and discuss the challenges and prospects associated with the development of pesticide residue detection tools.

Highly Sensitive and Rapid Screening Technique for the Detection of Organophosphate Pesticides and Copper Compounds Using Bifunctional Recombinant TrxA-PvCarE1

Enabling the detection of organophosphate pesticide (OP) residues through enzyme inhibition-based technology is crucial for ensuring food safety and human health. However, the use of acetylcholinesterase, the primary target enzyme for OPs, isolated from animals in practical production poses challenges in terms of sensitivity and batch stability. To address this issue, we identified a highly sensitive and reproducible biorecognition element, TrxA-PvCarE1, derived from red kidney beans and successfully overexpressed it in Escherichia coli. The resulting recombinant TrxA-PvCarE1 exhibited remarkable sensitivity toward 10 OPs, surpassing that of commercial acetylcholinesterase. Additionally, this approach demonstrated the capability to simultaneously detect copper compounds with high sensitivity, expanding the range of pesticides detectable using the traditional enzyme inhibition method. Spiking recovery tests conducted on cowpea and carrot samples verified the suitability of the TrxA-PvCarE1-based technique for real-life sample analysis. In summary, this study highlights a promising comprehensive candidate for the rapid detection of pesticide residues.

Emerging Insights into the Use of Advanced Nanomaterials for the Electrochemiluminescence Biosensor of Pesticide Residues in Plant-Derived Foodstuff

Pesticides have an important role in rising the overall productivity and yield of agricultural foods by eliminating and controlling insects, pests, fungi, and various plant-related illnesses. However, the overuse of pesticides has caused pesticide pollution of water bodies and food products, along with disruption of environmental and ecological systems. In this regard, developing low-cost, simple, and rapid-detecting approaches for the accurate, rapid, efficient, and on-site screening of pesticide residues is an ongoing challenge. Electrochemiluminescence (ECL) possesses the benefits of great sensitivity, the capability to resolve several analytes using different emission wavelengths or redox potentials, and excellent control over the light radiation in time and space, making it a powerful strategy for sensing various pesticides. Cost-effective and simple ECL systems allow sensitive, selective, and accurate quantification of pesticides in agricultural fields. Particularly, the development and progress of nanomaterials, aptamer/antibody recognition, electric/photo-sensing, and their integration with electrochemiluminescence sensing technology has presented the hopeful potential in reporting the residual amounts of pesticides. Current trends in the application of nanoparticles are debated, with an emphasis on sensor substrates using aptamer, antibodies, enzymes, and molecularly imprinted polymers (MIPs). Different strategies are enclosed in labeled and label-free sensing along with luminescence determination approaches (signal-off, signal-on, and signal-switch modes). Finally, the recent challenges and upcoming prospects in this ground are also put forward.

Advances in Microfluidics Techniques for Rapid Detection of Pesticide Residues in Food

Food safety is a significant issue that affects people worldwide and is tied to their lives and health. The issue of pesticide residues in food is just one of many issues related to food safety, which leave residues in crops and are transferred through the food chain to human consumption. Foods contaminated with pesticide residues pose a serious risk to human health, including carcinogenicity, neurotoxicity, and endocrine disruption. Although traditional methods, including gas chromatography, high-performance liquid chromatography, chromatography, and mass spectrometry, can be used to achieve a quantitative analysis of pesticide residues, the disadvantages of these techniques, such as being time-consuming and costly and requiring specialist staff, limit their application. Therefore, there is a need to develop rapid, effective, and sensitive equipment for the quantitative analysis of pesticide residues in food. Microfluidics is rapidly emerging in a number of fields due to its outstanding strengths. This paper summarizes the application of microfluidic techniques to pyrethroid, carbamate, organochlorine, and organophosphate pesticides, as well as to commercial products. Meanwhile, the study also outlines the development of microfluidics in combination with 3D printing technology and nanomaterials for detecting pesticide residues in food.