Comprehensive strategy for analysis of pesticide multi-residues in food by GC–MS/MS and UPLC-Q-Orbitrap

Recent Advances in Nontargeted Screening of Chemical Hazards in Foodstuffs

The emergence of several chemical substances continues to enrich and facilitate the development of food science, but their irrational use also poses a threat to food safety and human health. Nontargeted screening (NTS) has become an important tool for rapid traceability and efficient identification of chemical hazards in food matrices. NTS in food analysis is highly integrated with sample pretreatment, instrumental analysis platforms, data acquisition and analysis, and toxicology. This article is a systemic review of current sample preparation, analytical platforms, and toxicity-guided NTS techniques and provides the latest advancements in workflows and innovative applications of the NTS process based on mass spectrometric techniques. High-throughput toxicity screening platforms play an important role in NTS of unknown chemical hazards of complex food matrices. Advanced machine learning and artificial intelligence are increasingly accessible fields that may effectively process large-scale screening data and advance food NTS research.

Suspect and nontarget screening of pesticides and their transformation products in agricultural products using liquid chromatography-high-resolution mass spectrometry

Intensive agricultural production involves the extensive use of chemicals, leading to the presence of pesticides and their transformation products (TPs) in agricultural products. Our study developed a high-coverage method to map the occurrence of pesticides and their transformation products in agricultural products using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). Initially, a suspect list of 1265 pesticides was compiled based on in-house standards and online databases to identify potential parent pesticides. Besides, the reported and predicted TPs, as well as the multi-class characteristic fragment ions (CFIs) of pesticides, were summarized. Subsequently, nontarget features were identified by matching with 10226 TPs and 39-classes of CFIs. Both known and unknown parent pesticides and their TPs can be identified via suspect and nontarget screening procedures. Ultimately, the proposed method was applied to strawberry samples to demonstrate its effectiveness. We identified 67 parent pesticides and 57 TPs in 107 samples, with the majority at low concentrations, and preliminary traceability suggesting they may migrate from soil. The findings suggest that our method can enable suspect and nontarget screening of pesticides and their TPs, and it is also applicable to other food matrices. This method may facilitate regulatory agencies in strengthening the supervision of unknown risk substances or TPs, thereby comprehensively safeguarding consumer health.

In situ quantification of fungicide residue on wheat leaf surfaces using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging technology

To overcome the time-consuming off-site limitations in conventional pesticide detection, this contribution presents an in situ quantitative analysis detection strategy for pesticides on leaf surfaces using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry imaging technology. Taking fungicide metrafenone as a representative, we initially screened seven commonly used matrices, and identifying α-cyano-4-hydroxycinnamic acid as the most effective one in positive mode. Subsequently, coating the matrix using sublimation spraying method resulted in the highest mass intensity. The optimal combination of operation parameters were established with imaging step size of 30 μm × 30 μm, laser diameter of 75 μm, and laser energy of 4.01 μJ/pulse. Under these conditions, a lowest detection limit of 0.6 ng/mm2 was reached for metrafenone, demonstrating extremely high sensitivity and strong repeatability. This method exhibits great potential for the analysis of various pesticides, including triadimefon and tebuconazole, thereby offering innovative approaches to the analysis of pesticide residues.

Programmability of dual-color DNA-templated silver nanoclusters for modular design of FRET aptasensors toward multiplexed detection

By exploiting the programmability of DNA, dual-color DNA-templated silver nanoclusters have been synthesized to serve as a label-free fluorescent probe with a G5-linker at the 3' end. This advancement facilitates the modular design of universal FRET-based aptasensors using aptamers with a C5-linker at the 3' end for multiplexed detection, making them easily switch their applications.

A Facile Determination of Herbicide Residues and Its Application in On-Site Analysis

Abuse of herbicides in food safety is a vital concern that has an influence on the sustainable development of the world. This work presents, a modified ionization method with separation of the sample and carrier gas inlets, which was utilized for efficient ionization and analyte transfer of herbicides in crops. The working parameters of voltage, injective distance, desorption temperature, and the carrier gas flow rate were optimized to achieve the high efficiency of the transfer and ionization of the analyte. When it was applied in the analysis of herbicides in laboratory, the method exhibited excellent performance in achieving the quantitative detection of herbicides in solutions and residues spiked in an actual matrix with a limit of quantification of 1-20 μg/kg and relative standard deviations of less than 15%. Although a simple QuEchERS process was used, the programmable heating platform ensured efficient gasification and transfer of the target analyte, with the advantages of high speed and selectivity, avoiding the noted matrix effect. The method exhibited a relatively acceptable performance by using air as the discharged gas (open air). It could be used to monitor herbicide residues in the growth stage via on-site non-destructive analysis, which obtained low LODs by dissociating the herbicides from the crops without any pretreatment. It showed great potential for the supervision of the food safety market by achieving non-destructive detection of crops anytime and anywhere. This finding may provide new insights into the determination of pesticide emergence and rice quality assessment.

Occurrence and health risk of pesticide residues in Chinese herbal medicines from Shandong Province, China

Pesticide residue was one of the stress factors affecting quality and safety of Chinese herbal medicines (CHMs). The present study was designed to investigate the occurrence and dietary exposure of 70 pesticide residues in 307 samples of CHMs, including 104 American ginseng, 100 Ganoderma lucidum (G. lucidum), and 103 Dendrobium officinale (D. officinale) in Shandong Province, China. The study revealed that a total of 29 pesticides were detected in the majority (92.5%) of samples, and the pesticide residues of 85 (27.7%) samples exceeded the maximum residue levels (MRLs). Particularly, the maximum concentration of chlorpyrifos was 23.8 mg kg-1, almost 50 times of the MRLs in food in GB 2763-2021, while there's no standard restrictions specified in CHMs in China. The chronic, acute, and cumulative risk assessment results indicated that risk exposure of the three types of CHMs were unlikely to pose a health risk to consumers. However, more attention should be paid to the multiple residues with the presence of four or more pesticides in one sample and high over-standard rate of pesticides. The pesticide users and the government should pay more attention to the pesticides used in CHMs and regularly monitor the presence of these compounds. The study recommended the MRLs of these pesticides in CHMs should be established and perfected by the relevant departments in China.

A New Type of Quantum Fertilizer (Silicon Quantum Dots) Promotes the Growth and Enhances the Antioxidant Defense System in Rice Seedlings by Reprogramming the Nitrogen and Carbon Metabolism

To promote the growth and yield of crops, it is necessary to develop an effective silicon fertilizer. Herein, a new type of 2 nm silicon quantum dot (SiQD) was developed, and the phenotypic, biochemical, and metabolic responses of rice seedlings treated with SiQDs were investigated. The results indicated that the foliar application of SiQDs could significantly improve the growth of rice seedlings by increasing the uptake of nutrient elements and activating the antioxidative defense system. Furthermore, metabolomics revealed that the supply of SiQDs could significantly up-regulate several antioxidative metabolites (oxalic acid, maleic acid, glycine, lysine, and proline) by reprogramming the nitrogen- and carbon-related biological pathways. The findings provide a new strategy for developing an effective and promising quantum fertilizer in agriculture.

Rapid analysis of insecticidal metabolites from the entomopathogenic fungus Beauveria bassiana 331R using UPLC-Q-Orbitrap MS

Beauveria bassiana, a representative entomopathogenic fungus, is increasingly being utilized as an eco-friendly pest management alternative to chemical insecticides. This fungus produces a range of insecticidal secondary metabolites that act as antimicrobial and immunosuppressive agents. However, detailed qualitative and quantitative analysis related to these compounds remains scarce, we developed a method for the rapid analysis of these metabolites. Eight secondary metabolites (bassianin, bassianolide, beauvericin, beauveriolide I, enniatin A, A1, and B, and tenellin) were efficiently extracted when B. bassiana-infected Tenebrio molitor larvae were ground in 70% EtOH extraction solvent and subsequently subjected to ultrasonic treatment for 30 min. The eight metabolites were rapidly and simultaneously analyzed using ultra-performance liquid chromatography-quadrupole-Orbitrap mass spectrometry (UPLC-Q-Orbitrap MS). Bassianolide (20.6-51.1 µg/g) and beauvericin (63.6-109.8 µg/g) were identified as the main metabolites in B. basssiana-infected larvae, indicating that they are likely major toxins of B. bassiana. Validation of the method exhibited recovery rates in the range of 80-115% and precision in the range of 0.1-8.0%, indicating no significant interference from compounds in the matrix. We developed a method to rapidly analyze eight insecticidal metabolites using UPLC-Q-Orbitrap MS. This can be extensively utilized for detecting and producing insecticidal fungal secondary metabolites.

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

Herein, we developed a method coupling TLC and enzyme inhibition principles to rapidly detect OPs (dichlorvos, paraoxon and parathion). After the removal of the organic solvent from the samples using TLC and paper-based chips, the enzyme was added to the detection system. The results showed that the current method effectively reduced the effects of solvents on enzyme behavior. Moreover, the pigments could be successfully retained on TLC with 40% ddH₂O/ACN solution (v/v) as a developing solvent. Additionally, the detection limits (LODs) were 0.002 µg/mL for dichlorvos, 0.006 µg/mL for paraoxon, and 0.003 µg/mL for parathion. Finally, the method was applied to spiked cabbage, cucumber, and spinach and showed good average recoveries ranging between 70.22% and 119.79%. These results showed that this paper-based chip had high sensitivity, precleaning, and elimination of organic solvent properties. Furthermore, it provides a valuable idea for sample pretreatment and rapid determination of pesticide residues in food.

Degradation of the Novel Heterocyclic Insecticide Pyraquinil in Water: Kinetics, Degradation Pathways, Transformation Products Identification, and Toxicity Assessment

As new pesticides are continuously introduced into agricultural systems, it is essential to investigate their environmental behavior and toxicity effects to better evaluate their potential risks. In this study, the degradation kinetics, pathways, and aquatic toxicity of the new fused heterocyclic insecticide pyraquinil in water under different conditions were investigated for the first time. Pyraquinil was classified as an easily degradable pesticide in natural water, and hydrolyzes faster in alkaline conditions and at higher temperatures. The formation trends of the main transformation products (TPs) of pyraquinil were also quantified. Fifteen TPs were identified in water using ultrahigh-performance liquid chromatography coupled to quadrupole Orbitrap high-resolution mass spectrometry (UHPLC-Orbitrap-HRMS) and Compound Discoverer software, which adopted suspect and nontarget screening strategies. Among them, twelve TPs were reported for the first time and 11 TPs were confirmed by synthesis of their standards. The proposed degradation pathways have demonstrated that the 4,5-dihydropyrazolo[1,5-a]quinazoline skeleton of pyraquinil is stable enough to retain in its TPs. ECOSAR prediction and laboratory tests showed that pyraquinil was "very toxic" or "toxic" to aquatic organisms, while the toxicities of all of the TPs are substantially lower than that of pyraquinil except for TP484, which was predicted to pose a higher toxicity. The results are important for elucidating the fate and assessing the environmental risks of pyraquinil, and provide guidance for scientific and reasonable use.

Evaluation of Matrix Complexity in Nontargeted Analysis of Small-Molecule Toxicants by Liquid Chromatography-High-Resolution Mass Spectrometry

Complex mixtures, characterized by high density of compounds, challenge trace detection and identification. This is further exacerbated in nontargeted analysis, where a compound of interest may be well hidden under thousands of matrix compounds. We studied the effect of matrix complexity on nontargeted detection (peak picking) by LC-MS/MS (Orbitrap) analysis. A series of ∼20 drugs, V-type chemical warfare agents and pesticides, simulating toxic unknowns, were spiked at various concentrations in several complex matrices including urine, rosemary leaves, and soil extracts. Orbitrap "TraceFinder" software was used to explore their peak intensities in relation to the matrix (peak location in an intensity-sorted list). Average practical detection limits of nontargets were determined. While detection among the first 10,000 peaks was achieved at 0.3-1 ng/mL levels in the extract, for the more realistic "top 1000" list, much higher concentrations were required, approaching 10-30 ng/mL. A negative power law functional dependence between the peak location in an intensity-sorted suspect list and the nontarget concentration is proposed. Controlled complexity was explored with a series of urine dilutions, resulting in an excellent correlation between the power law coefficient and dilution factor. The intensity distribution of matrix peaks was found to spread (unevenly) on a broad range, fitting well the Weibull distribution function with all matrices and extracts. The quantitative approach demonstrated here gives a measure of the actual capabilities and limitations of LC-MS in the analysis of nontargets in complex matrices. It may be used to estimate and compare the complexity of matrices and predict the typical detection limits of unknowns.

Covalent Organic Frameworks-Based Electrochemical Sensors for Food Safety Analysis

Food safety is a key issue in promoting human health and sustaining life. Food analysis is essential to prevent food components or contaminants causing foodborne-related illnesses to consumers. Electrochemical sensors have become a desirable method for food safety analysis due to their simple, accurate and rapid response. The low sensitivity and poor selectivity of electrochemical sensors working in complex food sample matrices can be overcome by coupling them with covalent organic frameworks (COFs). COFs are a kind of novel porous organic polymer formed by light elements, such as C, H, N and B, via covalent bonds. This review focuses on the recent progress in COF-based electrochemical sensors for food safety analysis. Firstly, the synthesis methods of COFs are summarized. Then, a discussion of the strategies is given to improve the electrochemistry performance of COFs. There follows a summary of the recently developed COF-based electrochemical sensors for the determination of food contaminants, including bisphenols, antibiotics, pesticides, heavy metal ions, fungal toxin and bacterium. Finally, the challenges and the future directions in this field are discussed.

Synthesis of recyclable SERS platform based on MoS2@TiO2@Au heterojunction for photodegradation and identification of fungicides

Surface-enhanced Raman spectroscopy (SERS) substrates based on metal/semiconductors have attracted much attention due to their excellent photocatalytic activity and SERS performance. However, they generally exhibit low light utilization and photocatalytic efficiencies. Herein, molybdenum disulfide coated titanium dioxide modified with gold nanoparticles (MoS₂@TiO₂@Au) as a heterojunction-based recyclable SERS platform was fabricated for the efficient determination of fungicides. Results showed that the MoS₂@TiO₂@Au platform could rapidly degrade 90.7% crystal violet in 120 min under solar light irradiation and enable reproducible and sensitive SERS analysis of three fungicides (methylene blue, malachite green, and crystal violet) and in-situ monitor of the photodegradation process. The platform could also be reused five times due to the unique integrated merits of the MoS₂@TiO₂@Au heterojunction. Meanwhile, experiments in determining methylene blue in prawn protein solution achieved a limit of detection of 1.509 μg/L. Therefore, it is hoped that this work could expand detection applications of photocatalytic materials.

Determination of diflufenican and azaconazole pesticides in wastewater samples by GC-MS after preconcentration with stearic acid functionalized magnetic nanoparticles-based dispersive solid-phase extraction

This study presents the preconcentration of diflufenican and azaconazole from domestic wastewater samples by using dispersive solid-phase extraction (dSPE) for determination by gas chromatography-mass spectrometry (GC-MS). Stearic acid-coated magnetic nanoparticles were used as adsorbents for dSPE method. In order to maximize the efficiency of the extraction process, parameters such as magnetic nanoparticle (MNP) type and amount, eluent type and volume, mixing type, and mixing period were all optimized. The linear range obtained for azaconazole and diflufenican was 7.50-500 ng/mL and 7.50-750 ng/mL, and their limits of detection/quantification (LOD/LOQ) were calculated as 1.3/4.3 ng/mL and 1.4/4.7 ng/mL, respectively. By comparing the LOD values of direct GC-MS and the developed dSPE method, azaconazole and diflufenican recorded approximately 35 and 38 folds enhancement in detection power. Recovery experiments with domestic wastewater were carried out to certify the proposed method's accuracy and applicability. By using the matrix matching calibration strategy, the good percent recovery results between 98 and 105% were obtained.

Profiling of pesticides and pesticide transformation products in Chinese herbal teas

Herbal teas have potential health benefits, but they also contain a variety of pesticides and pesticide transformation products (PTPs) that might brings health risks. Our study maps the pesticides and PTPs in two herbal teas (chrysanthemum and Lusterleaf Holly) from two main producing areas in China. Almost all 122 samples contain pesticides, with concentration ranging from 0.0005 to 10.305 mg/kg. Nearly 40% carbendazim and imidacloprid in chrysanthemum teas and λ-cyhalothrin in Lusterleaf Holly have higher concentration levels than the values permitted in EC Regulation No. 396/2005. Distinct distributions of pesticides were found in different teas and production areas. Eight PTPs were identified along with their parents, and were confirmed using a biosynthetic strategy. Acute, chronic and cumulative health risk assessments of pesticides revealed acceptable results. Our study uncovers the profile of pesticides in herbal teas, and provides new insight into discovering the potential environmental pollution and food contaminants.

Use of molecular imprinted polymers as sensitive/selective luminescent sensing probes for pesticides/herbicides in water and food samples

As non-biological molecules, molecular imprinted polymers (MIPs) can be made as antibody mimics for the development of luminescence sensors for various targets. The combination of MIPs with nanomaterials is further recognized as a useful option to improve the sensitivity of luminescence sensors. In this work, the recent progresses made in the fabrication of fluorescence, phosphorescence, chemiluminescence, and electrochemiluminescence sensors based on such combination have been reviewed with emphasis on the detection of pesticides/herbicides. Accordingly, the materials that are most feasible for the detection of such targets are recommended based on the MIP technologies.

Comprehensive Strategy for Sample Preparation for the Analysis of Food Contaminants and Residues by GC-MS/MS: A Review of Recent Research Trends

Food safety and quality have been gaining increasing attention in recent years. Gas chromatography coupled to tandem mass spectrometry (GC-MS/MS), a highly sensitive technique, is gradually being preferred to GC-MS in food safety laboratories since it provides a greater degree of separation on contaminants. In the analysis of food contaminants, sample preparation steps are crucial. The extraction of multiple target analytes simultaneously has become a new trend. Thus, multi-residue analytical methods, such as QuEChERs and adsorption extraction, are fast, simple, cheap, effective, robust, and safe. The number of microorganic contaminants has been increasing worldwide in recent years and are considered contaminants of emerging concern. High separation in MS/MS might be, in certain cases, favored to sample preparation selectivity. The ideal sample extraction procedure and purification method should take into account the contaminants of interest. Moreover, these methods should cooperate with high-resolution MS, and other sensitive full scan MSs that can produce a more comprehensive detection of contaminants in foods. In this review, we discuss the most recent trends in preparation methods for highly effective detection and analysis of food contaminants, which can be considered tools in the control of food quality and safety.

A Quantitative and Confirmatory Method Employing Liquid Chromatography Coupled to Hybrid High-Resolution Mass Spectrometry and QuEChERS for the Determination of Thirty-Seven Growth Promoter Residues in Bovine Urine

In this work, 37 growth promoters were quantitatively determined in bovine urine using a QuEChERS approach with acetonitrile, NaCl, and MgSO₄:PSA for sample extraction. The analytes were separated and detected by liquid chromatography coupled to hybrid high-resolution mass spectrometry. The method was validated in accordance with the Decision 657/2002/EC guidelines, in which recoveries fell within the range 84-113%, relative standard varied between 2 and 32%, and detection limit between 0.1 and 2.5 μg L^-1. An adequate performance was evidenced during a proficiency test evaluation, and the developed method has been applied to routine analysis of growth promoters in Brazil. A highlight is the easiness of sample extraction combined with a quantitative determination of forbidden drugs using high-resolution mass spectrometry, which enables retrospective analysis in a surveillance perspective.

Evaluation and application of machine learning-based retention time prediction for suspect screening of pesticides and pesticide transformation products in LC-HRMS

Computational QSAR models have gradually been preferred for retention time prediction in data mining of emerging environmental contaminants using liquid chromatography coupled with mass spectrometry. Generally, the model performance relies on the components such as machine learning algorithms, chemical features, and example data. In this study, we evaluated the performances of four algorithms on three feature sets, using 321 and 77 pesticides as the training and validation sets, respectively. The results were varied with different combinations of algorithms on distinct feature sets. Two strategies including enhancing the complexity of chemical features and enlarging the size of the training set were proved to improve the results. XGBoost, Random Forest, and lightGBM algorithms exhibited the best results when built on a large-scale chemical descriptors, while the Keras algorithm preferred fingerprints. These four models have comparable prediction accuracies that at least 90% of pesticides in validation set can be successfully predicted with ΔRT <1.0 min. Meanwhile, a blended prediction strategy using average results from four models presented a better result than any single model. This strategy was used for assisting identification of pesticides and pesticide transformation products in 120 strawberry samples from a national survey of food contamination. Twenty pesticides and twelve pesticide transformation products were tentatively identified, where all pesticides and two pesticide transformation products (bifenazate diazene and spirotetramat-enol) were confirmed by standard materials. The outcome of this study suggested that retention time prediction is a valuable approach in compound identification when integrated with in silico MS² spectra and other MS identification strategies.

Extraction and electrochemical sensing of pesticides in food and environmental samples by use of polydopamine-based materials

Polydopamine has high adsorption capacities for pollutants such as pesticides in food and environmental matrices. Consequently, it has found applications in some sorbent-based micro-extraction techniques such as solid phase micro-extraction and magnetic solid phase extraction. This paper gives a detailed review of the application of polydopamine-based adsorbents for the extraction of pesticides in food and environmental matrices using these techniques. The adhesive properties of polydopamine have made it to be a suitable material for the immobilisation of the components of electrochemical sensors used to detect pesticides in food and environmental matrices. This paper also gives a comprehensive review on the application of polydopamine in electrochemical sensors such as acetylcholinesterase sensors, molecularly imprinted sensors and aptasensors. The use of polydopamine-based adsorbents during the extraction and electrochemical sensing of pesticides in food and environmental matrices is not free of challenges. In this review, the challenges encountered during the use of polydopamine-based adsorbents are also discussed.

Improving the simultaneous target and non-target analysis LC-amenable pesticide residues using high speed Orbitrap mass spectrometry with combined multiple acquisition modes

The use of high-resolution mass spectrometry (HRMS) for the simultaneous target and non-target analysis of pesticide residues in food control is a subject that has been studied over the last decade. However, proving its efficacy compared to the more established triple quadrupole mass spectrometers (QQQ-MS2) is challenging. Various HRMS platforms have been evaluated, seemingly showing this approach not to be as effective as QQQ-MS2 for quantitative analysis, especially in routine food testing laboratories. The two main reasons are (i) the lower sensitivity especially in the case of the fragment ions produced and (ii) the lack of familiarity and an understanding of the most appropriate combination of HRMS acquisition modes to use. In fact, the number of different acquisition modes can appear as a puzzle to inexperienced users. This work was therefore focused on obtaining experimental data to gain a better understanding of the extended acquisition capabilities of a new Q-Orbitrap platform. Experimental data were obtained for 244 pesticides and their degradation products in commodities of varying matrix complexity (tomato, onion, avocado, and orange) using various combinations of acquisition modes. The best results for targeted analysis were obtained with a combination of full scan (FS), all-ions fragmentation (AIF) and target MS2 (tMS2) modes, and for non-target analysis using full scan (FS) and data-dependent MS2 (ddMS2) modes. All these acquisition modes (FS, AIF, tMS2, and ddMS2) could be applied simultaneously with cycle times ≤ 1 s. The tMS2 especially, proved to be a very powerful approach to increase sensitivity for MS2 fragments and identification rates. Overall, the results for the various pesticide-commodity combinations were fully satisfactory in terms of limit of quantitation (LOQ) repeatability and identification when considered against the SANTE EU Guideline criteria. In addition, the screening capabilities were evaluated for a non-target survey with the use of spectral libraries, the presence of non-target compounds was detected, thus proving the efficacy of the proposed approach. Another issue often overlooked is the optimization of use of spectral libraries, but in our experiments the compounds present in these libraries were not blindly sought in the screening analyses. To minimize the potential for false positives detects in our study, the extractability of the compounds present in the libraries, was also taken into account. The extractability of compounds using a QuEChERS acetonitrile procedure was estimated based on the physicochemical properties of target compounds. By removing compounds that will not be extracted, reduces the occurrences of false detects, reducing the time required for data processing and thus improving the efficiency of the overall screening workflow.

Label-free hairpin-like aptamer and EIS-based practical, biostable sensor for acetamiprid detection

Acetamiprid (ACE) is a kind of broad-spectrum pesticide that has potential health risk to human beings. Aptamers (Ap-DNA (1)) have a great potential as analytical tools for pesticide detection. In this work, a label-free electrochemical sensing assay for ACE determination is presented by electrochemical impedance spectroscopy (EIS). And the specific binding model between ACE and Ap-DNA (1) was further investigated for the first time. Circular dichroism (CD) spectroscopy and EIS demonstrated that the single strand AP-DNA (1) first formed a loosely secondary structure in Tris-HClO₄ (20 mM, pH = 7.4), and then transformed into a more stable hairpin-like structure when incubated in binding buffer (B-buffer). The formed stem-loop bulge provides the specific capturing sites for ACE, forming ACE/AP-DNA (1) complex, and induced the R_CT (charge transfer resistance) increase between the solution-based redox probe [Fe(CN)₆]^3−/4− and the electrode surface. The change of ΔR_CT (charge transfer resistance change, ΔR_CT = R_CT(after)-R_CT(before)) is positively related to the ACE level. As a result, the AP-DNA (1) biosensor showed a high sensitivity with the ACE concentration range spanning from 5 nM to 200 mM and a detection limit of 1 nM. The impedimetric AP-DNA (1) sensor also showed good selectivity to ACE over other selected pesticides and exhbited excellent performance in environmental water and orange juice samples analysis, with spiked recoveries in the range of 85.8% to 93.4% in lake water and 83.7% to 89.4% in orange juice. With good performance characteristics of practicality, sensitivity and selectivity, the AP-DNA (1) sensor holds a promising application for the on-site ACE detection.