Preparation method and application of copper-iron bimetallic nanoscale enzyme

Abstract

The application discloses a preparation method of a copper-iron bimetallic nano-enzyme and application thereof, and belongs to the technical field of nano-enzyme preparation and catalytic detection, and solves the technical problems of single nano-enzyme activity, low detection flux, and difficulty in simultaneously detecting multi-component pesticide residues in the prior art. The GMP, copper ions and iron ions are subjected to self-assembly reaction in a buffer solution, and after separation and drying, a GMP-CuFe bimetallic nano-enzyme is obtained. The GMP-CuFe nano-enzyme has dual activities of peroxidase and laccase, a colorimetric array sensor comprising three sensing channels of LAC incubation, LAC and POD is constructed, and by utilizing the differential colorimetric signals generated after different pesticides and the nano-enzyme act in different channels, and by combining linear discriminant analysis, the glyphosate, nicosulfuron, halosulfuron-methyl, metsulfuron-methyl and ferrous methylene bis (dimethyl dithiocarbamate) can be distinguished and quantitatively detected. The preparation method is simple and low in cost, the sensor array is high in sensitivity, good in selectivity and strong in anti-interference capability.

Description

Technical Field

[0001] This invention belongs to the field of nanozyme preparation and catalytic detection technology, specifically relating to a method for preparing copper-iron bimetallic nanozymes and their applications. Background Technology

[0002] Pesticides, as a key means of ensuring crop yields and controlling pests, diseases, and weeds, are widely used throughout the entire agricultural production chain. However, the residue problems caused by long-term excessive use are seriously threatening ecological environment safety and human health. Residues of different types of pesticides, such as organophosphates, sulfonylureas, and organosulfurs, can accumulate through the food chain, causing a series of health risks, including damage to the nervous system and immune dysfunction. On the other hand, the mixing and blending of pesticides during crop production is quite common, necessitating the development of analytical methods that can simultaneously detect multiple pesticides.

[0003] Traditional pesticide detection methods include chromatography (gas chromatography, liquid chromatography), chromatography-mass spectrometry, and capillary electrophoresis. While these methods offer high sensitivity and accuracy, they rely on large, sophisticated instruments, are complex to operate, and have long detection cycles, making them unsuitable for the practical needs of rapid on-site screening. Therefore, establishing rapid, sensitive, and accurate pesticide residue detection technologies is crucial.

[0004] In recent years, sensor array technology, inspired by the mammalian olfactory system, has become a research hotspot in multi-target analysis due to its advantages in cross-response characteristics and pattern recognition. This detection method utilizes multiple cross-reactions between sensing channels and analytes to generate characteristic fingerprint spectra. Based on this principle, array sensors constructed by combining fluorescence, colorimetry, and electrochemical techniques have been introduced into the field of pesticide detection. This technology integrates the differentiated signals of multiple sensing units to form unique fingerprint spectra, and combined with machine learning algorithms, it can achieve accurate differentiation and detection of multiple components in complex systems.

[0005] Nanozymes, as a class of functional nanomaterials possessing catalytic activity similar to natural enzymes, are often used as core recognition elements and signal sources in sensor arrays. Compared with natural enzymes, nanozymes have significant advantages such as simple preparation, low cost, strong stability, and tunable catalytic activity. Furthermore, their rich surface chemical properties and designable microstructures enable them to flexibly respond to different types of pesticide molecules. Based on their catalytic activity, nanozymes can be classified into oxidoreductase-like, hydrolase-like, lyase-like, and isomerase-like categories. Among these, oxidoreductase-like molecules account for over 90% of reported cases, further subdivided into peroxidase-like (POD), oxidase-like (OXD), superoxide dismutase-like (SOD), and catalase-like (CAT) categories. Simultaneously, the catalytic activity of nanozymes and pesticide molecules can be modulated through mechanisms such as coordination binding, hydrogen bonding, and redox reactions, achieving specific responses to specific pesticide classes. For example, copper-based nanozymes such as ASP-Cu, BPY-Cu, and GMP-Cu can be catalytically bound to pesticide molecules via Cu... 2+ Coordination with sulfonylurea pesticides enhances catalytic activity. These properties make nanozymes ideal materials for constructing highly sensitive and selective sensing units, laying the foundation for the detection of multi-component pesticides.

[0006] However, most reported nanozymes and their applications still face numerous technical bottlenecks. These include low catalytic activity, insufficient stability, lack of targeted catalytic center design, and a limited range of detectable pesticides. Therefore, developing a nanozyme with high catalytic activity capable of simultaneously detecting multiple pesticides is of great significance. Summary of the Invention

[0007] Technical problem to be solved: The present invention aims to overcome the shortcomings of the prior art and solve the problems of single nanozyme activity, low detection throughput, and difficulty in simultaneously detecting multiple pesticide residues.

[0008] Purpose of the invention: The purpose of this invention is to provide a method for preparing copper-iron bimetallic nanozymes and to construct an array sensing channel based on their multiple activities for the simultaneous detection of multi-component pesticide residues.

[0009] To achieve the above objectives, the present invention adopts the following technical solution: A method for preparing a copper-iron bimetallic nanozyme includes the following steps: S1. Dissolve N-hydroxyethylpiperazine-2-ethanesulfonic acid (HEPES) in ultrapure water, adjust the pH to 7.0-9.0 using HCl or NaOH solution, and mix thoroughly to obtain a 5-15 mM HEPES buffer solution. S2. Dissolve guanosine-5'-monophosphate (GMP) in ultrapure water and mix thoroughly to obtain a GMP solution with a concentration of 20-30 mM; dissolve a soluble divalent copper salt in ultrapure water and mix thoroughly to obtain a solution containing divalent copper ions with a concentration of 40-60 mM; dissolve a soluble trivalent ferric salt in ultrapure water and mix thoroughly to obtain a solution containing trivalent ferric ions with a concentration of 40-60 mM. S3. Thoroughly mix the GMP solution, HEPES buffer, solution containing divalent copper ions, and solution containing trivalent iron ions to carry out a self-assembly reaction to obtain a reaction solution; the volume ratio of the solution containing divalent copper ions to the solution containing trivalent iron ions is 100:1-10:1; the total volume ratio of the solution containing divalent copper ions and the solution containing trivalent iron ions to the volume ratio of the GMP solution is 0.5:1-1.5:1; the volume ratio of the HEPES buffer to the remaining solutions is 3:1-2:1. S4. Centrifuge the reaction solution to separate the solid and liquid components, discard the supernatant, collect the solid product, wash to obtain the precipitate, vacuum dry the precipitate, and grind the obtained solid into powder to obtain GMP-CuFe nanozyme material with dual activities of peroxidase and laccase.

[0010] Furthermore, the soluble divalent copper salt is CuCl2 or CuSO4, and the soluble trivalent iron salt is FeCl3, Fe2(SO4)3, or Fe(NO3)3.

[0011] This invention also discloses the application of copper-iron bimetallic nanozymes prepared by any of the above preparation methods in colorimetric array sensors for detecting pesticide residues.

[0012] Furthermore, the pesticide is one or more of glyphosate (Gly), nicosulfuron (Nic), chlorpyrifos (Hal), mesosulfuron-methyl (Met), and ferrous sulfate (Fer).

[0013] Furthermore, the sensor comprises three sensing channels, each containing a copper-iron bimetallic nanozyme. The three sensing channels are as follows: LAC incubation channel: used to pre-incubate copper-iron bimetallic nanozymes with the sample to be tested, and then react with laccase-like substrates; LAC channel: used to simultaneously react copper and iron bimetallic nanozymes, the sample to be tested, and laccase-like substrates; POD channel: used to simultaneously react copper and iron bimetallic nanozymes, the sample to be tested, and peroxidase-like substrates; The sample to be tested is added to the LAC incubation channel, LAC channel and POD channel respectively for reaction, and the absorbance value of each channel after reaction is detected. Based on the change of absorbance value of each channel, a response fingerprint spectrum of the sample to be tested is constructed. By comparing the response fingerprint spectrum or by processing it through a linear discriminant analysis model, the pesticide components in the sample to be tested can be detected simultaneously qualitatively and / or quantitatively.

[0014] Furthermore, the laccase-like substrates are 2,4-dichlorophenol (2,4-DP) and 4-aminoantipyridine (4-AP), and the peroxidase-like substrates are hydrogen peroxide (H2O2) and o-phenylenediamine (OPD). The laccase-like activity of the GMP-CuFe nanozyme catalyzes a colorimetric reaction with absorption at 510 nm using 2,4-DP and 4-AP as laccase-like substrates; the peroxidase-like activity of the GMP-CuFe nanozyme catalyzes a colorimetric reaction with absorption at 446 nm using H2O2 and OPD as peroxidase-like substrates.

[0015] Furthermore, the specific detection methods for the three sensing channels are as follows: LAC incubation channel: GMP-CuFe nanozyme material and pesticide to be tested are mixed and incubated at 37℃ for 50-70 min; then 2,4-DP and 4-AP are added to the reaction solution, and the reaction is carried out at 37℃ for 20-30 min, and the absorbance is measured at 510 nm. LAC channel: GMP-CuFe nanozyme material, pesticide to be tested, 2,4-DP and 4-AP were mixed and reacted at 37℃ for 20-30 min, and the absorbance was measured at 510 nm. POD channel: After mixing GMP-CuFe nanozyme material, pesticide to be tested, H2O2 and OPD, the absorbance was measured at 446 nm after reacting at 37℃ for 20-30 min.

[0016] Furthermore, in the LAC incubation channel and LAC channel, the concentration of GMP-CuFe nanozyme material was 0.05-0.10 mg / mL, the concentration of 2,4-DP and 4-AP was 0.8-1.2 mg / mL, and it was prepared with MES buffer solution at pH 6-7; in the POD channel, the concentration of GMP-CuFe nanozyme material was 0.10-0.20 mg / mL, the concentration of H2O2 was 1.6-2.4 mg / mL, the concentration of OPD was 0.8-1.2 mg / mL, and it was prepared with HAc / NaAc buffer solution at pH 4.0-5.5.

[0017] Furthermore, in the LAC incubation channel and the LAC channel, the volume ratio of GMP-CuFe nanozyme material, the pesticide to be tested, 2,4-DP and 4-AP is 1:1:1:1; in the POD channel, the volume ratio of GMP-CuFe nanozyme material, the pesticide to be tested, H2O2 and OPD is 1:1:1:1.

[0018] Furthermore, after absorbance detection, the absorbance change value (A-A0) / A0 obtained from the absorbance detection is first plotted based on the absorbance change value (A-A0) / A0, where A represents the absorbance of the experimental group and A0 represents the absorbance of the blank group. Then, the result of (A-A0) / A0 is calculated and analyzed by linear discriminant analysis (LDA).

[0019] Technical Principle: This invention successfully synthesized a GMP-CuFe bimetallic nanozyme. GMP, a biomolecule containing phosphate groups and guanine bases, can act as a ligand to coordinate with divalent copper ions and trivalent iron ions to self-assemble into a nanostructure. The introduction of trivalent iron ions alters the electronic structure and surface properties of the nanozyme, producing a synergistic catalytic effect, thereby significantly enhancing its peroxidase-like and laccase-like activities. In pesticide detection, pesticide molecules with different structures (such as organophosphates, sulfonylureas, and dithiocarbamates) interact with this nanozyme through different mechanisms, such as coordination, hydrogen bonding, and redox reactions. The presence of pesticides and other substances can have different effects on the dual enzyme activity of nanozymes. This invention cleverly utilizes this difference and designs three independent colorimetric sensing channels: the LAC incubation channel to examine the effect of pesticide-nanozyme binding kinetics on activity; the LAC channel to examine the interference effect of pesticides in the catalytic process; and the POD channel to examine the regulation of another enzyme activity by pesticides. The signals from these three channels constitute a three-dimensional fingerprint spectrum, with each pesticide (or pesticide mixture) having its unique fingerprint. Through statistical methods such as LDA, these subtle differences can be amplified, thereby enabling the simultaneous differentiation and quantitative detection of multi-component pesticides in complex systems.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention is the first to synthesize a GMP-CuFe nanozyme. The GMP-CuFe nanozyme has dual activities such as peroxidase and laccase. The synthesis method is simple, green, low cost, high catalytic activity, good stability, and easy to scale up. 2. Based on the dual activity of the GMP-CuFe nanozyme and its different interaction with pesticide molecules, this invention constructs a colorimetric array sensor containing three sensing channels: "LAC incubation, LAC, and POD". The colorimetric intensity of the three colorimetric sensing channels is linearly correlated with the concentration of the pesticide to be tested. This design increases the dimensionality of the sensor, captures richer pesticide-nanozyme interaction information, and improves the accuracy and discrimination ability of detection. 3. The three-channel sensor constructed in this invention can simultaneously detect one or more pesticides, and even distinguish between pesticides of different proportions. This is difficult to achieve with traditional single-channel sensors. It is easy to operate, has a fast response, and high detection sensitivity. It has broad application prospects in food quality and safety and environmental monitoring. 4. This invention significantly improves the catalytic activity of nanozymes by doping with Fe, laying the foundation for the construction of highly sensitive sensors. 5. The method of the present invention can achieve a detection limit of ppm for five pesticides: glyphosate, nicosulfuron, chlorpyrifos, metsulfuron-methyl, and ferbamectin, and can effectively eliminate interference from common metal ions and biomolecules, demonstrating excellent anti-interference ability. 6. The entire detection process is based on colorimetry, which is simple to operate and does not require complicated pretreatment or large instruments. It is suitable for rapid on-site screening of pesticide residues. Attached Figure Description

[0021] Figure 1 This is a transmission electron microscope (TEM) image of the GMP-CuFe prepared in this invention. Figure 2 This is an elemental surface scan of GMP-CuFe prepared according to the present invention; Figure 3 The following are the performance-enhancing spectra of GMP-CuFe prepared in this invention: A is the XRD pattern of GMP-CuFe, B is the FTIR pattern of GMP-CuFe, C is the XPS full spectrum of GMP-CuFe, D is the Cu 2p XPS spectrum of GMP-CuFe, E is the Fe 2p XPS spectrum of GMP-CuFe, F is the result of kinetic parameter determination of 2,4-DP enzyme, G is the result of kinetic parameter determination of OPD enzyme, and H is the result of kinetic parameter determination of H2O2 enzyme. Figure 4 The images show the enzyme activity verification results of this invention, where A is the laccase activity verification result diagram and B is the peroxidase activity verification result diagram. Figure 5 The results and spectra of the response of the GMP-CuFe-based array sensor to 50 ppm pesticides are shown in the figure. A is the fingerprint spectrum of the response of the GMP-CuFe-based array sensor to 50 ppm pesticides, and B is the LDA result of the response of the GMP-CuFe-based array sensor to 50 ppm pesticides. Figure 6The results and spectra of the response of the GMP-CuFe-based array sensor to 10 ppm pesticides are shown in the figure. A is the fingerprint spectrum of the response of the GMP-CuFe-based array sensor to 10 ppm pesticides, and B is the LDA result of the response of the GMP-CuFe-based array sensor to 10 ppm pesticides. Figure 7 The results and spectra of the response of the GMP-CuFe-based array sensor to 1 ppm pesticide are shown in the present invention. A is the fingerprint spectrum of the response of the GMP-CuFe-based array sensor to 1 ppm pesticide, and B is the LDA result of the response of the GMP-CuFe-based array sensor to 1 ppm pesticide. Figure 8 The diagrams show the linear discriminant analysis and linear relationship of the array sensor of the present invention for different concentrations of glyphosate. In the diagram, A is the linear discriminant analysis of the array sensor's response to different concentrations of glyphosate, and B is the linear relationship of the array sensor's response to different concentrations of glyphosate with Factor 1. Figure 9 The diagrams show the linear discriminant analysis and linear relationship of the array sensor of the present invention for different concentrations of ferrous iron, where A is the linear discriminant analysis of the array sensor's response to different concentrations of ferrous iron, and B is the linear relationship of the array sensor's response to different concentrations of ferrous iron with Factor 1. Figure 10 The diagrams show the linear discriminant analysis of the array sensor response to mixed samples at different ppm levels. Specifically, A represents the linear discriminant analysis of the array sensor response to a 10 ppm mixed sample, B represents the linear discriminant analysis of the array sensor response to a 5 ppm mixed sample, and C represents the linear discriminant analysis of the array sensor response to a 1 ppm mixed sample. Figure 11 This invention presents a fingerprint and LDA result diagram for distinguishing pesticides in the presence of interfering substances, where A is the fingerprint diagram for distinguishing pesticides in the presence of interfering substances and B is the LDA result diagram for pesticides in the presence of interfering substances. Detailed Implementation

[0022] The preferred embodiments of the present invention will now be described in detail with reference to specific examples. It should be understood that the following examples are given for illustrative purposes only and are not intended to limit the scope of the invention. Those skilled in the art can make various modifications and substitutions to the present invention without departing from its spirit and essence.

[0023] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0024] Unless otherwise specified, all materials and reagents used in the following examples are commercially available.

[0025] Example 1: This example provides a method for preparing copper-iron bimetallic nanozymes, including the following steps: S1. Dissolve N-hydroxyethylpiperazine-2-ethanesulfonic acid (HEPES) in ultrapure water, adjust the pH to 8.0 using HCl or NaOH solution, and mix thoroughly to obtain a 10 mM HEPES buffer solution. S2. Dissolve guanosine-5'-monophosphate (GMP) in ultrapure water and vortex vigorously for 2 min to obtain a 25 mM GMP solution; dissolve CuCl2 in ultrapure water and vortex vigorously for 2 min to obtain a 50 mM CuCl2 solution; dissolve FeCl3 in ultrapure water and vortex vigorously for 2 min to obtain a 50 mM FeCl3 solution. S3. Mix 6 mL of 25 mM GMP solution, 21 mL of 10 mM pH 8.0 HEPES buffer, 2.85 mL of 50 mM CuCl2 solution and 0.15 mL of 50 mM FeCl3 solution thoroughly in a centrifuge tube, and vortex vigorously for 2 min to carry out the self-assembly reaction to obtain the reaction solution. S4. Centrifuge at 11000 rpm for 5 min, discard the supernatant, and wash three times successively with ethanol and ultrapure water to obtain the precipitate. Place the precipitate in a vacuum dryer and vacuum dry for 8 h. Grind the obtained nanozyme solid into powder using a quartz mortar, collect and store at 4℃ to obtain GMP-CuFe nanozyme material with dual activities of peroxidase and laccase. When used, disperse in ultrapure water and sonicate for 5 min.

[0026] The microstructure of the GMP-CuFe nanozyme material was characterized using transmission electron microscopy (TEM). It was observed that the material consists of multiple spherical nanoparticles aggregated together, forming irregularly sized agglomerates, such as... Figure 1 As shown. At higher resolutions, no lattice fringes were observed in either material, indicating that they are amorphous materials.

[0027] The GMP-CuFe nanozyme material was characterized by X-ray diffraction (XRD). Figure 3 As shown in Figure A, a relatively broad diffraction peak appears between 15° and 40°, while there are no sharp diffraction peaks, proving the amorphous structure of the material.

[0028] The GMP-CuFe nanozyme material was characterized using Fourier transform infrared spectroscopy (FTIR). For example... Figure 3As shown in Figure B, the infrared spectrum of GMP-CuFe is based on GMP, indicating the presence of GMP ligands in the nanozyme, but a significant wavenumber shift has occurred. Specifically, at 3371 cm⁻¹... -1 For the stretching vibration of NH on the purine ring in GMP, Cu 2+ After Fe coordinates with GMP, the chemical environment of NH changes, causing it to redshift to 3341 cm⁻¹. -1 This indicates that guanosine in GMP is involved in coordination. The blue band in the figure corresponds to 1067 cm⁻¹. -1 and 976cm -1 These are the strong peak of the asymmetric stretching vibration and the weak peak of the symmetric stretching vibration of PO in GMP-CuFe, respectively. The stretching vibration of PO in GMP-CuFe exhibits a blue shift to 1079 cm⁻¹. -1 and 984 cm -1 This indicates that phosphoric acid in GMP also participates in Cu production. 2+ The combination of.

[0029] X-ray photoelectron spectroscopy (XPS) was used to analyze the chemical composition and elemental valence states of GMP-CuFe nanozyme materials. Figure 3 As shown in Table C, the full-spectrum scanning results confirm the presence of Cu, Fe, O, N, C, and P elements in the material, with the contents of each element listed in Table 1. Among these, C, O, N, and P elements mainly originate from the GMP molecular framework. XPS analysis of the Cu 2p orbitals in GMP-CuFe revealed... Figure 3 As shown in D, peak fitting reveals that Cu in the high-resolution spectrum 2+ 2p 3 / 2 and 2p 1 / 2 Electrons were located at 933.5 eV and 953.3 eV, respectively, with a satellite peak observed near 942 eV, confirming the presence of Cu(II) in the material. Further XPS analysis of the valence state of Fe was performed, such as... Figure 3 As shown in Figure E, the peak fitting of the Fe 2p orbital indicates that the characteristic peaks at 711.5 eV and 723.9 eV correspond to Fe 2+ 2p 3 / 2 and 2p 1 / 2 Electrons, while the main peaks of 715.9 eV and 726.9 eV are attributed to Fe. 3+ 2p 3 / 2 and 2p 1 / 2 The presence of electrons indicates the existence of mixed valence states of Fe(II) / Fe(III) in GMP-CuFe.

[0030] Table 1. GMP-CuFe Elemental Ratio Table .

[0031] like Figure 3 China F, Figure 3 China G and Figure 3 As shown in Figure H, the catalytic performance of GMP-CuFe nanozyme material, which resembles laccase and peroxidase, was studied through kinetic experiments. Specifically, the K+ catalytic activity of GMP-CuFe for 2,4-DP, OPD, and H2O2 was investigated. m The values ​​were 0.085 μM, 0.091 μM, and 1.400 μM, respectively, V max The values ​​were 1.18 μM / min, 0.58 μM / min, and 0.363 μM / min, respectively.

[0032] Example 2 illustrates the application of a copper-iron bimetallic nanozyme prepared according to the method described in Example 1 in a colorimetric array sensor for detecting pesticide residues. The sensor comprises three sensing channels, each containing a copper-iron bimetallic nanozyme. By analyzing the differentiated colorimetric responses generated by the nanozymes catalyzing different substrates or reaction conditions before and after the addition of the pesticide sample, combined with statistical methods such as linear discriminant analysis, the simultaneous differentiation and detection of five pesticides, including glyphosate, can be achieved. The three channels are as follows: LAC incubation channel: used to pre-incubate the nanozyme with the sample to be tested, and then react it with the laccase-like substrate; LAC channel: used to simultaneously react the nanozyme, the test sample, and the laccase-like substrate; POD channel: used to react the nanozyme, the sample to be tested, and the peroxidase-like substrate simultaneously.

[0033] The laccase activity of the GMP-CuFe nanozyme can catalyze a colorimetric reaction with absorption at 510 nm using 2,4-dichlorophenol (2,4-DP) and 4-aminoantipyridine (4-AP) as substrates, and the peroxidase activity can catalyze a colorimetric reaction with absorption at 446 nm using hydrogen peroxide (H2O2) and o-phenylenediamine (OPD) as substrates. The three channels are as follows: LAC incubation channel: GMP-CuFe nanozyme material and pesticide to be tested are mixed and incubated at 37℃ for 50-70 min; then 2,4-DP and 4-AP are added to the reaction solution, and the reaction is carried out at 37℃ for 20-30 min, and the absorbance is measured at 510 nm. LAC channel: GMP-CuFe nanozyme material, pesticide to be tested, 2,4-DP and 4-AP were mixed and reacted at 37℃ for 20-30 min, and the absorbance was measured at 510 nm. POD channel: After mixing GMP-CuFe nanozyme material, pesticide to be tested, H2O2 and OPD, the absorbance was measured at 446 nm after reacting at 37℃ for 20-30 min.

[0034] In the LAC incubation and LAC sensing channels, the concentration of GMP-CuFe nanozyme material was 0.05-0.10 mg / mL, and the concentrations of 2,4-DP and 4-AP were 0.8-1.2 mg / mL, prepared with MES buffer solution at pH 6-7; in the POD sensing channels, the concentration of GMP-CuFe nanozyme material was 0.10-0.20 mg / mL, the concentration of H2O2 was 1.6-2.4 mg / mL, and the concentration of OPD was 0.8-1.2 mg / mL, prepared with HAc / NaAc buffer solution at pH 4.0-5.5.

[0035] In the LAC incubation and LAC sensing channel, the volume ratio of GMP-CuFe nanozyme material, pesticide to be tested, 2,4-DP and 4-AP was 1:1:1:1; in the POD sensing channel, the volume ratio of GMP-CuFe nanozyme material, pesticide to be tested, H2O2 and OPD was 1:1:1:1.

[0036] The pesticide is one or more of glyphosate (Gly), nicosulfuron (Nic), chlorpyrifos (Hal), mesosulfuron (Met), and ferrous sulfate (Fer).

[0037] The LAC incubation process for the catalytic colorimetric reaction using the sensing channel included the following steps: 55 μL of 0.06 mg / mL GMP-CuFe and 55 μL of 10 ppm glyphosate (Gly), nicosulfuron (Nic), chlorpyrifos (Hal), mesosulfuron-methyl (Met), and ferric sulfate (Fer) were mixed in a 96-well plate and incubated at 37°C on an air shaker at 220 rpm for 1 h. Then, 55 μL of 1 mg / mL 2,4-DP and 55 μL of 1 mg / mL 4-AP were added to the reaction solution in the 96-well plate, and the reaction was continued at 37°C on an air shaker at 220 rpm for 25 min. The absorbance was measured at 510 nm. The LAC-sensing channel catalytic colorimetric reaction procedure included: mixing 55 μL of 0.06 mg / mL GMP-CuFe, 55 μL of 10 ppm Gly, Nic, Hal, Met, and Fer (five pesticides to be tested), 55 μL of 1 mg / mL 2,4-DP, and 55 μL of 1 mg / mL 4-AP into a 96-well plate, and reacting at 37°C on an air shaker at 220 rpm for 25 min. The absorbance was measured at 510 nm. The steps of the POD-sensing channel-catalyzed colorimetric reaction included: mixing 55 μL of 0.15 mg / mL GMP-CuFe, 55 μL of 10 ppm Gly, Nic, Hal, Met, and Fer (five pesticides to be tested), 55 μL of 2 mM H2O2, and 55 μL of 1 mM OPD in a 96-well plate, and reacting for 25 min at 37°C on an air shaker at 220 rpm. The absorbance was measured at 446 nm.

[0038] Each sample was repeated 3 times to form a 3×5×3 data matrix (3 channels × 5 pesticide samples × 3 repetitions).

[0039] After absorbance measurement, first use the absorbance measurement result (A-A0) / A0, where A represents the absorbance of the experimental group and A0 represents the absorbance of the blank group, to create a bar chart using Origin software, as shown below. Figure 5 As shown in Figure A, the result of (A-A0) / A0 is then calculated and analyzed using linear discriminant analysis (LDA), as follows: Figure 5 As shown in Figure B, at a pesticide concentration of 10 ppm, the confidence ellipse areas of each pesticide category are small and clearly separated from each other, indicating that the array sensor can clearly distinguish the five pesticides. The sensor array has excellent sensitivity and stability at this concentration.

[0040] Example 3, linear concentration ferrous iron detection, includes the following steps: Preparation of linear concentration ferrous iron (Fer) solutions: Weigh 0.010 g of ferrous iron (Fer) and dissolve it in 10 mL of dimethyl sulfoxide (DMSO). Vortex vigorously for 2 min to obtain a 1000 ppm Fer solution. Dilute the 1000 ppm Fer solution to 500 ppm with DMSO, and then dilute the 500 ppm Fer solution with ultrapure water to obtain 100 ppm, 50 ppm, 20 ppm, 10 ppm, 8 ppm, 5 ppm, 3 ppm, 1 ppm, and 0.5 ppm Fer solutions.

[0041] The synthesis and solution preparation of GMP-CuFe nanozyme material were carried out according to the same procedure as in Example 1. 55 μL of 0.15 mg / mL GMP-CuFe and 55 μL of 20 ppm ~ 0.5 ppm Fer solution were mixed in a 96-well plate. The construction of the array sensor and the parameters for sample detection were the same as in Example 2.

[0042] Each concentration of sample was tested three times, forming a 3 × 7 × 3 data matrix (3 channels × 7 pesticide samples × 3 replicates). The measured absorbance was calculated as (A-A0) / A0, where A represents the absorbance of the experimental group and A0 represents the absorbance of the blank group. A bar chart was then plotted using Origin software, as shown below. Figure 9 As shown in Figure A, the data is further analyzed using Linear Discriminant Analysis (LDA), as follows: Figure 9 As shown in B.

[0043] Depend on Figure 9 As shown in Figure B, there is no overlap between samples of different concentrations of ferrous sulfate, achieving a clear distinction. Simultaneously, Factor 1 is 96.3%, indicating that the first discriminant factor can explain almost all inter-group differences, with the inter-group separation information almost entirely concentrated on Factor 1. Using the average x-axis of each point within the region (i.e., Factor 1) as the Y-axis and the corresponding concentration as the X-axis, a linear graph showing the change in the location of the ferrous sulfate sample region with concentration is obtained. This demonstrates that the overall response of the three sensing channels of the array sensor based on GMP-CuFe nanozyme is linearly related to the ferrous sulfate concentration, with the linear equation being y = -1.3715x + 9.3064. Therefore, this array sensor can achieve quantitative detection of ferrous sulfate pesticide samples within a certain range, with a minimum detection concentration of 0.5 ppm. Similarly, the array sensor constructed in this chapter can also be applied to the quantitative detection of glyphosate, nicosulfuron, chlorpyrifos, and metsulfuron-methyl, with results as shown below. Figure 8 As shown in B, their linear equations are y=-1.5669x+10.6329, y=-1.9959x+15.6343, y=-3.5112x+16.0929 and y=-1.2765x+8.6617.

[0044] Example 4, detection of a mixed sample of glyphosate (Gly), nicosulfuron (Nic), clopyralid (Hal), mesosulfuron-methyl (Met), and ferrous sulfate (Fer), including the following steps: Preparation of pesticide mixture samples: Prepare 10 ppm solutions of five pesticides: Gly, Nic, Hal, Met, and Fer. Mix Nic and Fer in ratios of 7:3 and 3:7, and Hal and Gly in ratios of 7:3 and 3:7, respectively, to obtain 10 ppm Nic:Fer=7:3, Fer:Nic=7:3, Hal:Gly=7:3, and Gly:Hal=7:3 mixture samples. Mix Nic, Fer, Hal, and Gly in a ratio of 1:1:1:1, to obtain a 10 ppm Nic:Fer:Hal:Gly=1:1:1:1 mixture sample.

[0045] The synthesis and solution preparation of GMP-CuFe nanozyme material were carried out according to the same procedure as in Example 1. 55 μL of GMP-CuFe was mixed with 55 μL of 10 ppm mixed sample solution in a 96-well plate. The construction of the array sensor and the parameters for sample detection were the same as in Example 2.

[0046] Each concentration of sample was tested three times, forming a 3 × 5 × 3 data matrix (3 channels × 5 mixed samples × 3 replicates). The detected absorbance was calculated as (A-A0) / A0, where A represents the absorbance of the experimental group and A0 represents the absorbance of the blank group. The data were analyzed using linear discriminant analysis (LDA). Figure 10 As shown in Figure A.

[0047] Mixed samples at concentrations of 5 ppm and 1 ppm were prepared and tested in the same manner as the 10 ppm sample. Each concentration was tested three times, resulting in a 3 × 19 × 3 data matrix (3 channels × 10 mixed samples × 3 replicates). The absorbance was calculated as (A-A0) / A0, where A represents the absorbance of the experimental group and A0 represents the absorbance of the blank group. Linear discriminant analysis (LDA) was used to analyze the data. Figure 10 B, Figure 10 As shown in Figure C, the mixed samples of different concentrations were clearly separated, indicating that the array sensor can effectively distinguish mixed pesticides.

[0048] Example 5, Preparation of Interference Sample: Prepare a potential interfering substance Cu at a concentration of 10 ppm. 2+ Ca 2+ Mg 2+ Na + K + CO3 2- Glucose (Glu), chloramphenicol (Chl), and ascorbic acid (Asc) were used as interfering sample solutions.

[0049] The synthesis and solution preparation of GMP-CuFe nanozyme material were carried out according to the same procedure as in Example 1. 55 μL of GMP-CuFe was mixed with 55 μL of 10 ppm interference sample solution in a 96-well plate. The construction of the array sensor and the parameters for sample detection were the same as in Example 2.

[0050] Each concentration of sample was tested three times, forming a 3 × 9 × 3 data matrix (3 channels × 9 mixed samples × 3 replicates). The detected absorbance was calculated as (A-A0) / A0, where A represents the absorbance of the experimental group and A0 represents the absorbance of the blank group. A bar chart was plotted using Origin software, as shown below. Figure 11 As shown in Figure A, the data is further analyzed using Linear Discriminant Analysis (LDA), as follows: Figure 11As shown in B.

[0051] As shown in the figure, all interfering substances can be clearly distinguished from pesticides. This excludes ascorbic acid, which has strong reducing properties, and Cu, one of the metals used in the synthesis of GMP-CuFe nanozyme materials. 2+ Besides, the other interfering samples, similar to the blank, clustered together, demonstrating the anti-interference capability of the array sensor.

[0052] In summary, this invention successfully prepared a GMP-CuFe bimetallic nanozyme and constructed a three-channel colorimetric array sensor based on its dual enzyme activity. This sensor can simultaneously, rapidly, and sensitively detect and distinguish multiple single-component and mixed pesticides, and has good quantitative ability and anti-interference performance, showing great application potential in the field of rapid detection of multi-component pesticide residues in complex systems.

[0053] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for preparing a copper-iron bimetallic nanozyme, characterized in that, Includes the following steps: S1. Dissolve N-hydroxyethylpiperazine-2-ethanesulfonic acid (HEPES) in ultrapure water, adjust the pH to 7.0-9.0 using HCl or NaOH solution, and mix thoroughly to obtain a 5-15 mM HEPES buffer solution. S2. Dissolve guanosine-5'-monophosphate (GMP) in ultrapure water and mix thoroughly to obtain a GMP solution with a concentration of 20-30 mM; dissolve a soluble divalent copper salt in ultrapure water and mix thoroughly to obtain a solution containing divalent copper ions with a concentration of 40-60 mM; dissolve a soluble trivalent ferric salt in ultrapure water and mix thoroughly to obtain a solution containing trivalent ferric ions with a concentration of 40-60 mM. S3. Thoroughly mix the GMP solution, HEPES buffer, solution containing divalent copper ions, and solution containing trivalent iron ions to carry out a self-assembly reaction to obtain a reaction solution; the volume ratio of the solution containing divalent copper ions to the solution containing trivalent iron ions is 100:1-10:1; the total volume ratio of the solution containing divalent copper ions and the solution containing trivalent iron ions to the volume ratio of the GMP solution is 0.5:1-1.5:1; the volume ratio of the HEPES buffer to the remaining solutions is 3:1-2:

1. S4. Centrifuge the reaction solution to separate the solid and liquid components, discard the supernatant, collect the solid product, wash to obtain the precipitate, vacuum dry the precipitate, and grind the obtained solid into powder to obtain GMP-CuFe nanozyme material with dual activities of peroxidase and laccase.

2. The method for preparing copper-iron bimetallic nanozymes according to claim 1, characterized in that, The soluble divalent copper salt is CuCl2 or CuSO4, and the soluble trivalent iron salt is FeCl3, Fe2(SO4)3 or Fe(NO3)3.

3. The application of a copper-iron bimetallic nanozyme prepared by the preparation method of claim 1 or 2 in a colorimetric array sensor for detecting pesticide residues.

4. The application according to claim 3, characterized in that, The pesticide is one or more of glyphosate (Gly), nicosulfuron (Nic), chlorpyrifos (Hal), mesosulfuron (Met), and ferrous sulfate (Fer).

5. The application according to claim 4, characterized in that, The sensor comprises three sensing channels, each containing a copper-iron bimetallic nanozyme. The three sensing channels are as follows: LAC incubation channel: used to pre-incubate copper-iron bimetallic nanozymes with the sample to be tested, and then react with laccase-like substrates; LAC channel: used to simultaneously react copper and iron bimetallic nanozymes, the sample to be tested, and laccase-like substrates; POD channel: used to simultaneously react copper and iron bimetallic nanozymes, the sample to be tested, and peroxidase-like substrates; The sample to be tested is added to the LAC incubation channel, LAC channel and POD channel respectively for reaction, and the absorbance value of each channel after reaction is detected. Based on the change of absorbance value of each channel, a response fingerprint spectrum of the sample to be tested is constructed. By comparing the response fingerprint spectrum or by processing it through a linear discriminant analysis model, the pesticide components in the sample to be tested can be detected simultaneously qualitatively and / or quantitatively.

6. The application according to claim 4, characterized in that, The laccase-like substrates are 2,4-dichlorophenol (2,4-DP) and 4-aminoantipyridine (4-AP), and the peroxidase-like substrates are hydrogen peroxide (H2O2) and o-phenylenediamine (OPD). The laccase-like activity of the GMP-CuFe nanozyme catalyzes a color reaction with absorption at 510 nm using 2,4-DP and 4-AP as laccase-like substrates; the peroxidase-like activity of the GMP-CuFe nanozyme catalyzes a color reaction with absorption at 446 nm using H2O2 and OPD as peroxidase-like substrates.

7. The application according to claim 5, characterized in that, The specific detection methods for the three sensing channels are as follows: LAC incubation channel: GMP-CuFe nanozyme material and pesticide to be tested are mixed and incubated at 37℃ for 50-70 min; then 2,4-DP and 4-AP are added to the reaction solution, and the reaction is carried out at 37℃ for 20-30 min, and the absorbance is measured at 510 nm. LAC channel: GMP-CuFe nanozyme material, pesticide to be tested, 2,4-DP and 4-AP were mixed and reacted at 37℃ for 20-30 min, and the absorbance was measured at 510 nm. POD channel: After mixing GMP-CuFe nanozyme material, pesticide to be tested, H2O2 and OPD, the absorbance was measured at 446 nm after reacting at 37℃ for 20-30 min.

8. The application according to claim 7, characterized in that, In the LAC incubation and LAC channels, the concentration of GMP-CuFe nanozyme material was 0.05-0.10 mg / mL, and the concentrations of 2,4-DP and 4-AP were 0.8-1.2 mg / mL, prepared with MES buffer solution at pH 6-7. In the POD channel, the concentration of GMP-CuFe nanozyme material was 0.10-0.20 mg / mL, the concentration of H2O2 was 1.6-2.4 mg / mL, and the concentration of OPD was 0.8-1.2 mg / mL, prepared with HAc / NaAc buffer solution at pH 4.0-5.

5.

9. The application according to claim 7, characterized in that, In the LAC incubation channel and LAC channel, the volume ratio of GMP-CuFe nanozyme material, pesticide to be tested, 2,4-DP and 4-AP was 1:1:1:1; in the POD channel, the volume ratio of GMP-CuFe nanozyme material, pesticide to be tested, H2O2 and OPD was 1:1:1:

1.

10. The application according to claim 7, characterized in that, After absorbance detection, the absorbance change value (A-A0) / A0 obtained from the absorbance detection is first plotted, where A represents the absorbance of the experimental group and A0 represents the absorbance of the blank group. Then, the result of (A-A0) / A0 is calculated and analyzed by linear discriminant analysis (LDA).

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