Multi-pesticide detection method, electrochemical biosensor array and application

Abstract

The invention discloses a multi-pesticide detection method, an electrochemical biosensor array and application, and the method comprises the following steps: different pesticide molecules have different inhibition effects on cholinesterase protein, so that different peak currents are generated under the stimulation of the same voltage; after differencing, combining the decline peak values of the two enzymes under different concentrations to obtain a double-enzyme characteristic spectrum of the pesticide; and pesticide detection is carried out by adopting a nearest neighbor algorithm, and the types and concentrations of pesticides are accurately and timely determined according to the nearest distance between any new test sample and the feature set. The electrochemical biosensor array has relatively good accuracy and stability, relatively high sensitivity and relatively low cost in simultaneous detection of types and concentrations of pesticides. The screen printing technology is used for manufacturing the interdigital microelectrode, so that the production cost is low, mass production is facilitated, and the interdigital microelectrode is suitable for miniaturized portable electrochemical detection equipment and is more suitable for on-site rapid and accurate detection.

Description

Technical Field

[0001] The invention belongs to the field of detection technology and relates to a method for detecting multiple pesticides, an electrochemical biosensor array and applications. Background Art

[0002] Insecticides, herbicides, rodenticides, and fungicides are widely used to mitigate the impact of various pests on crop health. As a result, residues of these pesticides can be identified not only on crop surfaces but also in soil, air, and water sources. However, repeated exposure to pesticides has been linked to various health problems, including neurological disorders, autism, Alzheimer's disease, kidney failure, and cancer. Even at low concentrations, pesticide exposure may hinder early cognitive development in infants and young children. In addition, some highly toxic pesticides even persist for an extended period of time in the soil, adversely affecting local sustainable ecosystems.

[0003] Chromatography is key to analyzing pesticide residues, providing sensitive and reliable results. However, it is limited by the need for non-portable laboratory instruments, the need for valuable equipment, the requirement for skilled operators, sample pretreatment and time-consuming processes. For rapid on-site testing, inexpensive color cards or test strips using Raman spectroscopy are available. However, these methods face performance issues under harsh conditions such as light, temperature changes or low concentrations of pesticides.

[0004] In recent years, electrochemical biosensors have attracted widespread attention due to their sensitivity and selectivity, and have the advantages of fast response, rapid result processing, user-friendliness, and low cost. Figure 1 As shown, electrochemical biosensors usually include three parts: a biological receptor, a sensing electrode and an electrochemical workstation. By integrating with carefully designed biomaterials, the sensing electrode becomes specific and sensitive. The electrochemical workstation converts the biological reaction signals occurring on the electrode into various forms of electrical signals (voltage, current, resistance). The electrochemical workstation can obtain the concentration of the measured substance by measuring various forms of electrical signals.

[0005] However, existing electrochemical biosensors can only be used in very specific pesticide detection scenarios. The main reason is that they cannot cover a wide range of pesticide types and can only detect a single type of pesticide. There are currently more than 600 types of pesticides in the world. The high specificity of biological receptor rejection reactions means that existing electrochemical biosensors can only achieve a single biological receptor to recognize one pesticide. Using electrochemical biosensors to simultaneously detect the types and concentrations of multiple pesticides is a problem that existing technologies have not solved.

[0006] The prior art (CN 110793929 A, a method for detecting and distinguishing pesticide residues based on multi-enzyme inhibition) uses the principle of multi-enzyme inhibition and spectroscopy to achieve simultaneous detection of the types and concentrations of multiple pesticides. However, in the supplementary materials, only the detection of different types of pesticide residues at the same concentration and the detection of different concentrations of the same pesticide are achieved. There is no implementation case for simultaneous detection of pesticide types and concentrations. At the same time, its detection method also has the inherent disadvantages of spectroscopy. The sensitivity is low, and it is difficult to accurately analyze the target substance qualitatively and quantitatively when the pesticide concentration is low; the sample pretreatment is complicated, and complex sample pretreatment steps are required before application. During use, a reaction time of 30-40 minutes is required, which cannot meet the needs of rapid on-site detection.

[0007] At the same time, for screen-printed electrodes often used in electrochemical biosensors, the concentration range of pesticides that can be detected is limited, and pesticide detection requires the electrodes to have extremely high sensitivity. Summary of the invention

[0008] The purpose of the present invention is to provide an electrochemical biosensor array for detecting multiple pesticides, which solves the problems of low detection sensitivity, cumbersome sample pretreatment and inability to conduct rapid on-site detection in the prior art.

[0009] To solve the above problems, the technical solution adopted by the present invention includes:

[0010] A method for detecting multiple pesticides, comprising: using acetylcholinesterase and butyrylcholinesterase to detect multiple pesticides;

[0011] Different pesticide molecules have different inhibitory effects on cholinesterase protein and produce different peak currents under the same voltage stimulation. After taking the difference, the decreasing peak values ​​of the two enzymes at different concentrations are combined to obtain the dual-enzyme characteristic map of the pesticide. The nearest neighbor algorithm is used for pesticide detection to determine the type and concentration of the pesticide based on the closest distance between any new test sample and the feature set.

[0012] Optionally, obtaining the dual enzyme characteristic spectrum of the pesticide specifically includes:

[0013] Collect IV curve data of different pesticides at different concentrations; record the IV curves of acetylcholinesterase and butyrylcholinesterase respectively;

[0014] Peak extraction: For each IV curve, extract the peak value of the Faraday current;

[0015] Linear difference: For each pesticide sample, calculate the difference between the current peak and the maximum peak, which is the current peak when there is no pesticide, and get the drop peak;

[0016] Feature merging: Merge the decreasing peaks of two enzymes at different concentrations to construct dual enzyme features;

[0017] Feature matrix: The dual enzyme features of all pesticide samples are combined into a feature matrix, each row represents a pesticide category, each column represents a concentration, and each cell stores the dual enzyme features of the pesticide of the corresponding concentration and category.

[0018] Optionally, the detection method specifically includes:

[0019] Data preprocessing: extract the Faraday current peak from the IV curves of acetylcholinesterase and butyrylcholinesterase; perform linear subtraction to eliminate the influence of noise; merge the decreasing peaks of acetylcholinesterase and butyrylcholinesterase at different concentrations to construct dual enzyme features;

[0020] Nearest neighbor algorithm: Use the nearest neighbor algorithm to classify based on the feature matrix; calculate the distance between the sample to be tested and all samples in the training set, and select the nearest k neighbors; determine the category and concentration of the sample to be tested based on neighbor voting or averaging;

[0021] Input: k value, dual enzyme feature matrix, feature matrix label and features of the sample to be tested;

[0022] Initialize the distance list: used to store the distance between each sample in the feature matrix and the sample to be tested and the corresponding label;

[0023] Calculate distance: traverse the feature matrix, calculate the Euclidean distance between each sample and the sample to be tested, and store the result in the distance list;

[0024] Sorting: Sort the distance list in ascending order to find the nearest k neighbors; Select the nearest k neighbors: Select the first k elements from the sorted list;

[0025] Count labels: Initialize a dictionary to count the number of times each label appears in k neighbors;

[0026] Voting: Find the tag with the most occurrences;

[0027] Return result: Return the label with the highest number of occurrences as the prediction result, that is, the type and concentration of the pesticide solution to be tested.

[0028] A multiple pesticide detection electrochemical biosensor array implements any multiple pesticide detection method described in the present invention, and is provided with working electrodes, wherein the working electrodes are composed of two pairs of micro-scale interdigitated structures, which are arranged in parallel as two rectangular working electrodes 1 and 2; the interdigitated fingers of the counter electrode are interwoven with the interdigitated fingers of the two working electrodes; and a reference electrode is located between and below the two working electrodes to form an inverted "T" structure.

[0029] Optionally, the method for preparing the sensor array includes:

[0030] Step 1: Add the ZIF-8 suspension dropwise to the working electrode of the interdigitated microelectrode and wait for it to dry completely;

[0031] Step 2: Add the carboxymethyl chitosan solution dropwise to the working electrode 1 and working electrode 2 of the interdigitated microelectrode respectively, and wait until they are completely dried;

[0032] Step 3: Add the acetylcholinesterase solution dropwise to the working electrode 1 of the interdigitated microelectrode and wait for it to completely dry;

[0033] Step 4: Add the butyrylcholinesterase solution dropwise to the working electrode 2 of the interdigitated microelectrode and wait for it to completely dry.

[0034] Optionally, the concentration of the ZIF-8 suspension is 0.1 mg / uL;

[0035] The mass fraction of carboxymethyl chitosan solution is 0.05%;

[0036] Acetylcholinesterase solution 0.002u / uL;

[0037] Butyrylcholinesterase solution 0.002u / uL;

[0038] Optionally, the amount of the ZIF-8 suspension, acetylcholinesterase solution and butyrylcholinesterase solution added is 10uL; the amount of the carboxymethyl chitosan solution added is 3uL.

[0039] Optionally, the preparation steps include:

[0040] Step 1: Use a three-layer screen printing structure to prepare different parts of the electrode structure;

[0041] Step 2: Use polyimide as a substrate and place it under the first layer to print the conductor;

[0042] Step 3: Create the working and counter electrodes by printing carbon ink;

[0043] Step 4: Print the reference electrode using silver / silver chloride ink;

[0044] Step 5: Use a waterproof layer for packaging.

[0045] Application of any of the multiple pesticide detection electrochemical biosensor arrays described in the present invention for pesticide detection.

[0046] Optionally, IV curves of different pesticides at different concentrations can be established, including:

[0047] A. Take 10uL of iodinated acetylthiocholine solution and drop it into the electrochemical biosensor array, connect the electrode to the electrochemical workstation, use the differential pulse voltammetry provided by the electrochemical workstation to detect the current generated by the electrode, and record the current-voltage curves generated by the iodinated acetylthiocholine solution on the working electrode 1 and the working electrode 2 in the absence of pesticides;

[0048] B. Take 10uL of a certain concentration of a pesticide solution and drop it onto the electrochemical biosensor array, then take 10uL of iodinated acetylthiocholine solution and drop it onto the electrochemical biosensor array, let it stand for 30 to 60 seconds, connect the electrodes to the electrochemical workstation, use the differential pulse voltammetry provided by the electrochemical workstation to detect the current generated by the electrodes, and record the current-voltage curves generated by the pesticide solution of the concentration at the working electrode 1 and the working electrode 2 respectively;

[0049] C. Repeat process B to obtain a set of current-voltage curves of a certain pesticide solution with different concentrations on working electrode 1 and working electrode 2;

[0050] D. Repeat processes B and C to obtain the current-voltage curves of different types and concentrations of pesticides generated on working electrodes 1 and 2.

[0051] The beneficial effects of the present invention are:

[0052] The screen printing technology is used to make interdigitated microelectrodes for use as sensing electrode arrays, and nanocomposites are used to fix acetylcholinesterase and butyrylcholinesterase on the surface of the sensing electrode array to make enzyme electrode arrays, which are used as electrochemical biosensor arrays. The electrochemical biosensor array has good accuracy, stability, high sensitivity and low cost in the simultaneous detection of pesticide types and concentrations. The screen printing technology is used to make interdigitated microelectrodes, which have low production costs, are easy to mass produce, and can be applied to miniaturized portable electrochemical detection equipment, which is more suitable for rapid and accurate on-site detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present invention but do not constitute a limitation of the present invention. In the accompanying drawings:

[0054] Figure 1 is a diagram of the electrochemical biosensor structure;

[0055] Figure 2 It is a flow chart of the construction of pesticide characteristics;

[0056] Figure 3 It is the dual enzyme characteristic diagram of different pesticides;

[0057] Figure 4 is a flow chart of interdigitated microelectrode preparation;

[0058] Figure 5 It is the structural parameter diagram of screen-printed electrodes and interdigitated microelectrodes;

[0059] Figure 6 is a diagram of the electrochemical biosensor array structure;

[0060] Figure 7 This is a diagram of the solution diffusion pattern on the surface of a common three-electrode and an interdigitated microelectrode;

[0061] Figure 8 This is the simulation result diagram of the surface charge density of the screen-printed electrode and the interdigitated microelectrode;

[0062] Fig. 9 This is a comparison of the electrochemical detection results of the electrochemical biosensor array and the ordinary screen-printed electrode;

[0063] Fig.10 is the confusion matrix for the classification of different types of pesticides;

[0064] Fig.11 It is the confusion matrix of different concentrations of 9 pesticides. ;

[0065] Fig.12 It is the result of simultaneous detection of the types and concentrations of 9 pesticides. DETAILED DESCRIPTION

[0066] In order to make the purpose and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0067] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0068] The existing multi-pesticide detection technology based on multi-enzyme inhibition and spectroscopy has low sensitivity. When the pesticide concentration is low, it is difficult to accurately perform qualitative and quantitative analysis of the target substances. The sample pretreatment is complicated and requires complex sample pretreatment steps before application. During use, 30-40 minutes of reaction time is required, which cannot meet the needs of rapid and accurate on-site detection.

[0069] For existing electrochemical biosensors, their sensing electrodes are not sensitive enough to low concentrations of pesticides. In actual use, low concentrations of pesticides can only cause weak current changes, usually at the microampere level. This tiny change poses a huge challenge to the sensor and is difficult to detect.

[0070] The technical solution adopted by the present invention is:

[0071] (1) Using the principle of multi-enzyme inhibition, electrochemical biosensor technology was used to detect the types and concentrations of multiple pesticides. In order to improve the accuracy and reliability of pesticide detection, a set of unique features were created from the IV curves of two enzymes to represent multiple pesticides.

[0072] Because electrochemical detection technology has the advantages of high precision, fast response and fast result processing, it meets the needs of fast and accurate detection on site. Acetylcholinesterase and butyrylcholinesterase are used to detect a variety of pesticides. Various pesticide molecules have different inhibitory effects on the two enzymes. By detecting the difference in the degree of inhibition, the detection of multiple pesticides can be achieved. Specifically, different pesticide molecules have different inhibitory effects on cholinesterase protein, resulting in different peak currents under the same voltage stimulation. The different effects of different pesticides on the two enzymes enable the sensor to distinguish and detect multiple pesticide residues.

[0073] The effective faradaic current of the reactants is obtained from the electrochemical biosensor array, such as Figure 2 (a) To improve the accuracy and reliability of pesticide detection, a set of unique features were created from the IV curves of the two enzymes to represent multiple pesticides. Figure 2 As shown in (b), first, the Faraday current peaks are extracted from the IV curves of the two enzymes. These peaks represent the electrochemical response caused by the interaction between the enzyme and the pesticide and are the key markers for distinguishing different types of pesticides. Next, in order to ensure the consistency of the data set and eliminate the influence of noise, linear subtraction is performed to align the data. Specifically, the maximum value in the data set (i.e., the current peak value obtained when there is no pesticide) is subtracted from each peak to obtain the falling peak value, as shown in Figure 2 This approach effectively minimizes differences between samples, ensuring that the analysis focuses on intrinsic differences in enzyme-pesticide interactions rather than experimental differences.

[0074] After subtraction, the decreasing peaks of the two enzymes at different concentrations are combined to obtain the dual enzyme signature of the pesticide. This combination of electrochemical responses constructs a comprehensive electrochemical map for each pesticide, encapsulating the interaction of different pesticides with each enzyme in a subtle way. The resulting data matrix forms a unique dual enzyme signature, including combined, normalized peak pairs of multiple pesticides at different concentration ranges, resulting in a dual enzyme signature map for all pesticides, such as Figure 3 As shown. Based on these features, the nearest neighbor algorithm is used for pesticide detection. This is a classification task that can accurately and timely determine the type and concentration of pesticides based on the closest distance between any new test sample and the feature set.

[0075] In order to improve the detection performance of electrochemical biosensors at low concentrations of pesticides, a new electrode array was designed to maximize the sensitivity of the sensor and achieve accurate qualitative and quantitative analysis of the target substances. The structure of the electrode array was designed to improve its sensitivity by reactants diffusing to the electrode surface. Specifically, the electrode consists of two pairs of micro-scale interdigitated structures, with the interdigitated fingers of the counter electrode and the interdigitated fingers of the dual working electrodes intricately intertwined. In addition, a reference electrode, mirroring the same micro-scale structure, is located below the two working electrodes. In contrast to traditional large electrodes (diameters above the millimeter level), the structure of the micrometer-scale interdigitated array significantly increases the peak current without increasing the electrode surface area. These are all attributed to the different diffusion behaviors of the solution on the electrodes.

[0076] Part I:

[0077] The complete steps of the method of the present invention are described

[0078] An electrochemical biosensor array for multiple pesticide detection and a preparation method thereof, the specific steps are as follows:

[0079] (1) Preparation of interdigitated microelectrodes:

[0080] Figure 4 The workflow for fabricating interdigitated microelectrodes is described in detail. Screen printing technology was selected as a cost-effective method to fabricate interdigitated microelectrodes.

[0081] Step 1: Use a three-layer screen-printing structure to prepare different parts of the electrode structure.

[0082] Second step: Use polyimide as a substrate and place it under the first layer to print the conductor.

[0083] Step 3: Create the working and counter electrodes by printing carbon ink.

[0084] Step 4: Print the reference electrode using silver / silver chloride ink.

[0085] Step 5: Encapsulate with a waterproof layer to improve durability.

[0086] The interdigitated microelectrode is prepared. Figure 5 shown.

[0087] (2) Preparation of electrochemical biosensor array

[0088] The two enzymes, acetylcholinesterase and butyrylcholinesterase, were immobilized on the electrode by physical adsorption, using carboxymethyl chitosan to bond the enzymes to the ZIF-8 modified electrode surface.

[0089] 1) Prepare the solution:

[0090] ZIF-8 suspension (solute: zinc imidazolate metal organic framework-8 (ZIF-8) solvent: anhydrous ethanol / distilled water / deionized water 0.1 mg / uL).

[0091] PBS solution (solute: PBS phosphate buffer dry powder, solvent: distilled water / deionized water, 0.1 mol / L).

[0092] Carboxymethyl chitosan solution (solute: carboxymethyl chitosan, solvent: PBS solution, mass fraction 0.05%).

[0093] Acetylcholinesterase solution (solute: acetylcholinesterase, solvent: PBS solution, 0.002u / uL).

[0094] Butyrylcholinesterase solution (solute: butyrylcholinesterase, solvent: PBS solution, 0.002u / uL).

[0095] 2) Electrode modification:

[0096] Step 1: Add 10uL ZIF-8 suspension to the working electrode of the interdigital microelectrode and wait for it to dry completely (dry at 35℃ at the highest).

[0097] Step 2: Add 3uL of carboxymethyl chitosan solution to the working electrode 1 (WE1) and working electrode 2 (WE2) of the interdigitated microelectrode respectively, and wait for them to dry completely.

[0098] Step 3: Add 10uL of acetylcholinesterase solution to the working electrode 1 of the interdigital microelectrode and wait for it to dry completely.

[0099] Step 4: Add 10uL of butyrylcholinesterase solution to the working electrode 2 of the interdigitated microelectrode and wait for it to dry completely.

[0100] The electrode is prepared, and the prepared electrochemical biosensor array is as follows Figure 6 shown.

[0101] (3) Detection of multiple pesticides

[0102] 1) Establishment of standard IV curve

[0103] Use pesticide solutions of known concentration and type to establish a standard IV curve, record the electrochemical response data, and establish a standard IV curve. The standard IV curve is the electrochemical signal spectrum corresponding to different concentrations of pesticides, which is used for quantitative and qualitative analysis in subsequent sample testing.

[0104] The pesticide standard solutions used were methyl parathion, chlorpyrifos, dimethoate, trichlorfon, profenofos, acephate, glyphosate, cypermethrin and isothiocyanate.

[0105] A. Take 10uL of iodinated acetylthiocholine solution and add it to the electrochemical biosensor array, connect the electrodes to the electrochemical workstation, use the differential pulse voltammetry provided by the electrochemical workstation to detect the current generated by the electrodes, and record the current-voltage curves generated by the iodinated acetylthiocholine solution on working electrode 1 (WE1) and working electrode 2 (WE2) in the absence of pesticides.

[0106] B. Take 10uL of a pesticide solution of a certain concentration and add it to the electrochemical biosensor array, then take 10uL of iodinated acetylthiocholine solution and add it to the electrochemical biosensor array, let it stand for 30 to 60 seconds, connect the electrodes to the electrochemical workstation, use the differential pulse voltammetry provided by the electrochemical workstation to detect the current generated by the electrodes, and record the current-voltage curves generated by the pesticide solution of this concentration on WE1 and WE2 respectively.

[0107] C. Repeat process B to obtain a set of current-voltage curves produced by a certain pesticide solution with different concentrations on WE1 and WE2.

[0108] D. Repeat processes B and C to obtain the current-voltage curves of different types and concentrations of pesticides produced on WE1 and WE2.

[0109] The IV curves of different pesticides at different concentrations were established.

[0110] 1) Construction of dual enzyme features

[0111] Below is a detailed step and pseudo code showing how to extract the dual enzyme features feature_vector from the electrochemical response data and construct the feature matrix feature_matrix.

[0112] Feature construction process:

[0113] Data collection: Collect IV curve data of different pesticides at different concentrations. Record the IV curves of two enzymes (acetylcholinesterase and butyrylcholinesterase) separately.

[0114] Peak extraction: For each IV curve, extract the peak value of the Faraday current.

[0115] Linear difference: For each pesticide sample, the difference between the current peak and the maximum peak (the current peak without pesticide) is calculated to obtain the drop peak.

[0116] Feature merging: Merge the decreasing peaks of two enzymes at different concentrations to construct a dual enzyme feature.

[0117] Feature matrix: The dual enzyme features of all pesticide samples are combined into a feature matrix, each row represents a pesticide category, each column represents a concentration, and each unit stores the dual enzyme features of the pesticide of the corresponding concentration and category (the decreasing peak value at the corresponding concentration).

[0118] The specific testing process includes:

[0119] Input: IV curve data of enzyme 1 and enzyme 2 under different pesticides and different concentrations, and the maximum current peak value when there is no pesticide.

[0120] Initialize feature matrix: used to store the feature vector of each pesticide sample.

[0121] Extract peak value: traverse the IV curve of each pesticide at different concentrations and extract the Faraday current peak value.

[0122] Calculate the descending peak value: Calculate the descending peak value (the difference from the maximum peak value) at each concentration.

[0123] Constructing feature vector: Merge the decreasing peaks of enzyme 1 and enzyme 2 to construct a dual enzyme feature vector.

[0124] Update feature matrix: Combine the feature vectors of all pesticide samples into a feature matrix.

[0125] Return result: Returns the constructed feature matrix.

[0126] Through the above steps and pseudocode, the dual enzyme features can be extracted from the raw electrochemical data and the feature matrix can be constructed to provide input for the subsequent pesticide detection algorithm.

[0127] 1) Multiple pesticide detection algorithms

[0128] The process of pesticide detection using the nearest neighbor algorithm. The following are the detailed steps and pseudo code of the process.

[0129] Process steps:

[0130] Data preprocessing: Extract the Faraday current peak from the IV curves of the two enzymes. Perform linear subtraction to eliminate the influence of noise. Combine the decreasing peaks of the two enzymes at different concentrations to construct the dual enzyme feature test_sample.

[0131] Nearest Neighbor Algorithm:

[0132] Classification is performed based on the feature matrix using the nearest neighbor algorithm.

[0133] Calculate the distance between the sample to be tested and all samples in the training set, and select the nearest k neighbors.

[0134] The category and concentration of the sample to be tested are determined based on neighbor voting or averaging.

[0135] Input: k value, dual enzyme feature matrix, feature matrix label and features of the sample to be tested.

[0136] Initialize the distance list: used to store the distance between each sample in the feature matrix and the sample to be tested and the corresponding label.

[0137] Calculate distance: traverse the feature matrix, calculate the Euclidean distance between each sample and the sample to be tested, and store the results in the distance list.

[0138] Sorting: Sort the distance list in ascending order to find the nearest k neighbors.

[0139] Select the k nearest neighbors: pick the first k elements from the sorted list.

[0140] Count labels: Initialize a dictionary to count the number of times each label appears in k neighbors.

[0141] Voting: Find the tag with the most occurrences.

[0142] Return result: Return the label with the highest number of occurrences as the prediction result, that is, the type and concentration of the pesticide solution to be tested.

[0143] The above algorithm can be used to achieve qualitative and quantitative analysis of various pesticides.

[0144] Zinc imidazolate metal organic framework-8 (ZIF-8): Zinc imidazolate metal organic framework-8.

[0145] Acetylcholinesterase: Acetylcholinesterase is derived from the fly head, 200u / g.

[0146] Butyrylcholinesterase: Butyrylcholinesterase is derived from horse serum, >4u / mg.

[0147] PBS phosphate buffer dry powder: 0.01M PBS phosphate buffer dry powder.

[0148] Carboxymethyl chitosan: Carboxymethyl chitosan, BR, water soluble.

[0149] Acetylthiocholine iodide: Acetylthiocholine iodide, 98%.

[0150] Electrochemical workstation: Chenhua CHI620E electrochemical workstation.

[0151] Electrochemical workstation operating parameters: starting potential (V) = 0.4, ending potential (V) = 0.9, increasing voltage (V) = 0.004, pulse amplitude (V) = 0.05, pulse width (sec) = 0.05, sampling width (sec) = 0.0167, pulse period (sec) = 0.5, standing time (sec) = 2, sensitivity (A / V) = 1e-4.

[0152] Operating temperature: room temperature (20-35°C).

[0153] Response time: 30~45s.

[0154] Part II:

[0155] Definition of electrode sensitivity: In electrochemistry, sensitivity s refers to the ability of an electrochemical device to detect changes in the concentration of the substance being measured, usually defined as the peak current Δi detected. P ΔM values ​​with analyte concentration.

[0156]

[0157] Peak current i p Affected by the interface between the electrode and the solution containing the electroactive substance. According to the Cottrell equation, the peak current i p The response over time can be modeled as:

[0158]

[0159] Here, n is the number of transferred electrons, A is the electrode area, and M0 is the concentration distribution of the electroactive substance near the electrode. F and D are the Faraday constant and the solution diffusion coefficient, respectively. In order to increase the peak current, it is necessary to expand the electrode area A or improve the concentration distribution M0 near the electrode. Although expanding the area of ​​the electrode can improve sensitivity, it also increases background noise and cost, and reduces convenience due to the larger size.

[0160] Inspired by microelectrode technology in neuroscience, the structure of traditional sensing electrodes has been modified with the aim of improving their sensitivity by refining the concentration curve M0. Figure 5 As shown, the electrode designed by the present invention consists of two pairs of micro-scale comb-like electrode structures, in which the "fingers" of the counter electrode are intricately interwoven between the fingers of the dual working electrodes. In addition, a reference electrode, mirroring the same micro-scale structure, is located below the two working electrodes.

[0161] Compared with the traditional screen-printed electrodes ( Figure 3 , 5 mm in diameter) In contrast, the micrometer-scale staggered array structure significantly improves the peak current without increasing the electrode surface area. All of this can be attributed to the different diffusion behaviors of the solution on the electrode.

[0162] For molecules diffusing freely in a solution, the mean square diffusion distance x in time is 2 It can be expressed as x 2 =2Dt. Where D is the diffusion coefficient and t is the diffusion time. Since the diffusion coefficient of the aqueous solution at room temperature is only (0.1-10)×10 -9 m 2 / s, the estimated diffusion distance moves on average 10 to 1000 μm. When the electrode size r0 is much larger than the material distance x, the diffusion of the reactants is mainly one-dimensional, that is, linear motion from the solution volume to the electrode surface (e.g. Figure 7 This diffusion mode leads to limited mass transfer rate, especially after the reaction has been carried out for a period of time, the analyte near the electrode surface is exhausted, further slowing down the diffusion rate. When the electrode size r0 is equal to or less than the diffusion distance x, the substance in the solution not only diffuses to the electrode surface in a linear path, but also diffuses around the electrode in a hemispherical shape (see Figure 7 Interdigitated microelectrodes). Due to this combined mode of radial and planar diffusion, mass transfer across the microelectrode is more efficient. No stirring is required, and a more uniform concentration profile can be maintained by natural convection and diffusion.

[0163] According to Fick's law, the radial diffusion effect on the micro-sized electrode can increase the concentration distribution M0 of the electroactive substances around the electrode.

[0164]

[0165] in, It can be seen that when the electrode size decreases, the concentration distribution M0 around the electrode is larger and the peak current i p Also higher.

[0166] From this, it can be seen that in order to increase the peak current generated by the electrode, the width of the electrode fingers and the distance between the electrode fingers should be reduced as much as possible.

[0167] Screen printing technology is used to prepare electrode arrays because of its low cost and mass production. Due to the limitation of processing accuracy of screen printing technology, the maximum processing accuracy is 250um. In order to maximize the sensitivity of electrode detection, the width of the electrode fork and the distance between the electrode fork are set to 250um. At the same time, due to the need for multi-pesticide detection, the electrode is expanded into an electrode array.

[0168] Part III:

[0169] In order to verify the performance of the designed interdigitated microelectrode (hereinafter referred to as IME), COMSOL simulation was performed, and real-world pesticide detection experiments were carried out and compared with a macro-sized screen-printed electrode (hereinafter referred to as SPE). Since the electrochemical biosensor array designed in the present invention involves the joint detection of pesticides by two enzymes, two working electrodes WE1 and WE2 need to be designed. In order to ensure fairness, only part of WE1 is used for comparison here to ensure that the area is almost the same as that of the traditional screen-printed electrode. In addition, the same manufacturing process (screen printing) and material (carbon) are used to manufacture the two types of electrodes. For specific design parameters, see Figure 5 The influence of two electrode structures on the surface current density was simulated by using the secondary current interface of COMSOL electrochemistry module. Figure 8 It can be clearly seen that the interdigitated microelectrode designed in the present invention has a higher current density than the macroelectrode of the same area. Fig. 9 As shown in the figure, it can be clearly seen from the IV curve of real-world pesticide detection that for the same concentration (10 -15 mol / L) of glyphosate pesticide, the interdigitated microelectrode detected a larger peak current, which shows that the interdigitated microelectrode has a higher sensitivity.

[0170] Part V:

[0171] List various embodiments

[0172] Embodiment 1:

[0173] Nine of the most commonly used organophosphorus pesticides (OPs) in the world were selected to evaluate the performance of the sensor. They are methyl parathion, chlorpyrifos, dimethoate, trichlorfon, profenofos, acephate, glyphosate, cypermethrin and isothiocyanate. For each pesticide, it was diluted into five concentration gradients, from 10 -7 -10 -15 mol / L, and each time it decreases by 100×. The reason for choosing this concentration range is based on the maximum residue levels of pesticides allowed by the World Health Organization Food Code (MRLs = 0.01 mg / kg ≈ 10 -9 mol / L). Therefore, using this concentration as a reference, lower and higher levels were included to study the effects below and above the MRL.

[0174] Datasets and testing: A total of 360 sets of electrochemical measurement data (9 pesticides × 5 concentrations × 8 electrodes) were collected. Cross-validation was used to validate the system model, of which 225 datasets were used for feature construction and 135 datasets were used for testing.

[0175] Accuracy of pesticide type detection. Fig.10The confusion matrix for nine pesticides is shown. It can be seen that in most cases, the different types of pesticides can be accurately distinguished, with the system achieving an average detection rate of 93.3%. However, for a very small amount of the pesticide, trichlorfon, the system's detection accuracy dropped slightly to 70%. This is due to the fact that the effect of this pesticide on the enzyme is similar to that of the pesticide profenofos, resulting in a similar dual enzyme signature. Consider increasing the sample size or using more sophisticated feature extraction methods, such as deep learning, to resolve this issue.

[0176] Accuracy of concentration detection. Fig.11 The concentration detection performance of the sensor in 9 pesticides. As can be seen from the figure, after specifying the pesticide type, the sensor has an average detection rate of 98.5% for pesticide concentration, and only 2 of the 135 data sets misidentified the concentration level. The results show that the sensor is not only capable of qualitative identification of pesticides, but also has high accuracy in quantitative analysis of pesticides.

[0177] The performance of the sensor in measuring pesticide type and pesticide concentration simultaneously was verified. Fig.12 As can be seen in the figure, the average recognition accuracy is 81%. Notably, it accurately identified the types and concentrations of three pesticides (acephate (Ace), glyphosate (Gly), and aniphos (Ani)). This demonstrates the potential of the sensor for simultaneous qualitative and quantitative analysis of multiple pesticides.

[0178] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for detecting multiple pesticides, characterized in that: include: Utilize acetylcholinesterase and butyrylcholinesterase to detect multiple pesticides; Different pesticide molecules have different inhibitory effects on cholinesterase protein and produce different peak currents under the same voltage stimulation. After taking the difference, the decreasing peak values ​​of the two enzymes at different concentrations are combined to obtain the dual-enzyme characteristic map of the pesticide. The nearest neighbor algorithm is used for pesticide detection to determine the type and concentration of the pesticide based on the closest distance between any new test sample and the feature set.

2. The method for detecting multiple pesticides according to claim 1, characterized in that: Obtaining the dual enzyme characteristic spectrum of the pesticide specifically includes: Collect IV curve data of different pesticides at different concentrations; record the IV curves of acetylcholinesterase and butyrylcholinesterase respectively; Peak extraction: For each IV curve, extract the peak value of the Faraday current; Linear difference: For each pesticide sample, calculate the difference between the current peak and the maximum peak, which is the current peak when there is no pesticide, and get the drop peak; Feature merging: Merge the decreasing peaks of two enzymes at different concentrations to construct dual enzyme features; Feature matrix: The dual enzyme features of all pesticide samples are combined into a feature matrix, each row represents a pesticide category, each column represents a concentration, and each cell stores the dual enzyme features of the pesticide of the corresponding concentration and category.

3. The method for detecting multiple pesticides according to claim 1 or 2, characterized in that: The detection method specifically comprises: Data preprocessing: extract the Faraday current peak from the IV curves of acetylcholinesterase and butyrylcholinesterase; perform linear subtraction to eliminate the influence of noise; merge the decreasing peaks of acetylcholinesterase and butyrylcholinesterase at different concentrations to construct dual enzyme features; Nearest neighbor algorithm: Use the nearest neighbor algorithm to classify based on the feature matrix; calculate the distance between the sample to be tested and all samples in the training set, and select the nearest k neighbors; determine the category and concentration of the sample to be tested based on neighbor voting or averaging; Input: k value, dual enzyme feature matrix, feature matrix label and features of the sample to be tested; Initialize the distance list: used to store the distance between each sample in the feature matrix and the sample to be tested and the corresponding label; Calculate distance: traverse the feature matrix, calculate the Euclidean distance between each sample and the sample to be tested, and store the result in the distance list; Sorting: Sort the distance list in ascending order to find the nearest k neighbors; Select the nearest k neighbors: Select the first k elements from the sorted list; Count labels: Initialize a dictionary to count the number of times each label appears in k neighbors; Voting: Find the tag with the most occurrences; Return result: Return the label with the highest number of occurrences as the prediction result, that is, the type and concentration of the pesticide solution to be tested.

4. An electrochemical biosensor array for detecting multiple pesticides, which implements the multiple pesticide detection method according to any one of claims 1 to 3, characterized in that: Setting a working electrode, wherein the working electrode is composed of two pairs of micro-scale interdigitated structures, which are arranged in parallel as two rectangular working electrodes 1 and 2; The interdigitated fingers of the counter electrode are intertwined with the interdigitated fingers of the two working electrodes; A reference electrode is located between and below the two working electrodes to form an inverted "T" structure.

5. The electrochemical biosensor array for detecting multiple pesticides according to claim 4, characterized in that: The method for preparing the sensor array comprises: Step 1: Add the ZIF-8 suspension dropwise to the working electrode of the interdigitated microelectrode and wait for it to dry completely; Step 2: Add the carboxymethyl chitosan solution dropwise to the working electrode 1 and working electrode 2 of the interdigitated microelectrode respectively, and wait until they are completely dried; Step 3: Add the acetylcholinesterase solution dropwise to the working electrode 1 of the interdigitated microelectrode and wait for it to completely dry; Step 4: Add the butyrylcholinesterase solution dropwise to the working electrode 2 of the interdigitated microelectrode and wait for it to completely dry.

6. The electrochemical biosensor array for detecting multiple pesticides according to claim 5, characterized in that: The concentration of the ZIF-8 suspension is 0.1 mg / uL; The mass fraction of carboxymethyl chitosan solution is 0.05%; Acetylcholinesterase solution 0.002u / uL; Butyrylcholinesterase solution 0.002u / uL.

7. The electrochemical biosensor array for detecting multiple pesticides according to claim 6, characterized in that: The addition amount of ZIF-8 suspension, acetylcholinesterase solution and butyrylcholinesterase solution was 10uL; the addition amount of carboxymethyl chitosan solution was 3uL.

8. The electrochemical biosensor array for detecting multiple pesticides according to any one of claims 4 to 7, characterized in that: The preparation steps include: Step 1: Use a three-layer screen printing structure to prepare different parts of the electrode structure; Step 2: Use polyimide as a substrate and place it under the first layer to print the conductor; Step 3: Create working and counter electrodes by printing carbon ink; Step 4: Print the reference electrode using silver / silver chloride ink; Step 5: Use a waterproof layer for packaging.

9. Use of the electrochemical biosensor array for detecting multiple pesticides according to any one of claims 4 to 8 for detecting pesticides.

10. The use according to claim 9, characterized in that: IV curves of different pesticides at different concentrations were established, including: A. Take 10uL of iodinated acetylthiocholine solution and drop it into the electrochemical biosensor array, connect the electrode to the electrochemical workstation, use the differential pulse voltammetry provided by the electrochemical workstation to detect the current generated by the electrode, and record the current-voltage curves generated by the iodinated acetylthiocholine solution on the working electrode 1 and the working electrode 2 in the absence of pesticides; B. Take 10uL of a certain concentration of a pesticide solution and drop it onto the electrochemical biosensor array, then take 10uL of iodinated acetylthiocholine solution and drop it onto the electrochemical biosensor array, let it stand for 30 to 60 seconds, connect the electrodes to the electrochemical workstation, use the differential pulse voltammetry provided by the electrochemical workstation to detect the current generated by the electrodes, and record the current-voltage curves generated by the pesticide solution of the concentration at the working electrode 1 and the working electrode 2 respectively; C. Repeat process B to obtain a set of current-voltage curves of a certain pesticide solution with different concentrations on working electrode 1 and working electrode 2; D. Repeat processes B and C to obtain the current-voltage curves of different types and concentrations of pesticides generated on working electrodes 1 and 2.

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