Pesticide residue rapid detection system and method based on fluorescence immunochromatography

Abstract

The invention belongs to the technical field of pesticide residue detection, and discloses a rapid pesticide residue detection system and method based on fluorescence immunochromatography. Comprising the following steps: collecting pv to-be-detected samples, and performing deep extraction on the to-be-detected samples to obtain pv to-be-detected sample extracting solutions; extracting pf to-be-detected sample extracting solutions, recording the pf to-be-detected sample extracting solutions as to-be-detected sample detecting solutions, carrying out primary pesticide residue detection on the to-be-detected sample detecting solutions, obtaining environmental data in a primary pesticide residue detection time period, and judging whether secondary pesticide residue detection is carried out or not according to the environmental data; acquiring the pesticide concentration in the to-be-detected sample detection liquid according to the primary pesticide residue detection result and the judgment result; extracting the residual to-be-detected sample extracting solution, recording the residual to-be-detected sample extracting solution as a to-be-detected sample prediction solution, and obtaining the pesticide concentration in the to-be-detected sample prediction solution according to the pesticide concentration in the to-be-detected sample detection solution; and pesticide residue detection is rapidly and accurately carried out on the to-be-detected sample.

Description

Technical Field

[0001] The present invention relates to the technical field of pesticide residue detection, and more specifically, to a rapid detection system and method for pesticide residues based on fluorescence immunochromatography. Background Art

[0002] The patent with application publication number CN112946105A discloses a rapid detection system and detection method for pesticide residues. The rapid detection system for pesticide residues includes: a sample collection module, a sample processing module, a sample detection module, a detection result acquisition module, a detection result identification module, a central processing and control module, a data transmission module, a network server module, a voice broadcast module, and a human-computer interaction module. The present invention can quantitatively collect and process samples through the sample collection module and the sample processing module, reducing the heavy work of picking and processing for the staff. At the same time, through the network server module, the detection end and the network end can be integrated, shortening the release time of the detection data, improving the timeliness and effectiveness of the data, forming vegetable safety big data, realizing the large-scale transformation of achievements, and then ensuring the quality and safety of food products, improving the domestic and international competitiveness of food, and promoting sustainable development.

[0003] However, in the process of detecting pesticide residues, traditional pesticide residue detection is slow and cannot detect the concentration of pesticides, which poses a threat to food safety. External environmental factors will also affect the results of pesticide residue detection. For a large number of samples to be tested, if they are tested one by one, it will take a lot of time and cause unnecessary waste of manpower and material resources.

[0004] In view of this, the present invention proposes a rapid detection system and method for pesticide residues based on fluorescent immunochromatography to solve the above problems. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solution: a rapid detection method for pesticide residues based on fluorescent immunochromatography, comprising:

[0006] Step S1: Collect p_v samples to be tested, perform deep extraction on the samples to be tested, and obtain p_v extracts of the samples to be tested;

[0007] Step S2: extract p_f portions of the sample extract to be tested and record them as the sample test solution to be tested, conduct a primary test of pesticide residues on the sample test solution to be tested, obtain environmental data within the time period of the primary test of pesticide residues, and determine whether to conduct a secondary test of pesticide residues based on the environmental data;

[0008] Step S3: obtaining the pesticide concentration in the test solution of the sample to be tested according to the result of the first test of pesticide residues and the judgment result;

[0009] Step S4: extract the remaining sample extract to be detected and record it as the sample prediction solution to be detected, and obtain the pesticide concentration in the sample prediction solution to be detected according to the pesticide concentration in the sample test solution to be detected.

[0010] Furthermore, the method of performing deep extraction on the sample to be detected to obtain p_v portions of sample extract to be detected comprises:

[0011] chopping and grinding p_v parts of the sample to be tested, adding a solvent to the ground sample to be tested, and obtaining p_v parts of a preliminary extract;

[0012] Stir and filter p_v parts of the preliminary extract to obtain p_v parts of the sample extract to be tested.

[0013] Furthermore, the method for performing a single detection of pesticide residues on a sample test solution to be detected comprises:

[0014] Aspirate d (uL) of the sample test solution to be detected by a pipette, where d is the volume of the sample test solution to be detected aspirated by the pipette, and uL is the volume unit in microliters, and add d (uL) of the sample test solution to be detected to the sample area of ​​the fluorescent immunochromatography reagent test card;

[0015] The fluorescent immunochromatographic reagent detection card comprises a sample area, a binding area, a fluorescent area and a detection area, wherein a binding antibody is arranged in the binding area, a fluorescent marker is arranged in the fluorescent area, and a capture antibody is arranged in the detection area;

[0016] The sample test liquid to be tested flows from the sample area to the binding area. If there are pesticide molecules in the sample test liquid to be tested, they will bind to the binding antibodies in the binding area to form an antigen-antibody complex. Otherwise, no antigen-antibody complex will be formed.

[0017] The sample test solution to be tested flows from the binding area to the fluorescent area. If there is an antigen-antibody complex in the sample test solution to be tested, it will combine with the fluorescent marker in the fluorescent area to form a fluorescent-antigen-antibody complex. Otherwise, no fluorescent-antigen-antibody complex will be formed.

[0018] The sample test solution to be tested flows from the fluorescence area to the detection area. If there is a fluorescent-antigen-antibody complex in the sample test solution to be tested, it will combine with the capture antibody in the detection area to form a fluorescent signal. Otherwise, no fluorescent signal will be formed.

[0019] Furthermore, the environmental data includes environmental temperature, environmental humidity and concentration of particulate matter in the air;

[0020] The method for determining whether to perform secondary detection of pesticide residues based on environmental data includes:

[0021] Step D1: Establish a temperature blank coordinate system, divide the time period equally into n time points, fill the n time points into the abscissa of the temperature blank coordinate system in sequence, set the ordinate of the temperature blank coordinate system to the ambient temperature, and fill the ambient temperature at the time point into the temperature blank coordinate system, obtain ambient temperature data sample points, connect the ambient temperature data sample points in sequence through straight lines in chronological order, and obtain an ambient temperature change line graph;

[0022] Determine whether the ambient temperature change is abnormal based on the ambient temperature change line graph. If the ambient temperature change is abnormal, conduct a secondary test for pesticide residues.

[0023] Step D2: Repeat step D1 to obtain a line graph of environmental humidity change and a line graph of particle concentration change, and determine whether the environmental humidity change and the particle concentration change are abnormal according to the line graph of environmental humidity change and the line graph of particle concentration change. If the environmental humidity change or the particle concentration change is abnormal, perform a secondary test for pesticide residues;

[0024] Step D3: setting an ambient temperature threshold range, an ambient humidity threshold range and a particle concentration threshold, and performing a secondary detection of pesticide residues when the ambient temperature within the time period of the primary detection of pesticide residues exceeds the ambient temperature threshold range or the ambient humidity exceeds the ambient humidity threshold range or the particle concentration is greater than or equal to the particle concentration threshold;

[0025] Step D4: When the ambient temperature is within the ambient temperature threshold range, the ambient humidity is within the ambient humidity threshold range, the particle concentration is less than the particle concentration threshold, and the ambient temperature, ambient humidity and particle concentration changes are normal, no secondary detection of pesticide residues is performed.

[0026] Furthermore, the method for judging whether the ambient temperature change is abnormal according to the ambient temperature change line graph includes:

[0027] Starting from the second ambient temperature data sample point, the straight line length between the ambient temperature data sample point and the previous ambient temperature data sample point is obtained, and recorded as the first straight line length, and the first straight line length threshold is set. When the first straight line length is greater than or equal to the first straight line length threshold, the ambient temperature change is abnormal, otherwise, the ambient temperature change is normal.

[0028] Furthermore, the method for obtaining the pesticide concentration in the test solution of the sample to be tested according to the result of the first detection of pesticide residues and the judgment result includes:

[0029] If the secondary pesticide residue test is not performed, the pesticide concentration in the test solution of the sample to be tested is obtained based on the result of the primary pesticide residue test, including:

[0030] Prepare a pesticide standard stock solution with a pesticide concentration of e (mg / mL), where mg is the mass unit of milligrams and mL is the volume unit of milliliters. Dilute the pesticide standard stock solution into f portions of pesticide standard solutions with different pesticide concentrations, and label the pesticide standard solutions as i, where i=1, 2, 3, ..., f. Perform a pesticide residue test on the pesticide standard solutions once, and obtain the fluorescence signal intensity after the test.

[0031] A two-dimensional rectangular coordinate system is established, and the numbers of the pesticide standard solutions are filled in the abscissa of the two-dimensional rectangular coordinate system in order from small to large. The ordinate of the two-dimensional rectangular coordinate system is set to the fluorescence signal intensity, and the fluorescence signal intensity corresponding to the pesticide standard solution with the corresponding number is filled in the two-dimensional rectangular coordinate system, and the fluorescence signal data sample points are obtained, and the fitting parameters are obtained. The fluorescence signal data sample points are fitted according to the fitting parameters to obtain the pesticide concentration-fluorescence signal intensity correlation function: y=a0+a1x+a2x 2 +……+a m x m ;

[0032] Among them, y is the fluorescence signal intensity, x is the pesticide concentration, a0, a1, a2, ..., a m is the fitting parameter;

[0033] Obtaining the fluorescence signal intensity corresponding to the test solution of the sample to be detected. If the fluorescence signal intensity corresponding to the test solution of the sample to be detected is zero, there is no pesticide residue in the test solution of the sample to be detected. Otherwise, the fluorescence signal intensity corresponding to the test solution of the sample to be detected is input into the pesticide concentration-fluorescence signal intensity correlation function to obtain the pesticide concentration in the test solution of the sample to be detected;

[0034] If a secondary test for pesticide residues is performed, the pesticide concentration in the test solution of the sample to be tested is obtained based on the result of the secondary test for pesticide residues.

[0035] Furthermore, the method for obtaining fitting parameters includes:

[0036] Find the fitting parameters a0, a1, a2, ..., a m , so that the error sum of squares S is minimized, specifically including:

[0037] in,

[0038] Among them, y i is the fluorescence signal intensity corresponding to the pesticide standard solution labeled i, x i is the pesticide concentration of the pesticide standard solution labeled i;

[0039] The pesticide concentration-fluorescence signal intensity correlation function was converted into a matrix form: Y = XA;

[0040] Where Y is the column vector of fluorescence signal intensity y, y1 is the fluorescence signal intensity corresponding to the pesticide standard solution labeled 1, y2 is the fluorescence signal intensity corresponding to the pesticide standard solution labeled 2, and y f is the fluorescence signal intensity corresponding to the pesticide standard solution labeled f, X is the design matrix of the pesticide concentration x, x1 is the pesticide concentration of the pesticide standard solution labeled 1, x2 is the pesticide concentration of the pesticide standard solution labeled 2, and x f is the pesticide concentration of the pesticide standard solution labeled f, and A is the column vector of fitting parameters;

[0041] The fitting parameters a0, a1, a2, ..., a are obtained according to the matrix form of the correlation function between pesticide concentration and fluorescence signal intensity. m ;

[0042] in, X T is the transpose of the design matrix of pesticide concentration x, (X T X) -1 Represents X T The inverse matrix of X.

[0043] Furthermore, the method for obtaining the pesticide concentration in the predicted solution of the sample to be detected according to the pesticide concentration in the test solution of the sample to be detected comprises:

[0044] Obtaining the time interval between the collection time of the sample to be tested and the time of spraying the pesticide, the dosage of the pesticide spraying, and the rainfall from the time of spraying the pesticide to the collection time corresponding to the test solution of the sample to be tested;

[0045] Construct a pesticide concentration recursive model, including:

[0046] Based on the LSTM basic framework, the input layer, LSTM layer, fully connected layer and output layer are set. The input of the input layer is set to the time interval, pesticide dosage and rainfall. The activation function of the fully connected layer is ReLU. The output of the output layer is the pesticide concentration.

[0047] Using the Adam algorithm, the loss function is: F(k) represents the model output pesticide concentration of the kth sample, F'(k) represents the actual pesticide concentration of the kth sample, N is the number of samples, δ is the weight coefficient, and k is the index of the number of samples;

[0048] Training and using pesticide concentration recursive models, including:

[0049] Step B1: Collect p_f samples to form a sample set, and divide it into a training set and a validation set in a ratio of 8:2. The training set is divided into batches and input into the pesticide concentration recursive model in sequence for forward propagation;

[0050] Step B2: Obtain the pesticide concentration output by the pesticide concentration recursive model, calculate the loss value using the loss function, calculate each parameter in the model using the back propagation algorithm, and update the parameters using the gradient descent algorithm;

[0051] Step B3: Repeat steps B1 and B2 until the loss function value of the pesticide concentration recursive model no longer changes, import the validation set for validation, and when the validation is successful, obtain the trained pesticide concentration recursive model; when the validation is unsuccessful, repeat step B3;

[0052] Step B4: Obtain the time interval between the collection time and the pesticide spraying time of the sample to be tested, the pesticide spraying dosage, and the rainfall from the pesticide spraying time to the collection time corresponding to the predicted liquid of the sample to be tested, and input them into the trained pesticide concentration recursive model to obtain the pesticide concentration in the predicted liquid of the sample to be tested.

[0053] Furthermore, the method of collecting p_f samples to form a sample set includes:

[0054] The time interval between the collection time and the pesticide spraying time of the sample to be tested corresponding to the test solution of the sample to be tested, the pesticide spraying dosage, the rainfall from the pesticide spraying time to the collection time, and the pesticide concentration are taken as a sample, and p_f samples are collected to form a sample set.

[0055] The rapid detection system for pesticide residues based on fluorescent immunochromatography includes:

[0056] A data acquisition module is used to collect p_v samples to be tested;

[0057] The residue detection module is used to perform deep extraction on the sample to be tested, obtain p_v parts of the sample extract to be tested, extract p_f parts of the sample extract to be tested, and record them as the sample test solution to be tested, perform a primary pesticide residue test on the sample test solution to be tested, and obtain environmental data within the time period of the primary pesticide residue test, and determine whether to perform a secondary pesticide residue test based on the environmental data;

[0058] The concentration acquisition module obtains the pesticide concentration in the test solution of the sample to be tested according to the result of the first pesticide residue test and the judgment result, extracts the remaining extract of the sample to be tested and records it as the predicted solution of the sample to be tested, and obtains the pesticide concentration in the predicted solution of the sample to be tested according to the pesticide concentration in the test solution of the sample to be tested.

[0059] The technical effects and advantages of the rapid detection system and method of pesticide residues based on fluorescent immunochromatography of the present invention are as follows:

[0060] Collect p_v samples to be tested, perform deep extraction on the samples to be tested, obtain p_v extracts of the samples to be tested, so that the pesticide components can be released from the samples more efficiently, maximize the extraction of pesticides, remove undissolved solid particles, and reduce interference with pesticide detection. Take p_f extracts of the samples to be tested and record them as the test solutions of the samples to be tested. Perform a pesticide residue test on the test solutions of the samples to be tested, and obtain environmental data within the time period of the first pesticide residue test. Determine whether to conduct a secondary pesticide residue test based on the environmental data. Environmental factors will interfere with the pesticide detection results. When environmental factors interfere with the pesticide detection results, When interference occurs in the results, a secondary test for pesticide residues is performed, which greatly improves the accuracy of the pesticide test results. The pesticide concentration in the test solution of the sample to be tested is obtained based on the results of the first test of pesticide residues and the judgment result. The pesticide concentration is specifically obtained, which makes the grasp of the pesticide residues in the sample to be tested clearer and ensures food safety. The remaining extract of the sample to be tested is extracted and recorded as the predicted solution of the sample to be tested. The pesticide concentration in the predicted solution of the sample to be tested is obtained based on the pesticide concentration in the test solution of the sample to be tested. The pesticide concentration in the predicted solution of the sample to be tested does not need to be tested, but is directly predicted, which greatly improves the rate of pesticide residue detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the rapid detection method of pesticide residues based on fluorescence immunochromatography of the present invention;

[0062] Figure 2 This is a schematic diagram of the rapid detection system for pesticide residues based on fluorescent immunochromatography of the present invention. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] Example 1

[0065] See also Figure 1 As shown, the rapid detection method of pesticide residues based on fluorescent immunochromatography described in this embodiment includes:

[0066] Step S1: Collect p_v samples to be tested, perform deep extraction on the samples to be tested, and obtain p_v extracts of the samples to be tested;

[0067] Step S2: extract p_f portions of the sample extract to be tested and record them as the sample test solution to be tested, conduct a primary test of pesticide residues on the sample test solution to be tested, obtain environmental data within the time period of the primary test of pesticide residues, and determine whether to conduct a secondary test of pesticide residues based on the environmental data;

[0068] Step S3: obtaining the pesticide concentration in the test solution of the sample to be tested according to the result of the first test of pesticide residues and the judgment result;

[0069] Step S4: extract the remaining sample extract to be detected and record it as the sample prediction solution to be detected, and obtain the pesticide concentration in the sample prediction solution to be detected according to the pesticide concentration in the sample test solution to be detected.

[0070] The process of collecting p_v samples to be tested includes:

[0071] The samples to be tested include fruits on fruit trees after pesticide spraying, farmland after pesticide spraying, water sources, etc.

[0072] If the sample to be tested is a fruit on a fruit tree after pesticide spraying, then obtain j (mg) peels of p_v fruits as the sample to be tested, j is the weight of the obtained fruit peels, mg is the mass unit milligram; if the sample to be tested is a farmland after pesticide spraying, then obtain b (mg) soil in p_v farmlands as the sample to be tested, b is the weight of the obtained soil; if the sample to be tested is a water source, then obtain c (mL) water in p_v water sources as the sample to be tested, c is the volume of the obtained water, mL is the volume unit milliliter;

[0073] It needs to be explained that the samples collected for testing are distributed in different regions.

[0074] The process of deeply extracting the sample to be tested and obtaining p_v portions of the sample extract to be tested includes:

[0075] chopping and grinding p_v parts of the sample to be tested, adding a solvent to the ground sample to be tested, and obtaining p_v parts of a preliminary extract;

[0076] Stirring and filtering p_v parts of the preliminary extract to obtain p_v parts of the sample extract to be tested;

[0077] It needs to be explained that chopping and grinding the sample to be tested can increase the surface area in contact with the solvent, so that the pesticide components can be released from the sample more efficiently. The purpose of stirring is to allow the solvent to evenly penetrate the sample to be tested and maximize the extraction of pesticides. The purpose of filtering is to remove undissolved solid particles and reduce interference with pesticide detection.

[0078] The process of conducting a primary pesticide residue test on the sample test solution to be tested includes:

[0079] Aspirate d (uL) of the sample test solution to be detected by a pipette, where d is the volume of the sample test solution to be detected aspirated by the pipette, and uL is the volume unit in microliters, and add d (uL) of the sample test solution to be detected to the sample area of ​​the fluorescent immunochromatography reagent test card;

[0080] The fluorescent immunochromatographic reagent detection card comprises a sample area, a binding area, a fluorescent area and a detection area, wherein a binding antibody is arranged in the binding area, and the binding antibody can bind to the pesticide molecules in the sample detection liquid to be detected to form an antigen-antibody complex, and a fluorescent marker is arranged in the fluorescent area, and the fluorescent marker can bind to the antigen-antibody complex to form a fluorescent-antigen-antibody complex, and a capture antibody is arranged in the detection area, and the capture antibody can capture the fluorescent-antigen-antibody complex to form a fluorescent signal;

[0081] The sample test liquid to be tested flows from the sample area to the binding area. If there are pesticide molecules in the sample test liquid to be tested, they will bind to the binding antibodies in the binding area to form an antigen-antibody complex. If there are no pesticide molecules in the sample test liquid to be tested, no antigen-antibody complex will be formed.

[0082] The sample test solution to be tested flows from the binding area to the fluorescent area. If there is an antigen-antibody complex in the sample test solution to be tested, it combines with the fluorescent marker in the fluorescent area to form a fluorescent-antigen-antibody complex. If there is no antigen-antibody complex in the sample test solution to be tested, no fluorescent-antigen-antibody complex is formed.

[0083] The test liquid of the sample to be detected flows from the fluorescence area to the detection area. If there is a fluorescent-antigen-antibody complex in the test liquid of the sample to be detected, it will combine with the capture antibody in the detection area to form a fluorescent signal. If there is no fluorescent-antigen-antibody complex in the test liquid of the sample to be detected, no fluorescent signal will be formed.

[0084] The process of obtaining environmental data within the time period of the first pesticide residue detection and determining whether to conduct a second pesticide residue detection based on the environmental data includes:

[0085] The environmental data include ambient temperature, ambient humidity and concentration of particulate matter in the air;

[0086] The ambient temperature is obtained through the temperature sensor, the ambient humidity is obtained through the humidity sensor, and the concentration of particulate matter in the air is obtained through the particulate matter detection equipment;

[0087] Establish a temperature blank coordinate system, divide the time period equally into n time points, fill the n time points into the abscissa of the temperature blank coordinate system in sequence, set the ordinate of the temperature blank coordinate system to the ambient temperature, and fill the ambient temperature at the time point into the temperature blank coordinate system, obtain ambient temperature data sample points, connect the ambient temperature data sample points in sequence through straight lines in chronological order, and obtain an ambient temperature change line graph;

[0088] Set the ambient temperature threshold range. When the ambient temperature during the first pesticide residue detection period exceeds the ambient temperature threshold range, a second pesticide residue detection is performed.

[0089] Starting from the second ambient temperature data sample point, obtain the straight line length between the ambient temperature data sample point and the previous ambient temperature data sample point, and record it as the first straight line length, and set the first straight line length threshold. When the first straight line length is greater than or equal to the first straight line length threshold, the ambient temperature change is abnormal, and a secondary detection of pesticide residues is performed. Otherwise, the ambient temperature change is normal.

[0090] Establish a humidity blank coordinate system, fill n time points into the horizontal coordinate of the humidity blank coordinate system in sequence, set the vertical coordinate of the humidity blank coordinate system to the ambient humidity, and fill the ambient humidity at the time point into the humidity blank coordinate system, obtain ambient humidity data sample points, connect the ambient humidity data sample points in sequence through straight lines in chronological order, and obtain an ambient humidity change line graph;

[0091] Set the environmental humidity threshold range. When the environmental humidity during the time period of the first pesticide residue detection exceeds the environmental humidity threshold range, a second pesticide residue detection is performed.

[0092] Starting from the second environmental humidity data sample point, obtain the straight line length between the environmental humidity data sample point and the previous environmental humidity data sample point, and record it as the second straight line length, and set the second straight line length threshold. When the second straight line length is greater than or equal to the second straight line length threshold, the environmental humidity change is abnormal, and a secondary detection of pesticide residues is performed. Otherwise, the environmental humidity change is normal.

[0093] Establish a particle concentration blank coordinate system, fill n time points into the abscissa of the particle concentration blank coordinate system in sequence, set the ordinate of the particle concentration blank coordinate system to the particle concentration, and fill the particle concentration at the time point into the particle concentration blank coordinate system to obtain the particle concentration data sample points, connect the particle concentration data sample points in sequence with straight lines in chronological order, and obtain a particle concentration change line graph;

[0094] Set a particle concentration threshold. When the particle concentration within the time period of the first pesticide residue detection is greater than or equal to the particle concentration threshold, conduct a second pesticide residue detection.

[0095] Starting from the second particle concentration data sample point, obtain the straight line length between the particle concentration data sample point and the particle concentration data sample point before the particle concentration data sample point, and record it as the third straight line length, and set the third straight line length threshold. When the third straight line length is greater than or equal to the third straight line length threshold, the particle concentration changes abnormally, and a secondary detection of pesticide residues is performed. Otherwise, the particle concentration changes normally.

[0096] When the ambient temperature is within the ambient temperature threshold range, the ambient humidity is within the ambient humidity threshold range, the particle concentration is less than the particle concentration threshold, and the ambient temperature, ambient humidity and particle concentration changes are normal, no secondary detection of pesticide residues is performed;

[0097] It needs to be explained that the process of secondary testing of pesticide residues is the same as that of primary testing of pesticide residues.

[0098] The process of obtaining the pesticide concentration in the test solution of the sample to be tested based on the result of the first test of pesticide residues and the judgment result includes:

[0099] If the secondary test for pesticide residues is not performed, the pesticide concentration in the test solution of the sample to be tested is obtained based on the result of the primary test for pesticide residues;

[0100] Prepare a pesticide standard stock solution with a pesticide concentration of e (mg / mL), dilute the pesticide standard stock solution into f portions of pesticide standard solutions with different pesticide concentrations, and label the pesticide standard solutions as i, i=1, 2, 3, ..., f, perform a pesticide residue test on the pesticide standard solutions, and obtain the fluorescence signal intensity after the test;

[0101] It needs to be explained that the smaller the number of the pesticide standard solution, the lower the pesticide concentration of the pesticide standard solution, and the larger the number of the pesticide standard solution, the higher the pesticide concentration of the pesticide standard solution;

[0102] A two-dimensional rectangular coordinate system is established, and the numbers of the pesticide standard solutions are filled in the abscissa of the two-dimensional rectangular coordinate system in order from small to large. The ordinate of the two-dimensional rectangular coordinate system is set to the fluorescence signal intensity, and the fluorescence signal intensity corresponding to the pesticide standard solution with the corresponding number is filled in the two-dimensional rectangular coordinate system to obtain the fluorescence signal data sample points, and the fluorescence signal data sample points are fitted to obtain the pesticide concentration-fluorescence signal intensity correlation function: y=a0+a1x+a2x 2 +……+a m x m ;

[0103] Among them, y is the fluorescence signal intensity, x is the pesticide concentration, a0, a1, a2, ..., a m is the fitting parameter to be obtained;

[0104] The process of obtaining fitting parameters includes:

[0105] Find the fitting parameters a0, a1, a2, ..., a m , so that the error sum of squares S is minimized;

[0106] in,

[0107] Among them, y i is the fluorescence signal intensity corresponding to the pesticide standard solution labeled i, x i is the pesticide concentration of the pesticide standard solution labeled i;

[0108] Find the fitting parameters a0, a1, a2, ..., a m , the process of minimizing the sum of squared errors S includes:

[0109] The pesticide concentration-fluorescence signal intensity correlation function was converted into a matrix form: Y = XA;

[0110] Where Y is the column vector of fluorescence signal intensity y, y1 is the fluorescence signal intensity corresponding to the pesticide standard solution labeled 1, y2 is the fluorescence signal intensity corresponding to the pesticide standard solution labeled 2, and y f is the fluorescence signal intensity corresponding to the pesticide standard solution labeled f, X is the design matrix of the pesticide concentration x, x1 is the pesticide concentration of the pesticide standard solution labeled 1, x2 is the pesticide concentration of the pesticide standard solution labeled 2, and x f is the pesticide concentration of the pesticide standard solution labeled f, A is the column vector of fitting parameters,

[0111] The fitting parameters were obtained according to the matrix form of the pesticide concentration-fluorescence signal intensity correlation function;

[0112] in, X T is the transpose of the design matrix of pesticide concentration x, (X T X) -1 Represents X T The inverse matrix of X;

[0113] Obtaining the fluorescence signal intensity corresponding to the test solution of the sample to be detected; if the fluorescence signal intensity corresponding to the test solution of the sample to be detected is zero, there is no pesticide residue in the test solution of the sample to be detected; if the fluorescence signal intensity corresponding to the test solution of the sample to be detected is not zero, inputting the fluorescence signal intensity corresponding to the test solution of the sample to be detected into the pesticide concentration-fluorescence signal intensity correlation function to obtain the pesticide concentration in the test solution of the sample to be detected;

[0114] If a secondary test for pesticide residues is performed, the pesticide concentration in the test solution of the sample to be tested is obtained based on the result of the secondary test for pesticide residues;

[0115] It should be explained that the process of obtaining the pesticide concentration in the test solution of the sample to be tested based on the result of the secondary test for pesticide residues is the same as the process of obtaining the pesticide concentration in the test solution of the sample to be tested based on the result of the primary test for pesticide residues.

[0116] The process of obtaining the pesticide concentration in the predicted solution of the sample to be tested according to the pesticide concentration in the test solution of the sample to be tested includes:

[0117] Obtaining the time interval between the collection time of the sample to be tested and the time of spraying the pesticide, the dosage of the pesticide spraying, and the rainfall from the time of spraying the pesticide to the collection time corresponding to the test solution of the sample to be tested;

[0118] Construct a pesticide concentration recursive model, including:

[0119] Based on the LSTM basic framework, the input layer, LSTM layer, fully connected layer and output layer are set. The input of the input layer is set to the time interval, pesticide dosage and rainfall. The activation function of the fully connected layer is ReLU. The output of the output layer is the pesticide concentration.

[0120] Using the Adam algorithm, the loss function is: F(k) represents the model output pesticide concentration of the kth sample, F′(k) represents the actual pesticide concentration of the kth sample, N is the number of samples, δ is the weight coefficient, and k is the index of the number of samples;

[0121] Training and using pesticide concentration recursive models, including:

[0122] Step B1: Collect p_f samples to form a sample set, and divide it into a training set and a validation set in a ratio of 8:2. The training set is divided into batches and input into the pesticide concentration recursive model in sequence for forward propagation;

[0123] Step B2: Obtain the pesticide concentration output by the pesticide concentration recursive model, calculate the loss value using the loss function, calculate each parameter in the model using the back propagation algorithm, and update the parameters using the gradient descent algorithm;

[0124] Step B3: Repeat steps B1 and B2 until the loss function value of the pesticide concentration recursive model no longer changes, import the validation set for validation, and when the validation is successful, obtain the trained pesticide concentration recursive model; when the validation is unsuccessful, repeat step B3;

[0125] Step B4: Obtain the time interval between the collection time of the sample to be tested and the pesticide spraying time, the pesticide spraying dosage, and the rainfall from the pesticide spraying time to the collection time corresponding to the predicted sample solution to be tested, and input them into the trained pesticide concentration recursive model to obtain the pesticide concentration in the predicted sample solution to be tested;

[0126] The process of collecting p_f samples to form a sample set includes:

[0127] The time interval between the collection time and the pesticide spraying time of the sample to be tested corresponding to the test solution of the sample to be tested, the pesticide spraying dosage, the rainfall from the pesticide spraying time to the collection time, and the pesticide concentration are taken as a sample, and p_f samples are collected to form a sample set.

[0128] In this embodiment, p_v samples to be tested are collected, and deep extraction is performed on the samples to be tested to obtain p_v extracts of the samples to be tested, so that the pesticide components can be released from the samples more efficiently, the pesticides are extracted to the maximum extent, the undissolved solid particles are removed, and the interference with the pesticide detection is reduced. P_f extracts of the samples to be tested are extracted and recorded as the test solutions of the samples to be tested. The test solutions of the samples to be tested are tested for pesticide residues once, and the environmental data within the time period of the first pesticide residue test is obtained. It is determined whether to perform a secondary pesticide residue test based on the environmental data. Environmental factors will interfere with the pesticide detection results. When environmental factors interfere with the pesticide detection results, When interference occurs in the pesticide detection result, a secondary detection of pesticide residues is carried out, which greatly improves the accuracy of the pesticide detection result. The pesticide concentration in the detection liquid of the sample to be detected is obtained according to the result of the first detection of pesticide residues and the judgment result. The pesticide concentration is specifically obtained, which makes the grasp of the pesticide residues in the sample to be detected clearer and ensures food safety. The remaining sample to be detected extract is extracted and recorded as the predicted sample to be detected liquid. The pesticide concentration in the predicted sample to be detected liquid is obtained according to the pesticide concentration in the detection liquid of the sample to be detected. The pesticide concentration in the predicted sample to be detected liquid does not need to be detected, but is directly predicted, which greatly improves the rate of pesticide residue detection.

[0129] Example 2

[0130] See also Figure 2 As shown, the part not described in detail in this embodiment is described in Example 1, and a rapid detection system for pesticide residues based on fluorescent immunochromatography is provided, comprising:

[0131] A data acquisition module is used to collect p_v samples to be tested;

[0132] The residue detection module is used to perform deep extraction on the sample to be tested, obtain p_v parts of the sample extract to be tested, extract p_f parts of the sample extract to be tested, and record them as the sample test solution to be tested, perform a primary pesticide residue test on the sample test solution to be tested, and obtain environmental data within the time period of the primary pesticide residue test, and determine whether to perform a secondary pesticide residue test based on the environmental data;

[0133] The concentration acquisition module obtains the pesticide concentration in the test solution of the sample to be tested according to the result of the first pesticide residue test and the judgment result, extracts the remaining extract of the sample to be tested and records it as the predicted solution of the sample to be tested, and obtains the pesticide concentration in the predicted solution of the sample to be tested according to the pesticide concentration in the test solution of the sample to be tested.

[0134] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0135] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0136] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0137] Finally: 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 principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A rapid detection method for pesticide residues based on fluorescent immunochromatography, characterized in that: The rapid detection method for pesticide residues based on fluorescent immunochromatography comprises: Step S1: Collect p_v samples to be tested, perform deep extraction on the samples to be tested, and obtain p_v extracts of the samples to be tested; Step S2: extract p_f portions of the sample extract to be tested and record them as the sample test solution to be tested, conduct a primary test of pesticide residues on the sample test solution to be tested, obtain environmental data within the time period of the primary test of pesticide residues, and determine whether to conduct a secondary test of pesticide residues based on the environmental data; Step S3: obtaining the pesticide concentration in the test solution of the sample to be tested according to the result of the first test of pesticide residues and the judgment result; Step S4: extract the remaining sample extract to be detected and record it as the sample prediction solution to be detected, and obtain the pesticide concentration in the sample prediction solution to be detected according to the pesticide concentration in the sample test solution to be detected.

2. The method for rapid detection of pesticide residues based on fluorescent immunochromatography according to claim 1, characterized in that: The method for performing deep extraction on the sample to be detected to obtain p_v portions of sample extract to be detected comprises: chopping and grinding p_v parts of the sample to be tested, adding a solvent to the ground sample to be tested, and obtaining p_v parts of a preliminary extract; Stir and filter p_v parts of the preliminary extract to obtain p_v parts of the sample extract to be tested.

3. The method for rapid detection of pesticide residues based on fluorescent immunochromatography according to claim 2, characterized in that: The method for performing a single detection of pesticide residues on a sample test solution to be detected comprises: Aspirate d (uL) of the sample test solution to be detected by a pipette, where d is the volume of the sample test solution to be detected aspirated by the pipette, and uL is the volume unit in microliters, and add d (uL) of the sample test solution to be detected to the sample area of ​​the fluorescent immunochromatography reagent test card; The fluorescent immunochromatographic reagent detection card comprises a sample area, a binding area, a fluorescent area and a detection area, wherein a binding antibody is arranged in the binding area, a fluorescent marker is arranged in the fluorescent area, and a capture antibody is arranged in the detection area; The sample test liquid to be tested flows from the sample area to the binding area. If there are pesticide molecules in the sample test liquid to be tested, they will bind to the binding antibodies in the binding area to form an antigen-antibody complex. Otherwise, no antigen-antibody complex will be formed. The sample test solution to be tested flows from the binding area to the fluorescent area. If there is an antigen-antibody complex in the sample test solution to be tested, it will combine with the fluorescent marker in the fluorescent area to form a fluorescent-antigen-antibody complex. Otherwise, no fluorescent-antigen-antibody complex will be formed. The sample test solution to be tested flows from the fluorescence area to the detection area. If there is a fluorescent-antigen-antibody complex in the sample test solution to be tested, it will combine with the capture antibody in the detection area to form a fluorescent signal. Otherwise, no fluorescent signal will be formed.

4. The method for rapid detection of pesticide residues based on fluorescent immunochromatography according to claim 3, characterized in that: The environmental data include ambient temperature, ambient humidity and concentration of particulate matter in the air; The method for determining whether to perform secondary detection of pesticide residues based on environmental data includes: Step D1: Establish a temperature blank coordinate system, divide the time period equally into n time points, fill the n time points into the abscissa of the temperature blank coordinate system in sequence, set the ordinate of the temperature blank coordinate system to the ambient temperature, and fill the ambient temperature at the time point into the temperature blank coordinate system, obtain ambient temperature data sample points, connect the ambient temperature data sample points in sequence through straight lines in chronological order, and obtain an ambient temperature change line graph; Determine whether the ambient temperature change is abnormal based on the ambient temperature change line graph. If the ambient temperature change is abnormal, conduct a secondary test for pesticide residues. Step D2: Repeat step D1 to obtain a line graph of environmental humidity change and a line graph of particle concentration change, and determine whether the environmental humidity change and the particle concentration change are abnormal according to the line graph of environmental humidity change and the line graph of particle concentration change. If the environmental humidity change or the particle concentration change is abnormal, perform a secondary test for pesticide residues; Step D3: setting an ambient temperature threshold range, an ambient humidity threshold range and a particle concentration threshold, and performing a secondary detection of pesticide residues when the ambient temperature within the time period of the primary detection of pesticide residues exceeds the ambient temperature threshold range or the ambient humidity exceeds the ambient humidity threshold range or the particle concentration is greater than or equal to the particle concentration threshold; Step D4: When the ambient temperature is within the ambient temperature threshold range, the ambient humidity is within the ambient humidity threshold range, the particle concentration is less than the particle concentration threshold, and the ambient temperature, ambient humidity and particle concentration changes are normal, no secondary detection of pesticide residues is performed.

5. The method for rapid detection of pesticide residues based on fluorescent immunochromatography according to claim 4, characterized in that: The method for judging whether the ambient temperature change is abnormal according to the ambient temperature change line graph comprises: Starting from the second ambient temperature data sample point, the straight line length between the ambient temperature data sample point and the previous ambient temperature data sample point is obtained, and recorded as the first straight line length, and the first straight line length threshold is set. When the first straight line length is greater than or equal to the first straight line length threshold, the ambient temperature change is abnormal, otherwise, the ambient temperature change is normal.

6. The method for rapid detection of pesticide residues based on fluorescent immunochromatography according to claim 5, characterized in that: The method for obtaining the pesticide concentration in the test solution of the sample to be tested according to the result of the first detection of pesticide residues and the judgment result comprises: If the secondary pesticide residue test is not performed, the pesticide concentration in the test solution of the sample to be tested is obtained based on the result of the primary pesticide residue test, including: Prepare a pesticide standard stock solution with a pesticide concentration of e (mg / mL), where mg is the mass unit of milligrams and mL is the volume unit of milliliters. Dilute the pesticide standard stock solution into f portions of pesticide standard solutions with different pesticide concentrations, and label the pesticide standard solutions as i, where i=1, 2, 3, ..., f. Perform a pesticide residue test on the pesticide standard solutions once, and obtain the fluorescence signal intensity after the test. A two-dimensional rectangular coordinate system is established, and the numbers of the pesticide standard solutions are filled in the abscissa of the two-dimensional rectangular coordinate system in order from small to large. The ordinate of the two-dimensional rectangular coordinate system is set to the fluorescence signal intensity, and the fluorescence signal intensity corresponding to the pesticide standard solution with the corresponding number is filled in the two-dimensional rectangular coordinate system, and the fluorescence signal data sample points are obtained, and the fitting parameters are obtained. The fluorescence signal data sample points are fitted according to the fitting parameters to obtain the pesticide concentration-fluorescence signal intensity correlation function: y=a0+a1x+a2x 2 +……+a m x m ; Among them, y is the fluorescence signal intensity, x is the pesticide concentration, a0, a1, a2, ..., a m is the fitting parameter; Obtaining the fluorescence signal intensity corresponding to the test solution of the sample to be detected. If the fluorescence signal intensity corresponding to the test solution of the sample to be detected is zero, there is no pesticide residue in the test solution of the sample to be detected. Otherwise, the fluorescence signal intensity corresponding to the test solution of the sample to be detected is input into the pesticide concentration-fluorescence signal intensity correlation function to obtain the pesticide concentration in the test solution of the sample to be detected; If a secondary test for pesticide residues is performed, the pesticide concentration in the test solution of the sample to be tested is obtained based on the result of the secondary test for pesticide residues.

7. The method for rapid detection of pesticide residues based on fluorescent immunochromatography according to claim 6, characterized in that: The method for obtaining the fitting parameters comprises: Find the fitting parameters a0, a1, a2, ..., a m , so that the error sum of squares S is minimized, specifically including: in, Among them, y i is the fluorescence signal intensity corresponding to the pesticide standard solution labeled i, x i is the pesticide concentration of the pesticide standard solution labeled i; The pesticide concentration-fluorescence signal intensity correlation function was converted into a matrix form: Y = XA; Where Y is the column vector of fluorescence signal intensity y, y1 is the fluorescence signal intensity corresponding to the pesticide standard solution labeled 1, y2 is the fluorescence signal intensity corresponding to the pesticide standard solution labeled 2, and y f is the fluorescence signal intensity corresponding to the pesticide standard solution labeled f, X is the design matrix of the pesticide concentration x, x1 is the pesticide concentration of the pesticide standard solution labeled 1, x2 is the pesticide concentration of the pesticide standard solution labeled 2, and x f is the pesticide concentration of the pesticide standard solution labeled f, and A is the column vector of fitting parameters; The fitting parameters a0, a1, a2, ..., a are obtained according to the matrix form of the correlation function between pesticide concentration and fluorescence signal intensity. m ; in, X T is the transpose of the design matrix of pesticide concentration x, X T X) -1 Represents X T The inverse matrix of X.

8. The method for rapid detection of pesticide residues based on fluorescent immunochromatography according to claim 7, characterized in that: The method for obtaining the pesticide concentration in the predicted solution of the sample to be detected according to the pesticide concentration in the test solution of the sample to be detected comprises: Obtaining the time interval between the collection time of the sample to be tested and the time of spraying the pesticide, the dosage of the pesticide spraying, and the rainfall from the time of spraying the pesticide to the collection time corresponding to the test solution of the sample to be tested; Construct a pesticide concentration recursive model, including: Based on the LSTM basic framework, the input layer, LSTM layer, fully connected layer and output layer are set. The input of the input layer is set to the time interval, pesticide dosage and rainfall. The activation function of the fully connected layer is ReLU. The output of the output layer is the pesticide concentration. Using the Adam algorithm, the loss function is: F(k) represents the model output pesticide concentration of the kth sample, F'(k) represents the actual pesticide concentration of the kth sample, N is the number of samples, δ is the weight coefficient, and k is the index of the number of samples; Training and using pesticide concentration recursive models, including: Step B1: Collect p_f samples to form a sample set, and divide it into a training set and a validation set in a ratio of 8:

2. The training set is divided into batches and input into the pesticide concentration recursive model in sequence for forward propagation; Step B2: Obtain the pesticide concentration output by the pesticide concentration recursive model, calculate the loss value using the loss function, calculate each parameter in the model using the back propagation algorithm, and update the parameters using the gradient descent algorithm; Step B3: Repeat steps B1 and B2 until the loss function value of the pesticide concentration recursive model no longer changes, import the validation set for validation, and when the validation is successful, obtain the trained pesticide concentration recursive model; when the validation is unsuccessful, repeat step B3; Step B4: Obtain the time interval between the collection time and the pesticide spraying time of the sample to be tested, the pesticide spraying dosage, and the rainfall from the pesticide spraying time to the collection time corresponding to the predicted liquid of the sample to be tested, and input them into the trained pesticide concentration recursive model to obtain the pesticide concentration in the predicted liquid of the sample to be tested.

9. The method for rapid detection of pesticide residues based on fluorescent immunochromatography according to claim 8, characterized in that: The method of collecting p_f samples to form a sample set includes: The time interval between the collection time and the pesticide spraying time of the sample to be tested corresponding to the test solution of the sample to be tested, the pesticide spraying dosage, the rainfall from the pesticide spraying time to the collection time, and the pesticide concentration are taken as a sample, and p_f samples are collected to form a sample set.

10. A rapid detection system for pesticide residues based on fluorescence immunochromatography, which is used to implement the rapid detection method for pesticide residues based on fluorescence immunochromatography according to any one of claims 1 to 9, characterized in that: include: A data acquisition module is used to collect p_v samples to be tested; The residue detection module is used to perform deep extraction on the sample to be tested, obtain p_v parts of the sample extract to be tested, extract p_f parts of the sample extract to be tested, and record them as the sample test solution to be tested, perform a primary pesticide residue test on the sample test solution to be tested, and obtain environmental data within the time period of the primary pesticide residue test, and determine whether to perform a secondary pesticide residue test based on the environmental data; The concentration acquisition module obtains the pesticide concentration in the test solution of the sample to be tested according to the result of the first pesticide residue test and the judgment result, extracts the remaining extract of the sample to be tested and records it as the predicted solution of the sample to be tested, and obtains the pesticide concentration in the predicted solution of the sample to be tested according to the pesticide concentration in the test solution of the sample to be tested.

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