A quantitative detection method for soybean residual toxicity suitable for various pesticide combined pollution

Abstract

The present application relates to the technical field of agricultural product quality and safety detection, and particularly relates to a quantitative detection method for the toxicity of soybean residues caused by multiple pesticide joint pollution, comprising the following steps: S1: taking representative soybean samples and performing purification treatment; S2: obtaining the instrument response value of each target pesticide in the purified sample liquid; S3: calculating the measured value of the pesticide residue concentration; S4: querying the joint toxicity coefficient query table to determine the joint toxicity coefficient; S5: calculating the comprehensive weighted joint pollution index of the soybean sample; S6: determining the pesticide residue joint toxicity risk grade of the soybean sample. According to the present application, the residue concentrations of multiple pesticides are uniformly converted into toxicity effective concentrations with comparability, and the joint toxicity coefficients are combined to perform weighted summation and grading determination, so that the quantitative, standardized and risk grading evaluation of the toxicity level of soybean multiple pesticide joint pollution is realized.

Description

Technical Field

[0001] This invention relates to the field of agricultural product quality and safety testing technology, and in particular to a quantitative detection method for soybean residue toxicity applicable to combined contamination by multiple pesticides. Background Technology

[0002] In the current agricultural product safety supervision system, soybeans, as a frequently consumed source of plant protein, have become a key target for pesticide residue detection and toxicity evaluation. Due to the wide variety of pesticides used in agricultural production, soybean samples often exhibit synergistic residues of multiple pesticides. This combined contamination not only increases the complexity of toxicity risk assessment but also challenges the traditional single residue limit detection model. In particular, in actual testing, it is necessary to simultaneously address the complex interference problems caused by different pesticide types, different residue concentrations, and different toxicity mechanisms. If multi-pesticide synergistic evaluation cannot be conducted within a unified framework, it will be difficult to accurately determine the true toxicity level of the sample, thus limiting the scientific nature of food safety assessment.

[0003] Existing detection methods primarily rely on quantitative pesticide detection and comparison with individual limits, lacking a systematic assessment mechanism for the synergistic toxicity interactions between pesticides. This is particularly problematic when multiple pesticide residue concentrations are within acceptable limits but may collectively produce highly toxic effects, making it difficult to determine risk levels. Furthermore, existing methods lack clarity regarding the quantitative indicators, combination relationships, and concentration normalization calculation paths for synergistic toxicity, resulting in incomparable and untraceable assessment results. Therefore, a quantitative detection method for soybean residue toxicity applicable to combined pesticide contamination is urgently needed to achieve quantitative assessment of soybean residue toxicity under conditions of combined pesticide contamination, thereby improving regulatory efficiency and accuracy. Summary of the Invention

[0004] To achieve the above objectives, this invention provides a quantitative detection method for soybean residue toxicity applicable to combined pollution by multiple pesticides.

[0005] A quantitative detection method for soybean residue toxicity applicable to combined pollution by multiple pesticides includes the following steps: S1: Take a representative soybean sample, crush it, and extract it by shaking with an organic solvent to obtain a crude extract containing the target pesticide; then purify the crude extract to obtain a purified sample solution. S2: Inject the purified sample solution into the multi-residue detection instrument and simultaneously analyze and detect multiple preset target pesticides to obtain the instrument response value corresponding to each target pesticide in the purified sample solution. S3: Substitute the instrument response values ​​of each target pesticide into their respective standard curve equations to calculate the measured residual concentration of each target pesticide in the soybean sample; and based on the daily allowable intake safety standard of each target pesticide, convert the measured residual concentration of each pesticide into the effective concentration of each pesticide with comparable toxicity. S4: Based on the effective concentrations of each pesticide obtained in S3, query the pre-established combined toxicity coefficient lookup table to determine the combined toxicity coefficients corresponding to the current combination of multiple pesticides; S5: Multiply the effective concentrations of each pesticide obtained in S3 with the combined toxicity coefficients obtained in S4, and sum the product results of all target pesticides to calculate the comprehensive weighted combined pollution index of the soybean sample. S6: Compare the comprehensive weighted combined pollution index of S5 with the preset toxicity risk level threshold range to determine the pesticide residue combined toxicity risk level of the soybean sample.

[0006] Optionally, S1 specifically includes: S11: After air-drying a representative soybean sample, grind it to a particle size of less than 0.5 mm, and weigh a preset mass of the pulverized sample and place it in an extraction container; S12: Add a preset volume of organic solvent to the extraction container, seal it, and perform oscillation extraction under preset oscillation frequency and preset oscillation time conditions to transfer the target pesticide from the sample matrix to the solvent phase and obtain the extract. S13: Perform solid-liquid separation on the extract and collect the solvent phase as the crude extract containing the target pesticide; S14: Add the preset purification adsorbent to the crude extract and mix for the preset mixing time to remove pigments, lipids and protein interferences by adsorption. S15: Centrifuge the mixed system and collect the supernatant to obtain the purified sample solution.

[0007] Optionally, S2 specifically includes: S21: Call the preset multi-pesticide simultaneous detection method parameter configuration file, which includes chromatographic conditions, mass spectrometry parameters and pesticide list information. The parameter configuration file includes quantitative analysis parameters such as retention time window, parent ion and fragment ion information, ion source voltage and collision energy for each target pesticide. S22: Inject the purified sample solution obtained in step S1 into a multi-residue detection instrument equipped with an autosampler, and use gas chromatography-tandem mass spectrometry or liquid chromatography-tandem mass spectrometry equipment to separate the target pesticide on the chromatographic column under the set chromatographic conditions; S23: Based on the completion of chromatographic separation, perform multi-channel parallel detection according to the preset precursor ion-fragment ion pairs of each target pesticide, and record the mass spectrometry peak area of ​​each target pesticide within its predetermined retention time window. S24: Use the mass spectrometry peak area value as the instrument response value of the corresponding target pesticide, and use the target pesticide name as the index number to output a dataset containing the response values ​​of all target pesticides.

[0008] Optionally, S23 specifically includes: S231: Based on the parameter file configured in step S21, load the parent ion and fragment ion combinations corresponding to each target pesticide, construct a multi-reaction monitoring channel set, and bind each monitoring channel to its corresponding target pesticide. S232: Within the preset retention time window of the target pesticide entering the mass spectrometry detection unit, the monitoring channel corresponding to the target pesticide is called to collect ion signals within a predetermined mass number range and record the response intensity curve within the time window in real time. S233: Integrate the acquired response intensity curves to obtain the total response intensity value of the target pesticide within the predetermined retention time window under the corresponding monitoring channel, and calculate its mass spectrometry peak area as the instrument response value of the target pesticide. .

[0009] Optionally, S3 specifically includes: S31: Call the standard curve equation library corresponding to each target pesticide. Each standard curve is calibrated and fitted by the instrument response value at a known concentration. S32: Read the instrument response values ​​of each target pesticide obtained in S2, match them to the corresponding standard curve equations, perform inverse calculation, and obtain the measured residual concentration of each target pesticide in the soybean sample. S33: Call the table of acceptable daily intake standards for each target pesticide and read the ADI value specified in the human intake safety assessment of the target pesticide; S34: Convert the measured residual concentration of each target pesticide with its corresponding ADI value to calculate the toxicity intensity, and obtain the effective concentration of each pesticide with comparable toxicity under a unified scale.

[0010] Optionally, S34 specifically includes: S341: Read the measured residual concentration values ​​of each target pesticide obtained in S32, and establish a residual concentration sequence using the target pesticide identifier; S342: Call the preset population exposure parameter table to obtain the daily intake parameters and body weight parameters of soybeans, and perform exposure dose conversion on the residue concentration sequence to obtain the daily intake per unit body weight of each target pesticide. ; S343: Call the daily acceptable intake standard table obtained in S33, and read the daily acceptable intake corresponding to each target pesticide. and will and The ratios are converted under the same dimensions, and the resulting ratios are recorded as the effective concentrations of each target pesticide. .

[0011] Optionally, S4 specifically includes: S41: Receive the effective concentrations of each target pesticide output by S34, and sort the effective concentrations according to the preset order of target pesticides to form a combination vector of effective pesticide concentrations corresponding to the current soybean sample. S42: Based on the pesticide effective concentration combination vector, extract the concentration ratio relationship between each target pesticide, and use the pesticide type combination and concentration ratio as the joint toxicity query key value. S43: Perform a matching search according to the query key value in the pre-established combined toxicity coefficient query table; S44: When the query key value matches the index item in the combined toxicity coefficient lookup table, the corresponding combined toxicity coefficient is directly read and used as the combined toxicity coefficient of the current combination of multiple pesticides under the effective concentration conditions.

[0012] Optionally, S41 specifically includes: SS411: Calls the preset pesticide type order rule table, which arranges all possible target pesticides in a fixed order and assigns a unique serial number label to each target pesticide; SS412: Read the effective concentration data of the target pesticides detected in the soybean sample obtained from S3, and sort the effective concentration values ​​according to the position of the serial number label in the sequence rule table; SS413: For target pesticide items that are not detected, insert a placeholder with a value of zero for the effective concentration at the corresponding position; SS414: Arranges the sorted effective concentration data in a fixed order according to the target pesticides, and generates a combination vector of effective pesticide concentrations corresponding to the current soybean sample, which serves as the retrieval input for subsequent joint toxicity queries.

[0013] Optionally, S5 specifically includes: S51: Receive the effective concentrations of all target pesticides obtained in S3, and receive the combined toxicity coefficients obtained in S4, and use both as input parameters for calculating the combined pollution index of the current sample. S52: Perform a weighted product operation on all effective concentration values ​​and the combined toxicity coefficient to obtain the weighted value of each target pesticide under the current combined toxicity background. ; S53: All weighted values The combined weighted contamination index of the soybean samples is calculated by summing the results. The formula is as follows: In the formula, For the first The effective concentration of the target pesticide; This represents the combined toxicity coefficient of the current pesticide combination at a given concentration ratio. The target number of pesticide types; This is a comprehensive weighted joint pollution index.

[0014] Optionally, S6 specifically includes: S61: Receive the comprehensive weighted combined contamination index of the soybean sample calculated by S5. It also calls a preset toxicity risk level threshold interval table, which is divided into multiple continuous and non-overlapping risk level intervals according to toxicological evaluation standards. S62: Combined Pollution Index The risk level segment is determined by sequentially matching the toxicity risk level threshold range with the range of toxicity risk levels. S63: Based on the matched threshold range, output the pesticide residue combined toxicity risk level label of the current soybean sample as the final judgment result.

[0015] The beneficial effects of this invention are: This invention constructs a complete process from pesticide extraction, purification, and quantitative detection in soybean samples to residue concentration calculation and toxicity normalization, enabling the synergistic detection and equivalent toxicity conversion of multiple pesticides in the same sample. Furthermore, by converting the measured residue concentrations of different target pesticides into dimensionless effective toxicity concentrations and introducing a unified order rule to generate concentration combination vectors, it can stably connect to the joint toxicity coefficient query process, ensuring consistent input parameter structure and strong matching ability, thereby improving the standardization capability of multi-pesticide combination toxicity identification.

[0016] This invention, by using a pre-constructed lookup table of combined toxicity coefficients, enables the precise retrieval of the interaction strength of multiple pesticides under different concentration ratios. Combined with effective concentration weighting, a comprehensive pollution index is calculated, and the final judgment result is output after comparison with the risk level threshold range. Thus, a multi-pesticide residue toxicity evaluation method with data traceability, unified index quantification, and clear risk classification is established, significantly improving the quantitative identification of combined pollution toxicity levels in soybean samples and the ability to support regulatory decision-making. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the soybean residue toxicity quantitative detection method according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the calculation process for the effective concentration of various pesticides in an embodiment of the present invention. Detailed Implementation

[0019] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should also be noted that, to make the embodiments more comprehensive, the following embodiments are the best and preferred embodiments, and those skilled in the art can use other alternative methods to implement some well-known technologies; moreover, the accompanying drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.

[0020] It should be noted that the use of terms such as "an embodiment," "an embodiment," "an exemplary embodiment," and "some embodiments" in the specification indicates that the described embodiment may include a specific feature, structure, or characteristic, but not every embodiment necessarily includes that specific feature, structure, or characteristic. Furthermore, when a specific feature, structure, or characteristic is described in connection with an embodiment, implementing such a feature, structure, or characteristic in conjunction with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the art.

[0021] Generally, terms can be understood at least partly from their use in context. For example, depending at least partly on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in a singular sense, or a combination of features, structures, or characteristics in a plural sense. Additionally, the term "based on" can be understood not necessarily to convey an exclusive set of factors, but rather, alternatively, depending at least partly on the context, to allow for the presence of other factors that are not necessarily explicitly described.

[0022] like Figures 1-2 As shown, a method for quantitative detection of soybean residue toxicity applicable to combined pollution by multiple pesticides includes the following steps: S1: Take a representative soybean sample, crush it, and extract it by shaking with an organic solvent to obtain a crude extract containing the target pesticide; then purify the crude extract to obtain a purified sample solution. S1 specifically includes: S11: After air-drying a representative soybean sample, grind it to a particle size of less than 0.5 mm, and weigh a preset mass of the pulverized sample and place it in an extraction container; S12: Add a preset volume of organic solvent to the extraction container, seal it, and perform oscillation extraction under preset oscillation frequency and preset oscillation time conditions to transfer the target pesticide from the sample matrix to the solvent phase and obtain the extract. S13: Perform solid-liquid separation on the extract and collect the solvent phase as the crude extract containing the target pesticide; S14: Add the preset purification adsorbent to the crude extract and mix for the preset mixing time to remove pigments, lipids and protein interferences by adsorption. S15: Centrifuge the mixed system and collect the supernatant to obtain the purified sample solution. The above steps, through sequential processing of shaking extraction and adsorption purification, ensure that the target pesticide enters the sample solution stably and removes matrix interference, providing a pretreatment basis for obtaining consistent instrument response values ​​in subsequent synchronous detection.

[0023] S2: Inject the purified sample solution into the multi-residue detection instrument and simultaneously analyze and detect multiple preset target pesticides to obtain the instrument response value corresponding to each target pesticide in the purified sample solution. S2 specifically includes: S21: Call the preset multi-pesticide simultaneous detection method parameter configuration file, which includes chromatographic conditions, mass spectrometry parameters and pesticide list information. The parameter configuration file includes quantitative analysis parameters such as retention time window, parent ion and fragment ion information, ion source voltage and collision energy for each target pesticide. S22: Inject the purified sample solution obtained in step S1 into a multi-residue detection instrument equipped with an autosampler, and use gas chromatography-tandem mass spectrometry (GC-MS / MS) or liquid chromatography-tandem mass spectrometry (LC-MS / MS) equipment to separate the target pesticide on the chromatographic column under the set chromatographic conditions; S23: Based on the completion of chromatographic separation, perform multi-channel parallel detection according to the preset precursor ion-fragment ion pairs of each target pesticide, and record the mass spectrometry peak area of ​​each target pesticide within its predetermined retention time window. S24: Use the mass spectrometry peak area value as the instrument response value of the corresponding target pesticide, and use the name of the target pesticide as the index number to output a dataset containing the response values ​​of all target pesticides; the above steps, by configuring multi-pesticide synchronous analysis parameters and utilizing the multi-channel selective monitoring function of tandem mass spectrometry, can efficiently acquire the response signals of multiple target pesticides in a single injection process, avoiding error accumulation and resource waste caused by repeated detection, and improving detection efficiency and consistency of quantitative data.

[0024] S23 specifically includes: S231: Based on the parameter file configured in step S21, load the parent ion and fragment ion combinations corresponding to each target pesticide, construct a multi-reaction monitoring channel set, and bind each monitoring channel to its corresponding target pesticide. S232: Within the preset retention time window of the target pesticide entering the mass spectrometry detection unit, the monitoring channel corresponding to the target pesticide is called to collect ion signals within a predetermined mass number range and record the response intensity curve within the time window in real time. S233: Integrate the acquired response intensity curves to obtain the total response intensity value of the target pesticide within the predetermined retention time window under the corresponding monitoring channel, and calculate its mass spectrometry peak area as the instrument response value of the target pesticide. The calculation formula is as follows: In the formula, Targeted pesticides The instrument response value; Targeted pesticides In time The intensity of the ion signal at a given time; Target pesticides The retention time window start and end times; the above steps, by binding each target pesticide to its specific mother-fragment ion pair channel and performing response signal acquisition and integration processing within a precisely defined retention time window, can effectively eliminate non-specific interference signals, ensuring that the instrument response value of each pesticide is highly specific and repeatable, providing stable and reliable input data for subsequent residual concentration calculation steps.

[0025] S3: Substitute the instrument response values ​​of each target pesticide into their respective standard curve equations to calculate the measured residual concentration of each target pesticide in the soybean sample; and based on the daily allowable intake safety standard of each target pesticide, convert the measured residual concentration of each pesticide into the effective concentration of each pesticide with comparable toxicity. S3 specifically includes: S31: Call the standard curve equation library corresponding to each target pesticide. Each standard curve is calibrated and fitted by the instrument response value at a known concentration, and includes parameter information such as slope, intercept and fitting interval range. S32: Read the instrument response values ​​of each target pesticide obtained in S2, match them to the corresponding standard curve equations, perform inverse calculation, and obtain the measured residual concentration of each target pesticide in the soybean sample. S33: Call the daily acceptable intake standard table for each target pesticide, read the ADI value of the target pesticide in the human intake safety assessment, and use it as the toxicity conversion benchmark. Table 1 Intake Standards In Table 1 above, the names of the target pesticides correspond to the pesticide components screened in the test samples; the pesticide code serves as a unique identifier; the corresponding ADI value is extracted for each target pesticide using this table as a reference for toxicity conversion; S34: Convert the measured residual concentrations of each target pesticide with their corresponding ADI values ​​to obtain the effective concentrations of each pesticide with comparable toxicity under a unified scale. The above steps accurately back-calculate the measured residual concentrations of different target pesticides based on the standard curve and normalize them in combination with their toxicological safety standards. This can transform pesticide concentrations with different dimensions and toxicity mechanisms into effective concentrations with a unified toxicity evaluation scale, providing rigorous data support for joint toxicity correction and weighted calculation in subsequent steps, and improving the scientificity and objectivity of risk assessment.

[0026] S34 specifically includes: S341: Read the measured residual concentration values ​​of each target pesticide obtained in S32, and establish a residual concentration sequence using the target pesticide identifier; S342: Call the preset population exposure parameter table to obtain the daily intake parameters and body weight parameters of soybeans, and perform exposure dose conversion on the residue concentration sequence to obtain the daily intake per unit body weight of each target pesticide. ; Table 2. Population Exposure Parameters S343: Call the daily acceptable intake standard table obtained in S33, and read the daily acceptable intake corresponding to each target pesticide. and will and The ratios are converted under the same dimensions, and the resulting ratios are recorded as the effective concentrations of each target pesticide. ; The expressions for the daily intake per unit body weight and the effective concentration are as follows: ; In the formula, For target pesticide indexing; Targeted pesticides Measured residual concentration values ​​in soybean samples; This refers to the daily intake of soybeans; For body weight; Targeted pesticides Daily intake per unit of body weight; Targeted pesticides The daily allowable intake; Targeted pesticides The effective concentration.

[0027] S4: Based on the effective concentrations of each pesticide obtained in S3, query the pre-established combined toxicity coefficient lookup table to determine the combined toxicity coefficients corresponding to the current combination of multiple pesticides; S4 specifically includes: S41: Receive the effective concentrations of each target pesticide output by S34, and sort the effective concentrations according to the preset order of target pesticides to form a combination vector of effective pesticide concentrations corresponding to the current soybean sample. S42: Based on the pesticide effective concentration combination vector, extract the concentration ratio relationship between each target pesticide, and use the pesticide type combination and concentration ratio as the joint toxicity query key value. S43: In the pre-established combined toxicity coefficient lookup table, perform a matching search according to the query key value. The combined toxicity coefficient lookup table uses pesticide combination type and corresponding concentration ratio range as index items to store the combined toxicity coefficients that correspond one-to-one with them. S44: When the query key value matches the index item in the combined toxicity coefficient lookup table, the corresponding combined toxicity coefficient is directly read as the combined toxicity coefficient of the current combination of multiple pesticides under the effective concentration conditions. The above steps, by converting the effective concentration combination of each target pesticide into a query key value with clear index rules and performing consistency matching in the pre-established combined toxicity coefficient lookup table, can accurately obtain the combined toxicity coefficient reflecting the intensity of multi-pesticide interaction without introducing additional computational uncertainty, thereby providing a stable and traceable correction basis for the subsequent calculation of the comprehensive weighted combined pollution index.

[0028] S41 specifically includes: SS411: Calls a preset pesticide type order rule table. The rule table arranges all possible target pesticides in a fixed order and assigns a unique serial number label to each target pesticide. The order rule remains consistent during the implementation of the method and does not change with the sample type or concentration. SS412: Read the effective concentration data of the target pesticides detected in the soybean sample obtained from S3, and sort the effective concentration values ​​according to the position of the serial number label in the sequence rule table; SS413: For undetected target pesticide items, insert a placeholder with a value of zero for effective concentration at the corresponding position to ensure that the length of the generated concentration combination vector is consistent with the total number of target pesticides in the sequence list, and that the structure is closed. SS414: Arrange the sorted effective concentration data in a fixed order according to the target pesticides to generate a combination vector of effective pesticide concentrations corresponding to the current soybean sample, which serves as the retrieval input for subsequent joint toxicity queries. The above steps, by introducing a fixed and unchanging order rule for the target pesticides, achieve a standardized representation of the effective pesticide concentration data of different samples in terms of structure and order, avoiding matching failures caused by inconsistent order of pesticide combination key values, and improving the retrieval accuracy and method universality of the joint toxicity query process.

[0029] The steps for establishing the above combined toxicity coefficient lookup table are as follows: First, based on the target pesticide list pre-set in the method, a set of joint toxicity modeling objects is constructed according to the combination relationship of pesticide types. The combination objects are limited to multiple pesticide combination types that are allowed to appear simultaneously in the actual detection scenario. A unique combination identifier is assigned to each combination for subsequent data collection and indexing. Then, for each pesticide combination, based on the dimensionless effective concentration defined in S3, the effective concentration ratio of each pesticide in the combination is divided into several continuous and non-overlapping ratio intervals according to the preset ratio division rules. Each ratio interval corresponds to a certain concentration ratio state, which is used to eliminate the interference of different absolute concentration levels on toxicity determination. Next, after determining the combination type and effective concentration ratio range, for each combination-ratio range pair, the corresponding toxicological experimental data were collected. The experimental data were all based on a unified toxicity endpoint index and evaluation method to ensure that the combined toxicity response results between different combinations were comparable. Subsequently, the toxicity response data of the same pesticide combination and the same effective concentration ratio range were normalized, and the combined toxicity coefficient in single numerical form was determined accordingly. This coefficient was used to quantitatively characterize the intensity of the toxicity interaction of the combination under the condition of the ratio range. The coefficient was kept fixed in the lookup table. Finally, the pesticide combination identifier, effective concentration ratio range and corresponding combined toxicity coefficient are stored in a structured manner to form a combined toxicity coefficient lookup table; the lookup table uses pesticide combination + effective concentration ratio range as the combined index item to support the consistency matching query in step S4.

[0030] S5: Multiply the effective concentrations of each pesticide obtained in S3 with the combined toxicity coefficients obtained in S4, and sum the product results of all target pesticides to calculate the comprehensive weighted combined pollution index of the soybean sample. S5 specifically includes: S51: Receive the effective concentrations of all target pesticides obtained in S3, and receive the combined toxicity coefficients obtained in S4, and use both as input parameters for calculating the combined pollution index of the current sample. S52: Perform a weighted product operation on all effective concentration values ​​and the combined toxicity coefficient to obtain the weighted value of each target pesticide under the current combined toxicity background. ; S53: All weighted values The combined weighted contamination index of the soybean samples is calculated by summing the results. The formula is as follows: In the formula, For the first The effective concentration of the target pesticide; This represents the combined toxicity coefficient of the current pesticide combination at a given concentration ratio. The target number of pesticide types; The comprehensive weighted joint pollution index is used to represent the overall toxicity level of the sample. The above steps, by weighting the effective concentration of each target pesticide with a unified joint toxicity coefficient and summing all weighted results, can quantify the complex synergistic toxicity effect of multiple pesticides into a single index, effectively reflecting the overall residual load and the intensity of toxicity superposition. S6: Compare the comprehensive weighted combined pollution index of S5 with the preset toxicity risk level threshold range to determine the pesticide residue combined toxicity risk level of soybean samples. S6 specifically includes: S61: Receive the comprehensive weighted combined contamination index of the soybean sample calculated by S5. It also calls the preset toxicity risk level threshold interval table, which divides multiple continuous and non-overlapping risk level intervals according to toxicological evaluation standards. S62: Combined Pollution Index The risk level segment is determined by sequentially matching the toxicity risk level threshold range with the range of toxicity risk levels. S63: Based on the matched threshold range, output the pesticide residue combined toxicity risk level label of the current soybean sample as the final judgment result.

[0031] Table 3. Threshold ranges for toxicity risk levels By directly comparing the pollution index risk level ranges defined in Table 3 with the pollution index values ​​of the actual tested samples, quantitative classification and determination of the combined toxicity level of pesticide residues can be achieved, improving the operability of risk assessment and the accuracy of classification and control, and helping to support the implementation of subsequent supervision and traceability management systems.

[0032] This invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. To provide the public with a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments; however, those skilled in the art will fully understand the invention even without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0033] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for quantitative detection of soybean residue toxicity applicable to combined pollution by multiple pesticides, characterized in that, Includes the following steps: S1: Take a representative soybean sample, crush it, and extract it by shaking with an organic solvent to obtain a crude extract containing the target pesticide; then purify the crude extract to obtain a purified sample solution. S2: Inject the purified sample solution into the multi-residue detection instrument and simultaneously analyze and detect multiple preset target pesticides to obtain the instrument response value corresponding to each target pesticide in the purified sample solution. S3: Substitute the instrument response values ​​of each target pesticide into their respective standard curve equations to calculate the measured residual concentration of each target pesticide in the soybean sample; and based on the daily allowable intake safety standard of each target pesticide, convert the measured residual concentration of each pesticide into the effective concentration of each pesticide with comparable toxicity. S4: Based on the effective concentrations of each pesticide obtained in S3, query the pre-established combined toxicity coefficient lookup table to determine the combined toxicity coefficients corresponding to the current combination of multiple pesticides; S5: Multiply the effective concentrations of each pesticide obtained in S3 with the combined toxicity coefficients obtained in S4, and sum the product results of all target pesticides to calculate the comprehensive weighted combined pollution index of the soybean sample. S6: Compare the comprehensive weighted combined pollution index of S5 with the preset toxicity risk level threshold range to determine the pesticide residue combined toxicity risk level of the soybean sample.

2. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 1, is characterized in that... S1 specifically includes: S11: After air-drying a representative soybean sample, grind it to a particle size of less than 0.5 mm, and weigh a preset mass of the pulverized sample and place it in an extraction container; S12: Add a preset volume of organic solvent to the extraction container, seal it, and perform oscillation extraction under preset oscillation frequency and preset oscillation time conditions to transfer the target pesticide from the sample matrix to the solvent phase and obtain the extract. S13: Perform solid-liquid separation on the extract and collect the solvent phase as the crude extract containing the target pesticide; S14: Add the preset purification adsorbent to the crude extract and mix for the preset mixing time to remove pigments, lipids and protein interferences by adsorption. S15: Centrifuge the mixed system and collect the supernatant to obtain the purified sample solution.

3. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 1, is characterized in that... S2 specifically includes: S21: Call the preset multi-pesticide simultaneous detection method parameter configuration file, which includes chromatographic conditions, mass spectrometry parameters and pesticide list information. The parameter configuration file includes quantitative analysis parameters such as retention time window, parent ion and fragment ion information, ion source voltage and collision energy for each target pesticide. S22: Inject the purified sample solution obtained in step S1 into a multi-residue detection instrument equipped with an autosampler, and use gas chromatography-tandem mass spectrometry or liquid chromatography-tandem mass spectrometry equipment to separate the target pesticide on the chromatographic column under the set chromatographic conditions; S23: Based on the completion of chromatographic separation, perform multi-channel parallel detection according to the preset precursor ion-fragment ion pairs of each target pesticide, and record the mass spectrometry peak area of ​​each target pesticide within its predetermined retention time window. S24: Use the mass spectrometry peak area value as the instrument response value of the corresponding target pesticide, and use the target pesticide name as the index number to output a dataset containing the response values ​​of all target pesticides.

4. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 1, is characterized in that... S23 specifically includes: S231: Based on the parameter file configured in step S21, load the parent ion and fragment ion combinations corresponding to each target pesticide, construct a multi-reaction monitoring channel set, and bind each monitoring channel to its corresponding target pesticide. S232: Within the preset retention time window of the target pesticide entering the mass spectrometry detection unit, the monitoring channel corresponding to the target pesticide is called to collect ion signals within a predetermined mass number range and record the response intensity curve within the time window in real time. S233: Integrate the acquired response intensity curves to obtain the total response intensity value of the target pesticide within the predetermined retention time window under the corresponding monitoring channel, and calculate its mass spectrometry peak area as the instrument response value of the target pesticide. .

5. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 1, is characterized in that... S3 specifically includes: S31: Call the standard curve equation library corresponding to each target pesticide. Each standard curve is calibrated and fitted by the instrument response value at a known concentration. S32: Read the instrument response values ​​of each target pesticide obtained in S2, match them to the corresponding standard curve equations, perform inverse calculation, and obtain the measured residual concentration of each target pesticide in the soybean sample. S33: Call the table of acceptable daily intake standards for each target pesticide and read the ADI value specified in the human intake safety assessment of the target pesticide; S34: Convert the measured residual concentration of each target pesticide with its corresponding ADI value to calculate the toxicity intensity, and obtain the effective concentration of each pesticide with comparable toxicity under a unified scale.

6. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 5, is characterized in that... S34 specifically includes: S341: Read the measured residual concentration values ​​of each target pesticide obtained in S32, and establish a residual concentration sequence using the target pesticide identifier; S342: Call the preset population exposure parameter table to obtain the daily intake parameters and body weight parameters of soybeans, and perform exposure dose conversion on the residue concentration sequence to obtain the daily intake per unit body weight of each target pesticide. ; S343: Call the daily acceptable intake standard table obtained in S33, and read the daily acceptable intake corresponding to each target pesticide. and will and The ratios are converted under the same dimensions, and the resulting ratios are recorded as the effective concentrations of each target pesticide. .

7. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 1, is characterized in that... S4 specifically includes: S41: Receive the effective concentrations of each target pesticide output by S34, and sort the effective concentrations according to the preset order of target pesticides to form a combination vector of effective pesticide concentrations corresponding to the current soybean sample. S42: Based on the pesticide effective concentration combination vector, extract the concentration ratio relationship between each target pesticide, and use the pesticide type combination and concentration ratio as the joint toxicity query key value. S43: Perform a matching search according to the query key value in the pre-established combined toxicity coefficient query table; S44: When the query key value matches the index item in the combined toxicity coefficient lookup table, the corresponding combined toxicity coefficient is directly read and used as the combined toxicity coefficient of the current combination of multiple pesticides under the effective concentration conditions.

8. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 7, is characterized in that... S41 specifically includes: SS411: Calls the preset pesticide type order rule table, which arranges all possible target pesticides in a fixed order and assigns a unique serial number label to each target pesticide; SS412: Read the effective concentration data of the target pesticides detected in the soybean sample obtained from S3, and sort the effective concentration values ​​according to the position of the serial number label in the sequence rule table; SS413: For target pesticide items that are not detected, insert a placeholder with a value of zero for the effective concentration at the corresponding position; SS414: Arranges the sorted effective concentration data in a fixed order according to the target pesticides, and generates a combination vector of effective pesticide concentrations corresponding to the current soybean sample, which serves as the retrieval input for subsequent joint toxicity queries.

9. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 1, is characterized in that... S5 specifically includes: S51: Receive the effective concentrations of all target pesticides obtained in S3, and receive the combined toxicity coefficients obtained in S4, and use both as input parameters for calculating the combined pollution index of the current sample. S52: Perform a weighted product operation on all effective concentration values ​​and the combined toxicity coefficient to obtain the weighted value of each target pesticide under the current combined toxicity background. ; S53: All weighted values The combined weighted contamination index of the soybean samples is calculated by summing the results. The formula is as follows: In the formula, For the first The effective concentration of the target pesticide; This represents the combined toxicity coefficient of the current pesticide combination at a given concentration ratio. The target number of pesticide types; This is a comprehensive weighted joint pollution index.

10. The method for quantitative detection of soybean residue toxicity in cases of combined pollution by multiple pesticides, as described in claim 9, is characterized in that... S6 specifically includes: S61: Receive the comprehensive weighted combined contamination index of the soybean sample calculated by S5. It also calls a preset toxicity risk level threshold interval table, which is divided into multiple continuous and non-overlapping risk level intervals according to toxicological evaluation standards. S62: Combined Pollution Index The risk level segment is determined by sequentially matching the toxicity risk level threshold range with the range of toxicity risk levels. S63: Based on the matched threshold range, output the pesticide residue combined toxicity risk level label of the current soybean sample as the final judgment result.

Images