Forward and reverse mass spectrum similarity matching method based on weighted characteristic peak quality accuracy

Abstract

The invention relates to the technical field of analytical chemistry and information processing, in particular to a weighted characteristic peak quality accuracy-based forward and reverse mass spectrogram similarity matching method, which is suitable for high-throughput screening of risk substances in food safety detection, and comprises the following steps: acquiring mass spectrogram data to be queried and standard mass spectrogram data in a database; fragment ions with the peak intensity ranked in the first 7 or larger than or equal to 10 in the mass spectrum to be inquired and the standard mass spectrum are selected; judging whether the m / z difference value of fragment ions in the mass spectrum to be queried and the standard mass spectrum is less than or equal to 5ppm or not; calculating a forward matching degree score of the to-be-queried mass spectrum and the standard mass spectrum, and a reverse matching degree score of the standard mass spectrum and the to-be-queried mass spectrum; calculating a mean value according to the forward matching degree score and the reverse matching degree score; the average value is output as the similarity score of the mass spectrum to be queried and the standard mass spectrum, and the possibility that the screening result shows false negative is greatly reduced by considering the quality accuracy of fragment ions.

Description

Technical Field

[0001] The present invention relates to the technical fields of analytical chemistry and information processing, and particularly relates to a method for matching the similarity of forward and reverse mass spectra based on the mass accuracy of weighted characteristic peaks, which is applicable to high-throughput screening of risk substances in food safety detection. Background Art

[0002] In the quality and safety detection of products such as feed, vegetables, livestock, poultry, eggs, and milk, there are a wide variety of risk substances. The current detection methods mainly rely on high-throughput mass spectrometry detection. In high-throughput detection, the risk substances in the sample are mainly screened based on the matching of the sample with the compounds in the database. After the compound is analyzed by high-resolution mass spectrometry, the primary and secondary fragment information of the compound can be obtained. After analyzing multiple compound standards, a standard compound database can be obtained. After the sample is analyzed, a large amount of primary and secondary fragment information of the compound can be obtained. By matching with the data in the database, it can be screened whether the sample contains the compounds in the database.

[0003] However, traditional Euclidean distance algorithms, cosine similarity, weighted dot product similarity algorithms, etc. do not consider the mass accuracy of the compound secondary fragments. For high-resolution mass spectrometry, the mass accuracy of secondary fragments can mostly reach 10 ppm. For example, the data in the database is m / z = 356.117, relative peak intensity = 80, and the two data in the sample are m / z = 356.115, relative peak intensity = 50 and m / z = 356.110, relative peak intensity = 70 respectively. In traditional algorithms, both mass spectra in the sample are similar to the mass spectrum in the database, but in fact, the compound with m / z = 356.110 and relative peak intensity = 70 is not the same compound as the compound in the database. Traditional similarity matching methods are prone to false negatives in screening results, affecting the accuracy of detection.

[0004] In order to identify unknown compounds in a sample, the computer calculates the similarity between the measured mass spectrum of the unknown compound and the mass spectra in the standard reference library, thereby determining the unknown compound. Residual veterinary drugs, pesticides, and mycotoxins in feed have a great impact on the growth of livestock and poultry, and even cause poisoning. After these livestock and poultry containing mycotoxin residues are consumed by humans, the drugs will accumulate in the body and cannot be excreted in time. When the toxicity accumulates to a certain stage, it will cause pathological reactions in the human body. The traditional multiple reaction monitoring (MRM) method is a target-based method and cannot be applied to the detection of non-target compounds or unknown compounds, while high-resolution mass spectrometry can collect both target and non-target mass spectrometry data in the full-scan mode. Therefore, a new method for matching the similarity of mass spectra is needed to improve the accuracy of risk substance screening. Summary of the Invention

[0005] The object of the present invention is to provide a method for matching the similarity of forward and reverse mass spectra based on the mass accuracy of weighted characteristic peaks. This method takes into account the mass accuracy of fragment ions during mass spectrum matching, and also considers that different intensities of fragment ions have different effects on the similarity of mass spectra. It calculates the similarity of spectra according to the qualitative conditions of compounds, thereby improving the accuracy and reliability of screening for risk substances.

[0006] The object of the present invention is to provide 1. A method for matching the similarity of forward and reverse mass spectra based on the mass accuracy of weighted characteristic peaks, which is characterized by including:

[0007] An acquisition step of acquiring the mass spectrum data to be queried and the standard mass spectrum data in the database;

[0008] A processing step, including: selecting the fragment ions with the top 7 in peak intensity or peak intensity ≥ 10 in the mass spectrum to be queried and the standard mass spectrum; judging whether the difference in m / z of the fragment ions in the mass spectrum to be queried and the standard mass spectrum is ≤ 5 ppm; calculating the forward matching degree score of the mass spectrum to be queried and the standard mass spectrum, and the reverse matching degree score of the standard mass spectrum and the mass spectrum to be queried; calculating the mean value according to the forward matching degree score and the reverse matching degree score;

[0009] An output step of outputting the mean value as the similarity score of the mass spectrum to be queried and the standard mass spectrum.

[0010] Preferably, the calculation of the forward matching degree score of the mass spectrum to be queried and the standard mass spectrum specifically includes:

[0011] Normalizing the peak intensity of the selected fragment ions in the mass spectrum to be queried to obtain the normalized peak intensity;

[0012] Normalizing the peak intensity of the selected fragment ions in the standard mass spectrum to obtain the normalized peak intensity;

[0013] Calculating the relative difference between the normalized peak intensity of each fragment ion in the mass spectrum to be queried and the normalized peak intensity of the corresponding fragment ion in the standard mass spectrum;

[0014] Determining the peak matching degree score K according to the relative difference;

[0015] Calculating the forward matching degree score based on the normalized peak intensity, the relative difference, and the peak matching degree score K.

[0016] Preferably, the calculation of the reverse matching degree score of the standard mass spectrum and the mass spectrum to be queried specifically includes:

[0017] Normalize the peak intensities of the selected fragment ions in the standard mass spectrum to obtain normalized peak intensities;

[0018] Normalize the peak intensities of the selected fragment ions in the mass spectrum to be queried to obtain normalized peak intensities;

[0019] Calculate the relative differences between the normalized peak intensities of each fragment ion in the standard mass spectrum and the normalized peak intensities of the corresponding fragment ions in the mass spectrum to be queried;

[0020] Determine the peak matching degree score K according to the relative differences;

[0021] Calculate the reverse matching degree score based on the normalized peak intensities, the relative differences, and the peak matching degree score K.

[0022] Preferably, the determining the peak matching degree score K according to the relative differences specifically includes:

[0023] When the relative difference is less than or equal to 0.2, the peak matching degree score K is 100;

[0024] When the relative difference is greater than 0.2 and less than 0.8, the peak matching degree score K is -100×the relative difference + 120;

[0025] When the relative difference is greater than or equal to 0.8, the peak matching degree score K is 40.

[0026] Preferably, the formula for calculating the forward matching degree score is:

[0027] Forward matching degree score = Σ ;

[0028] where X1 is the normalized peak intensity of the first fragment ion in the matched database, and K is the peak matching degree score.

[0029] Preferably, the formula for calculating the reverse matching degree score is:

[0030] Reverse matching degree score = Σ ;

[0031] where, is the normalized peak intensity of the first fragment ion in the input data, and K is the peak matching degree score.

[0032] Preferably, the formula for calculating the mean value according to the forward matching degree score and the reverse matching degree score is:

[0033] Similarity score = (forward matching degree score + reverse matching degree score) / 2.

[0034] Preferably, the method is used for screening risk substances in products such as food, feed, vegetables, livestock and poultry, eggs and milk, and the risk substances include at least one of veterinary drugs, pesticides, and mycotoxins.

[0035] Preferably, before obtaining the mass spectrometry data to be queried, it further includes:

[0036] Pretreating the sample to extract the possible risk substances;

[0037] Sending the pretreated sample into a high-resolution mass spectrometer for detection to obtain the original mass spectrometry data;

[0038] Processing the original mass spectrometry data to obtain the mass spectrometry data to be queried.

[0039] Preferably, after the output step, it further includes:

[0040] Comparing the similarity score with a preset threshold;

[0041] When the similarity score is higher than the preset threshold, it is determined that the compound corresponding to the standard mass spectrometry diagram is contained in the mass spectrometry diagram to be queried.

[0042] The beneficial effects of the present invention include:

[0043] 1. By considering the mass accuracy of fragment ions, the possibility of false negatives in the screening results is greatly reduced;

[0044] 2. Through the forward and reverse bidirectional matching mechanism, a more comprehensive similarity evaluation is provided, enhancing the reliability of the matching;

[0045] 3. Through the selective peak inclusion strategy, focusing on the discriminative characteristic peaks, the calculation efficiency and accuracy are improved;

[0046] 4. Through the adaptive peak matching scoring mechanism, differential processing is provided for different degrees of peak intensity differences, making the similarity calculation more accurate;

[0047] 5. It is particularly suitable for high-resolution mass spectrometry data, making full use of the technical advantages of modern mass spectrometry instruments;

[0048] 6. It can be effectively applied to the high-throughput screening of food safety risk substances, improving the comprehensiveness and accuracy of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is the overall flowchart of the forward and reverse mass spectrometry diagram similarity matching method based on the weighted characteristic peak mass accuracy;

[0050] Figure 2 It is the flowchart of mass spectrometry diagram similarity calculation;

[0051] Figure 3 Flow chart for determining the peak matching degree score K Detailed implementation manners

[0052] Please refer to the appended Figures 1-3 , and the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments

[0053] The technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention

[0054] The method for matching the similarity of the forward and reverse mass spectra based on the weighted characteristic peak mass accuracy proposed by the present invention includes an acquisition step, a processing step, and an output step

[0055] In the acquisition step, the present invention acquires the mass spectrum data to be queried and the standard mass spectrum data in the database. Preferably, the mass spectrum data to be queried comes from the data obtained after high-resolution mass spectrometry analysis of the sample to be detected, and the standard mass spectrum data is the data in a pre-established mass spectrometry database containing known risk substances

[0056] In the processing step, first select the fragment ions with the top 7 peak intensities or peak intensities ≥ 10 in the mass spectrum to be queried and the standard mass spectrum. In the embodiments of the present invention, these fragment ions are selected because the fragment ions with higher peak intensities usually have higher signal-to-noise ratios and better stabilities, and can provide more reliable matching information. Selecting the top 7 peak intensities is based on empirical values. In practical applications, it has been found that usually, the first 7 peaks with the highest intensities already contain the main characteristic information of the compound. The threshold of selecting peak intensities ≥ 10 is considered because the peaks below this value may be greatly affected by background noise and have low reliability

[0057] Next, determine whether the difference in m / z of the fragment ions in the mass spectrum to be queried and the standard mass spectrum is ≤ 5 ppm. Here, 5 ppm is determined based on the mass accuracy characteristics of modern high-resolution mass spectrometry instruments. Generally speaking, the mass accuracy of high-resolution mass spectrometry instruments can reach 10 ppm. Selecting 5 ppm as the judgment standard can ensure the matching accuracy while taking into account a certain degree of flexibility and avoiding false exclusions caused by instrument measurement errors

[0058] Then, calculate the forward matching degree score between the mass spectrum to be queried and the standard mass spectrum, as well as the reverse matching degree score between the standard mass spectrum and the mass spectrum to be queried. The present invention adopts a two-way matching mechanism, which not only considers the matching degree of the mass spectrum to be queried to the standard mass spectrum (forward), but also considers the matching degree of the standard mass spectrum to the mass spectrum to be queried (reverse). This two-way matching can more comprehensively evaluate the similarity between the two mass spectra.

[0059] Finally, calculate the mean value based on the forward matching degree score and the reverse matching degree score to obtain the final similarity score.

[0060] In the output step, output the mean value as the similarity score between the mass spectrum to be queried and the standard mass spectrum. This similarity score is an important indicator for evaluating the matching degree of two mass spectra and can be used for subsequent substance identification and risk assessment.

[0061] The method for calculating the forward matching degree score. This method first normalizes the peak intensities of the fragment ions selected in the mass spectrum to be queried and the standard mass spectrum respectively to obtain the normalized peak intensities. The purpose of the normalization process is to eliminate the influence caused by different total intensities between different mass spectra and make the comparison of peak intensities more reasonable. Preferably, the normalization process can be achieved by dividing the intensity of each peak by the sum of the intensities of all selected peaks.

[0062] Next, calculate the relative difference between the normalized peak intensity of each fragment ion in the mass spectrum to be queried and the normalized peak intensity of the corresponding fragment ion in the standard mass spectrum. The relative difference is represented by the formula where is the normalized peak intensity of the fragment ion in the mass spectrum to be queried, and is the normalized peak intensity of the corresponding fragment ion in the standard mass spectrum.

[0063] Determine the peak matching degree score K according to the relative difference. The peak matching degree score K is a piecewise function set based on the size of the relative difference and is used to give different evaluations to different degrees of peak intensity differences. The specific piecewise function will be described in detail later.

[0064] Finally, calculate the forward matching degree score based on the normalized peak intensity, the relative difference, and the peak matching degree score K. The calculation formula will be described in detail later.

[0065] Similarly, the method for calculating the reverse matching degree score is similar to the method for calculating the forward matching degree score, except that the roles are swapped: the standard mass spectrum is used as the query source, and the mass spectrum to be queried is used as the reference object. First, the peak intensities of the selected fragment ions in the standard mass spectrum and the mass spectrum to be queried are normalized respectively, then the relative difference between the normalized peak intensity of each fragment ion in the standard mass spectrum and the normalized peak intensity of the corresponding fragment ion in the mass spectrum to be queried is calculated, the peak matching degree score K is determined according to the relative difference, and finally the reverse matching degree score is calculated.

[0066] The method for determining the peak matching degree score K according to the relative difference is specifically as follows: when the relative difference is less than or equal to 0.2, the peak matching degree score K is 100. This means that when the intensities of the corresponding peaks in the two spectra are very close (the difference does not exceed 20%), it is considered a high-quality match and the highest score is given. When the relative difference is greater than 0.2 and less than 0.8, the peak matching degree score K is -100×relative difference + 120. This is a linear attenuation function, and as the difference increases, the score gradually decreases. When the relative difference is greater than or equal to 0.8, the peak matching degree score K is 40. This indicates that when the difference is very large, the matching quality is considered low, but a basic score is still given because even if the peak intensity difference is large, it may still be fragments from the same compound.

[0067] The selection of 0.2 and 0.8 as the cut-off points is determined based on a large amount of experimental data and professional experience. Generally speaking, when the relative difference in peak intensity is less than 20%, it can be considered a very good match; when the difference is between 20% - 80%, the matching quality decreases linearly with the increase of the difference; when the difference exceeds 80%, although the matching quality is low, it may still have certain reference value.

[0068] The calculation formula for the forward matching degree score:

[0069] Forward matching degree score ;

[0070] where is the normalized peak intensity of the first fragment ion matched in the database, is the normalized peak intensity of the corresponding fragment ion in the standard mass spectrum, is the peak matching degree score. In this formula, represents the weight ratio of this peak among all the selected peaks, is the score determined according to the relative difference. This formula comprehensively considers the weight of the fragment ion, the relative difference, and the matching quality, and can more comprehensively evaluate the spectrum matching degree.

[0071] Similarly, the calculation formula for the reverse matching degree score:

[0072] Reverse matching degree score ;

[0073] Among them, is the normalized peak intensity of the first fragment ion in the input data, is the normalized peak intensity of the corresponding fragment ion in the mass spectrum to be queried, is the peak matching degree score. This formula is consistent with the calculation formula idea of the forward matching degree score, except that the roles are reversed.

[0074] Formula for calculating the final similarity score based on the forward matching degree score and the reverse matching degree score:

[0075] Similarity score = (forward matching degree score + reverse matching degree score) / 2

[0076] The arithmetic mean of the forward matching degree score and the reverse matching degree score is used as the final similarity score. This processing method takes into account the results of bidirectional matching and can more comprehensively evaluate the similarity between mass spectra.

[0077] Specifically, the method is as follows:

[0078] Similarity = peak ratio * peak matching degree (forward) + peak ratio * peak matching degree (reverse)

[0079] Peak matching degree (K):

[0080] When 0 ≤ ≤ 0.2, or 0 ≤ ≤ 0.2, K = 100;

[0081] When 0.2 < ≤ 0.8, or 0.2 ≤ ≤ 0.8, K = -100 × + 120;

[0082] When > 0.8, or > 0.8, K = 40;

[0083] ;

[0084] X1 is the normalized peak intensity of the first fragment ion in the matched database, is the normalized peak intensity of the first fragment ion in the input data.

[0085] Match the original data obtained from the mass spectrum with the data in the database. If the similarity is higher than the set threshold, it is considered that a suspicious risk substance has been detected.

[0086] The method of the present invention can be used for screening risk substances in products such as food, feed, vegetables, livestock and poultry, eggs and milk, and the risk substances include at least one of veterinary drugs, pesticides, and mycotoxins. There are a wide variety of risk substances in these fields. By the method of the present invention, the screening accuracy of these substances can be improved, and food safety can be guaranteed.

[0087] Before obtaining the mass spectrometry data to be queried, it is first necessary to pretreat the sample to extract the possible risk substances. Preferably, the pretreatment method can select an appropriate extraction method according to the characteristics of the substance to be detected, such as liquid-liquid extraction, solid-phase extraction, etc. Then, the pretreated sample is sent to a high-resolution mass spectrometer for detection to obtain the original mass spectrometry data. Finally, the original mass spectrometry data is processed, such as denoising, peak extraction, etc., to obtain the mass spectrometry data to be queried.

[0088] After the similarity score is output, first compare the similarity score with a preset threshold. The selection of the preset threshold depends on the specific application scenario and the tolerance for false positives / false negatives. Usually, the threshold can be set between 80-90. A higher threshold will reduce false positives but may increase false negatives, and a lower threshold will have the opposite effect. When the similarity score is higher than the preset threshold, it is determined that the compound corresponding to the standard mass spectrometry is contained in the mass spectrometry to be queried. This determination result can be used for subsequent risk assessment and processing.

[0089] The following illustrates the implementation process of the present invention through a specific embodiment:

[0090] In this embodiment, the method of the present invention is used to screen for possible antibiotic residues in feed samples.

[0091] First, take 5 g of feed sample, add an appropriate amount of extraction solvent (such as a mixed solution of acetonitrile / water), ultrasonically extract for 30 minutes, and after centrifugation, take the supernatant for filtration to obtain a pretreated sample.

[0092] Inject the pretreated sample into a high-resolution mass spectrometer (such as a quadrupole-time-of-flight mass spectrometer Q-TOF) for detection in the full scan mode, and collect the first-order and second-order mass spectrometry data. Process the original mass spectrometry data, such as removing background noise, peak extraction, etc., to obtain the mass spectrometry data to be queried.

[0093] At the same time, prepare a mass spectrometry database containing common antibiotic standards as a reference.

[0094] Select the top 7 fragment ions in terms of peak intensity or fragment ions with a peak intensity ≥10 from the mass spectrometry to be queried and the standard mass spectrometry respectively. For example, assume that the following fragment ions (m / z and normalized peak intensity) are selected from the mass spectrometry to be queried:

[0095] (356.115, 100), (158.072, 85), (114.055, 70), (256.195, 50),(328.140, 40), (200.108, 35), (285.125, 25);

[0096] While in the standard mass spectrum (such as the standard spectrum of enrofloxacin), the following fragment ions are selected:

[0097] (356.117, 100), (158.070, 90), (114.056, 65), (256.190, 55),(328.145, 45), (200.105, 30), (285.130, 20);

[0098] Judge whether the difference in m / z of the fragment ions between the mass spectrum to be queried and the standard mass spectrum is ≤ 5 ppm. Calculate the difference in m / z of each pair of corresponding fragment ions:

[0099] The difference between 356.115 and 356.117 is approximately 5.6 ppm (exceeding the threshold, not matching);

[0100] The difference between 158.072 and 158.070 is approximately 12.7 ppm (exceeding the threshold, not matching);

[0101] The difference between 114.055 and 114.056 is approximately 8.8 ppm (exceeding the threshold, not matching); ...

[0103] (And so on to calculate the differences of other corresponding fragment ions);

[0104] Suppose after judgment, there are 4 pairs of fragment ions with m / z differences ≤ 5 ppm, and these fragment ions are used for subsequent similarity calculation.

[0105] Calculate the forward matching degree score: For each pair of matching fragment ions, calculate the relative difference and determine the peak matching degree score K, and then calculate the score according to the formula. Suppose the calculated forward matching degree score is 85.

[0106] Calculate the reverse matching degree score: Similarly, calculate the reverse matching degree score, and suppose the obtained score is 80.

[0107] Calculate the similarity score: (85 + 80) / 2 = 82.5.

[0108] Compare the similarity score 82.5 with the preset threshold (such as 80). Since 82.5 > 80, it is determined that the mass spectrum to be queried contains the compound corresponding to the standard mass spectrum, that is, it is determined that there is enrofloxacin residue in the sample.

[0109] Through the above steps, the method of the present invention can accurately determine whether a specific risk substance is contained in a sample, greatly improving the accuracy and reliability of screening.

[0110] Those skilled in the art should understand that the present invention is not limited to the specific embodiments described above, and various changes and modifications can be made without departing from the concept of the present invention, and these changes and modifications should all be within the protection scope of the present invention. For example, the criteria for fragment ion selection, the threshold of the m / z difference, the parameters of the peak matching degree scoring function, etc. can be adjusted according to specific application scenarios to optimize the performance and adaptability of the method.

Claims

1. A method for matching similarity of forward and reverse mass spectra based on weighted characteristic peak mass accuracy, characterized in that: include: An acquisition step, acquiring the mass spectrum data to be queried and standard mass spectrum data in a database; The processing steps include: selecting the fragment ions with the top 7 peak intensities or the peak intensities ≥10 in the mass spectrum to be queried and the standard mass spectrum; judging whether the difference of the m / z of the fragment ions in the mass spectrum to be queried and the standard mass spectrum is ≤5ppm; calculating the forward matching score between the mass spectrum to be queried and the standard mass spectrum, and the reverse matching score between the standard mass spectrum and the mass spectrum to be queried; and calculating the mean according to the forward matching score and the reverse matching score; The output step is to output the mean value as a similarity score between the mass spectrum to be queried and the standard mass spectrum.

2. The method according to claim 1, characterized in that The calculating of the forward matching score between the mass spectrum to be queried and the standard mass spectrum specifically includes: Normalizing the peak intensities of the fragment ions selected from the mass spectrum to be queried to obtain normalized peak intensities; Normalizing the peak intensities of the fragment ions selected from the standard mass spectrum to obtain normalized peak intensities; Calculating the relative difference between the normalized peak intensity of each fragment ion in the mass spectrum to be queried and the normalized peak intensity of the corresponding fragment ion in the standard mass spectrum; Determine a peak matching score K according to the relative difference; The forward matching score is calculated based on the normalized peak intensity, the relative difference and the peak matching score K.

3. The method according to claim 1, characterized in that The calculating of the reverse matching score between the standard mass spectrum and the mass spectrum to be queried specifically includes: Normalizing the peak intensities of the fragment ions selected from the standard mass spectrum to obtain normalized peak intensities; Normalizing the peak intensities of the fragment ions selected from the mass spectrum to be queried to obtain normalized peak intensities; Calculating the relative difference between the normalized peak intensity of each fragment ion in the standard mass spectrum and the normalized peak intensity of the corresponding fragment ion in the mass spectrum to be queried; Determine a peak matching score K according to the relative difference; The reverse matching score is calculated based on the normalized peak intensity, the relative difference and the peak matching score K.

4. The method according to claim 2 or 3, characterized in that: Determining the peak matching score K according to the relative difference specifically includes: When the relative difference is less than or equal to 0.2, the peak matching score K is 100; When the relative difference is greater than 0.2 and less than 0.8, the peak matching score K is -100×the relative difference+120; When the relative difference is greater than or equal to 0.8, the peak matching score K is 40.

5. The method according to claim 2, characterized in that: The calculation formula of the positive matching score is: Positive matching score = Σ[ ]; Wherein, X1 is the normalized peak intensity of the first fragment ion in the matched database, and K is the peak matching score.

6. The method according to claim 3, characterized in that The calculation formula of the reverse matching score is: Reverse matching score = Σ[ ]; in, is the normalized peak intensity of the first fragment ion in the input data, and K is the peak matching score.

7. The method according to claim 1, characterized in that The formula for calculating the mean value based on the forward matching score and the reverse matching score is: Similarity score = (forward match score + reverse match score) / 2.

8. The method according to claim 1, characterized in that The method is used for screening risk substances in food, feed, vegetables, livestock and poultry, eggs, milk and other products, and the risk substances include at least one of veterinary drugs, pesticides and mycotoxins.

9. The method according to claim 1, characterized in that: Before obtaining the mass spectrum data to be queried, the method further includes: Pre-treat samples to extract possible risk substances; The pre-treated sample is sent to a high-resolution mass spectrometer for detection to obtain raw mass spectrum data; The original mass spectrum data is processed to obtain the mass spectrum data to be queried.

10. The method according to claim 1, characterized in that After the output step, the method further includes: comparing the similarity score with a preset threshold; When the similarity score is higher than the preset threshold, it is determined that the mass spectrum to be queried contains a compound corresponding to the standard mass spectrum.

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