Similarity matching method of forward and reverse mass spectra based on weighted characteristic peak mass accuracy

Abstract

The present invention relates to the field of analytical chemistry and information processing technology, and in particular to a method for matching similarities of forward and reverse mass spectra based on weighted characteristic peak mass accuracy, which is suitable for high-throughput screening of risk substances in food safety testing. The method comprises the following steps: obtaining mass spectrum data to be queried and standard mass spectrum data in a database; selecting fragment ions with peak intensities ranked in the top 7 or with peak intensities ≥10 in the mass spectrum to be queried and the standard mass spectrum; judging whether the difference in m / z of the fragment ions between the mass spectrum to be queried and the standard mass spectrum is ≤5ppm; calculating a forward matching score between the mass spectrum to be queried and the standard mass spectrum, and a reverse matching score between the standard mass spectrum and the mass spectrum to be queried; calculating a mean value based on the forward matching score and the reverse matching score; and outputting the mean value as a similarity score between the mass spectrum to be queried and the standard mass spectrum. By considering the mass accuracy of the fragment ions, the possibility of a false negative in the screening result is greatly reduced.

Description

Technical Field

[0001] The present invention relates to the fields of analytical chemistry and information processing technology, and in particular to a method for matching similarities of forward and reverse mass spectra based on weighted characteristic peak mass accuracy, which is suitable for high-throughput screening of risk substances in food safety testing. Background Art

[0002] In the quality and safety testing of feed, vegetables, livestock, poultry, eggs, and milk, a wide variety of risk substances are detected. Current detection methods primarily rely on high-throughput mass spectrometry. In high-throughput testing, samples are screened for risk substances based on matching them with compounds in a database. High-resolution mass spectrometry analysis of compounds yields primary and secondary fragment information. Analysis of multiple compound standards yields a database of standard compounds. Sample analysis yields primary and secondary fragment information for a large number of compounds. By matching this information with the database, samples can be screened for compounds listed in the database.

[0003] However, traditional algorithms such as Euclidean distance, cosine similarity, and weighted dot-product similarity fail to account for the mass accuracy of secondary fragments. For high-resolution mass spectrometry, the mass accuracy of secondary fragments can typically reach 10 ppm. For example, if a database contains data with m / z = 356.117 and a relative peak intensity of 80, and two data points in a sample are m / z = 356.115 and a relative peak intensity of 50, and m / z = 356.110 and a relative peak intensity of 70, respectively, traditional algorithms will find both mass spectra in the sample similar to the database mass spectrum. However, the compound with m / z = 356.110 and a relative peak intensity of 70 is not the same compound in the database. Traditional similarity matching methods can easily lead to false negatives in screening results, compromising detection accuracy.

[0004] To identify unknown compounds in a sample, a computer calculates the similarity between the mass spectrum of the measured unknown compound and the mass spectra in a standard reference library, thereby determining the unknown compound. Veterinary drug and pesticide residues in feed, as well as the mycotoxins produced, have a significant impact on the growth of livestock and poultry, and can even cause poisoning. When these livestock and poultry containing mycotoxin residues are consumed by humans, the drugs accumulate in the body and cannot be excreted in time. When the toxicity accumulates to a certain level, it can cause pathological reactions in the human body. Traditional multiple reaction monitoring (MRM) methods are target-based and cannot be applied to the detection of non-target compounds or unidentified compounds. High-resolution mass spectrometry, however, can simultaneously collect target and non-target mass spectral data in full-scan mode. Therefore, a new mass spectrum similarity matching method is needed to improve the accuracy of risk substance screening. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for matching the similarity of forward and reverse mass spectra based on weighted characteristic peak mass accuracy. This method takes into account the mass accuracy of fragment ions during mass spectrum matching, and the different effects of different fragment ion intensities on mass spectrum similarity. The similarity of the spectra is calculated according to the qualitative conditions of the compounds, thereby improving the accuracy and reliability of risk substance screening.

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

[0007] an acquisition step, acquiring the mass spectrum data to be queried and standard mass spectrum data in a database;

[0008] The processing steps include: selecting fragment ions with peak intensities ranked in the top 7 or with peak intensities ≥10 in the mass spectrum to be queried and the standard mass spectrum; determining 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 a forward matching score between the mass spectrum to be queried and the standard mass spectrum, and a reverse matching score between the standard mass spectrum and the mass spectrum to be queried; and calculating an average based on the forward matching score and the reverse matching score.

[0009] The output step outputs the mean as a similarity score between the mass spectrum to be queried and the standard mass spectrum.

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

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

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

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

[0014] Determine a peak matching score K based on the relative difference;

[0015] The forward matching score is calculated based on the normalized peak intensity, the relative difference and the peak matching score K.

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

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

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

[0019] 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 query mass spectrum;

[0020] Determine a peak matching score K based on the relative difference;

[0021] The reverse matching score is calculated based on the normalized peak intensity, the relative difference and the peak matching score K.

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

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

[0024] 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;

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

[0026] Preferably, the calculation formula for the positive matching score is:

[0027] Positive matching score = Σ[ ];

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

[0029] Preferably, the calculation formula of the reverse matching score is:

[0030] Reverse matching score = Σ[ ];

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

[0032] Preferably, the formula for calculating the mean value based on the forward matching score and the reverse matching score is:

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

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

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

[0036] Pre-process samples to extract possible risk substances;

[0037] The pre-treated sample is sent to a high-resolution mass spectrometer for detection to obtain raw mass spectrum data;

[0038] The original mass spectrum data is processed to obtain the mass spectrum data to be queried.

[0039] Preferably, after the output step, the method further comprises:

[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 query mass spectrum contains a compound corresponding to the standard mass spectrum.

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

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

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

[0045] 3. Through the selective peak inclusion strategy, we focus on the characteristic peaks with discriminative power, thus improving the computational efficiency and accuracy;

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

[0047] 5. 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 high-throughput screening of food safety risk substances to improve the comprehensiveness and accuracy of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 The figure is the overall flow chart of the forward and reverse mass spectrum similarity matching method based on weighted characteristic peak mass accuracy;

[0050] Figure 2 Flowchart for mass spectrum similarity calculation;

[0051] Figure 3 Flowchart for determining the peak matching score K. DETAILED DESCRIPTION

[0052] Please refer to the attached Figure 1-3 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 with reference to specific embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0054] The invention proposes a forward and reverse mass spectrum similarity matching method based on weighted characteristic peak mass accuracy, which includes an acquisition step, a processing step and an output step.

[0055] In the acquisition step, the present invention obtains the mass spectrum data to be queried and the standard mass spectrum data in the database. Preferably, the mass spectrum data to be queried is data obtained from the sample to be tested after high-resolution mass spectrometry analysis, and the standard mass spectrum data is data from a pre-established mass spectrum 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 an embodiment of the present invention, these fragment ions are selected because fragment ions with higher peak intensities generally have higher signal-to-noise ratios and better stability, and can provide more reliable matching information. The selection of the top 7 peak intensities is based on empirical values. In actual applications, it is found that, under normal circumstances, the top 7 peaks with the highest intensities already contain the main characteristic information of the compound. The threshold value of selecting a peak intensity ≥10 is based on the consideration that peaks below this value may be greatly affected by background noise and have lower reliability.

[0057] Next, a determination is made as to whether the m / z difference between the fragment ions in the query mass spectrum and the reference mass spectrum is ≤5 ppm. The 5 ppm value here is based on the mass accuracy characteristics of modern high-resolution mass spectrometers. Generally, high-resolution mass spectrometers can achieve mass accuracy of 10 ppm. Selecting 5 ppm as the criterion ensures matching accuracy while maintaining a certain degree of flexibility to avoid false exclusions due to instrumental measurement errors.

[0058] Next, a forward matching score is calculated between the query mass spectrum and the reference mass spectrum, as well as a reverse matching score between the reference mass spectrum and the query mass spectrum. This bidirectional matching mechanism considers both the forward matching of the query spectrum to the reference spectrum and the reverse matching of the reference spectrum to the query spectrum. This bidirectional matching allows for a more comprehensive assessment of the similarity between the two spectra.

[0059] Finally, the average of the forward matching score and the reverse matching score is calculated to obtain a final similarity score.

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

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

[0062] Next, calculate the relative difference between the normalized peak intensity of each fragment ion in the query mass spectrum and the normalized peak intensity of the corresponding fragment ion in the standard mass spectrum. The relative difference is expressed as Indicates that is the normalized peak intensity of the fragment ion in the mass spectrum to be queried, is the normalized peak intensity of the corresponding fragment ion in the standard mass spectrum.

[0063] The peak matching score K is determined based on the relative difference. The peak matching score K is a piecewise function based on the relative difference, used to evaluate peak intensity differences of varying magnitude. The specific piecewise function is described in detail later.

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

[0065] Similarly, the method for calculating the reverse match score is similar to the method for calculating the forward match score, except that the roles are reversed: the standard mass spectrum serves as the query source, and the query mass spectrum serves as the reference. The peak intensities of the selected fragment ions in the standard mass spectrum and the query mass spectrum are first normalized. 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 query mass spectrum is then calculated. The peak match score K is determined based on this relative difference, and the reverse match score is finally calculated.

[0066] The peak match score K is determined based on relative difference. Specifically, when the relative difference is less than or equal to 0.2, the peak match score K is 100. This means that when the intensities of corresponding peaks in the two spectra are very close (difference of no more than 20%), it is considered a high-quality match and is given the highest score. When the relative difference is greater than 0.2 and less than 0.8, the peak match score K is -100 × relative difference + 120. This is a linear decay function, with the score gradually decreasing as the difference increases. When the relative difference is greater than or equal to 0.8, the peak match score K is 40. This means that when the difference is very large, the match quality is considered low, but a basic score is still given, because even large differences in peak intensity can still represent fragments from the same compound.

[0067] The choice of 0.2 and 0.8 as the cutoff points was based on extensive 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% and 80%, the match quality decreases linearly as the difference increases. When the difference exceeds 80%, although the match quality is lower, it may still have some reference value.

[0068] The calculation formula for the positive matching score is:

[0069] Positive matching score ;

[0070] in, The normalized peak intensity of the first fragment ion in the matching database, is the normalized peak intensity of the corresponding fragment ion in the standard mass spectrum, is the peak matching score. In this formula, Represents the weight ratio of the peak in all selected peaks, The score is determined based on relative differences. This formula takes into account the weight of the fragment ions, relative differences, and match quality, providing a more comprehensive assessment of spectral matching.

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

[0072] Reverse match score ;

[0073] in, 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, This formula is the same as the forward matching score calculation formula, but the roles are reversed.

[0074] The formula for calculating the final similarity score based on the forward matching score and the reverse matching score is:

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

[0076] The final similarity score is the arithmetic mean of the forward and reverse matching scores. This processing method takes into account the results of two-way matching and can more comprehensively evaluate the similarity between mass spectra.

[0077] Specifically, the method is as follows:

[0078] Similarity = Peak Ratio * Peak Matching (Forward) + Peak Ratio * Peak Matching (Reverse)

[0079] Peak matching (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] The raw data obtained from the mass spectrometry is matched 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 to screen for risky substances in food, feed, vegetables, livestock, poultry, eggs, and milk, among other products. These risky substances include at least one of veterinary drugs, pesticides, and mycotoxins. The variety of risky substances in these areas is vast, and the method of the present invention can improve the accuracy of screening for these substances, ensuring food safety.

[0087] Before obtaining the mass spectrum data to be queried, the sample must first be pretreated to extract any potential risk substances. Preferably, appropriate extraction methods, such as liquid-liquid extraction or solid-phase extraction, can be selected based on the characteristics of the substance to be detected. The pretreated sample is then passed through a high-resolution mass spectrometer for detection to obtain raw mass spectrum data. Finally, the raw mass spectrum data is processed, such as through denoising and peak extraction, to obtain the mass spectrum data to be queried.

[0088] After outputting the similarity score, the system first compares it to a preset threshold. The choice of the threshold depends on the specific application scenario and the tolerance for false positives and false negatives. Typically, the threshold is set between 80 and 90. A higher threshold reduces false positives but may increase false negatives, while a lower threshold has the opposite effect. If the similarity score exceeds the preset threshold, the query mass spectrum is determined to contain a compound corresponding to the reference mass spectrum. This determination can be used for subsequent risk assessment and action.

[0089] The implementation process of the present invention is described below through a specific embodiment:

[0090] In this example, the method of the present invention was used to screen for antibiotic residues that may be present 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), perform ultrasonic extraction for 30 minutes, centrifuge and filter the supernatant to obtain a pre-treated sample.

[0092] The pretreated sample is injected into a high-resolution mass spectrometer (such as a quadrupole-time-of-flight mass spectrometer (Q-TOF)) for full-scan detection, collecting primary and secondary mass spectrometric data. The raw mass spectrometric data is processed, such as by removing background noise and performing peak extraction, to obtain the mass spectrum data to be queried.

[0093] Meanwhile, a mass spectrometric database containing common antibiotic standards was prepared as a reference.

[0094] Select the fragment ions with the top 7 peak intensities or peak intensities ≥ 10 from the query mass spectrum and the standard mass spectrum, respectively. For example, suppose the following fragment ions (m / z and normalized peak intensity) are selected from the query mass spectrum:

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

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

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

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

[0099] The difference between 356.115 and 356.117 is about 5.6ppm (exceeding the threshold, mismatch);

[0100] The difference between 158.072 and 158.070 is about 12.7ppm (exceeding the threshold, mismatch);

[0101] The difference between 114.055 and 114.056 is about 8.8ppm (exceeding the threshold, mismatch); ...

[0103] (The difference of other corresponding fragment ions can be calculated in the same way);

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

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

[0106] Calculate the reverse match score: Similarly, calculate the reverse match score, assuming the obtained score is 80.

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

[0108] The similarity score of 82.5 is compared with a preset threshold (e.g., 80). Since 82.5 > 80, it is determined that the query mass spectrum contains a compound corresponding to the standard mass spectrum, which means that enrofloxacin residues are present in the sample.

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

[0110] Those skilled in the art will appreciate that the present invention is not limited to the specific embodiments described above, and that various changes and modifications may be made without departing from the scope of the present invention. Such changes and modifications are intended to be within the scope of the present invention. For example, the criteria for fragment ion selection, the m / z difference threshold, and the parameters of the peak matching scoring function may be adjusted according to the specific application scenario to optimize the performance and adaptability of the method.

Claims

1. A method for similarity matching 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 fragment ions with peak intensities ranked in the top 7 or with peak intensities ≥10 in the mass spectrum to be queried and the standard mass spectrum; determining 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, and if the difference is ≤5 ppm, calculating a forward matching score between the mass spectrum to be queried and the standard mass spectrum, and a reverse matching score between the standard mass spectrum and the mass spectrum to be queried; calculating an average based on the forward matching score and the reverse matching score; otherwise, not performing a match; an output step of outputting the mean as a similarity score between the mass spectrum to be queried and the standard mass spectrum; The calculating of the forward matching score between the query mass spectrum 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 a first normalized peak intensity; Normalizing the peak intensities of the fragment ions selected from the standard mass spectrum to obtain a second normalized peak intensity; Calculating the positive relative difference between the first normalized peak intensity of each fragment ion in the query mass spectrum and the second normalized peak intensity of the corresponding fragment ion in the standard mass spectrum; Forward relative difference using the formula Indicates that X is the first normalized peak intensity of the fragment ion in the mass spectrum to be queried, X ′ is the second normalized peak intensity of the corresponding fragment ion in the standard mass spectrum; Determine the forward peak matching score K1 according to the forward relative difference; Calculating the forward matching score based on the first normalized peak intensity, the second normalized peak intensity, the forward relative difference, and the forward peak matching score K1; Calculating 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 a second normalized peak intensity; Normalizing the peak intensities of the fragment ions selected from the mass spectrum to be queried to obtain a first normalized peak intensity; Calculating the reverse relative difference between the second normalized peak intensity of each fragment ion in the standard mass spectrum and the first normalized peak intensity of the corresponding fragment ion in the query mass spectrum; Reverse relative difference using the formula Indicates that X is the first normalized peak intensity of the fragment ion in the mass spectrum to be queried, X ′ is the second normalized peak intensity of the corresponding fragment ion in the standard mass spectrum; Determine a reverse peak matching score K2 according to the reverse relative difference; The reverse matching score is calculated based on the second normalized peak intensity, the first normalized peak intensity, the reverse relative difference and the reverse peak matching score K2.

2. The method according to claim 1, characterized in that Determining the forward peak matching score K1 according to the forward relative difference specifically includes: When the positive relative difference is less than or equal to 0.2, the positive peak matching score K1 is 100; When the positive relative difference is greater than 0.2 and less than 0.8, the positive peak matching score K1 is -100×the positive relative difference+120; When the positive relative difference is greater than or equal to 0.8, the positive peak matching score K1 is 40; Determining the reverse peak matching score K2 according to the reverse relative difference specifically includes: When the reverse relative difference is less than or equal to 0.2, the reverse peak matching score K2 is 100; When the reverse relative difference is greater than 0.2 and less than 0.8, the reverse peak matching score K2 is -100×the reverse relative difference+120; When the reverse relative difference is greater than or equal to 0.8, the reverse peak matching score K2 is 40.

3. The method according to claim 1, characterized in that The calculation formula of the positive matching score is: Wherein, X1 is the normalized peak intensity of the first fragment ion in the matched database, and K1 is the peak matching score.

4. The method according to claim 2, characterized in that The calculation formula of the reverse matching score is: in, is the normalized peak intensity of the first fragment ion in the input data, and K2 is the peak matching score.

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

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

7. The method according to claim 1, characterized in that Before obtaining the mass spectrum data to be queried, the method further includes: Pre-process 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.

8. 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 query mass spectrum contains a compound corresponding to the standard mass spectrum.

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