A non-targeted screening method for mycotoxins in food

Abstract

The application discloses a non-target screening method for mycotoxins in food. For food samples, a non-target data acquisition platform of ultra-high performance liquid chromatography-high resolution mass spectrometry is used to construct a mycotoxin mass spectrum feature extraction and non-target screening method, and structure identification is combined with retention time, mass spectrum fragmentation rules and multi-source databases. The application has obvious advantages in the screening of mycotoxins in complex food matrix, and has the advantages of high analysis efficiency and high accuracy.

Description

Technical Field

[0001] This invention establishes an analytical method based on an ultra-high performance liquid chromatography-high resolution mass spectrometry platform to extract fungal toxicity mass spectrometry characteristics and perform non-targeted screening in a food matrix, belonging to the fields of analytical detection and food safety. Background Technology

[0002] Mycotoxins are secondary metabolites of fungi, characterized by low molecular weight and high accumulation, posing a significant threat to human health upon ingestion. Currently, over 400 mycotoxins have identified structures, with common ones including aflatoxin B1 (AFB1), zearalenone (ZEN), deoxynivalenol (DON), T-2 toxin, ochratoxin A (OTA), fumonisin B1 (FB1), and enniatin A. Ingestion may lead to acute or chronic illnesses such as various types of cancer, gastrointestinal toxicity, liver disease, various hemorrhagic syndromes, and immune and neurological disorders. Due to climate, inappropriate production methods, and poor crop storage conditions, food is susceptible to mycotoxin contamination at every stage of the production chain, posing a substantial threat to human and animal health.

[0003] Ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) is widely used in the detection of mycotoxins in food matrices due to its advantages such as high sensitivity and resolution, wide dynamic linear range, and broad detection coverage. However, current research mostly targets specific mycotoxins, failing to detect modified mycotoxins formed through reactions, microorganisms, or plant metabolism, such as glucosylated, acetylated, and sulfation products. Studies have shown that modified mycotoxins may have the same or even greater toxicity as the original mycotoxins. Therefore, to achieve the goal of food safety risk monitoring, it is necessary to develop a non-targeted screening technology for mycotoxins in food.

[0004] This invention uses an ultra-high performance liquid chromatography-high resolution mass spectrometry platform to collect non-targeted data, extract the mass spectrometric features of fungal toxins, and use these features to perform non-targeted screening of fungal toxins in food samples. It also combines retention time, mass spectrometry fragmentation patterns, and multi-source databases for structural identification. Summary of the Invention

[0005] This invention aims to achieve non-targeted screening of mycotoxins in food matrices. After sample pretreatment, primary and secondary mass spectrometry data are simultaneously acquired using an ultra-high performance liquid chromatography-high resolution mass spectrometry platform. Then, mass spectrometry characteristics of different types of mycotoxins are extracted to achieve non-targeted screening of sample data. Suspected substances are identified by combining retention time, mass spectrometry fragmentation patterns, and multi-source databases.

[0006] The specific technical methods employed in this invention are as follows:

[0007] (1) After pretreatment, flour samples were subjected to high performance liquid chromatography-high resolution mass spectrometry to acquire non-target data. 200 mg of wheat flour was weighed into a 2 mL centrifuge tube, and 1 mL of acetonitrile-water-formic acid (79:20:1, v / v) extractant was added. The mixture was vortexed for 1 min to mix evenly. Extraction was performed at room temperature using a thermostatic mixer (ThermoMixer C, Thermo Fisher Scientific, Rockford, IL, USA). The thermostatic mixer was set to a speed of 800 rpm for 90 min. The centrifuge tube was then centrifuged at 4 °C and 14,000 rpm for 10 min. 600 μL of the supernatant was transferred to another 2 mL centrifuge tube, and an equal volume of water-acetonitrile-formic acid (79:20:1, v / v) diluent was added. The mixture was vortexed for 1 min to mix evenly. The mixture was then centrifuged again at 4 °C and 14,000 rpm for 10 min. The supernatant was transferred to a sample vial and analyzed using a simultaneous first-stage and second-stage mass spectrometry method coupled with ultra-high performance liquid chromatography (UPLC, Waters, Milford, MA, USA) and high-resolution mass spectrometry (Q Exactive HF, Thermo Fisher Scientific, Rockford, IL, USA). The mobile phases A and B were 5 mmol ammonium formate aqueous solution containing 0.1% (v / v) formic acid and 5 mmol methanol-water (95 / 5, v / v) solution containing 0.1% (v / v) formic acid, respectively. The flow rate was 0.3 mL / min, and the total analysis time was 12 min. The elution gradient was: 5% B for 0-1 min, linearly increasing to 100% B for 1-8 min, 100% B for 8-10 min, decreasing to 5% B for 10-10.1 min, and equilibrating the column with 5% B for 10.1-12 min. The mass spectrometry collision energies were a mixture of 15, 30, and 45 eV.

[0008] (2) The collected raw data underwent peak matching and extraction using the instrument's built-in software Compound Discoverer 3.1. After obtaining the compound peak table, background interference was subtracted. Specifically, the response area in each solvent blank (equal volume of extractant and diluent mixed) exceeded 5 × 10⁻⁶. 5 The compounds were considered background noise interference from the experimental process and were removed.

[0009] (3) Extraction of mass spectrometry features for seven types of mycotoxins. The secondary mass spectrometry information of 45 mycotoxin standard sample solutions collected using the above analytical conditions was compared with that of 24 mycotoxins collected from the open-source mass spectrometry database MassBank of North America (MoNA) after a series of filtering and comparative sorting processes. Mass spectrometry features with a frequency greater than 50% for each type of mycotoxin were identified, including fragment ions and neutral loss. Subsequently, the structures were confirmed using the mass spectrometry structure analysis software MassFrontier 8.0 and relevant literature on mass spectrometry analysis for each type of mycotoxin, resulting in the mass spectrometry features for the seven types of mycotoxins. A frequency greater than or equal to 0.87 was considered a mandatory mass spectrometry feature, while a frequency less than 0.87 was considered a potentially desirable feature. This was used to establish screening rules.

[0010] (4) Non-targeted screening of sample data. The collected raw sample data were converted into MGF files containing secondary fragments using secondary conversion software. The secondary mass spectrometry information in each MGF file was compared with the screening rules. The mass accuracy deviation of the secondary mass spectrometry fragments m / z was less than 10 ppm. Compounds that met the screening rules for any type of mycotoxin were then compared with the peak table. H2 was added to the compounds on the peak table. + or NH4 + Compounds with a mass spectrometry accuracy deviation of less than 5 ppm and a retention time deviation of less than 0.2 min are considered suspicious compounds. The structure of these suspicious compounds is identified by combining retention time, mass spectrometry fragmentation patterns, and multi-source databases (internal mycotoxin database, MoNA, Metall, Drugbank, etc.). This invention has significant advantages in screening mycotoxins in complex food matrices, offering high analytical efficiency and accuracy. Attached Figure Description

[0011] Figure 1 The flowchart of this invention shows the confirmation process of mass spectrometry features and screening rules on the left and the non-targeted screening process of actual samples on the right.

[0012] Figure 2 Qualitative results of compounds screened out from non-targeted samples. (A) Selected ion chromatogram and mass spectrum of deoxynivalenol in the sample, (B) Selected ion chromatogram and mass spectrum of deoxynivalenol standard. Detailed Implementation

[0013] The following detailed description of the implementation of the present invention is provided in conjunction with the accompanying drawings: This embodiment is implemented based on the technical solution of the present invention, and provides detailed implementation methods and specific operation processes, but the protection scope of the present invention is not limited to the following embodiments.

[0014] Example 1

[0015] (1) Sample data acquisition based on ultra-high performance liquid chromatography-high resolution mass spectrometry.

[0016] Eight samples of commercially available wheat flour were collected, with three samples taken from each sample, for a total of 24 samples. The samples were first pretreated as follows: 200 mg (±0.2 mg) of flour was weighed into a 2 mL centrifuge tube, and 1 mL of acetonitrile-water-formic acid (79:20:1, v / v) extractant was added. The mixture was vortexed for 1 min to ensure homogeneity. Extraction was then performed at room temperature using a ThermoMixer C (Thermo Fisher Scientific, Rockford, IL, USA) with the speed set at 800 rpm for 90 minutes. The centrifuge tubes were then centrifuged at 4°C and 14,000 rpm for 10 min. 600 μL of the supernatant was transferred to another 2 mL centrifuge tube, and an equal volume of water-acetonitrile-formic acid (79:20:1, v / v) diluent was added. The mixture was vortexed for 1 min to ensure homogeneity, and then centrifuged again at 4°C and 14,000 rpm for 10 min. The supernatant was transferred to a sample vial and analyzed using a simultaneous first-stage and second-stage mass spectrometry method coupled with ultra-high performance liquid chromatography (UPLC, Waters, Milford, MA, USA) and high-resolution mass spectrometry (Q Exactive HF, Thermo Fisher Scientific, Rockford, IL, USA). The chromatographic column was an ACQUITY BEH C18 column (2.1 mm × 50 mm, 1.7 μm, Waters, Milford, MA, USA). The chromatographic mobile phases A and B were 5 mmol ammonium formate aqueous solution containing 0.1% (v / v) formic acid and 5 mmol methanol-water (95 / 5, v / v) solution containing 0.1% (v / v) formic acid, respectively. The flow rate was 0.3 mL / min, and the total analysis time was 12 min. The elution gradient was: 5% B for 0–1 min, linearly increasing to 100% B for 1–8 min, 100% B for 8–10 min, decreasing to 5% B for 10–10.1 min, and equilibrating the column with 5% B for 10.1–12 min. The mass spectrometry collision energies were a mixture of 15, 30, and 45 eV.

[0017] (2) Peak extraction and background interference removal of raw data

[0018] Step (1) analyzed the raw data and two parallel injections of solvent blanks (equal volumes of extractant and diluent). The combined data were then used to perform peak extraction and matching using the instrument's built-in software, Compound Discoverer 3.1. The resulting peak table included the molecular weight, retention time, and response area of ​​each compound in each sample, totaling 2188 compounds. Subsequently, the response area in each solvent blank (equal volumes of extractant and diluent) exceeded 5 × 10⁻⁶. 5 Compounds deemed to be background noise interference during the experiment were removed, and the remaining 1894 compounds underwent non-targeted screening. Some peak information is shown in Table 1.

[0019] (3) Automated extraction based on fungal virology mass spectrometry characteristics

[0020] The above analytical method was used to analyze 45 existing mycotoxins (i.e., mycotoxins from internal sources in Table 2) standard sample mixtures (except for Aflatoxin B1, Aflatoxin G1, and α-Zearalanol, which had concentrations of 2 μg / mL, Aflatoxin B, Aflatoxin G2, and Aflatoxin B2, which had concentrations of 0.5 μg / mL, and the others, which had concentrations of 1 μg / mL). 24 mycotoxins from the open-source mass spectrometry database MassBank of North America (MoNA) were also collected, along with 124 secondary mass spectra corresponding to different collision energies. Their information was compiled in an Excel spreadsheet, as shown in Table 2. The mycotoxin information was obtained by consulting the literature ([1]).

[0021] Jia W, Shi L, Zhang F, et al. Multiplexing data independent untargeted workflows for mycotoxins screening on a quadrupole-Orbitrap high resolution mass spectrometry platform[J]. Food Chemistry, 2019, 278: 67-76. [2] Grovey J F. The trichothecenes and their biosynthesis.[J]. Springer Vienna, 2007.) and other methods to classify them into 7 categories, namely trichothecenes, aflatoxin, ochratoxin, fumonisin, zearalenone toxins, enfuracin and ergot alkaloids. Then the mass spectrometry features were extracted and the screening rules were confirmed. The process is as follows Figure 1As shown in the left section, the secondary mass spectra of the same mycotoxin with different collision energies are first fused and normalized (i.e., secondary fragments from multiple spectra are statistically analyzed; the relative intensities of secondary fragments with the same mass-to-charge ratio are summed, while the relative intensities of secondary fragments with different mass-to-charge ratios remain unchanged; then, the secondary fragment with the highest relative intensity is taken as 100%, and the relative intensities of other secondary fragments are calculated proportionally to obtain the final result), so that one mycotoxin corresponds to one spectrum. Secondary mass spectrometry fragments with a relative intensity less than 1% are considered unstable mass spectrometry signals or interference noise and are deleted without further statistical analysis. Subsequently, the frequency and average intensity of each fragment with a precise mass deviation within 10 ppm are statistically analyzed, and neutral loss is calculated by subtracting the secondary mass spectrometry ion from the parent ion. The frequency and average intensity of each neutral loss are also statistically analyzed. Mass spectrometry fragments with an occurrence frequency less than 50% and neutral losses are considered not to be mass spectrometric features of this type of mycotoxin and are removed. Mass spectrometry fragments with a mass-to-charge ratio less than 100 and neutral losses with a mass less than 12 are also removed because they are prone to false positives. Finally, the mass spectrometry characteristics of each type of fungal toxin were obtained from high to low frequency. If the frequencies were the same, they were sorted from high to low average intensity. Mass spectrometry structure analysis software MassFrontier 8.0 and mass spectrometry analysis of each type of fungal toxin were used to analyze relevant literature ([1] Arroyo-Manzanares N, Malysheva S V, Vanden Bussche J, et al. Holistic approach based on high resolution and multiple stage mass spectrometry to investigate ergot alkaloids in cereals[J]. Talanta, 2014, 118: 359-67. [2] Toth K, Nagy L, Mandi A, et al. Collision-induced dissociation of aflatoxins[J]. Rapid Commun Mass Spectrom, 2013, 27(4): 553-9. [3] Liu ZY, Yu CH, Wan L, et al. Fragmentation study of five trichothecenes using electronspray hybrid ion trap / time-of-flight mass spectrometry with accurate mass measurements[J]. International Journal of Mass Spectrometry,2012,309:133-40.The structures of fungal toxins (e.g., [unclear]) were confirmed, and the mass spectrometry characteristics of seven types of fungal toxins were obtained, as shown in Table 3. A frequency of 0.87 or higher was considered a necessary diagnostic mass spectrometry characteristic, while a frequency of less than 0.87 was considered a possible auxiliary qualitative mass spectrometry characteristic. Screening rules were established based on this. Specifically, trichothecene toxins have the following mass spectrometry features: m / z 109.06479, m / z 125.05971, m / z 137.05971, m / z 215.10666, m / z 123.04406, and m / z 203.10666. Among these, m / z 109.06479 and m / z 125.05971 appear in almost every trichothecene toxin. Therefore, the first rule is that these two mass spectrometry features must be detected. The remaining four mass spectrometry features may appear in some trichothecene toxins. To avoid excessively high false positive and false negative rates, a second rule is set: at least two of these four mass spectrometry features must be detected. Compounds that meet both rules are considered suspicious trichothecene toxins. Similarly, fumonisin has the following mass spectrometry features: m / z 109.10118, m / z 208.20598, m / z 109.06479, m / z 125.05971, m / z 137.05971, m / z 215.10666, m / z 123.04406, and m / z 203.10666. 159.02880, m / z 354.33666, m / z 336.32609, M+H-18.01057, M+H-36.02113, where m / z 109.10118 and M+H-18.01057 are mandatory detections, and at least three of the remaining five mass spectrometry features must be detected; zearalenone toxins have the following mass spectrometry features: m / z 189.05462, m / z 177.05462, m / z 205.08592, m / z 257.15361, m / z 125.09609, and M+H-116.08373, of which m / z 189.05462 and m / z 177.05462 are mandatory detections, and at least three of the remaining four mass spectrometry features must be detected; ochratoxin has the following mass spectrometry features: m / z 239.01056, m / z 120.08078, M+H-18.01057, M+H-46.00548, and M+H-165.0 7898, of which M+H-18.01057 and M+H-46.00548 are mandatory detections, and at least two of the remaining three mass spectrometry features must be detected; Entamoebasil has mass spectrometry features m / z 228.15942, m / z 166.08626, m / z 314.19619, m / z 200.16451. Since none of the four mass spectrometry features appear in every entamoebasil, i.e., the frequency is low (all 0.6), they are not mandatory detections. Detection of two of the four mass spectrometry features is considered suspicious for entamoebasil; Aflatoxin has mass spectrometry features m / z 257.08084, m / z 243.06519, M+H-27.99492, M+H-74.00040, of which M+H-27.99492 is a mandatory detection, and at least two of the remaining three mass spectrometry features must be detected. Ergot alkaloids have the following mass spectrometry features: m / z 208.07569, m / z 197.10732, m / z 223.12297, m / z 268.14444, and m / z 251.11789. Of these, m / z 208.07569 and m / z 197.10732 are mandatory detections, and at least one of the remaining three mass spectrometry features must be detected.

[0022] (4) Non-targeted screening based on mycotoxins in samples

[0023] The collected raw data was converted into MGF files containing information such as retention time, precursor ion mass-to-charge ratio, fragment ion mass-to-charge ratio, and scan number using secondary conversion software (OSI-SMMS_Export_MS2.7z) for non-targeted screening. The specific process is as follows: Figure 1 As shown in the right part, secondary fragments with a relative intensity of less than 1% were first filtered out. Then, the mgf file information of each sample was compared one by one with the screening rules of the seven types of mycotoxins. The mass accuracy deviation of the m / z of the secondary mass spectrometry fragments was less than 10 ppm. Compounds that met the screening rules of any type of mycotoxin were then compared with the peak table (the information of 1894 compounds obtained in step (2)). Compounds with a mass accuracy deviation of less than 5 ppm for H+ or NH4+ addition and a retention time deviation of less than 0.2 min were considered suspicious compounds. Through the above method, a total of 21 suspicious compounds were screened out, as shown in Table 4.

[0024] The structures of the suspected compounds were identified by combining retention time, mass spectrometry fragmentation patterns, and multiple databases (internal database of 45 mycotoxins, online databases MoNA, Metlin, Drugbank, etc.). The compound with m / z 297.13275 was ultimately identified as deoxynivalenol (DON), which was detected in both samples (samples 6 and 7).

[0025] The screened mycotoxins were quantitatively analyzed to determine whether they exceeded the limits. Different amounts of the screened deoxynivalenol standard samples were added to the extract of blank flour samples (i.e., flour samples without screened mycotoxins) to form a series of deoxynivalenol concentration gradient solutions (4000, 1600, 800, 400, 160, 80, 40, 16, 8, 4 μg / kg). These solutions were analyzed under the same conditions as the actual samples, and a standard curve was plotted. The standard curve equation was y = 73611x - 211312, and the correlation coefficient (R²) was [missing information]. 2The value was 0.9990, where x was the concentration of deoxynivalenol and y was the response area of ​​deoxynivalenol in blank flour. The concentration of deoxynivalenol was calculated by substituting the response area of ​​the actual samples into the standard curve equation. The quantitative results are shown in Table 2. The average concentrations of deoxynivalenol in samples 6 and 7 were 2793.35 μg / kg and 839.34 μg / kg, respectively. Sample 6 significantly exceeded the limit of 1000 μg / kg for deoxynivalenol in wheat flour specified in GB 2761-2011 National Food Safety Standard for Limits of Mycotoxins in Food.

[0026] This invention targets food matrices. After pretreatment, data is collected using an ultra-high performance liquid chromatography-high resolution mass spectrometry platform. Subsequently, mycotoxin mass spectrometry features are extracted and non-targeted screening of mycotoxins in the sample is performed. It has the advantages of high analytical efficiency and accurate results, and can provide technical support for the contamination status and risk warning of mycotoxins in food matrices.

[0027] Table 1 after removing blanks Flour Peak Information (part)

[0028]

[0029] Table 2 Information on 7 types of mycotoxins (Note: Sources are 45 mycotoxins from a self-built database). MoNA (24 fungal toxins collected for online database)

[0030]

[0031]

[0032] Table 3. Mass spectrometric characteristics of seven types of fungal toxins

[0033]

[0034] Table 4 Information on suspicious compounds screened from flour samples

[0035]

[0036] Table 5. Quantitative results of mycotoxins screened in flour samples (unit: μg / kg)

[0037]

Claims

1. A non-targeted screening method for mycotoxins in food, characterized in that, Includes the following steps: (1) After food sample pretreatment, non-target data acquisition was performed using an ultra-high performance liquid chromatography-high resolution mass spectrometry platform. (2) Peak extraction and peak matching, as well as background interference removal, are performed on the collected raw data; (3) Screening of suspicious substances in samples: extract the mass spectrometry features of mycotoxins and use these features to screen for mycotoxins in samples. Then, combine retention time, mass spectrometry fragmentation patterns and information databases containing mycotoxins to identify the structure. The specific procedure for extracting the mass spectrometry features of mycotoxins is as follows: collect existing secondary mass spectrometry spectra of mycotoxins, remove interfering noise, then count the frequency and average intensity of each fragment with a precise mass deviation within 10 ppm, and calculate neutral loss by subtracting fragment ions from parent ions, and count the frequency and average intensity of each neutral loss. Mass spectrometry fragments with an occurrence frequency of less than 50%, as well as neutral loss, mass-to-charge ratio (M / C ratio) fragments, and neutral loss with a mass of less than 12, were sequentially removed. Finally, the mass spectrometry characteristics of mycotoxins were output in descending order of frequency, i.e., mass spectrometry fragments and neutral loss; if frequencies were the same, they were sorted in descending order of average intensity. Through analysis using mass spectrometry structure analysis software and relevant literature, the mass spectrometry characteristics of each type of mycotoxin were determined, including the molecular formula, mass-to-charge ratio of the mass spectrometry fragments, and the mass of the neutral loss. Using the analytical methods described in steps (1) and (2) above, secondary mass spectrometry information was collected from a mixed solution of 45 existing mycotoxin standard samples. Alternatively, 24 secondary mass spectrometry features corresponding to different collision energies of mycotoxins were collected from the open-source mass spectrometry database MassBank of North America. The collision energies were less than or equal to 45 eV. Mass spectrometry characteristics of 7 classes of mycotoxins were obtained, as follows: Trichothecene toxins had mass spectrometry features m / z 109.06479, m / z 125.05971, m / z 137.05971, m / z 215.10666, m / z 123.04406, and m / z 203.10666. Among these, m / z 109.06479 and m / z 125.05971 were mandatory, and at least two of the other four mass spectrometry features were detected. Fumonisins had mass spectrometry features m / z The mass spectrometry features are: 109.10118, m / z 208.20598, m / z 159.02880, m / z 354.33666, m / z 336.32609, M+H-18.01057, M+H-36.02113. Among these, m / z 109.10118 and M+H-18.01057 are mandatory, and at least three of the remaining five mass spectrometry features must be detected. Zearalenone toxins have the following mass spectrometry features: m / z 189.05462, m / z 177.05462, m / z 205.08592, m / z 257.15361, m / z 125. 09609, M+H-116.08373, of which m / z 189.05462 and m / z 177.05462 are mandatory detections, and at least three of the remaining four mass spectrometry features must be detected; ochratoxin has the mass spectrometry features m / z 239.01056, m / z 120.08078, M+H-18.01057, M+H-46.00548, M+H-165.07898, of which M+H-18.01057 and M+H-46.00548 is a mandatory detection, and at least two of the remaining three mass spectrometry features must be detected; Fusarium oxysporin has the mass spectrometry features m / z 228.15942, m / z 166.08626, m / z 314.19619, m / z 200.16451, and the detection of two of the four mass spectrometry features is considered suspicious for Fusarium oxysporin; Aflatoxin has the mass spectrometry features m / z 257.08084, m / z 243.06519, M... +H-27.99492, M+H-74.00040, where M+H-27.99492 is a mandatory detection, and at least two of the remaining three mass spectrometry features must be detected; ergot toxins have mass spectrometry features m / z 208.07569, m / z 197.10732, m / z 223.12297, m / z 268.14444, m / z 251.11789, where m / z 208.07569 and m / z 197.00040 are the most significant.10732 must be detected; at least one of the remaining three mass spectrometry features must be detected. Step (3) Utilize mass spectrometry features to achieve non-targeted screening of mycotoxins in the sample. The specific process is as follows: The collected raw sample data is converted into an mgf file containing information such as retention time, parent ion mass-to-charge ratio, and mass-to-charge ratio of secondary mass spectrometry fragments using secondary conversion software. Then, secondary fragments with a relative intensity of less than 1% are filtered out. The secondary mass spectrometry information in the sample's mgf file is compared one by one with the screening rules for mycotoxins confirmed above. The mass accuracy deviation of the secondary mass spectrometry fragment m / z is less than 10 ppm. Compounds that meet any of the screening rules for mycotoxins are then compared with the peak table. Compounds with a mass accuracy deviation of less than 5 ppm for adding H+ or NH4+ and a retention time deviation of less than 0.2 min are considered suspicious compounds. Step (3) Extracting the mass spectrometry features of mycotoxins: The specific process is as follows: The analysis methods in steps (1) and (2) above are used to collect secondary mass spectrometry information of the existing mycotoxin standard sample mixture solution, and / or, the secondary mass spectrometry corresponding to different collision energies of mycotoxins with mass spectrometry collision energies less than or equal to 45 eV are collected from the open-source mass spectrometry database MassBank of North America. The information is statistically analyzed in an Excel spreadsheet, and then the mass spectrometry features are extracted. First, the secondary mass spectrometry of the same mycotoxin with different collision energies is fused and normalized, that is, the secondary fragments of multiple spectra are statistically analyzed. The relative intensities of secondary fragments with the same mass-to-charge ratio are accumulated, and the relative intensities of secondary fragments with different mass-to-charge ratios remain unchanged. Then, the secondary fragment with the highest relative intensity is taken as 100%, and the relative intensities of other secondary fragments are calculated according to this ratio to obtain the final result, so that one mycotoxin corresponds to one spectrum. Then, the secondary mass spectrometry fragments with a relative intensity of less than 1% are considered to be unstable mass spectrometry signals or interference noise, and are therefore deleted and not further statistically analyzed. Subsequently, the frequency and average intensity of each fragment with a precise mass deviation within the range of 10 ppm were statistically analyzed, and neutral loss was calculated by subtracting fragment ions from parent ions. The frequency and average intensity of each neutral loss were then statistically analyzed. Mass spectrometry fragments and neutral loss with a frequency of less than 50%, mass spectrometry fragments with a mass-to-charge ratio of less than 100, and neutral loss with a mass of less than 12 are removed in sequence. Finally, the mass spectrometry features of each type of fungal toxin are output in descending order of frequency, i.e., mass spectrometry fragments and neutral loss. If the frequencies are the same, they are sorted in descending order of average intensity. The structures were confirmed using the mass spectrometry structure analysis software Mass Frontier 8.0 and relevant literature on mass spectrometry analysis of each type of mycotoxin. The mass spectrometry characteristics of each type of mycotoxin were obtained. It was determined that a frequency of occurrence greater than or equal to 0.87 was a necessary mass spectrometry characteristic, and a frequency of occurrence less than 0.87 was considered a possible mass spectrometry characteristic. Screening rules were set accordingly.

2. The method according to claim 1, characterized in that: The pretreatment method used in step (1) is as follows: Weigh 200 mg of food sample into a 2 mL centrifuge tube, add 1 mL of acetonitrile-water-formic acid, 79:20:1, v / v extractant, and vortex for 1 min to mix evenly; use a constant temperature mixer to extract at room temperature, with the parameters of the constant temperature mixer set to 800 rpm for 90 minutes; then place the centrifuge tube in a centrifuge at 4℃ and 14000 rpm for 10 min, take 600 μL of supernatant into another 2 mL centrifuge tube, add an equal volume of water-acetonitrile-formic acid, 79:20:1, v / v diluent, vortex for 1 min to mix evenly, and then place it in a centrifuge again at 4℃ and 14000 rpm for 10 min; take the supernatant and transfer it to a sample vial for the next step of analysis.

3. The method according to claim 1, characterized in that: Step (1) Non-targeted data acquisition was performed using an ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HMS) platform. Specific parameters were as follows: simultaneous primary and secondary mass spectrometry acquisition using UHPLC-HMS was employed. The secondary acquisition mode was Data dependent acquisition TOP 10, the injection chamber temperature was 4℃, the column temperature was 45℃, and the chromatographic column was an ACQUITY BEH C18. The column was prepared using mobile phases A and B, which were 5 mmol ammonium formate solution containing 0.1% v / v formic acid and 5 mmol methanol-water solution containing 0.1% v / v formic acid, respectively. The flow rate was 0.3 mL / min, the total analysis time was 12 min, and the elution gradient v / v was as follows: 0-1 min to maintain 5% B, 1-8 min to linearly increase to 100% B, 8-10 min to maintain 100% B, 10-10.1 min to decrease to 5% B, and 10.1-12 min to maintain 5% B to equilibrate the column. The mass spectrometry collision energies were 15, 30, and 45 eV mixed energies.

4. The method according to claim 1, characterized in that: The raw data from step (2) were used for peak matching and peak extraction using Compound Discoverer 3.1 software on the mass spectrometer to obtain a compound peak table, including compound mass, retention time and response area information in each sample; then background interference was removed, that is, compounds with a response area exceeding 5×105 in each solvent blank, extractant and diluent mixed in equal volumes were considered to be background noise interference in the experiment and were deleted.

5. The method according to claim 1, characterized in that: Step (3) combines retention time, mass spectrometry fragmentation patterns, and information databases containing mycotoxins for structural identification; the databases are one or more of the following: self-built mycotoxin database, MoNA, Metlin, and Drugbank.

6. The method according to claim 1, characterized in that: The food sample is one or more of the following grains: wheat, rice, and corn.

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