A detection method for identifying components of peanut oil and application thereof

Abstract

This invention discloses a method for identifying peanut oil components and its applications. The invention screens and identifies three peanut oil-specific markers: alfalfa ketone, stigmatine, and chiricanine A. Based on these three markers and their characteristic ion pairs, peanut oil components can be accurately identified qualitatively using liquid chromatography-tandem mass spectrometry, with a detection limit of 1% (mass ratio). The method provided by this invention has the advantages of high accuracy, good specificity, and applicability to the detection of various vegetable oils, and can be widely applied in fields such as food authenticity identification, quality supervision, and related forensic identification.

Description

Technical Field

[0001] This invention relates to the field of food testing, specifically to a method for identifying the components of peanut oil, particularly a method for qualitatively identifying the components of peanut oil based on specific molecular markers, and the application of said molecular markers. Background Technology

[0002] Peanut oil is an important edible vegetable oil in my country, favored by consumers for its unique flavor and nutritional value, with annual consumption exceeding 3 million tons and a market size exceeding 60 billion yuan. However, due to its relatively high price, there are instances of cheaper vegetable oils being sold as peanut oil in the market. This phenomenon of inaccurate product labeling not only harms consumers' interests, directly infringing upon their right to know and their legitimate rights, but also disrupts normal market competition. Furthermore, peanuts are one of the eight major food allergens recognized by the World Health Organization. According to a meta-analysis by the Chinese Center for Disease Control and Prevention, peanut allergies account for 4% of all food allergy sufferers. It has been reported that insufficiently refined peanut oil may still contain residual allergenic proteins. For people with peanut allergies, ingesting such insufficiently refined peanut oil may still trigger allergic reactions and endanger their health.

[0003] The peanut oil industry is one of my country's important agricultural product processing industries, involving multiple stages such as planting, processing, and sales, and affecting the vital interests of numerous farmers and enterprises. Some edible oil products engage in false labeling, passing off cheap vegetable oils as peanut oil. This not only harms consumer interests but also disrupts normal market competition and creates unfair competition for law-abiding and honest businesses. Establishing scientific and accurate peanut oil testing standards will help regulate market order, protect the legitimate rights and interests of honest businesses, and promote the healthy and sustainable development of the industry. Regulatory authorities urgently need an accurate, sensitive, and reliable qualitative testing method for peanut oil components as a basis for enforcement to meet the needs of food safety regulations.

[0004] In recent years, liquid chromatography-tandem mass spectrometry (LC-MS / MS) has been increasingly applied to the identification of molecular characteristics in vegetable oils due to its high sensitivity and precise molecular-level identification capabilities. However, no standard system has yet been established to systematically identify molecular markers that can specifically identify peanut oil components and apply them to various vegetable oil systems. Therefore, there is an urgent need to develop accurate, efficient, highly specific, and widely applicable molecular markers for peanut oil and their qualitative identification methods. Summary of the Invention

[0005] The purpose of this invention is to provide a method for qualitatively identifying peanut oil components and its application, so as to solve the problems of low accuracy and weak specificity in existing peanut oil identification methods.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] On the one hand, the present invention provides a method for qualitatively identifying the components of peanut oil, comprising the following steps:

[0008] (1) Sample pretreatment: Take vegetable oil sample, add organic solvent to extract, centrifuge and take the supernatant, filter to obtain test solution;

[0009] (2) Liquid chromatography-tandem mass spectrometry detection: The test solution obtained in step (1) is injected into the liquid chromatography-tandem mass spectrometer, and the molecular marker is detected using multiple reaction monitoring mode;

[0010] (3) Result determination: The retention time, mass spectrometry characteristic ions and relative ion abundance ratio are used as the comprehensive determination criteria. If any of the molecular markers are detected, the sample is determined to contain peanut oil components.

[0011] In some embodiments, the molecular markers include one or more of alfalfa ketone, santalin, and chiricanine A.

[0012] In some embodiments, the molecular marker is a combination of alfalfa ketone, santalin, and chiricanine A.

[0013] In some embodiments, the molecular formula of the alfalfa ketone is C0 17 H 16 O5, CAS number 70561-31-8; the molecular formula of the described sterol is C 16 H 14 O4, CAS number 32383-76-9; the molecular formula of Chiricanine A is C 19 H 20 O2, CAS number 350593-30-5.

[0014] In some embodiments, the organic solvent in step (1) includes, but is not limited to, one or more of methanol and ethanol, with methanol being preferred.

[0015] In some embodiments, the concentration of the organic solvent in step (1) is 70-100%, preferably 75-90%, and more preferably 80%.

[0016] In some embodiments, step (1) specifically includes: accurately weighing the vegetable oil sample, adding methanol, vortexing and shaking, centrifuging, and taking the supernatant; the lower layer of oil is then repeatedly extracted with methanol, the supernatants are combined, and filtered through an organic phase microporous membrane.

[0017] In some embodiments, the extraction in step (1) is repeated 2-3 times, preferably 3 times.

[0018] In some embodiments, step (1) specifically includes: accurately weighing the vegetable oil sample, adding 80% methanol, vortexing and shaking, centrifuging, and taking the supernatant; the lower layer of oil is extracted twice more with 80% methanol, the supernatants are combined, and the solution is obtained by filtration through a 0.22μm organic phase microporous membrane.

[0019] In some embodiments, the liquid chromatography conditions in step (2) include: mobile phase A is an aqueous solution containing 0.025% formic acid and 2 mM ammonium acetate, and mobile phase B is a methanol solution containing 0.025% formic acid and 2 mM ammonium acetate. Elution gradient: 40% B phase at 0–1 min; linear gradient increasing to 95% B at 1–9 min and maintaining this level until 13 min; rapidly decreasing to 40% B at 13.1 min, and ending at 40% B at 15 min.

[0020] In some embodiments, the liquid chromatography conditions in step (2) include: a C18 column, 1.8 μm, 100 mm × 2.1 mm; a flow rate of 0.3 mL / min; a column temperature of 40 °C; and an injection volume of 2 μL.

[0021] In some embodiments, the mass spectrometry acquisition conditions in step (2) are as follows: data are acquired using a liquid chromatography-tandem mass spectrometer equipped with a DuoSpray electrospray ionization source in both positive and negative ion modes.

[0022] In some embodiments, the mass spectrometry parameters in step (2) are as follows: the ion source is an electrospray ion source; the ion source temperature is 550°C; the spray voltage is +5500V for positive ion mode and -4500V for negative ion mode; the atomizing gas (GAS1) is 50psi, the auxiliary gas (GAS2) is 55psi, and the curtain gas (CUR) is 30psi.

[0023] In some embodiments, the mass spectrometry detection parameters of the molecular markers in step (2) are as follows: cloverone retention time 5.4 min, parent ion m / z 301.1, daughter ion m / z 107.0, 135.0 and 163.0; santalin retention time 5.5 min, parent ion m / z 271.1, daughter ion m / z 109.1, 137.1 and 161.1; chiricanine A retention time 6.9 min, parent ion m / z 279.1, daughter ion m / z 109.1, 179.1 and 223.1.

[0024] In some embodiments, the result judgment criteria in step (3) are: the retention time of the chromatographic peak of the molecular marker in the sample is consistent with that of the standard substance, and the relative deviation is within ±2.5%; the qualitative ion pairs of the molecular marker are consistent with those of the standard substance, and the relative deviation of the ion pair abundance ratio is within the allowable range.

[0025] In some embodiments, the result determination rule in step (3) is as follows: if any one of alfalfa ketone, santalin, and chiricanine A is present in the sample, it is determined that the sample contains peanut oil components; if none of the above three characteristic markers are present in the sample, it is determined that the sample does not contain peanut oil components.

[0026] In some embodiments, the detection limit of alfalfa ketone is: a sample containing 1% (by mass) peanut oil;

[0027] The detection limit for the aforementioned santalin is: samples containing 2% (by mass) peanut oil;

[0028] The detection limit for Chiricanine A is: samples containing 10% (by mass) peanut oil.

[0029] On the one hand, the present invention also provides the use of at least one of alfalfa ketone, santalin, and chiricanine A as a molecular marker for detecting peanut oil components.

[0030] In some embodiments, alfalfa ketone is used as a molecular marker for detecting components in peanut oil.

[0031] In some embodiments, santalin is used as a molecular marker for detecting components in peanut oil.

[0032] In some embodiments, Chiricanine A is used as a molecular marker for detecting peanut oil components.

[0033] In some embodiments, the combination of alfalfa ketone, santalin, and chiricanine A is used as a molecular marker for detecting peanut oil components.

[0034] In some embodiments, alfalfa ketone is selected as a molecular marker for detecting peanut oil components in samples containing at least 1% (by mass) peanut oil.

[0035] In some embodiments, alfalfa ketone and / or santalin are selected as molecular markers for detecting peanut oil components in samples containing at least 2% (by mass) peanut oil.

[0036] In some embodiments, alfalfa ketone styrax and / or chiricanine A are used as molecular markers for detecting peanut oil components in samples containing at least 10% (by mass) peanut oil.

[0037] On the one hand, the present invention also provides the application of at least one of alfalfa ketone, santalin, and chiricanine A as a molecular marker in the qualitative identification of peanut oil components in edible oils.

[0038] In some embodiments, the edible oil includes, but is not limited to, one or more of peanut oil, rapeseed oil, soybean oil, sunflower seed oil, corn oil, rice bran oil, palm oil, cottonseed oil, camellia seed oil, olive oil, sesame oil, flaxseed oil, walnut oil, or blended edible vegetable oils.

[0039] On the one hand, the present invention also provides a detection method for qualitative identification of peanut oil components in a sample, the method being as described in any embodiment of the present invention.

[0040] The beneficial effects of this invention are:

[0041] This invention is the first to propose a method for detecting peanut oil components using three molecular markers: alfalfa ketone, santalin, and chiricanine A. This method is characterized by high accuracy and high specificity.

[0042] The three molecular markers screened in this invention exhibit high specificity in common vegetable oils and can accurately identify peanut oil components. This invention is applicable to single vegetable oils and blended oils, including peanut oil, rapeseed oil, soybean oil, corn oil, sesame oil, cottonseed oil, olive oil, walnut oil, and other oil systems.

[0043] It employs standardized solvent extraction and universal chromatography / mass spectrometry configurations, making it easy for laboratories to implement and conduct large-scale testing.

[0044] It can detect trace specific molecules in peanut oil, ensuring effective identification even at low concentrations. The qualitative analysis is objective and clear, meeting diverse needs such as food safety supervision, forensic identification, and enterprise self-inspection. Attached Figure Description

[0045] Figure 1 These are the secondary mass spectra of three compounds and their corresponding standards. A1 is the measured secondary mass spectrum of the alfalfa ketone sample, and A2 is the secondary mass spectrum of the alfalfa ketone standard. B1 is the measured secondary mass spectrum of the santalin sample, and B2 is the secondary mass spectrum of the santalin standard. C1 is the measured secondary mass spectrum of the chiricanine A sample, and C2 is the secondary mass spectrum of the chiricanine A standard.

[0046] Figure 2 Here are the MRM chromatogram (A) and characteristic ion-pair mass spectra (B) of alfalfa ketone;

[0047] Figure 3 The images show the MRM chromatogram (A) and characteristic ion-pair mass spectrum (B) of santalin.

[0048] Figure 4Here are the MRM chromatogram (A) and characteristic ion-pair mass spectra (B) of Chiricanine A;

[0049] Figure 5 This is the sensitivity verification result of characteristic markers in peanut oil sample No. 1;

[0050] Figure 6 This is the sensitivity verification result of the characteristic markers in peanut oil sample No. 2;

[0051] Figure 7 This is the sensitivity verification result of the characteristic markers in peanut oil sample No. 3. Detailed Implementation

[0052] The present invention will be further described by way of examples, but the present invention is not limited to the following examples.

[0053] Experimental Example 1: Screening, Identification, Detection and Application of Characteristic Markers for Peanut Oil

[0054] I. Experimental Methods

[0055] 1. Non-targeted screening and identification of characteristic markers of peanut oil

[0056] Take 10 parts each of peanut oil, soybean oil, corn oil, palm oil, cottonseed oil, sesame oil, rapeseed oil, rice bran oil, walnut oil, sunflower seed oil, olive oil, flaxseed oil, and camellia seed oil, and accurately weigh 1g of each. Add 3mL of methanol-water solution (80:20, volume ratio), and extract by vigorous shaking for 10min, followed by centrifugation at 6000g for 10min. Repeat the above extraction and centrifugation steps three times for the lower oil phase of each sample. Collect and combine the supernatants from the three extractions, filter them through a 0.22μm organic phase microporous membrane, and use them for analysis.

[0057] Detection was performed using liquid chromatography-tandem high-resolution mass spectrometry (UPLC-QTOF-MS).

[0058] Liquid chromatography conditions: Separation was performed using a C18 reversed-phase column (1.8 μm particle size, 100 mm × 2.1 mm inner diameter). Mobile phase A was an aqueous solution containing 0.025% formic acid and 2 mmol / L ammonium acetate, and mobile phase B was methanol containing 0.025% formic acid and 2 mmol / L ammonium acetate. A binary gradient elution program was used: 40% B phase was used from 0 to 1 min; the concentration was increased linearly to 95% B from 1 to 9 min and maintained until 13 min; the concentration was rapidly reduced to 40% B at 13.1 min, and the equilibrium was reached at 40% B at 15 min. The flow rate was 0.3 mL / min, the column temperature was 40 °C, and the injection volume was 2 μL.

[0059] Mass spectrometry acquisition conditions: A high-resolution mass spectrometer equipped with an electrospray ionization source was used to acquire data in both positive and negative ion modes. Information-dependent acquisition (IDA) combined with dynamic background subtraction (DBS) and real-time multiple mass loss filtering (MMDF) strategies was employed to acquire full-scan primary and secondary mass spectrometry data in a single injection. AnalystTF 1.7.1 was used as the data acquisition software. Key mass spectrometry parameters: Ion source temperature 550℃; Spray voltage +5500V for positive ion mode, -4500V for negative ion mode; Nebulizing gas (GAS1) 50psi, auxiliary gas (GAS2) 55psi, curtain gas (CUR) 30psi; Declustering voltage (DP) +80V for positive ion mode, -80V for negative ion mode. The full-scan TOF-MS acquisition range was 100–1000 m / z, and the accumulation time was 200 ms. In MS / MS secondary mass spectrometry mode, the collision energy (CE) is set to +35 eV for positive ion mode and -35 eV for negative ion mode, with the collision energy extension (CES) set to 15 eV. The MS / MS scan range is 50–1000 m / z, and the accumulation time is 50 ms.

[0060] Data Processing and Biomarker Identification: The acquired UPLC-QTOF-MS raw data were preprocessed using MS-DIAL software, including denoising, baseline correction, peak extraction and deconvolution, and retention time alignment. Subsequently, the FormulaFinder and Fragment Pane tools in PeakView 2.2 software were used to identify characteristic ions. During the identification process, only characteristic ions with secondary mass spectrometry information and not generated by in-source fragmentation were selected for molecular formula deduction. FormulaFinder was used to automatically match the molecular formula based on the accurate primary mass, secondary fragment ions, and natural isotope distribution, requiring the measured mass to deviate from the theoretical mass by less than 5 ppm and the measured isotope distribution to deviate from the theoretical value by less than 20%. The elemental composition was limited to: C≤60, H≤60, N≤10, O≤20. After determining the molecular formula and ion adduct type, the fragment ion analysis function of Fragment Pane was used to infer the structure of candidate compounds based on the secondary mass spectrometry fragmentation pattern.

[0061] Candidate compounds were retrieved from metabolite databases such as MassBank, HMDB, METLIN, and MoNA. Fragment ion prediction was used to match theoretical fragments with measured secondary mass spectrometry fragments, initially identifying the structures of characteristic compounds. Finally, the chemical structures of the screened characteristic markers were confirmed by reviewing literature and purchasing standards.

[0062] 2. Optimization of liquid chromatography-tandem mass spectrometry detection parameters for characteristic markers of peanut oil

[0063] Mass spectrometry (MS / MS) parameters for the identified characteristic biomarkers were optimized using a triple quadrupole tandem mass spectrometer (LC-MS). The effects of declustering voltage (DP) and collision energy (CE) on the signal intensity of characteristic ions were investigated through continuous injection experiments to determine the optimal detection parameters. The DP optimization range was set from 0 to 300 V (incrementing by approximately 1.4 V per step), and the CE optimization range was set from 0 to 180 eV (incrementing by 1 eV per step). The voltage / energy was gradually increased until the optimal response value for each biomarker fragment ion was obtained.

[0064] 3. Specificity verification of peanut oil characteristic markers

[0065] Based on the optimized liquid chromatography-tandem mass spectrometry method, specificity verification experiments were conducted on different types of edible oils. The MRM mode was used to detect the signals of three characteristic markers in pure peanut oil and non-peanut oil samples, confirming that these markers appeared only in peanut oil and not in other vegetable oils, thus verifying the method's specificity.

[0066] II. Test Results

[0067] Through the above-mentioned non-targeted metabolite screening, several unique metabolite signals were found in peanut oil samples. By comparing the chromatographic and mass spectrometric data of different oils, three specific molecular markers were finally identified, which were found only in peanut oil and not detected in the other 12 vegetable oils. The molecular formulas of these three compounds were deduced using high-resolution mass spectrometry and fragmentation information, and their structures were confirmed by comparison with standards. They were identified as alfalfa ketone (C... 17 H 16 O5, CAS 70561-31-8), Medigen Pterocarpus (C 16 H 14 O4 (CAS 32383-76-9) and Chiricanine A (C 19 H 20 O2 (CAS 350593-30-5).

[0068] like Figure 1 As shown, the secondary mass spectra of the three compounds detected in the sample are in high agreement with those of the corresponding standards (1 in the spectrum is the measured fragment ion peak of the sample, and 2 is the fragment ion peak of the standard). The m / z values ​​and abundance ratios of the main characteristic fragment ions are consistent, which fully demonstrates the reliability of the marker identification results. These molecular markers are all secondary metabolites unique to peanut oil.

[0069] By optimizing the fragment ion generation conditions for each marker using triple quadrupole mass spectrometry, the combination of mass spectrometry parameters with the highest sensitivity and signal-to-noise ratio was obtained (see Table 1 for details). In positive ion mode, the [M+H] fraction of alfalfa ketone... +The optimal DP and CE of fragment ions obtained after optimization for the parent ion (m / z 301.1) are approximately +80V and +45eV for 107.0; approximately +100V and +25eV for 135.0; and approximately +80V and +25eV for 163.0. [M+H] of the parent ion. + The optimized power dispersive ion (DP) for the parent ion (m / z 271.1) corresponding to fragments 109.1, 137.1, and 161.1 is approximately +80V, with optimal cedivisions (CE) of +40eV, +22eV, and +20eV, respectively. Chiricanine A in negative ion mode [M–H]... - The optimized peak voltammetry (DP) values ​​for fragments 109.1, 179.1, and 223.1 of the parent ion (m / z 279.1) were approximately -120V, -120V, and -150V, respectively, with optimal cedivision values ​​of -30eV, -43eV, and -29eV. These optimization results are consistent with the information identified by high-resolution mass spectrometry, and the abundance of each characteristic ion pair was significantly improved.

[0070] Table 13 Characteristic Biomarkers of Peanut Oil and Their Main Reference Mass Spectrometry Parameters

[0071]

[0072] from Figure 2-4 The MRM chromatogram and corresponding characteristic ion pair mass spectra show that alfalfa ketone, santalin, and chiricanine A all exhibit clear chromatographic peaks, and the fragment ion signals are specific and have good intensity, proving that the optimized MRM detection method can be used for subsequent sample analysis.

[0073] An optimized liquid chromatography-tandem mass spectrometry (LC-MS / MS) method was used to detect the three characteristic biomarkers mentioned above in various pure oil samples, excluding peanut oil. These biomarkers were not detected in rapeseed oil, soybean oil, sunflower oil, corn oil, rice bran oil, palm oil, cottonseed oil, camellia seed oil, olive oil, sesame oil, flaxseed oil, and walnut oil. This result verifies the high specificity of the screened biomarkers: they are molecules unique to peanut oil and not present in other common edible vegetable oils. Therefore, the presence of peanut oil components in a sample can be accurately determined based on the detection of any one of alfalfa ketone, stigmata methylphenidate, or chiricanine A, without false positives due to other oil matrices.

[0074] Example 2: Sensitivity Verification of Peanut Oil Characteristic Markers

[0075] Three peanut oil samples and three soybean oil samples were randomly selected and mixed into a series of oil samples with peanut oil content of 0%, 1%, 2%, 5%, 10%, 20%, 50%, and 100% (mass ratio). The molecular marker signals in each mixed sample were detected using an optimized liquid chromatography-tandem mass spectrometry method in MRM mode to evaluate the detection limit (sensitivity) of this method for peanut oil components. By comparing the identifiable responses of the markers at different proportions, the lowest detectable proportion of peanut oil was determined.

[0076] Tests on peanut oil-soybean oil mixtures prepared in different proportions showed that this method has excellent detection sensitivity for peanut oil components (see...). Figure 5-7 Specifically, in three randomly selected peanut oil-soybean oil mixtures, alfalfa ketone was reliably detected at a peanut oil content of 1% (by mass) (the minimum detection rate for all three peanut oil samples was 1%); santalin was detectable at 1% in two samples and 2% in another, therefore the higher value indicates that the marker signal is clearly discernible at at least 2% peanut oil; chiricanine A showed an effective signal at 5% peanut oil in two samples and required 10% in another, thus its minimum detection limit was set at 10%.

[0077] In summary, alfalfa ketone is the most sensitive marker, indicating peanut oil content as low as 1%; chiricanine A has relatively lower sensitivity, and the combination of multiple markers can corroborate each other. In practical applications, the judgment rule is "the detection of any one of the three markers is sufficient to determine the presence of peanut oil," therefore, the overall detection limit for peanut oil using this method is approximately 1%. In other words, even if the edible oil contains approximately 1% peanut oil, the method of this invention can still accurately identify it.

[0078] The experimental results of this invention demonstrate that the selected peanut oil characteristic markers, combined with optimized liquid chromatography-tandem mass spectrometry detection conditions, can achieve highly specific identification and highly sensitive detection of peanut oil components. This method is applicable to various types of edible oils, including single pure oils and blended oils, and has broad application prospects in food identification, quality supervision, and forensic identification.

Claims

1. A method for identifying the components of peanut oil, characterized in that, Includes the following steps: (1) Sample pretreatment: Take vegetable oil sample, add organic solvent to extract, centrifuge and take supernatant, filter to obtain test solution; (2) Liquid chromatography-tandem mass spectrometry detection: The test solution obtained in step (1) is injected into the liquid chromatography-tandem mass spectrometer, and the molecular marker is detected using multiple reaction monitoring mode; (3) Result determination: The retention time, mass spectrometry characteristic ions and relative ion abundance ratio are used as the comprehensive determination criteria. If Chiricanine A in the molecular marker is detected, the sample is determined to contain peanut oil components.

2. The detection method according to claim 1, wherein the molecular marker further includes one or two of alfalfa ketone and santalin.

3. The detection method according to claim 2, wherein the organic solvent in step (1) is 75-90% methanol.

4. The detection method according to claim 2, wherein the organic solvent in step (1) is 80% methanol.

5. The detection method according to any one of claims 1-4, wherein step (1) specifically includes: Accurately weigh the vegetable oil sample, add organic solvent, vortex and shake, centrifuge, and collect the supernatant; The lower oil layer is then repeatedly extracted with an organic solvent, and the supernatant is combined and filtered through an organic phase microporous membrane; the extraction is repeated 2-3 times.

6. The detection method as described in claim 5, wherein step (1) specifically includes: Accurately weigh the vegetable oil sample, add 80% methanol, vortex, centrifuge, and collect the supernatant; The lower oil layer was extracted twice more with 80% methanol. The supernatants were combined and filtered through a 0.22 μm organic phase microporous membrane to obtain the test solution.

7. The detection method according to claim 2, wherein the liquid chromatography conditions in step (2) satisfy the following conditions: (1) Mobile phase A is an aqueous solution containing 0.025% formic acid and 2 mM ammonium acetate, and mobile phase B is a methanol solution containing 0.025% formic acid and 2 mM ammonium acetate; elution gradient: 40% of phase B at 0–1 min; linear gradient increases to 95% B at 1–9 min and is maintained until 13 min; rapidly decreases to 40% B at 13.1 min, and ends equilibrium at 40% B at 15 min; (2) The chromatographic column was a C18 column, 1.8 μm, 100 mm × 2.1 mm; the flow rate was 0.3 mL / min; the column temperature was 40℃; and the injection volume was 2 μL.

8. The detection method as described in claim 7, wherein the mass spectrometry conditions in step (2) satisfy the following conditions: (1) Mass spectrometry acquisition conditions: A triple quadrupole tandem mass spectrometer was used, equipped with an electrospray ionization source, to acquire data in positive ion mode and negative ion mode; (2) Mass spectrometry parameters: The ion source is an electrospray ion source; the ion source temperature is 550℃; the spray voltage is +5500V for positive ion mode and -4500V for negative ion mode; (3) The mass spectrometry detection parameters of the molecular markers are as follows: cloverone retention time 5.4 min, parent ion m / z 301.1, daughter ion m / z 107.0, 135.0 and 163.0; santalin retention time 5.5 min, parent ion m / z 271.1, daughter ion m / z 109.1, 137.1 and 161.1; chiricanine A retention time 6.9 min, parent ion m / z 279.1, daughter ion m / z 109.1, 179.1 and 223.

1.

9. The detection method as described in claim 2, wherein the result judgment criteria in step (3) are: the retention time of the chromatographic peak of the molecular marker in the sample is consistent with that of the standard substance, and the relative deviation is within ±2.5%; the qualitative ion pairs of the molecular marker are consistent with those of the standard substance, and the relative deviation of the ion pair abundance ratio is within the allowable range; The result determination rule is as follows: if Chiricanine A is present in the sample, it is determined that the sample contains peanut oil; if Chiricanine A is not present in the sample, it is determined that the sample does not contain peanut oil.

10. The detection method according to claim 9, wherein the detection limit of Chiricanine A is: a sample containing 10% peanut oil by mass.

11. The detection method according to claim 10, wherein the detection limit of alfalfa ketone is: a sample containing 1% peanut oil by mass; and the detection limit of santalin is: a sample containing 2% peanut oil by mass.

12. Application of Chiricanine A as a molecular marker in the qualitative identification of peanut oil components in edible oils; The edible oils include one or more of the following: peanut oil, rapeseed oil, soybean oil, sunflower seed oil, corn oil, rice bran oil, palm oil, cottonseed oil, camellia seed oil, olive oil, sesame oil, flaxseed oil, walnut oil, or blended edible vegetable oils.

13. Application of the combination of alfalfa ketone, santalin, and chiricanine A as molecular markers for detecting peanut oil components in the qualitative identification of peanut oil components in edible oils; The edible oils include one or more of the following: peanut oil, rapeseed oil, soybean oil, sunflower seed oil, corn oil, rice bran oil, palm oil, cottonseed oil, camellia seed oil, olive oil, sesame oil, flaxseed oil, walnut oil, or blended edible vegetable oils.

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