Screening method of sealwort processing degree markers and marker group

Abstract

The invention discloses a screening method of sealwort processing degree markers and a marker group, and belongs to the technical field of traditional Chinese medicine quantitative analysis. The method comprises the following steps: S1, taking raw rhizoma polygonati and rhizoma polygonati processed products with different processing degrees; s2, respectively detecting the raw rhizoma polygonati and the processed product thereof by using ultra-high performance liquid chromatography and Fourier transform mass spectrometry, and determining metabolite information through MJDBPM; s3, analyzing the metabolite information obtained in the step S2 by using a partial least square method to obtain a potential marker I; s4, analyzing the metabolite information obtained in the step S2 by using a single factor variance analysis method to obtain a potential marker II; and S5, obtaining a potential marker III through an intersection of the steps S3 and S4 by virtue of a Venn graph, further screening by virtue of heat map clustering, and taking the potential marker III with a good clustering effect as a rhizoma polygonati processing degree marker. The chemical components in the rhizoma polygonati in different processing stages are qualitatively and quantitatively analyzed, and reference is provided for quality evaluation of the rhizoma polygonati.

Description

Technical Field

[0001] The invention relates to the technical field of quantitative analysis of traditional Chinese medicines, and in particular to a screening method and a marker group for markers of processing degree of polygonatum sibiricum. Background Art

[0002] Huangjing nourishes qi and yin, and has the effects of strengthening the spleen, moistening the lungs and benefiting the kidneys. Raw Huangjing has a numbing taste and stings the throat, so processed Huangjing is used to reduce its toxicity and enhance its efficacy. It is often used to treat spleen and stomach qi deficiency, lung deficiency and dry cough, internal heat and thirst, etc. As early as the Southern and Northern Dynasties, "Leigong Paozhi Lun" recorded the processing technology of Huangjing single steaming method, and later evolved on this basis into double steaming method and nine steaming and nine drying. In addition, there are many more common processing techniques for Huangjing, such as "Taiping Shenghui Fang" records its wine steaming method, "Lu Fu Jin Fang" records the black bean method, and so on.

[0003] The current "Chinese Pharmacopoeia" (Volume 1 of the 2020 edition) contains the processing methods of processed polygonatum slices, processed polygonatum and wine polygonatum. To process polygonatum, take the medicinal polygonatum collected in spring and autumn, remove the fibrous roots, wash, blanch in boiling water or steam until thoroughly cooked, and dry, which is often called "one steaming and one drying". According to literature records, the number of steaming and drying has a great influence on the content of each component. By controlling the processing process of nine steamings and nine dryings, the content of each component can be adjusted as a basis for quality control. However, the current quality standards for the number of steaming and drying of polygonatum are still mainly based on appearance, color, taste, etc. The lack of quantitative standards leads to large differences in product quality. Therefore, it is necessary to conduct qualitative and quantitative analysis of the chemical components in polygonatum at different processing stages to provide a reference for its quality evaluation. Summary of the invention

[0004] On the one hand, an embodiment of the present invention provides a method for screening markers of processing degree of Polygonatum sibiricum, the method comprising: S1: Take raw Polygonatum sibiricum and processed Polygonatum sibiricum with different processing degrees and prepare test solution.

[0005] S2: Use ultra-high performance liquid chromatography tandem Fourier transform mass spectrometry (UHPLC-FT-MS / MS) to detect the test solutions of raw Polygonatum sibiricum and its processed products, respectively, to obtain the mass spectrum information of the compounds contained, and determine the metabolite information and expression level through Meiji's self-built plant metabolite database MJDBPM (based on the expression level, principal component analysis can be used for preliminary judgment to determine whether to proceed to the subsequent steps).

[0006] S3: The metabolite information obtained in step S2 was analyzed using the partial least squares method (PLS-DA), and the compounds with an absolute value of variable importance projection (VIP) greater than or equal to 1.5 and a p value less than or equal to 0.05 were identified as potential markers.

[0007] S4: One-way analysis of variance (ANOVA) was used to analyze the metabolite information obtained in step S2, and compounds with an absolute value of variable importance projection greater than or equal to 1.5 and a p value less than or equal to 0.05 were identified as potential markers II.

[0008] S5: The potential marker three is obtained by taking the intersection of steps S3 and S4 through the Venn diagram, and then further screened through heat map clustering, and the potential marker three with good clustering effect is used as the marker of the processing degree of Polygonatum sibiricum.

[0009] Among them, processed products of Polygonatum sibiricum with different processing degrees include: "one steaming and one sun-drying" Polygonatum sibiricum to "nine steaming and nine sun-drying" Polygonatum sibiricum. Among them, the preparation method of "one steaming and one sun-drying" Polygonatum sibiricum is: according to the 2020 edition of the "Chinese Pharmacopoeia", take the raw Polygonatum sibiricum, screen and wash (completely remove mud and impurities), steam until the core is cooked, and dry it in the sun. The preparation method of "twice steaming and two sun-drying" Polygonatum sibiricum is: according to the 2020 edition of the "Chinese Pharmacopoeia", "one steaming and one sun-drying" Polygonatum sibiricum is added with rice wine at a ratio of 20% (specifically by mass ratio) and soaked for 12 hours, steamed and dried again to obtain "two steaming and two sun-drying" Polygonatum sibiricum; repeat the above process 1-7 times to obtain "three steaming and three sun-drying" Polygonatum sibiricum to "nine steaming and nine sun-drying" Polygonatum sibiricum.

[0010] The preparation method of the test solution is as follows: take 100 mg of solid sample in a 2 mL centrifuge tube, add grinding beads and 800 μL of extract to obtain the sample solution. The sample solution is ground in a frozen tissue grinder for 6 minutes, and then extracted by low-temperature ultrasound for 30 minutes; the sample is allowed to stand at -20°C for 30 minutes, then centrifuged for 15 minutes, and the supernatant is taken; the extract is a 4:1 volume ratio of methanol and water and contains four internal standards.

[0011] Among them, in the ultra-high performance liquid chromatography-tandem Fourier transform mass spectrometry detection, the chromatographic column separation conditions are: injection volume of 3μl, BEH C18 chromatographic column, column temperature of 40°C, mobile phase A is 2% (volume concentration) acetonitrile aqueous solution, mobile phase B is acetonitrile, and the flow rate is 0.40mL / min. Gradient elution: 0-0.5min, 2% (volume ratio of mobile phase B to eluent); 0.5-7.5min, 2%-35%; 7.5-13min, 35%-95%; 13-14.4min, 95%; 14.4-14.5min, 95%-2%; 14.5-16min, 2%; in mass spectrometry detection, positive and negative ion scanning mode was adopted, and the conditions were: mass scanning range m / z: 70-1050; ion spray voltage, positive ion voltage 3500V, negative ion voltage -3000V, sheath gas 50psi, auxiliary heating gas 13psi, ion source heating temperature 450℃, 20-40-60V cyclic collision energy, MS1 resolution 70000, MS2 resolution 17500.

[0012] Specifically, the mass spectrometry information analysis was processed by the software Progenesis QI, and the metabolite information was determined through the MJDBPM, a plant metabolite database built by Meiji. The processing process of the software Progenesis QI includes: data is imported into the software Progenesis QI for baseline filtering, peak identification, integration, retention time correction and peak alignment, and finally a data matrix of retention time, mass-to-charge ratio and peak intensity is obtained, and then the data matrix is ​​processed as follows: eigenvalue removal, missing value filling, data normalization, QC verification and Log value taking.

[0013] Specifically, in step S3, partial least squares analysis is performed using SIMCA software.

[0014] Specifically, in step S4, one-way ANOVA was performed using the R language ropls package.

[0015] Specifically, in step S5, Venn diagram processing is performed using jvenn software, and heat map clustering is performed using the pheatmap package of the R language.

[0016] Specifically, an embodiment of the present invention provides a method for screening markers of processing degree of Polygonatum sibiricum, the method comprising: S1: Take raw polygonatum and processed polygonatum with different processing degrees and prepare test solution; processed polygonatum with different processing degrees include: "one steaming and one drying" polygonatum to "nine steaming and nine drying" polygonatum.

[0017] S2: Use ultra-high performance liquid chromatography-tandem Fourier transform mass spectrometry to detect the test solutions of raw Polygonatum sibiricum and its processed products, respectively, to obtain the mass spectrometry information of the compounds contained, and determine the metabolite information and expression levels through Meiji's self-built plant metabolite database MJDBPM.

[0018] S3: The metabolite information obtained in step S2 was analyzed using the partial least squares method using SIMCA software, and the compounds with the absolute value of the variable importance projection greater than or equal to 1.5 and the p value less than or equal to 0.05 were identified as potential markers one.

[0019] S4: The metabolite information obtained in step S2 was analyzed using the one-way ANOVA method using the R language ropls package, and the compounds with the absolute value of the variable importance projection greater than or equal to 1.5 and the p value less than or equal to 0.05 were identified as potential markers II.

[0020] S5: Perform Venn diagram analysis using jvenn software, and take the intersection of steps S3 and S4 to obtain potential marker three; perform heat map clustering using the pheatmap package of R language, and use potential marker three with good clustering effect as a marker for the degree of processing of Polygonatum sibiricum. On the other hand, the present invention also discloses a marker group obtained by screening the aforementioned method for screening markers of processing degree of polygonatum, wherein the marker group includes: risperidone, Ps (lte4 / 18:3 (9z, 12z, 15z)), CDP-DG (a-15:0 / i-14:0), Pgp (20:3 (8z, 11z, 14z) / pgd2), ganoderic acid Mg, L-threonine, fangfang pine, 2-feruloyl-1, 2'-dianisinoyl gentiobiose, lansioside B and fasciculicacid C. The model established by the above marker group can realize the judgment of processing degree of polygonatum. It has been verified (the number of polygonatum samples is greater than 50) that the identification of processed polygonatum products can be basically realized by using the marker group and its model for identification.

[0021] The method for discovering quality markers of raw Polygonatum and its processed products of the present invention is based on the non-targeted metabolome of raw Polygonatum and different processing stages, and UHPLC-FT-MS / MS technology is used to identify and analyze the components of raw Polygonatum and Polygonatum at different processing stages. UHPLC-FT-MS / MS technology can detect most of the types of compounds in Polygonatum, and then partial least squares discrimination analysis is performed on ten groups of raw Polygonatum and Polygonatum samples at different processing stages to find differences. This method can accurately analyze the types and relative contents of differential substances through metabolite expression, and then screen the differential substances with p<0.05 as potential differential compounds through the significance of one-way variance analysis. Finally, the accuracy of the method for clustering is improved by Venn diagram and heat map analysis, and the final differential compounds are determined. This method can provide a basis for quality control, efficacy research and clinical use of raw Polygonatum and processed Polygonatum at different stages. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flow chart of the screening method for markers of processing degree of Polygonatum sibiricum; Figure 2 The principal component analysis diagram of raw polygonatum and polygonatum at each processing stage in Example 1 of the present invention; Among them, QC stands for quality control sample, R stands for raw polygonatum, and P1-P9 stand for polygonatum that has been steamed once and dried for one time to steamed nine times and dried for nine times, respectively. Figure 3 The PLS-DA diagram of raw Polygonatum sibiricum and Polygonatum sibiricum at various processing stages in Example 1 of the present invention; Figure 4 It is a cross-validation graph of 200 permutation tests of PLS-DA of raw Polygonatum sibiricum and Polygonatum sibiricum at various processing stages in Example 1 of the present invention; Figure 5 Venn diagram for PLS-DA and ANOVA analysis; Figure 6The differential compound expression calorimeter can distinguish raw polygonatum and polygonatum at different processing stages; Figure 7 This is the expression trend diagram of the markers in raw polygonatum and processed products; Figure 8 A heat map of potential differential compound clusters was drawn for one-way ANOVA only; Fig. 9 To draw cluster heat maps for the analysis of potential differential compounds or total metabolite expression using only PLS-DA; Fig.10 This is a heat map of total expression. DETAILED DESCRIPTION

[0023] Embodiment 1: Embodiment 1 provides a method for screening markers of processing degree of polygonatum, comprising the following steps: 1. Instruments and reagents 1.1 Instrument Ultra-high performance liquid chromatography-tandem Fourier transform mass spectrometry (UHPLC-QExactive) was purchased from Thermo Fisher Scientific; BEHC18 chromatographic column (100 mm × 2.1 mm i.d., 1.7 µm) was purchased from Waters Corporation; BEHAmide chromatographic column (100 mm × 2.1 mm i.d., 1.7 µm) was purchased from Waters Corporation; JXDC-20 nitrogen purge instrument was purchased from Shanghai Jingxin Industrial Development Co., Ltd.; LNG-T88 desktop rapid centrifugal concentrator and dryer was purchased from Taicang Huamei Biochemical Instrument Factory; Wonbio-96c high-throughput tissue disruptor was purchased from Shanghai Wanbo Biotechnology Co., Ltd.; SBL-10DT ultrasonic cleaner 300W-10L was purchased from Ningbo Xinzhi Biotechnology Co., Ltd.; Centrifuge5430R high-speed refrigerated centrifuge was purchased from Eppendorf, Germany; and NewClassicMFMS105DU electronic balance was purchased from Mettler, Switzerland.

[0024] 1.2 Reagents Chromatographic grade methanol (Fisher), chromatographic grade acetonitrile (Fisher), chromatographic grade formic acid (Fisher), chromatographic grade water (Fisher), chromatographic grade propanol (Fisher).

[0025] The nine-steamed and nine-dried Polygonatum sample comes from Hubei Lingzhou Pharmaceutical Co., Ltd.

[0026] 2 Methods and Results 2.1 Sample preparation Take 100 mg of sample dry powder in a 2 mL centrifuge tube and add a grinding bead with a diameter of 6 mm. 800 μL of extract (methanol: water = 4:1 (v:v)) containing four internal standards (L-2-chlorophenylalanine (0.02 mg / mL), etc., which is a conventional technique) is used to extract metabolites. The sample solution is ground in a frozen tissue grinder for 6 minutes (-10°C, 50 Hz), and then low-temperature ultrasonic extraction is performed for 30 minutes (5°C, 40 kHz). The sample is placed at -20°C for 30 minutes, centrifuged for 15 minutes (4°C, 13000g), and the supernatant is transferred to a vial with an inner insert for analysis.

[0027] 2.2 Establishment of liquid quality conditions 2.2.1 Liquid phase conditions The injection volume was 3 μL; the sample was separated by a BEH C18 column (100 mm×2.1 mm id, 1.7 µm) and then entered the mass spectrometer detection. Mobile phase A was 2% acetonitrile water (containing 0.1% formic acid), and mobile phase B was acetonitrile (containing 0.1% formic acid). The gradient conditions were as follows: 0-0.5 min, mobile phase B maintained at 2%; 0.5-7.5 min, mobile phase B increased from 2% to 35%; 7.5-13 min, mobile phase B increased from 35% to 95%; 13-14.4 min, mobile phase B maintained at 95%; 14.4-14.5 min, mobile phase B decreased from 95% to 2%; 14.5-16 min, mobile phase B maintained at 2%. The flow rate was 0.40 mL / min, and the column temperature was 40 °C.

[0028] 2.2.2 Mass spectrometry conditions Positive and negative ion scanning modes were used, with a mass scanning range of m / z: 70-1050. Ion spray voltage, positive ion voltage 3500V, negative ion voltage -3000V, sheath gas 50psi, auxiliary heating gas 13psi, ion source heating temperature 450℃, 20-40-60V cycle collision energy, MS1 resolution 70000, MS2 resolution 17500.

[0029] 2.3 Chemometric analysis 2.3.1 Data preprocessing The data from LC-MS were imported into the metabolomics processing software Progenesis QI (Waters Corporation, Milford, USA) for baseline filtering, peak identification, integration, retention time correction, and peak alignment. Finally, a data matrix of retention time, mass-to-charge ratio, and peak intensity was obtained. The data matrix was processed as follows: removing eigenvalues ​​(missing values ​​in each group>20%), filling missing values ​​(minimum values ​​of each sample group), data normalization (sum normalization method), QC verification (RSD≤30%), and Log value (log10). 905 ion peaks were detected in positive ion mode, 2066 ion peaks were detected in negative ion mode, and 2936 ion peaks in mixed mode. 326 compounds were annotated by MJDBPM, the self-built library of Meiji Biotechnology, and the computer-simulated MS / MS secondary spectral library, and .xls format files were obtained.

[0030] 2.3.2 Principal Component Analysis (PCA) The software SIMCA (version: 14.1) was used to perform principal component analysis (PCA) on the preprocessed data matrix. PCA is a multidimensional data statistical analysis method for unsupervised pattern recognition. A set of variables that may be correlated is converted into a set of linearly uncorrelated variables through orthogonal transformation. The converted set of variables is called principal components. The present invention uses the relative peak areas of 2936 components of 10 batches of Polygonatum sibiricum from raw to nine-steaming and nine-drying as variables to perform PCA to identify different processing stages. The results showed that the cumulative contribution rate of the five principal components was 82.7%. The constructed score graph is shown in Figure 2 The distance between sample points represents the similarity of the compounds in different processing stages of Polygonatum odoratum, that is, the closer the distance, the more similar the components. The results show that there are large differences between raw and three-steamed and three-dried Polygonatum odoratum, and the chemical compositions of four-steamed and four-dried Polygonatum to nine-steamed and nine-dried Polygonatum odoratum are similar, but can be distinguished by PCA.

[0031] 2.3.3 Partial Least Squares Discriminant Analysis (PLS-DA) The software SIMCA (version: 14.1) was used to establish a PLS-DA model for the preprocessed data matrix to screen the key quality markers of Polygonatum sibiricum at different processing stages. Figure 3 As shown, the PLS-DA model has R2X=0.96, R2Y=0.984, and Q2=0.856, indicating that the model is stable and has good predictive ability. A total of 14 principal components were identified in the model. Figure 4200 permutation tests were performed. Due to the small number of samples in the group, the intercept was greater than 0.05, but the regression line showed an upward trend, which also showed that the model did not have overfitting. The chemical components of Polygonatum sibiricum at different processing stages were sorted by VIP value, and 28 significant differential components (VIP value ≥ 1.5) were screened out.

[0032] 2.3.4 One-way Analysis of Variance (ANOVA) One-way ANOVA was performed using the R language ropls package to screen components with VIP values ​​≥ 1.5 and p < 0.05 as potential differential components. The results showed that a total of 25 potential differential components were screened out.

[0033] 2.3.5 Venn diagram analysis Use jvenn and PLS-DA to perform Venn diagram analysis on the differential components, such as Figure 5 As shown, there are 22 common potential differential compounds.

[0034] 2.3.6 Heatmap Clustering The R language pheatmap package was used to draw a heat map of the above 22 potential differential compounds, and the compounds that could obtain good clustering results were screened as quality markers of Polygonatum sibiricum at different processing stages. Figure 6 As shown, a total of 10 compounds were screened, namely: risperidone, Ps(lte4 / 18:3(9z,12z,15z)), CDP-DG(a-15:0 / i-14:0), Pgp(20:3(8z,11z,14z) / pgd2), ganoderic acid Mg, L-threonine, fangfang pine, 2-feruloyl-1,2'-dianisinoyl gentiobiose, lansioside B and fasciculicacid C.

[0035] The expression trends of the above ten quality markers in raw Polygonatum and its processed products are as follows: Figure 7 As shown. Among them, L-threonine showed a downward trend in the processed products as a whole, and there were significant differences in the P8 and P9 stages, reaching the lowest value in P9; Pgp (20:3 (8z, 11z, 14z) / pgd2), CDP-DG (a-15:0 / i-14:0), and Lansioside B showed the same trend, and reached the highest content in the "one steaming and one sun-drying" Polygonatum. For the "four steaming and four sun-drying" to "eight steaming and eight sun-drying" Polygonatum, which is more difficult to distinguish, in the P5 stage, in addition to the lower expression of Lansioside B, the expression content of 2-feruloyl-1, 2'-dianisinoyl gentiobiose was higher, which can be distinguished from P8, the highest expression of ganoderic acid Mg was in the P6 stage, and the highest expression of fasciculic acid C was in the P7 stage.

[0036] Comparative Example 1 The R language pheatmap package was used to draw the cluster heat map of potential differential compounds in ANOVA and PLS-DA analysis. Only one-way ANOVA was used to draw the cluster heat map of potential differential compounds. The clustering results are shown in Figure 8. The "two steaming and two drying", "four steaming and four drying", "five steaming and five drying" and "seven steaming and seven drying" Polygonatum sibiricum could not be clustered into one branch.

[0037] Only PLS-DA was used to analyze the potential differential compounds or total metabolite expression levels to draw a cluster heat map. The clustering results are shown in Figure 9. The "four steaming and four drying", "five steaming and five drying" and "seven steaming and seven drying" Polygonatum sibiricum could not be clustered into one branch.

[0038] That is, in this patent, the screening by Venn diagram can not only reduce the amount of data (from Fig.10 It can be seen that the amount of data is very large and clustering is difficult), and it can also improve the accuracy of quality marker screening (this patent can achieve complete clustering).

[0039] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for screening markers of processing degree of Polygonatum sibiricum, characterized in that: The method comprises: S1: Take raw polygonatum and processed polygonatum with different processing degrees and prepare test solution; S2: Use ultra-high performance liquid chromatography-tandem Fourier transform mass spectrometry to detect the test solutions of raw Polygonatum sibiricum and its processed products, obtain the mass spectrometry information of the compounds contained, and determine the metabolite information and expression level through the MJDBPM, a proprietary plant metabolite database built by Meiji; S3: using partial least squares method to analyze the metabolite information obtained in step S2, compounds with absolute values ​​of variable importance projection greater than or equal to 1.5 and p-values ​​less than or equal to 0.05 are determined as potential markers 1; S4: using one-way ANOVA to analyze the metabolite information obtained in step S2, and determining the compounds with the absolute value of variable importance projection greater than or equal to 1.5 and p-value less than or equal to 0.05 as potential marker 2; S5: The potential marker three is obtained by taking the intersection of steps S3 and S4 through the Venn diagram, and then further screened through heat map clustering, and the potential marker three with good clustering effect is used as the marker of the processing degree of Polygonatum sibiricum.

2. The method for screening markers of processing degree of Polygonatum sibiricum according to claim 1, characterized in that: The processed products of Polygonatum odoratum with different processing degrees include: "one steaming and one drying" Polygonatum odoratum to "nine steaming and nine drying" Polygonatum odoratum; The preparation method of the "steaming and drying" polygonatum is as follows: according to the 2020 edition of the Chinese Pharmacopoeia, raw polygonatum is selected, cleaned, steamed until the core is cooked, and dried in the sun; The preparation method of the "twice-steamed and twice-dried" polygonatum is as follows: according to the 2020 edition of the "Chinese Pharmacopoeia", the "one-steamed and one-dried" polygonatum is added with rice wine at a ratio of 20% and soaked for 12 hours, steamed and dried again to obtain the "twice-steamed and twice-dried" polygonatum; and the above process is repeated 1-7 times to obtain the "three-steamed and three-dried" to "nine-steamed and nine-dried" polygonatum.

3. The method for screening markers of processing degree of Polygonatum sibiricum according to claim 1, characterized in that: The preparation method of the test solution is: Take 100 mg of solid sample in a 2 mL centrifuge tube, add grinding beads and 800 μL of extract to obtain the sample solution; grind the sample solution in a frozen tissue grinder for 6 minutes, and then extract it by low-temperature ultrasound for 30 minutes; let the sample stand at -20°C for 30 minutes, then centrifuge for 15 minutes, and take the supernatant; the extract is a mixture of methanol and water in a volume ratio of 4:1 and contains four internal standards.

4. The method for screening markers of processing degree of Polygonatum sibiricum according to claim 1, characterized in that: In the ultra-high performance liquid chromatography tandem Fourier transform mass spectrometry detection, The chromatographic column separation conditions were as follows: injection volume 3 μl, BEH C18 chromatographic column, column temperature 40 °C, mobile phase A 2% acetonitrile aqueous solution, mobile phase B acetonitrile, flow rate 0.40 mL / min; gradient elution: 0-0.5 min, 2%; 0.5-7.5 min, 2%-35%; 7.5-13 min, 35%-95%; 13-14.4 min, 95%; 14.4-14.5 min, 95%-2%; 14.5-16 min, 2%; In mass spectrometry detection, positive and negative ion scanning modes were used with the following conditions: mass scanning range m / z: 70-1050; ion spray voltage, positive ion voltage 3500 V, negative ion voltage -3000 V, sheath gas 50 psi, auxiliary heating gas 13 psi, ion source heating temperature 450 °C, 20-40-60 V cyclic collision energy, MS1 resolution 70000, MS2 resolution 17500.

5. The method for screening markers of processing degree of Polygonatum sibiricum according to claim 1, characterized in that: The mass spectrometry information analysis was processed using the software Progenesis QI, and the metabolite information was determined using the MJDBPM, a plant metabolite database built by Meiji; The processing process of the software Progenesis QI includes: data is imported into the software Progenesis QI for baseline filtering, peak identification, integration, retention time correction and peak alignment, and finally a data matrix of retention time, mass-to-charge ratio and peak intensity is obtained, and then the data matrix is ​​processed as follows: eigenvalue removal, missing value filling, data normalization, QC verification and Log value taking.

6. The method for screening markers of processing degree of Polygonatum sibiricum according to claim 1, characterized in that: In step S3, partial least squares analysis is performed using SIMCA software.

7. The method for screening markers of processing degree of Polygonatum sibiricum according to claim 1, characterized in that: In step S4, one-way ANOVA was performed using the ropls package in R language.

8. The method for screening markers of processing degree of Polygonatum sibiricum according to claim 1, characterized in that: In step S5, Venn diagram processing is performed using jvenn software, and heat map clustering is performed using the pheatmap package of the R language.

9. The method for screening markers of processing degree of Polygonatum sibiricum according to claim 1, characterized in that: The method comprises: S1: Take raw polygonatum and processed polygonatum with different processing degrees and prepare test solution; processed polygonatum with different processing degrees include: "one steaming and one drying" polygonatum to "nine steaming and nine drying" polygonatum; S2: Use ultra-high performance liquid chromatography-tandem Fourier transform mass spectrometry to detect the test solutions of raw Polygonatum sibiricum and its processed products, obtain the mass spectrometry information of the compounds contained, and determine the metabolite information and expression level through the MJDBPM, a proprietary plant metabolite database built by Meiji; S3: Analyze the metabolite information obtained in step S2 using the partial least squares method using SIMCA software, and identify the compounds with the absolute value of the variable importance projection greater than or equal to 1.5 and the p value less than or equal to 0.05 as potential markers 1; S4: The metabolite information obtained in step S2 was analyzed using the one-way ANOVA method using the R language ropls package, and the compounds with the absolute value of the variable importance projection greater than or equal to 1.5 and the p value less than or equal to 0.05 were identified as potential markers II; S5: Perform Venn diagram analysis using jvenn software, and take the intersection of steps S3 and S4 to obtain potential marker three; perform heat map clustering using the pheatmap package of R language, and use potential marker three with good clustering effect as a marker for the degree of processing of Polygonatum sibiricum.

10. The marker group obtained by screening the method for screening markers of processing degree of polygonatum sibiricum according to claim 1, characterized in that: The marker group includes: risperidone, Ps (lte4 / 18:3 (9z, 12z, 15z)), CDP-DG (a-15:0 / i-14:0), Pgp (20:3 (8z, 11z, 14z) / pgd2), ganoderic acid Mg, L-threonine, fangfang pine, 2-feruloyl-1,2'-dianisinoyl gentiobiose, lansioside B and fasciculicacid C.

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