Birch bark quality comprehensive evaluation method based on fingerprint spectrum in combination with chemometrics and quantitative analysis of multi-components by single marker

Abstract

The invention provides a birch bark quality comprehensive evaluation method based on combination of a fingerprint spectrum, chemometrics and a quantitative analysis of multiple components by single marker, and relates to the technical field of quality control and evaluation of birch bark. Comprising the following five steps: preparing a birch bark sample, setting chromatography and mass spectrometry conditions, generating a fingerprint spectrum and evaluating similarity, analyzing chemometrics data, and carrying out quantitative analysis by using a single-marker multi-evaluation method. Multiple components can be quantified at the same time, and the quality of the birch bark is comprehensively evaluated. The multi-component analysis mode can cover the key effective components in the medicinal materials, so that the quality evaluation deviation caused by neglecting other components is avoided, and the reference can be provided for the quality control and evaluation of the birch bark accurately, simply and conveniently in combination with a chemometrics method through the established birch bark fingerprint spectrum and the multi-index component determination method.

Description

Technical Field

[0001] The present invention relates to the technical field of birch bark quality control and evaluation, and in particular to a birch bark quality comprehensive evaluation method based on fingerprint spectrum combined with chemometrics and a one-test-multiple-evaluation method. Background Art

[0002] Birch bark (Betula platyphylla Suk) is the dried, soft outer bark of the Betula genus, a member of the Betulaceae family. It has a long history, having been documented as early as the Song Dynasty's Kaibao Compendium of Materia Medica. It is widely used in Traditional Chinese Medicine as a traditional Chinese medicinal material. Birch bark has multiple pharmacological effects, including clearing heat and dampness, detoxifying, expectorating and relieving coughs, and relieving pain and carbuncle. It is commonly used to treat ailments such as cough and asthma, sore throat, diarrhea, intestinal carbuncle, mastitis, burns, scalds, and sores. Modern pharmacological studies have shown that birch bark has significant pharmacological effects and exhibits multiple biological activities, including anti-inflammatory, antioxidant, and hypoglycemic properties.

[0003] Birch bark is included in the "Jilin Province Traditional Chinese Medicine Standard" (2019 edition). The quality of birch bark is closely related to factors such as its origin, harvesting method, and processing technology. The chemical composition of birch bark is complex and diverse, mainly including natural products such as betulin, betulic acid, betulinal, oleanolic acid, and its derivatives. These components not only determine the pharmacological effects of birch bark but also affect its overall quality.

[0004] Traditional quality control methods often rely on the determination of a single marker, such as the content of betulin or betulic acid. However, birch bark contains a variety of active ingredients, each of which plays a different role in drug efficacy, and a single marker cannot fully reflect the overall quality of birch bark. For example, betulin has a high content in birch bark and is a marker commonly used for quantitative analysis, but the remaining ingredients such as oleanolic acid and lupeol also play an important role in the drug efficacy of birch bark. Therefore, the detection of a single component easily ignores the influence of other key components and cannot truly achieve comprehensive quality control of birch bark. Then how to systematically and comprehensively evaluate the quality of birch bark has become a hot topic and difficulty in current research on quality control of traditional Chinese medicine. Therefore, the present invention proposes a comprehensive evaluation method for birch bark quality based on fingerprint spectrum combined with chemometrics and a one-measurement-multiple-evaluation method to solve the problems existing in the prior art. Summary of the Invention

[0005] In response to the above problems, the purpose of the present invention is to propose a comprehensive evaluation method for birch bark quality based on fingerprint spectrum combined with chemometrics and one-measurement-multiple-evaluation method. This comprehensive evaluation method for birch bark quality based on fingerprint spectrum combined with chemometrics and one-measurement-multiple-evaluation method can not only improve the analysis efficiency, but also ensure the stability and reliability of the quality of traditional Chinese medicine, thereby solving the problems in the prior art.

[0006] To achieve the purpose of the present invention, the present invention is implemented by the following technical solution: a comprehensive evaluation method for birch bark quality based on fingerprint spectrum combined with chemometrics and one-measurement-multiple-evaluation method, comprising the following steps:

[0007] Step 1: Prepare birch bark samples

[0008] Collecting several groups of birch bark samples, grinding and drying them to obtain birch bark dried medicinal material powder, then using the birch bark dried medicinal material powder to prepare a test solution, and then preparing a mixed reference solution;

[0009] Step 2: Set up chromatography and mass spectrometry conditions

[0010] First, the chromatographic analysis conditions were set to use a Waters ACQUITY UPLC HSS T3 column, with a 0.1% formic acid aqueous solution (A)-0.1% formic acid acetonitrile (B) mobile phase, gradient elution, a flow rate of 0.3 mL / min, a column temperature of 40°C, and an injection volume of 10 μL. Then, the mass spectrometry conditions were set to use an electrospray ion source, the fingerprint scan type was SCAN mode, and the multi-component content determination scan type was MRM mode.

[0011] Step 3: Generate fingerprint and evaluate similarity

[0012] Under the conditions set in step 2, the test solution and the reference solution obtained in step 1 were subjected to chromatographic determination to obtain chromatographic data, which were then processed and analyzed using a traditional Chinese medicine chromatographic fingerprint similarity evaluation system to establish a birch bark UPLC fingerprint, and then similarity evaluation was performed;

[0013] Step 4: Perform chemometric data analysis

[0014] Based on the birch bark UPLC fingerprint data from step three, a hierarchical cluster analysis method was used to group the birch samples, showing the impact of different origins and processing methods on quality. Then, principal component analysis was performed to evaluate the differences in chemical composition of different batches of birch bark and extract the main components affecting birch bark quality. Finally, supervised discriminant analysis was performed using an orthogonal partial least squares discriminant analysis model to reveal the key components that cause quality differences between different batches of birch bark.

[0015] Step 5: Conduct quantitative analysis using the one-test-multiple-evaluation method

[0016] Betulin was used as an internal reference for QAMS quantitative analysis, and relative correction factors of other components were established. Then, the external standard method and the one-measurement-multiple-evaluation method were used to determine the contents of other components, respectively, to verify the reliability of the results and complete the comprehensive evaluation of birch bark quality.

[0017] A further improvement is that in step 1, the specific method of preparing the sample solution is: taking 45 kg of dried birch bark medicinal powder, adding 4 times the amount of 95% ethanol, soaking and extracting at room temperature three times, each time with an interval of 72 hours, filtering, combining the three extracts, concentrating under reduced pressure at 55°C, and drying to obtain an extract, and then adding methanol to dissolve and dilute the extract to a solution containing 1 mg of birch bark medicinal powder per 1 mL, which is used as the test solution.

[0018] A further improvement is that in step 1, the specific method of preparing the reference solution is:

[0019] Take 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane, betulinic acid, betulin, erythrodiol, betulin aldehyde, oleanolic acid 3-acetate, and lupeol reference substances, place them in 10 mL volumetric flasks, add methanol to dissolve and shake, and adjust the volume to prepare mixed reference substance solutions with mass concentrations of 3.042 μg / mL, 10.11 μg / mL, 27.46 μg / mL, 8 μg / mL, 2.104 μg / mL, 10.02 μg / mL, and 7.014 μg / mL, respectively.

[0020] A further improvement is that in step 2, the elution gradient is specifically as follows: 0-18 min, 5%→25% B; 18-20 min, 25%→40% B; 20-26 min, 40%→60% B; 26-31 min, 60%→65% B; 31-36 min, 65% B; 36-60 min, 65%→80% B; 60-61 min, 80%→95% B; 61-80 min, 95% B; 80-81 min, 95%→5% B; 81-85 min, 5% B.

[0021] Further improvements are as follows: in step 3, in the Chinese medicine chromatographic fingerprint similarity evaluation system, the time window width is set to 0.1 min, and the average method is used to perform multi-point correction and Mark peak matching to establish the birch bark UPLC fingerprint.

[0022] Further improvement lies in: in the step 4, the specific method of the systematic cluster analysis method is: using SPSS27.0 software, taking the peak area information of several groups of common peaks in the birch bark UPLC fingerprint data as variables, performing standardization processing, selecting the inter-group linkage method, and using the square Euclidean distance for cluster analysis.

[0023] Further improvement lies in: in the step 4, the specific method of principal component analysis is: using SPSS27.0 software, with the peak area information of several groups of common peaks in the birch bark UPLC fingerprint data as variables, standardization processing is performed, and then the KMO test and Bartlett test are performed. Then, according to the principle of extracting the number of principal components, the factors with eigenvalues greater than 1 are taken as the principal components.

[0024] A further improvement is that in step 4, the specific method of supervised discriminant analysis is: using the peak area information of several groups of common peaks in the birch bark UPLC fingerprint data as variables to form a new C×D matrix, and performing OPLS-DA analysis on the matrix, where C is the number of samples and D is the number of common peaks.

[0025] A further improvement is that in step five, the other ingredients include betulinic acid, betulinal, oleanolic acid 3-acetate, erythrodiol, lupeol, and 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane.

[0026] The beneficial effects of the present invention are:

[0027] (1) The present invention combines fingerprint technology, a single measurement, multiple evaluation method (QAMS), and chemometric analysis to simultaneously quantify multiple components and comprehensively evaluate the quality of birch bark. This multi-component analysis method can cover the key active ingredients in the medicinal material and avoid the quality assessment bias caused by ignoring other components. The established birch bark fingerprint and multi-index component determination method can accurately and simply provide a reference for the quality control and evaluation of birch bark in combination with chemometric methods.

[0028] (2) This invention improves the scientificity and objectivity of quality assessment by introducing modern chemical analysis technology and data mining methods. The combination of chemometric methods and fingerprints makes quality control not only more accurate, but also more reproducible and operable. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic flow chart of the steps of the present invention.

[0030] Figure 2 It is a schematic diagram of the UPLC fingerprint spectrum and the reference spectrum of the birch bark extract of the present invention.

[0031] Figure 3 It is a schematic diagram of cluster analysis of birch bark birch medicinal materials of the present invention.

[0032] Figure 4 Schematic diagram of birch bark principal component analysis gravel of the present invention.

[0033] Figure 5Schematic diagram of birch bark OPLS-DA analysis of the present invention.

[0034] Figure 6 It is a schematic diagram of the contents of seven components in birch bark measured by the ESM method and the QAMS method of the present invention. DETAILED DESCRIPTION

[0035] In order to deepen the understanding of the present invention, the present invention will be further described in detail below with reference to the examples. The examples are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0036] Traditional quality control methods often rely on the determination of a single marker, such as betulin or betulic acid. However, birch bark contains multiple active ingredients, each of which plays a different role in its efficacy, and a single marker cannot fully reflect the overall quality of birch bark. For example, betulin is present in high levels in birch bark and is a marker commonly used for quantitative analysis, but other components such as oleanolic acid and lupeol also play an important role in the efficacy of birch bark. Therefore, the detection of a single component easily overlooks the impact of other key components and cannot truly achieve comprehensive quality control of birch bark.

[0037] At the same time, the chemical composition of traditional Chinese medicine is complex and diverse. Traditional methods usually only perform quantitative analysis on several main components, while ignoring the influence of other components. As an important Chinese medicinal material, birch bark needs to be comprehensively evaluated from multiple dimensions for quality control. Traditional single marker analysis methods can no longer meet the needs of modern Chinese medicine quality control. Therefore, the quality evaluation system based on fingerprint analysis, chemometric analysis and one-measurement-multiple-evaluation method of the present invention provides a more comprehensive, scientific and efficient solution. This novel quality control method can not only improve the analysis efficiency, but also ensure the stability and reliability of the quality of Chinese medicinal materials, providing solid technical support for the sustainable development of the Chinese medicine industry.

[0038] In the following examples, the instruments and reagents involved are described:

[0039] XPE26 electronic balance (Mettler-Toledo Instrument Co., Ltd., 1 / 100,000); Waters AcquityUPLC ultrahigh performance liquid chromatograph (Waters Corporation, USA); Waters Q-TOF-MS / MS mass spectrometer (Waters Corporation, USA); ACQUITYUPLC HSS T3 chromatographic column (Waters Corporation, USA, 100×2.1 mm×1.7 μm); YMC-Triart PFP chromatographic column (YMC Corporation, Japan, 100×2.1 mm×1.9 μm); KQ-1000E ultrasonic cleaning machine (Kunshan Ultrasonic Instrument Co., Ltd.).

[0040] The reference substances betulinal (batch number BHZQ20200707) and betulinol (batch number BHZC20200322) were purchased from Nanjing Chunqiu Bioengineering Co., Ltd., betulic acid (batch number wkq20052806) was purchased from Sichuan Weikeqi Biotechnology Co., Ltd., erythrodiol (batch number DST200919-068), lupeol (batch number DSTDY011001), oleanolic acid 3-acetate (batch number DST230831- 130) and 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane (batch number DST220226-339) were purchased from Chengdu Desit Biotechnology Co., Ltd., with all reference standards having a mass fraction of ≥98%. Methanol and acetonitrile were purchased from Thermo Fisher Scientific Inc., China, LC-MS grade; formic acid was purchased from Thermo Fisher Scientific Inc., China, chromatography grade; and Yibao purified water was purchased from China Resources Yibao Beverage Co., Ltd., China. All other reagents were of analytical grade. Source information for birch bark medicinal materials is shown in Table 1.

[0041] Table 1 Birch bark medicinal material sample information

[0042]

[0043]

[0044] according to Figures 1-6 As shown, this embodiment proposes a comprehensive evaluation method for birch bark quality based on fingerprint spectrum combined with chemometrics and one-measurement-multiple-evaluation method, which includes the following steps:

[0045] Step 1: Prepare birch bark samples

[0046] Several groups of birch bark samples were collected. In this embodiment, 30 groups of birch bark samples were used as a benchmark, and they were ground and dried to obtain birch bark dried medicinal material powder. The birch bark dried medicinal material powder was then used to prepare the test solution, and then the mixed reference solution was prepared.

[0047] The specific method for preparing the sample solution is as follows: 45 kg of dried birch bark medicinal powder is added with 4 times the amount of 95% ethanol, and the mixture is soaked and extracted three times at room temperature, with an interval of 72 hours between each extraction. The extracts are then filtered, and the three extracts are combined. The extract is concentrated under reduced pressure at 55°C and dried to obtain an extract. The extract is then dissolved and diluted with methanol until a solution containing 1 mg of birch bark medicinal powder per 1 mL is used as the test solution.

[0048] The specific method for preparing the reference solution is:

[0049] Take 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane, betulinic acid, betulin, erythrodiol, betulin aldehyde, oleanolic acid 3-acetate, and lupeol reference substances, place them in 10 mL volumetric flasks, add methanol to dissolve and shake, and adjust the volume to prepare mixed reference substance solutions with mass concentrations of 3.042 μg / mL, 10.11 μg / mL, 27.46 μg / mL, 8 μg / mL, 2.104 μg / mL, 10.02 μg / mL, and 7.014 μg / mL, respectively.

[0050] Step 2: Set up chromatography and mass spectrometry conditions

[0051] First, the chromatographic analysis conditions were set to use a Waters ACQUITY UPLC HSS T3 (100×2.1mm×1.7μm) chromatographic column, and 0.1% formic acid aqueous solution (A)-0.1% formic acid acetonitrile (B) as the mobile phase, gradient elution, a flow rate of 0.3mL / min, a column temperature of 40°C, and an injection volume of 10μL. Then, the mass spectrometry conditions were set to use an electrospray ion source (ESI+), the fingerprint scan type was SCAN mode, the multi-component content determination scan type was MRM mode, the scanning range was m / z 50-1200Da; capillary voltage was 2kV; cone voltage was 20V; ion source temperature was 120°C; drying gas temperature was 500°C; cone gas flow rate was 50L / h; drying gas flow rate was 500L / h; and the flow rate was 5μL / min. In the MSE mode, the trap collision energy of the low-energy function was set to 6 eV, and the high-energy corresponding function of the slope-trap collision energy was set to 20–40 eV (ESI+).

[0052] The elution gradient is as follows: 0-18 min, 5%→25% B; 18-20 min, 25%→40% B; 20-26 min, 40%→60% B; 26-31 min, 60%→65% B; 31-36 min, 65% B; 36-60 min, 65%→80% B; 60-61 min, 80%→95% B; 61-80 min, 95% B; 80-81 min, 95%→5% B; 81-85 min, 5% B, which means that from 0 to 18 minutes, the concentration of component B in the mobile phase increases from 5% to 25%, and then from 18 to 20 minutes, the concentration of component B increases from 25% to 40%, and so on.

[0053] Step 3: Generate fingerprint and evaluate similarity

[0054] Under the conditions set in step 2, the test solution and the reference solution obtained in step 1 were subjected to chromatographic determination to obtain chromatographic data, which were then processed and analyzed using a traditional Chinese medicine chromatographic fingerprint similarity evaluation system to establish a birch bark UPLC fingerprint, and then similarity evaluation was performed;

[0055] Specifically, 30 batches of birch bark extract test solutions were prepared and measured under the conditions of step 2. The chromatographic data were imported into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System (2012.130723 Edition) Software" in CDF format for processing and analysis. Figure 2 As shown, Figure 2 A is the UPLC fingerprint of birch bark extract, and B is the reference spectrum. Using the sample S7 spectrum as the reference spectrum, the time window width was set to 0.1 min, the average method was used, multi-point calibration and Mark peak matching were performed, 30 batches of birch bark UPLC fingerprints were established and the fingerprint spectrum R was generated (see Figure 2 ), and then similarity evaluation was performed. The results showed that the similarity of 30 batches of birch bark extract samples (S1~S30) was between 0.921 and 1.000, indicating that the quality of birch bark medicinal materials from different origins was stable. After Mark peak matching, 25 common peaks were identified. Through mass spectrum information and comparison with the mixed reference solution spectrum, 7 common peaks were confirmed, including peak 14 (3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane), peak 16 (betulic acid), peak 17 (betulinol), peak 18 (erythrodiol), peak 21 (oleanolic acid 3-acetate), peak 22 (betulaldehyde), and peak 25 (lupeol). Among them, peak 17 (betulic acid) was well separated, with a stable peak shape and high response, so it was used as the reference peak (S).

[0056] Step 4: Perform chemometric data analysis

[0057] Based on the birch bark UPLC fingerprint data from step three, the birch samples were grouped using a systematic cluster analysis method to show the impact of different origins and processing methods on quality. Principal component analysis was then performed to evaluate the chemical composition differences between different batches of birch bark and extract the main components affecting the quality of birch bark. Finally, an orthogonal partial least squares discriminant analysis model was used for supervised discriminant analysis to reveal the key components that contribute to the quality differences between different batches of birch bark.

[0058] Specifically, the specific method of the systematic cluster analysis method is as follows: using SPSS27.0 software, the peak area information of 25 common peaks of 30 batches of birch bark extracts was used as the variable, the clustering method selected the inter-group linkage method, the cluster distance used the squared Euclidean distance, and after standardization, cluster analysis was performed. The results are as follows Figure 3As shown in the figure, the 30 batches of birch bark samples can be divided into two major categories and five minor categories: when the cluster distance is 25, S1-S3 are clustered into a major category (I), and the other samples are clustered into a major category (II); when the cluster distance is 5, S1-S3 are clustered into a minor category (a), S4-S6 and S9 are clustered into a minor category (b), S7-S8 and S10-S12 are clustered into a minor category (c), S16-S25 are clustered into a minor category (d), and S13-S15 and S26-S30 are clustered into a minor category (e). From the overall observation of the data, the quality of birch bark medicinal materials from different batches varies to a certain extent, which may be related to factors such as the origin, harvest period, growth age, and differences between cultivated and wild varieties.

[0059] The specific method of principal component analysis is as follows: the peak area of the common peak of 30 batches of birch bark fingerprints is used as a variable, and after standardization processing using SPSS27.0 software, the KMO test and Bartlett test are first performed, and the KMO measurement value is 0.647, P<0.001. According to the principle of extracting the number of principal components, the factors with eigenvalues greater than 1 are taken as principal components. In this embodiment, 5 principal components are extracted, and their cumulative variance contribution rate reaches 91.157%, indicating that principal components 1 to 5 can represent most of the information of the common peak of birch bark. The relevant information is shown in Table 2. Combined with the total variance interpretation results, the scree plot ( Figure 4 ), the steepness of the curve slows down significantly from the sixth principal component, indicating that the analysis results of the first five principal components can fully reflect the basic characteristic values and main information of the 25 common peaks, and can be used as a differential variable to reflect the overall quality of birch bark batches from different origins. Table 2 is shown below:

[0060] Table 2 Principal component analysis eigenvalues and variance contribution rates

[0061]

[0062] The specific method of supervised discriminant analysis is as follows: using the peak area information of several groups of common peaks in the birch bark UPLC fingerprint data as variables, a new C×D matrix is formed, and OPLS-DA analysis is performed on this matrix, where C is the number of samples and D is the number of common peaks. Specifically, the peak areas of 25 common peaks in 30 batches of birch bark medicinal material fingerprints are imported into SIMPA-P 14.0 software, and the peak area data of 25 common peaks in 30 batches of samples are used as variables to form a new 30×25 matrix, and OPLS-DA analysis is performed on this matrix ( Figure 5 ). Figure 5 middle, Figure 5 A represents the OPLS-DA score graph, Figure 5 B represents the permutation test result diagram, Figure 5 C represents the VIP value graph of the common peaks of the permutation fingerprint.

[0063] The fitting parameters R2X=0.895, R2Y=0.84, and the prediction parameter Q2=0.776 are all greater than 0.5, indicating that the prediction model is effective. The constructed model was further verified using the permutation test, and the data was cycled 200 times. The results are as follows Figure 5 As shown in Figure B, R2 and Q2 are (0.0, 0.106) and (0.0, -0.462), respectively. The Y-intercept of Q2 and the fitting line is negative, and the rightmost point Q2 and R2 are higher than those on the left, indicating that the model has no background correlation and overfitting phenomenon and is stable and reliable. The generated variable importance projection (VIP) diagram is combined for correlation analysis, see Figure 5 C. With VIP>1.0 as the standard, there were 10 differential markers, namely peak 17 (betulin), peak 11, peak 10, peak 4, peak 16 (betulinic acid), peak 21 (oleanolic acid 3-acetate), peak 5, peak 22 (betulinaldehyde), peak 23, and peak 20. These components may be potential markers for the quality differences of birch bark from different origins and can be used as reference components for the determination of birch bark content.

[0064] Step 5: Conduct quantitative analysis using the one-test-multiple-evaluation method

[0065] Betulin was used as an internal reference for QAMS quantitative analysis, and relative correction factors of other components were established. Then, the external standard method and the one-measurement-multiple-evaluation method were used to determine the contents of other components, respectively. The reliability of the results was verified, and a comprehensive evaluation of the quality of birch bark was completed. Other components included betulinic acid, betulinal, oleanolic acid 3-acetate, erythrodiol, lupeol, and 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane.

[0066] Because the content of betulin is relatively high and its reference substance is relatively easy to obtain, the present invention uses betulin as the internal reference substance (s) and combines the peak area data obtained by continuous injection of the above-mentioned mixed reference solution for 6 times, according to the formula:

[0067] RCF=f s / f i =C i A s / (C s A i )

[0068] The RCFs of other test components, 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane, betulinic acid, erythrodiol, betulinal, oleanolic acid 3-acetate, and lupeol, were calculated respectively, where s is the internal reference, i is the other test component, A is the peak area, and C is the concentration of the corresponding reference substance.

[0069] The results showed that the RSDs of the RCFs of other components were all less than 3% when birch bark was used as the internal reference, as shown in Table 3:

[0070] Table 3 Retention time differences of the analytes under different chromatographic columns

[0071]

[0072]

[0073] Thirty batches of birch bark medicinal materials were taken and carried out according to steps one and two, and the peak areas were recorded. The contents of 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane, betulinic acid, erythrodiol, betulinal, oleanolic acid 3-acetate, and lupeol in the birch bark medicinal material extract were calculated using ESM and QAMS methods, respectively. A t-test was performed on the ESM and QAMS values, and the results showed that the P values were all greater than 0.05, and the RSDs of the determination results of the two methods were both less than 5%. Figure 6 As shown in the figure, there is no significant difference between the results of the two methods, indicating that the established QAMS method has good accuracy and feasibility. This shows that the QAMS method is suitable for the determination of the content of multiple index components in birch bark and is feasible for birch bark quality control.

[0074] Thus, the present invention established fingerprints for 30 batches of birch bark. The similarity ranged from 0.947 to 1.000 using the control fingerprint as a reference, indicating that the quality of these 30 batches of samples was relatively stable. Analysis using a series of chemometric methods, including HCA, PCA, and OPLS-DA, revealed certain differences between the different batches of samples. Ten common peaks with VIP values greater than 1 were screened out: peak 17 (betulin), peak 11, peak 10, peak 4, peak 16 (betulinic acid), peak 21 (oleanolic acid 3-acetate), peak 5, peak 22 (betulinaldehyde), peak 23, and peak 20. These peaks indicate that these components may be potential markers for the quality differences of birch bark from different origins and can serve as reference components for birch bark content determination. Birch bark contains a large number of triterpenes and some diarylheptanes. To ensure comprehensive quantitative determination, this invention selects diarylheptanes (3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane) as one of the components for multi-index quantification. Furthermore, erythrodiol and lupeol, as lupeol-type triterpenes with a certain degree of specificity in birch bark, both possess anti-inflammatory, antioxidant, wound healing, and antibacterial effects, and can be used as potential markers for birch bark efficacy-related components for quality control. In summary, seven components, including betulin, were selected for quantitative determination.

[0075] According to the guiding principles of the QAMS method, the internal standard should select the active ingredient or index component in the medicinal material, and should be the same as the component to be measured as the same component or parent nucleus, and the spectral characteristics are basically the same. Because betulin is the main active ingredient for birch bark to treat inflammatory diseases such as epidermolysis bullosa. And the relative amount is higher, the property is relatively stable, the peak symmetry and separation are all good, and the reference substance is easy to obtain. Therefore, the QAMS method established by the present invention selects betulin as the internal reference, establishes the relative correction factors of the other 6 components to be measured such as betulic acid, and verifies the accuracy of QAMS with ESM at the same time. However, from the measurement results, there are certain batch differences in the 7 component contents of different batches of birch bark, suggesting that future research should focus on the harvesting period of birch bark raw materials, the standardization of growth years, and establish a multidimensional quality control system (such as origin tracing, multi-index detection, production process specification) to ensure component stability and batch consistency.

[0076] In summary, the fingerprint content determination method established in the present invention is scientific, stable and feasible, and can provide a basis for the quality evaluation of birch bark.

[0077] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above-described embodiments. The above-described embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and improvements may be made to the present invention without departing from the framework and scope of application of the present invention. Such changes and improvements are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A comprehensive evaluation method for birch bark quality based on fingerprint analysis combined with chemometrics and a one-measurement-multiple-evaluation approach, characterized by: The following steps are involved: Step 1: Prepare birch bark samples Collecting several groups of birch bark samples, grinding and drying them to obtain birch bark dried medicinal material powder, then using the birch bark dried medicinal material powder to prepare a test solution, and then preparing a mixed reference solution; Step 2: Set up chromatography and mass spectrometry conditions First, the chromatographic analysis conditions were set to use a Waters ACQUITY UPLC HSS T3 column, with a 0.1% formic acid aqueous solution (A)-0.1% formic acid acetonitrile (B) mobile phase, gradient elution, a flow rate of 0.3 mL / min, a column temperature of 40°C, and an injection volume of 10 μL. Then, the mass spectrometry conditions were set to use an electrospray ion source, the fingerprint scan type was SCAN mode, and the multi-component content determination scan type was MRM mode. Step 3: Generate fingerprint and evaluate similarity Under the conditions set in step 2, the test solution and the reference solution obtained in step 1 were subjected to chromatographic determination to obtain chromatographic data, which were then processed and analyzed using a traditional Chinese medicine chromatographic fingerprint similarity evaluation system to establish a birch bark UPLC fingerprint, and then similarity evaluation was performed; Step 4: Perform chemometric data analysis Based on the birch bark UPLC fingerprint data from step three, a hierarchical cluster analysis method was used to group the birch samples, showing the impact of different origins and processing methods on quality. Then, principal component analysis was performed to evaluate the differences in chemical composition of different batches of birch bark and extract the main components affecting birch bark quality. Finally, supervised discriminant analysis was performed using an orthogonal partial least squares discriminant analysis model to reveal the key components that cause quality differences between different batches of birch bark. Step 5: Conduct quantitative analysis using the one-test-multiple-evaluation method Betulin was used as an internal reference for QAMS quantitative analysis, and relative correction factors of other components were established. Then, the external standard method and the one-measurement-multiple-evaluation method were used to determine the contents of other components, respectively, to verify the reliability of the results and complete the comprehensive evaluation of birch bark quality.

2. The method for comprehensive evaluation of birch bark quality based on fingerprint analysis combined with chemometrics and one-measurement-multiple-evaluation method according to claim 1, characterized in that: In the step 1, the specific method for preparing the sample solution is as follows: 45 kg of dried birch bark medicinal powder is added with 4 times the amount of 95% ethanol, and the mixture is soaked and extracted three times at room temperature, with an interval of 72 hours between each extraction. The extraction solutions are filtered, the three extraction solutions are combined, and the mixture is concentrated under reduced pressure at 55° C. and dried to obtain an extract. The extract is then dissolved and diluted with methanol until a solution containing 1 mg of birch bark medicinal powder per 1 mL is used as the test solution.

3. The method for comprehensive evaluation of birch bark quality based on fingerprint combined with chemometrics and one-measurement-multiple-evaluation method according to claim 1, characterized in that: In the step 1, the specific method of preparing the reference solution is: Take 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane, betulinic acid, betulin, erythrodiol, betulin aldehyde, oleanolic acid 3-acetate, and lupeol reference substances, place them in 10 mL volumetric flasks, add methanol to dissolve and shake, and adjust the volume to prepare mixed reference substance solutions with mass concentrations of 3.042 μg / mL, 10.11 μg / mL, 27.46 μg / mL, 8 μg / mL, 2.104 μg / mL, 10.02 μg / mL, and 7.014 μg / mL, respectively.

4. The method for comprehensive evaluation of birch bark quality based on fingerprint analysis combined with chemometrics and one-measurement-multiple-evaluation method according to claim 1, characterized in that: In the step 2, the elution gradient is specifically as follows: 0-18 min, 5%→25% B; 18-20 min, 25%→40% B; 20-26 min, 40%→60% B; 26-31 min, 60%→65% B; 31-36 min, 65% B; 36-60 min, 65%→80% B; 60-61 min, 80%→95% B; 61-80 min, 95% B; 80-81 min, 95%→5% B; 81-85 min, 5% B.

5. The method for comprehensive evaluation of birch bark quality based on fingerprint combined with chemometrics and one-measurement-multiple-evaluation method according to claim 1, characterized in that: In the step 3, in the Chinese medicine chromatographic fingerprint similarity evaluation system, the time window width is set to 0.1 min, and the average method is used to perform multi-point correction and Mark peak matching to establish the birch bark UPLC fingerprint.

6. The method for comprehensive evaluation of birch bark quality based on fingerprint combined with chemometrics and one-measurement-multiple-evaluation method according to claim 1, characterized in that: In step 4, the specific method of the systematic cluster analysis method is: using SPSS27.0 software, taking the peak area information of several groups of common peaks in the birch bark UPLC fingerprint data as variables, performing standardization processing, selecting the inter-group linkage method, and using the squared Euclidean distance for cluster analysis.

7. The method for comprehensive evaluation of birch bark quality based on fingerprint combined with chemometrics and one-measurement-multiple-evaluation method according to claim 1, characterized in that: In step 4, the principal component analysis is specifically performed as follows: using SPSS27.0 software, the peak area information of several groups of common peaks in the birch bark UPLC fingerprint data is used as a variable, and normalization processing is performed, and then the KMO test and Bartlett test are performed. Then, according to the principle of extracting the number of principal components, the factors with eigenvalues greater than 1 are taken as the principal components.

8. The method for comprehensive evaluation of birch bark quality based on fingerprint combined with chemometrics and one-measurement-multiple-evaluation method according to claim 1, characterized in that: In step 4, the specific method of supervised discriminant analysis is: using the peak area information of several groups of common peaks in the birch bark UPLC fingerprint data as variables to form a new C×D matrix, and performing OPLS-DA analysis on the matrix, where C is the number of samples and D is the number of common peaks.

9. The method for comprehensive evaluation of birch bark quality based on fingerprint combined with chemometrics and one-measurement-multiple-evaluation method according to claim 1, characterized in that: In the step 5, other ingredients include betulinic acid, betulinal, oleanolic acid 3-acetate, erythrodiol, lupeol, and 3-hydroxy-1,7-bis(4,4-dimethoxyphenyl)-heptane.

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