Quality evaluation method of asparagus from different producing areas based on HPLC fingerprint spectrum

Abstract

The application belongs to the technical field of traditional Chinese medicine detection, and provides a quality evaluation method for asparagus cochinchinensis from different producing areas based on HPLC fingerprint spectrum. The quality evaluation method comprises the following steps: (1) preparing a test sample solution; (2) performing HPLC chromatographic analysis on the test sample solution; (3) preparing test sample solutions of asparagus cochinchinensis samples from different producing areas according to step (1), and performing sample injection under the chromatographic conditions of step (2) to generate different HPLC superimposed spectra of the asparagus cochinchinensis samples and a control fingerprint spectrum; (4) taking the control fingerprint spectrum as a reference, and applying a similarity evaluation system software to derive the similarity of the asparagus cochinchinensis samples from different producing areas and the control fingerprint spectrum. The method can collect asparagus cochinchinensis samples from different producing areas, perform sample extraction and detection, establish HPLC fingerprint spectra of asparagus cochinchinensis from different producing areas, obtain a control fingerprint spectrum, derive the similarity evaluation range of asparagus cochinchinensis from different producing areas, and provide a reference basis for comprehensively evaluating the quality of asparagus cochinchinensis from different producing areas.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of traditional Chinese medicine detection, in particular to a quality evaluation method for asparagus cochinchinensis from different producing areas based on HPLC fingerprint. BACKGROUND

[0002] Asparagus cochinchinensis is also known as Tianmen Dong, which is the dry tuber of asparagus cochinchinensis belonging to Liliaceae. It is mainly distributed in Sichuan, Guizhou, Guangxi and Yunnan. It has the effects of nourishing yin, moistening dryness, clearing lung and generating fluid. It is listed as the top grade in the medical classic Shennong's Herbal Classic, and it is recorded that it tastes bitter and is flat. Long-term consumption can light the body, benefit qi and prolong life. As a traditional Chinese medicine, it is widely used in the treatment of dry cough, sticky phlegm, dry throat, constipation and other symptoms. Modern research shows that asparagus cochinchinensis mainly contains saponins, polysaccharides and amino acids and other active chemical components. Pharmacological studies have shown that asparagus cochinchinensis has antioxidant, anti-aging, anti-tumor, anti-inflammatory, antibacterial, anti-depression and hypoglycemic effects, and its main pharmacodynamic material basis is mainly concentrated in saponins.

[0003] Under the background of the rapid development of traditional Chinese medicine health industry, the quality control of traditional Chinese medicinal materials will be more strictly controlled. Studies have shown that the content and composition of secondary metabolites in medicinal plants are often affected by the producing area, especially the accumulation of active ingredients. The 2020 edition of Chinese Pharmacopoeia only reflects the appearance and the index of extractives, which cannot reflect the internal quality from the chemical composition characteristics, and cannot evaluate and analyze the quality of asparagus cochinchinensis as a whole.

[0004] Traditional Chinese medicine fingerprint technology can characterize the characteristic information of traditional Chinese medicine composition group as a whole, comprehensively reflect the types and quantities of chemical components, and meet the characteristics of the whole and fuzziness of traditional Chinese medicine. It has been widely used in the quality evaluation mode of traditional Chinese medicine. However, there is no relevant report on the fingerprint and characteristic difference components of asparagus cochinchinensis from different producing areas, and asparagus cochinchinensis still lacks an effective quality control evaluation method. SUMMARY

[0005] In view of the above deficiencies in the prior art, the purpose of the present application is to provide a quality evaluation method for asparagus cochinchinensis from different producing areas based on HPLC fingerprint. The method collects asparagus cochinchinensis samples from different producing areas, extracts and detects the samples, establishes the high performance liquid chromatography (HPLC) fingerprint of asparagus cochinchinensis from different producing areas and obtains the control fingerprint, and obtains the similarity evaluation range of asparagus cochinchinensis from different producing areas, which can provide a reference for comprehensive evaluation of the quality of asparagus cochinchinensis from different producing areas.

[0006] In order to achieve the above purpose, the solution adopted by the present application is:

[0007] A quality evaluation method of asparagus from different producing areas based on HPLC fingerprint spectrum, comprising: (1) preparing a test sample solution: using methanol to ultrasonically extract asparagus test sample powder; (2) performing HPLC chromatographic analysis on the test sample solution; the HPLC chromatographic analysis conditions comprise: a medium spectrum red ODS-HC18 chromatographic column (4.6mm x 250mm, 5um); the mobile phase is acetonitrile-methanol-0.1% phosphoric acid water, gradient elution, volume flow rate 1.0mL·min -1 , column temperature 30 DEG C, detection wavelength 215nm, injection amount 10uL; (3) preparing test sample solutions of asparagus samples from different producing areas according to step (1), and injecting under the chromatographic conditions of step (2) to obtain different liquid chromatograms, introducing the liquid chromatograms into a traditional Chinese medicine chromatographic fingerprint similarity evaluation system software, taking the chromatogram of one sample as a control chromatogram, adopting a median method, setting a time window width of 0.1min, correcting by multiple points and adopting a Mark peak matching method to generate HPLC superimposed chromatograms and control fingerprint chromatograms of different asparagus samples, selecting chromatographic peaks with good separation, stable retention time and peak area in the chromatogram as characteristic chromatographic peaks, calibrating common peaks, identifying common peaks according to retention time by comparing the control chromatogram and the sample chromatogram; (4) taking the control fingerprint chromatogram as a reference, applying a similarity evaluation system software to export the similarity of asparagus samples from different producing areas and the control fingerprint chromatogram, and obtaining that: the similarity of asparagus from Sichuan is 0.791-0.912, which is stable in quality; the similarity of asparagus from Guangxi is 0.715-0.951, which is stable in quality; the similarity of asparagus from Guizhou is 0.712-0.899, which is stable in quality; and the similarity of asparagus from Yunnan is 0.794-0.885, which is stable in quality.

[0008] Further, in the preferred embodiment of the application, in step (1), the preparation of the test sample solution comprises: taking asparagus test sample powder 2g, weighing, placing in a conical flask with a plug, adding methanol 50mL, weighing, standing for 0.5h, ultrasonically treating for 30min, making up the weight, filtering, taking 25mL of the filtrate, recovering the solution to dryness, dissolving the residue in water 10mL, adding 10mL of anhydrous ether, shaking and extracting once, taking the lower layer solution, adding water-saturated n-butanol, shaking and extracting twice, 10mL each time, discarding the lower layer solution, recovering the n-butanol layer solution, evaporating to dryness, dissolving in methanol and making up to 10mL in a volumetric flask, filtering through a 0.45um microporous filter, and taking the filtrate, thereby obtaining the test sample solution.

[0009] Further, in the preferred embodiment of the present application, in step (2), the gradient elution procedure comprises: 0-20 min, 6% acetonitrile-92% methanol-2% 0.1% phosphoric acid water; 20-30 min, 23% acetonitrile-75% methanol-2% 0.1% phosphoric acid water; 30-38 min, 33% acetonitrile-65% methanol-2% 0.1% phosphoric acid water; 38-40 min, 40% acetonitrile-58% methanol-2% 0.1% phosphoric acid water; 40-50 min, 60% acetonitrile-38% methanol-2% 0.1% phosphoric acid water; 50-55 min, 79% acetonitrile-19% methanol-2% 0.1% phosphoric acid water; 55 min, 6% acetonitrile-92% methanol-2% 0.1% phosphoric acid water.

[0010] Further, in the preferred embodiment of the present application, the preparation of the asparagus test sample powder comprises: drying the asparagus sample in an oven, powdering, and passing through a No. 3 pharmacopoeia sieve for standby use.

[0011] The asparagus quality evaluation method based on the HPLC fingerprint provided by the present application has the beneficial effects that:

[0012] (1) The quality evaluation method provided by the present application collects asparagus samples from different origins, extracts and detects the samples, establishes the high performance liquid chromatography (HPLC) fingerprint of asparagus from different origins and obtains the reference fingerprint, obtains the similarity evaluation range of asparagus from different origins, and provides a reference basis for comprehensively evaluating the quality of asparagus from different origins, and is verified in chemometrics analysis.

[0013] (2) The quality evaluation method provided by the present application establishes the HPLC chromatogram under the process conditions of the mobile phase, detection wavelength, column temperature and gradient elution in the HPLC chromatographic analysis of the methanol ultrasonic extraction asparagus test sample powder, and in the verification of precision, stability and repeatability, it is shown that the instrument precision is good, the chromatographic analysis method is good in repeatability, and the test sample solution is good in stability.

[0014] (3) The quality evaluation method provided by the present application has a similarity of 0.712-0.951 for asparagus from different origins, which shows that the overall quality of asparagus from different origins is relatively stable, and the similarity of asparagus from different origins is distinguished, the origin of the asparagus can be preliminarily judged by the similarity, and it is verified by chemometrics analysis. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is the asparagus fingerprint provided by the experimental example 1 of the present application;

[0016] Figure 2 is the asparagus fingerprint provided by the comparative example 1 of the present application;

[0017] Figure 3 is the asparagus fingerprint provided by the present application comparative example 2;

[0018] Figure 4 is the asparagus fingerprint provided by the present application comparative example 3;

[0019] Figure 5 is the asparagus fingerprint provided by the present application comparative example 4;

[0020] Figure 6 is the asparagus fingerprint provided by the present application comparative example 5;

[0021] Figure 7 is the asparagus fingerprint provided by the present application comparative example 6;

[0022] Figure 8 is the asparagus fingerprint provided by the present application comparative example 7;

[0023] Figure 9 is the asparagus fingerprint provided by the present application comparative example 8;

[0024] Figure 10 is the asparagus fingerprint provided by the present application comparative example 9;

[0025] Figure 11 is the asparagus fingerprint provided by the present application comparative example 10;

[0026] Figure 12 is the asparagus fingerprint provided by the present application comparative example 11;

[0027] Figure 13 is the HPLC fingerprint of 21 batches of asparagus samples;

[0028] Figure 14 is the asparagus control fingerprint (A) and the HPLC chart of mixed control solution (B);

[0029] Figure 15 is the clustering analysis result of 21 batches of asparagus samples;

[0030] Figure 16 is the PCA score chart of 21 batches of asparagus samples. DETAILED DESCRIPTION

[0031] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the technical scheme in the embodiments of the present application will be described clearly and completely below. If the specific conditions are not indicated in the embodiments, the conventional conditions or the conditions suggested by the manufacturers are adopted. If the reagents or instruments are not indicated by the manufacturers, they are all the conventional products which can be purchased in the market.

[0032] The features and performances of the present application are further described in detail below in combination with examples.

[0033] The examples employ:

[0034] Instrument: Agilent 1260 high performance liquid chromatograph (USA, Agilent Technology); DFT-50A high-speed pulverizer (Tianjin Test Instrument Co., Ltd.); CP-225D electronic analytical balance (1 / 100,000, Germany, Sartorius); Milli-Q ultrapure water preparation system (Chengdu Ultra-pure Technology Co., Ltd.); KQ-5200DE ultrasonic cleaner (200W, 40KHz, Kunshan Ultrasonic Instrument Co., Ltd.);

[0035] Reagents and reagents: reference substance proto-dioscin (batch number 111937-202102, mass fraction 94.8%), pseudo-protodioscin (batch number 111855-201403, mass fraction 92.0%) were purchased from China Institute for Drug Control; methanol, acetonitrile (chromatographic pure, Thermo Fisher Scientific), phosphoric acid (chromatographic grade, Cologne Chemicals Co., Ltd.); water is ultrapure water; other reagents are analytical pure;

[0036] Medicinal materials: 4 different origins, a total of 21 batches of asparagus samples were dried in an oven, powdered, all passed through a No. 3 sieve, and used.

[0037] Example 1

[0038] The present example provides a quality evaluation method for asparagus from different origins based on HPLC fingerprint, comprising:

[0039] (1) Preparation of test solution: take asparagus test product powder 2g, weigh, put in a conical flask with plug, add pure methanol 50mL, weigh, soak for 0.5h, then ultrasonic treatment for 30min, make up the weight, filter, take 25mL of the filtrate, recover the solution to dryness, add water 10mL to dissolve, add 10mL of anhydrous ether, shake and extract once, then take the lower layer solution and add water saturated n-butyl alcohol, shake and extract twice, 10mL each time, discard the lower layer solution, recover the n-butyl alcohol layer solution, evaporate to dryness, dissolve in methanol and dilute to 10mL in a volumetric flask, filter through a 0.45μm microporous filter membrane, take the filtrate, and obtain it.

[0040] (2) The test solution is subjected to HPLC chromatographic analysis; the conditions of HPLC chromatographic analysis include: medium spectrum red ODS-HC18 chromatographic column (4.6mm x 250mm, 5um); the mobile phase is acetonitrile-methanol-0.1% phosphoric acid water, gradient elution, volume flow rate 1.0mL·min -1 , column temperature 30℃, detection wavelength 215nm, injection amount 10μL; the obtained asparagus fingerprint spectrum is shown inFigure 1 The gradient elution program is shown in Table 1:

[0041] Table 1 Gradient elution program

[0042] Time / min Acetonitrile / % 0.1% phosphoric acid water / % Methanol / % 0 6 2 92 5 6 2 92 20 23 2 75 23 23 2 75 30 33 2 65 38 40 2 58 40 60 2 38 50 79 2 19 55 6 2 92

[0043] (3) 21 batches of Asparagus cochinchinensis L. from Sichuan, Guangxi, Guizhou and Yunnan were prepared into test sample solution according to step (1), and injected into the chromatographic column according to the chromatographic conditions of step (2) to obtain different liquid chromatograms. The chromatogram of one sample was set as the control chromatogram, and the chromatograms of different Asparagus cochinchinensis L. samples were imported into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System Software" to generate the HPLC superimposed chromatogram and the control fingerprint chromatogram of different Asparagus cochinchinensis L. samples by the median method, time window width setting of 0.1 min, multi-point correction and Mark peak matching method. Chromatographic peaks with good separation, stable retention time and peak area were selected as characteristic chromatographic peaks, and the common peaks were labeled by comparing the control chromatogram and the sample chromatogram according to the retention time;

[0044] (4) The similarity of Asparagus cochinchinensis L. samples from different producing areas to the control fingerprint chromatogram was exported by applying the similarity evaluation system software with the control fingerprint chromatogram as the reference, and the similarity of Asparagus cochinchinensis L. from Sichuan was 0.791-0.912, which was stable in quality; the similarity of Asparagus cochinchinensis L. from Guangxi was 0.715-0.951, which was stable in quality; the similarity of Asparagus cochinchinensis L. from Guizhou was 0.712-0.899, which was stable in quality; and the similarity of Asparagus cochinchinensis L. from Yunnan was 0.794-0.885, which was stable in quality.

[0045] Comparative Example 1

[0046] This comparative example provides the establishment of an HPLC fingerprint chromatogram of Asparagus cochinchinensis L., which includes steps (1) and (2) of the example, and is different from Example 1 in that 85% methanol is used for extraction in the preparation of the test sample solution. The obtained HPLC fingerprint chromatogram is shown in Figure 2 .

[0047] Comparative Example 2

[0048] This comparative example provides the establishment of an HPLC fingerprint chromatogram of Asparagus cochinchinensis L., which includes steps (1) and (2) of the example, and is different from Example 1 in that ethanol is used for extraction in the preparation of the test sample solution, and the remaining steps are the same as those of Example 1. The obtained HPLC fingerprint chromatogram is shown in Figure 3 .

[0049] Comparative Example 3

[0050] The comparative example provides a kind of asparagus HPLC fingerprint, including the steps (1) and (2) of example, and the difference from example 1 is that in the preparation of test solution, using reflux extraction, the rest steps are same with example 1.The obtained HPLC fingerprint is seen Figure 4 .

[0051] Comparative example 4-5

[0052] The comparative example provides a kind of asparagus HPLC fingerprint, including the steps (1) and (2) of example, and the difference from example 1 is that in the preparation of test solution, using reflux extraction, the rest steps are same with example 1.The obtained HPLC fingerprint is seen Figure 5-6 .

[0053] Comparative example 6-7

[0054] The comparative example provides a kind of asparagus HPLC fingerprint, including the steps (1) and (2) of example, and the difference from example 1 is that in the preparation of test solution, using reflux extraction, the rest steps are same with example 1.The obtained HPLC fingerprint is seen Figure 7-8 .

[0055] Comparative example 8-9

[0056] The comparative example provides a kind of asparagus HPLC fingerprint, including the steps (1) and (2) of example, and the difference from example 1 is that in the preparation of test solution, using reflux extraction, the rest steps are same with example 1.The obtained HPLC fingerprint is seen Figure 9-10 .

[0057] Comparative example 10-11

[0058] The comparative example provides a kind of asparagus HPLC fingerprint, including the steps (1) and (2) of example, and the difference from example 1 is that in the preparation of test solution, using reflux extraction, the rest steps are same with example 1.The obtained HPLC fingerprint is seen Figure 11-12 .

[0059] Table 2

[0060] Time / min Acetonitrile / % 0.1% phosphoric acid water / % Methanol / % 0 3 2 95 5 3 2 95 30 23 75 35 33 2 65 45 38 2 60 60 83 2 15 65 4 2 94

[0061] Table 3

[0062] Time / min Acetonitrile / % 0.1% phosphoric acid water / % Methanol / % 0 8 2 90 5 8 2 90 25 23 2 75 28 33 2 65 38 33 2 65 43 40 2 58 60 8 2 90

[0063] Experimental example 1

[0064] Figure 1-3 The results show that, compared with using 85% methanol and ethanol extraction, using methanol for extraction, the chromatographic peak shape and response value are obviously improved;

[0065] Figure 1 The results show that, compared with using water bath reflux, using ultrasonic extraction is more convenient and efficient.

[0066] Figure 1 The results show that, compared with using acetonitrile-water, acetonitrile-0.1% phosphoric acid water, using acetonitrile-0.1% phosphoric acid water-methanol as the mobile phase, the obtained chromatogram has a stable baseline and good separation degree and peak shape of each peak.

[0067] Figure 1 The results show that, compared with using detection wavelength 203nm, 220nm, using detection wavelength 215nm, not only the chromatographic information is rich, but also the response value is high and the peak shape is good.

[0068] Figure 1 The results show that, compared with using column temperature 25℃ and 35℃, using column temperature 30℃ can obtain chromatographic peaks with better separation effect.

[0069] Figure 1 The results show that, the gradient elution program provided by Comparative Example 10 obtains fewer chromatographic peaks, and the separation effect of chromatographic peaks in the 36-42min time period is poor and the analysis time is long; the gradient elution program provided by Comparative Example 11 has more chromatographic peaks, and the analysis time of chromatographic peaks in the 34-44min time period is later. Compared with the above, the gradient elution program used in the present application not only obtains more chromatographic peaks, but also reduces the analysis time to 55min.

[0070] Experimental Example 2

[0071] Precision test

[0072] Take 2g of aspartic acid sample powder, accurately weigh, prepare the test sample solution according to the method of step (1) of Example 1, and continuously sample for determination 6 times according to the chromatographic conditions of step (2) of Example 1. Take the original dioscin chromatographic peak (S) as the reference peak, and calculate the RSD values of the relative retention time and the relative peak area of each common peak, which are less than 0.41% and 3.43% respectively, indicating that the instrument precision is good.

[0073] Repeatability test

[0074] Take the same batch of asparagus sample powder 6 each 2 g, precision weighing, prepared sample solution according to the method of step (1) of example 1, according to the chromatographic conditions of step (2) of example 1, sample determination. With the original dioscin chromatographic peak (S) as the reference peak, the relative retention time and relative peak area of each common peak were calculated, and the RSD values were less than 0.64% and 4.12% respectively, indicating that the repeatability of the method was good.

[0075] Stability test

[0076] Take 2 g of asparagus sample powder, precision weighing, prepared sample solution according to the method of step (1) of example 1, according to the chromatographic conditions of step (2) of example 1, respectively, sample determination at 0, 2, 4, 6, 8, 12, 24 h. With the original dioscin chromatographic peak (S) as the reference peak, the relative retention time and relative peak area of each common peak were calculated, and the RSD values were less than 1.42% and 4.81% respectively, indicating that the sample solution was stable within 24 h.

[0077] Experimental example 3

[0078] Example 1 through step (3), 21 batches of asparagus sample HPLC superimposed chromatogram and control fingerprint, see Figure 13 , select the chromatographic peak (peak 7) with good separation, stable retention time and peak area in the chromatogram as the characteristic chromatographic peak, and finally 11 common peaks are identified, through comparison of the chromatogram of the sample and the reference substance, 2 common peaks are identified according to the retention time, in which peak 7 is original dioscin and peak 8 is pseudo original dioscin.

[0079] Preparation of mixed reference substance solution: accurately weigh a certain amount of original dioscin and pseudo original dioscin reference substances, and put them into a 10 mL volumetric flask. Dissolve with methanol, dilute to volume, shake well, and prepare solutions with mass concentrations of about 109.15 and 14.55 μg / mL respectively.

[0080] The mixed reference substance solution was analyzed by chromatography according to step (2) of example 1;

[0081] The asparagus control fingerprint (A) and the HPLC chromatogram of the mixed reference substance solution (B) are shown in Figure 14 .

[0082] Using the HPLC control fingerprint of 21 batches of asparagus samples as reference, the similarity calculation results of asparagus from different origins and the generated control fingerprint were derived by using similarity evaluation system software, as shown in table 4:

[0083] Table 4 Similarity evaluation results of 21 batches of asparagus samples

[0084] Number Similarity Number Similarity Number Similarity S1 0.948 S8 0.912 S15 0.712 S2 0.951 S9 0.885 S16 0.862 S3 0.951 S10 0.827 S17 0.718 S4 0.715 S11 0.882 S18 0.851 S5 0.87 S12 0.791 S19 0.885 S6 0.745 S13 0.912 S20 0.88 S7 0.873 S14 0.899 S21 0.794

[0085] The results in Table 4 show that the similarity of the 21 batches of asparagus samples ranged from 0.712 to 0.951. Among these, samples from Guangxi had similarities ranging from 0.715 to 0.951, those from Sichuan had similarities ranging from 0.791 to 0.912, those from Guizhou had similarities ranging from 0.712 to 0.899, and those from Yunnan had similarities ranging from 0.794 to 0.885. Only six batches had similarities less than 0.8. These results indicate that the overall quality of asparagus from different origins is relatively stable, with some variability.

[0086] Experimental Example 4: Pattern Recognition Analysis

[0087] 4.1 Cluster Analysis

[0088] The 11 common peak areas of 21 batches of Asparagus cochinchinensis samples were used as variables to construct a 21×11 information matrix. This matrix was imported into the multivariate statistical analysis software SIMCA 14.1. After standardization, cluster analysis was performed using the Ward linkage method between groups and the sum of squared Euclidean distance as the measure. Figure 15 .

[0089] When the classification distance was 20, the asparagus from different origins were obviously clustered into four categories, among which S14-S17 asparagus from Guizhou were clustered into one category, S18-S21 asparagus from Yunnan were clustered into one category, S2-S3, S5-S8 asparagus from Guangxi were clustered into one category, and except for S1 and S4 which were asparagus from Guangxi, S9-12 asparagus from Sichuan were clustered into one category.

[0090] The results showed that there were certain regional differences in the quality of asparagus from different origins. At the same time, it was found that the asparagus from Guangxi and Sichuan clustered into one category when the classification distance was 30, indicating that the overall quality of the asparagus from the two places was relatively close.

[0091] 4.2 Principal Component Analysis

[0092] Unsupervised PCA was used to identify the overall chemical profile of Asparagus cochinchinensis from different origins, and further explore the differences in chemical composition between Asparagus cochinchinensis samples from different origins. A 21×11 order information matrix was constructed based on the 11 common peak areas of 21 batches of Asparagus cochinchinensis samples and imported into SIMCA 14.1 for PCA analysis. The PCA analysis scatter plot is shown in the figure. Figure 16 Using the unsupervised pattern recognition method PCA, we observed the natural clustering of samples and analyzed their differences. The four principal components extracted contributed a cumulative 87.30%, indicating that these four components encompassed the majority of the chemical information of the 11 components. The results showed that the 21 samples of Asparagus cochinchinensis were clearly divided into four categories, which is generally consistent with the cluster analysis results.

[0093] By using the quality evaluation method of asparagus from different habitats based on HPLC fingerprint provided by the application, the asparagus samples from different habitats are collected, sample extraction and detection are carried out, the HPLC fingerprint of asparagus from different habitats is established, the reference fingerprint is obtained, the similarity evaluation range of asparagus from different habitats is obtained, and reference basis can be provided for comprehensively evaluating the quality of asparagus medicinal materials from different habitats.

[0094] The above merely describes preferred embodiments of the present application, but is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for evaluating the quality of asparagus from different origins based on HPLC fingerprints, characterized in that: include: (1) Preparation of test solution: Ultrasonic extraction of asparagus powder using methanol; The preparation of the test solution comprises the following steps: taking 2 g of asparagus cochinchinensis test sample powder, weighing it, placing it in a stoppered conical flask, adding 50 mL of methanol, weighing it, letting it stand and soak for 0.5 h, then ultrasonically treating it for 30 min, replenishing the weight, filtering it, measuring 25 mL of the filtrate, recovering the solution until dry, adding 10 mL of water to dissolve the residue, adding 10 mL of anhydrous ether and shaking to extract it once, taking the lower layer solution and adding saturated n-butanol with water and shaking to extract it twice, each time 10 mL, discarding the lower layer solution, recovering the n-butanol layer solution, evaporating it to dryness, dissolving it with methanol and making up the volume in a 10 mL volumetric flask, filtering it through a 0.45 μm microporous filter membrane, and taking the filtrate to obtain the solution; (2) The sample solution was subjected to HPLC chromatography analysis; the HPLC chromatography analysis conditions included: a medium spectrum red ODS-HC18 chromatographic column; a mobile phase of acetonitrile-methanol-0.1% phosphoric acid water, gradient elution, and a volume flow rate of 1.0 mL·min -1 , column temperature 30 ° C, detection wavelength 215 nm, injection volume 10 μL; the gradient elution program includes: 0-20 min, 6% acetonitrile-92% methanol-2% 0.1% phosphoric acid water; 20-30 min, 23% acetonitrile-75% methanol-2% 0.1% phosphoric acid water; 30-38 min, 33% acetonitrile-65% methanol-2% 0.1% phosphoric acid water; 38-40 min, 40% acetonitrile-58% methanol-2% 0.1% phosphoric acid water; 40-50 min, 60% acetonitrile-38% methanol-2% 0.1% phosphoric acid water; 50-55 min, 79% acetonitrile-19% methanol-2% 0.1% phosphoric acid water; 55 min, 6% acetonitrile-92% methanol-2% 0.1% phosphoric acid water; (3) Preparation of mixed reference solution: Accurately weigh appropriate amounts of protodioscin and pseudoprotodioscin reference substances, place them in a 10 mL volumetric flask, dissolve them in methanol, make up to volume, and shake well to prepare solutions with mass concentrations of approximately 109.15 and 14.55 μg / mL, respectively; the mixed reference solution is subjected to chromatographic analysis according to step (2); (4) Taking asparagus samples from different origins and preparing the test solution according to step (1), injecting the sample under the chromatographic conditions of step (2) to obtain different liquid chromatograms, importing them into the "Chinese medicine chromatographic fingerprint similarity evaluation system software", setting the chromatogram of one of the samples as the reference chromatogram, using the median method, setting the time window width to 0.1 min, and generating HPLC superimposed chromatograms and reference fingerprints of different asparagus samples through multi-point calibration and Mark peak matching methods, selecting chromatographic peaks with good separation, stable retention time and peak area in the chromatogram as characteristic chromatographic peaks, calibrating common peaks, and identifying common peaks according to retention time by comparing the reference chromatogram and the sample chromatogram; finally, 11 common peaks were calibrated, and 2 common peaks were identified according to retention time, of which peak 7 was protodioscin and peak 8 was pseudo-protodioscin; (5) Using the control fingerprint as a reference, the similarity evaluation system software was used to derive the similarity between the asparagus samples from different origins and the control fingerprint, and the results showed that the similarity of the asparagus from Sichuan was 0.791-0.912, which indicated stable quality; the similarity of the asparagus from Guangxi was 0.715-0.951, which indicated stable quality; the similarity of the asparagus from Guizhou was 0.712-0.899, which indicated stable quality; and the similarity of the asparagus from Yunnan was 0.794-0.885, which indicated stable quality.

2. The method for evaluating the quality of Asparagus cochinchinensis from different producing areas based on HPLC fingerprint according to claim 1, wherein: The preparation of the asparagus cochinchinensis test sample powder comprises the following steps: drying the asparagus cochinchinensis sample in an oven, grinding the sample into powder, and passing the powder through a pharmacopoeia No. 3 sieve for later use.

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