A UPLC fingerprint of Lonicera japonica fruit, its establishment method and application

Abstract

The present application provides a UPLC fingerprint of honeysuckle fruit, a method for establishing it, and its application, belonging to the field of pharmaceutical analysis technology. The present application constructs a UPLC fingerprint of honeysuckle fruit for the first time. The UPLC fingerprint includes 23 common characteristic peaks and contains 8 qualitative identification characteristic peaks. The established UPLC fingerprint of honeysuckle fruit can quantitatively detect the contents of 8 active ingredients in honeysuckle fruit and identify the quality and origin of honeysuckle fruit medicinal material, providing a scientific basis for the identification of the quality and origin of honeysuckle fruit.

Description

Technical Field

[0001] The invention belongs to the technical field of drug analysis and relates to a UPLC fingerprint of honeysuckle fruit, an establishment method and an application thereof. Background Art

[0002] Lonicera japonica Lonicera japonica The ripe fruits of Thunb. are picked after the frost falls and sun-dried. According to classic herbal texts such as "Chinese Materia Medica" and "Chinese Pharmacology," the seeds of honeysuckle are cool in nature and sweet in taste. They have the effects of clearing heat and cooling blood, detoxifying and reducing swelling. They are mainly used to treat heat-induced swelling, ulcers, dysentery, eczema, and dermatitis.

[0003] Modern research shows that honeysuckle seeds have similar effects to honeysuckle and honeysuckle vines, and all have clear medicinal value. However, historical documents rarely record honeysuckle seeds, mainly because the fruit is scarce in late autumn, making it difficult to collect and meeting clinical usage requirements. In addition, honeysuckle seeds are berries with a high moisture content, making them difficult to dry and prone to spoilage, further affecting their circulation and application. In recent years, due to the impact of influenza and other factors, the market demand for honeysuckle, a common medicinal herb in bulk, has fluctuated greatly, and the imbalance between supply and demand has become increasingly prominent. As a result, a large number of flower buds have been abandoned due to overcapacity and converted to fruit production. In addition, modern drying technology has significantly shortened the drying time of honeysuckle seeds, ensuring the quality of the medicinal material. Therefore, if a large amount of honeysuckle seeds can be utilized as a resource and the pressure of overcapacity in honeysuckle can be diverted, it will not only increase the added value of the honeysuckle industry chain, but also alleviate the supply and demand contradiction in the honeysuckle market and promote the sustainable development of the industry.

[0004] Currently, the quality evaluation of silver flower seeds still relies on subjective experience-based grading and lacks objective standards, which seriously hinders its further development. Traditional Chinese medicine fingerprint technology, combined with multi-component quantitative analysis, can comprehensively characterize the quality of medicinal materials through chemical characteristics and has become an internationally recognized method for quality control of traditional Chinese medicine. However, there are currently no reports of a traditional Chinese medicine fingerprint for silver flower seeds. Summary of the Invention

[0005] In order to solve the development and utilization difficulties caused by the existing quality evaluation method of honeysuckle fruit relying on subjective experience classification, the present invention provides a honeysuckle fruit UPLC fingerprint, establishment method and application.

[0006] This application establishes the UPLC fingerprint of Ginkgo biloba seeds for the first time, and simultaneously determines the contents of eight characteristic components, including neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidinoside, luteolin, isochlorogenic acid A and isochlorogenic acid C. The data are integrated by combining the similarity evaluation of Chinese medicine chromatographic fingerprints and cluster analysis, principal component analysis, orthogonal partial least squares discriminant analysis and other methods to more intuitively reflect the quality differences of medicinal materials from different origins and between different batches.

[0007] Specifically, the present application provides a UPLC fingerprint of Lonicera japonica L., and the method for establishing the fingerprint comprises:

[0008] S01: Prepare a honeysuckle fruit test solution and a mixed reference solution, wherein the mixed reference solution is prepared from neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidyl glycoside, luteolin, isochlorogenic acid A and isochlorogenic acid C.

[0009] Prepare the honeysuckle fruit test solution: Grind the honeysuckle fruit and pass it through a 60-mesh sieve to obtain honeysuckle fruit powder. Add 75% methanol by volume to the honeysuckle fruit powder and sonicate at a power of 512 W and a frequency of 40 kHz for 30 minutes. After filtration, the filtrate is filtered through a 0.22 μm microporous membrane to obtain the honeysuckle fruit test solution.

[0010] Prepare reference solution: accurately weigh appropriate amounts of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, chlorogenic acid, isochlorogenic acid A, and isochlorogenic acid C, and dissolve them in methanol. At the same time, dissolve luteolin in 70% ethanol to form a concentration of 1.14 mg mL -1 , 2.01mg·mL -1 , 1.58mg·mL -1 , 1.13 mg·mL -1 , 1.18 mg·mL -1 , 1.37 mg·mL -1 , 1.23 mg·mL -1 , 0.13mg·mL -1 8 reference solutions.

[0011] Prepare mixed reference solution: 8 reference solution were measured separately, and methanol with a volume fraction of 75% was added to prepare the neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidyl glycoside, luteolin, isochlorogenic acid A, and isochlorogenic acid C, with the contents of 43.39 μg·mL -1 , 58.11 μg·mL -1 , 98.19 μg·mL -1 , 84.18 μg·mL -1 , 64.07 μg·mL -1 , 4.58 μg·mL -1 , 68.45 μg·mL -1 , 92.71 μg·mL -1 mixed reference solution.

[0012] S02: UPLC detection was performed on the honeysuckle fruit test solution and the mixed reference solution, respectively, to obtain a UPLC chromatogram of the test sample and a UPLC chromatogram of the mixed reference with 23 characteristic chromatographic peaks.

[0013] In this application, the UPLC detection conditions are as follows: Thermo Accucore™ C18 column (100 mm × 4.6 mm, 2.6 μm), mobile phase acetonitrile (A)-0.1% phosphoric acid aqueous solution (B), gradient elution, column temperature 30°C, volume flow rate 0.3 mL min -1 The injection volume was 1 μL, and the detection wavelength was 204-328 nm. The gradient elution program was: 0%-8% A (0-7 min); 8%-16% A (7-13 min); 16%-16% A (13-21 min); 16%-17% A (21-26 min); 17%-27% A (26-35 min); 27%-27% A (35-40 min). The detection wavelength dynamic switching program was: 326 nm (0-14.6 min); 246 nm (14.6-17.8 min); 238 nm (17.8-22.0 min); 204 nm (22.0-28.0 min); and 328 nm (28.0-40.0 min).

[0014] S03: Compare the UPLC chromatograms of the test sample and the mixed reference sample, match the common characteristic peaks in the UPLC chromatograms of the test sample and the mixed reference sample according to the retention time, and construct the UPLC fingerprint of the honeysuckle fruit. Among them, the UPLC fingerprint of the honeysuckle fruit includes 23 common characteristic peaks, and 8 qualitative identification characteristic peaks are identified, namely: Peak 1: neochlorogenic acid; Peak 4: chlorogenic acid; Peak 5: cryptochlorogenic acid; Peak 6: caffeic acid; Peak 10: chlorogenic acid; Peak 15: luteolin; Peak 19: isochlorogenic acid A; Peak 21: isochlorogenic acid C.

[0015] The UPLC fingerprint of the Fructus Lonicerae in this application is used to quantitatively analyze the active ingredients in the Fructus Lonicerae. Specifically, the method for quantitatively analyzing the active ingredients in the Fructus Lonicerae Lonicerae includes:

[0016] S01: Prepare a test solution and 8 reference solutions, wherein the 8 reference solutions are prepared from neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidyl glycoside, luteolin, isochlorogenic acid A and isochlorogenic acid C, respectively.

[0017] Prepare the test solution: Grind the honeysuckle fruit to be tested and pass it through a 60-mesh sieve to obtain honeysuckle fruit powder. Add 75% methanol by volume to the honeysuckle fruit powder. Ultrasonicate at a power of 512 W and a frequency of 40 kHz for 30 minutes. After filtration, filter the filtrate through a 0.22 μm microporous membrane to obtain the test solution.

[0018] Prepare reference solution: accurately weigh appropriate amounts of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, chlorogenic acid, isochlorogenic acid A, and isochlorogenic acid C, and dissolve them in methanol. At the same time, dissolve luteolin in 70% ethanol to form a concentration of 1.14 mg mL -1 , 2.01mg·mL -1 , 1.58mg·mL -1 , 1.13 mg·mL -1 , 1.18 mg·mL -1 , 1.37 mg·mL -1 , 1.23 mg·mL -1 , 0.13mg·mL -1 8 reference solutions.

[0019] S02: Perform UPLC detection on the reference solution respectively, calculate the linear equation and draw a standard curve with the reference sample injection concentration as the horizontal axis and the peak area as the vertical axis.

[0020] Eight reference solutions were precisely measured and diluted to six different concentrations with 75% methanol. After filtration through a 0.22 μm microporous membrane, UPLC analysis was performed to obtain UPLC chromatograms for each reference. UPLC analysis conditions were: a Thermo Accucore™ C18 column (100 mm × 4.6 mm, 2.6 μm), a mobile phase of acetonitrile (A)-0.1% aqueous phosphoric acid (B), gradient elution, column temperature at 30°C, and a flow rate of 0.3 mL / min. -1 , injection volume 1 μL, detection wavelength 204-328 nm. Gradient elution program: 0-7 min, 0%-8% A; 7-13 min, 8%-16% A; 13-21 min, 16%-16% A; 21-26 min, 16%-17% A; 26-35 min, 17%-27% A; 35-40 min, 27%-27% A. Detection wavelength dynamic switching program: 0-14.6 min, 326 nm; 14.6-17.8 min, 246 nm; 17.8-22.0 min, 238 nm; 22.0-28.0 min, 204 nm; 28.0-40.0 min, 328 nm. The injection concentration of the reference substance was μg·mL -1 With the peak area in the UPLC chromatogram as the horizontal coordinate X and the peak area in the UPLC chromatogram as the vertical coordinate Y, the linear regression equation was calculated and the standard curve was drawn.

[0021] S03: Perform UPLC detection on the test solution to be tested, record the peak areas of 8 active ingredients, and calculate the content of the active ingredient according to the linear equation.

[0022] The test solution was subjected to UPLC analysis according to the above UPLC detection conditions, and the peak areas of the eight active ingredients (neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidyl glycoside, luteolin, isochlorogenic acid A, and isochlorogenic acid C) were recorded. The peak areas were respectively substituted into the above linear regression equation to calculate the contents of the eight active ingredients.

[0023] In addition, the UPLC fingerprint of the honeysuckle fruit and the content of the active ingredient in this application are also used to identify the quality and origin of the honeysuckle fruit.

[0024] In this application, the method for identifying the quality of silver flower seeds includes:

[0025] The tested honeysuckle fruit is subjected to UPLC detection to obtain a UPLC chromatogram of the tested honeysuckle fruit; the similarity between the tested honeysuckle fruit UPLC chromatogram and the established honeysuckle fruit UPLC fingerprint is compared, and the honeysuckle fruit with a similarity greater than 0.90 is a qualified product.

[0026] In this application, the method for identifying the origin of silver flower seeds includes:

[0027] S01: UPLC analysis was performed on different batches of Yinhuazi to obtain Yinhuazi UPLC chromatograms. Based on the UPLC chromatograms of 13 batches of Yinhuazi, the peak areas of the eight active ingredients in each batch of Yinhuazi were determined. The peak areas were then substituted into the linear equation to calculate the contents of the eight active ingredients in the different batches of Yinhuazi. The UPLC analysis conditions were as follows: a ThermoAccucore™ C18 column (100mm × 4.6mm, 2.6μm), a mobile phase of acetonitrile (A)-0.1% phosphoric acid aqueous solution (B), gradient elution, a column temperature of 30°C, and a flow rate of 0.3mL·min. -1 The injection volume was 1 μL, and the detection wavelength was 204-328 nm. The gradient elution program was: 0-7 min, 0%-8% A; 7-13 min, 8%-16% A; 13-21 min, 16%-16% A; 21-26 min, 16%-17% A; 26-35 min, 17%-27% A; 35-40 min, 27%-27% A. The dynamic detection wavelength switching program was: 0-14.6 min, 326 nm; 14.6-17.8 min, 246 nm; 17.8-22.0 min, 238 nm; 22.0-28.0 min, 204 nm; 28.0-40.0 min, 328 nm.

[0028] S02: Cluster analysis, principal component analysis and orthogonal partial least squares discriminant analysis were performed on the silver flower seeds according to the contents of the eight active ingredients in the silver flower seeds, and different batches of silver flower seeds were classified.

[0029] S03: Screening potential quality markers based on the variable importance projection value in orthogonal partial least squares discriminant analysis; potential quality markers include chlorogenic acid, luteolin, and isochlorogenic acid A;

[0030] S04: Determine the origin of the silver flower seeds according to the content ratio of chlorogenic acid, luteolin, and isochlorogenic acid A. When the content ratio of chlorogenic acid, luteolin, and isochlorogenic acid A is 1:0.55-0.57:0.52-0.56, the silver flower seeds are produced in Shandong; when the content ratio of chlorogenic acid, luteolin, and isochlorogenic acid A is 1:2.17-2.23:1.22-1.38, the silver flower seeds are produced in Hebei; and when the content ratio of chlorogenic acid, luteolin, and isochlorogenic acid A is 1:1.28-1.29:0.63-0.64, the silver flower seeds are produced in Henan.

[0031] The present invention has the following beneficial effects:

[0032] (1) This application is the first to construct the UPLC fingerprint of Ginkgo biloba seeds. The UPLC fingerprint includes 23 common characteristic peaks, including 8 qualitative identification characteristic peaks, namely peak 1: neochlorogenic acid; peak 4: chlorogenic acid; peak 5: cryptochlorogenic acid; peak 6: caffeic acid; peak 10: chlorogenic acid; peak 15: luteolin; peak 19: isochlorogenic acid A; peak 21: isochlorogenic acid C.

[0033] (2) The UPLC fingerprint of Ginkgo biloba seeds established in this application can quantitatively detect the contents of 8 active ingredients in Ginkgo biloba seeds, and the linearity of each ingredient is good (r≥0.9990), with precision RSD <1.0%, repeatability RSD <1.0%, stability RSD within 24 hours <1.0%, and average sample recovery rate of 97.6%-101.7%.

[0034] (3) In this application, the established UPLC fingerprint of honeysuckle fruit was compared with the UPLC chromatogram of the honeysuckle fruit to be tested. The quality of honeysuckle fruit can be identified through similarity analysis, and the quality of the medicinal material can be comprehensively evaluated, providing an effective method for the quality control of honeysuckle fruit medicinal material.

[0035] (4) In this application, the contents of eight active ingredients in silver flower seeds were determined based on the established UPLC fingerprint of silver flower seeds. Through cluster analysis, principal component analysis and orthogonal partial least squares discriminant analysis, 13 batches of silver flower seeds from the three major production areas of Shandong, Henan and Hebei were accurately classified. The potential key active ingredients of silver flower seeds, chlorogenic acid, luteolin and isochlorogenic acid A, which are the key active ingredients in the quality difference of silver flower seeds, were obtained, providing a scientific basis for the identification of the origin and quality of silver flower seeds.

[0036] (5) The present invention establishes a UPLC fingerprint method and content determination method for the medicinal material of Ginkgo biloba, which has the advantages of being fast, accurate, and reproducible, and provides reliable technical support for the quality control and origin identification of the medicinal material of Ginkgo biloba. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is the UPLC fingerprint of the honeysuckle fruit in the examples of this application;

[0038] Figure 2 This is the UPLC chromatogram of the mixed reference substance in the examples of this application, and the characteristic peaks are: 1-neochlorogenic acid, 4-chlorogenic acid, 5-cryptochlorogenic acid, 6-caffeic acid, 10-dangoside, 15-luteolin, 19-isochlorogenic acid A, 21-isochlorogenic acid C;

[0039] Figure 3 UPLC fingerprints of 13 batches of silver flower seeds in the examples of this application; 1-6 are silver flower seeds produced in Shandong; 7-9 are silver flower seeds produced in Hebei; 10-13 are silver flower seeds produced in Henan; R is the reference spectrum formed by 13 batches of silver flower seeds samples;

[0040] Figure 4 This is a cluster analysis diagram of 13 batches of silver flower seeds in the examples of this application;

[0041] Figure 5 This is the PCA model diagram of 8 active ingredients in 13 batches of Yinhuazi in the examples of this application;

[0042] Figure 6 This is the OPLS-DA model diagram of 8 active ingredients in 13 batches of Yinhuazi in the examples of this application;

[0043] Figure 7 This is a graph showing the results of displacement testing of 8 active ingredients in 13 batches of Yinhuazi in the examples of this application;

[0044] Figure 8 This is the VIP diagram of 8 active ingredients in 13 batches of Yinhuazi in the examples of this application. DETAILED DESCRIPTION

[0045] The technical solution of the present invention is further explained and illustrated by means of specific embodiments below.

[0046] Example 1

[0047] The present application provides a UPLC fingerprint of Lonicera japonica fruit, and the method for establishing the fingerprint comprises:

[0048] (1) Prepare honeysuckle test solution, reference solution, and mixed reference solution

[0049] Prepare the honeysuckle fruit test solution: Grind the honeysuckle fruit and pass it through a 60-mesh sieve to obtain honeysuckle fruit powder. Add 50 mL of 75% methanol (volume fraction) to 0.3 g of honeysuckle fruit powder. Ultrasonicate at 512 W and 40 kHz for 30 min. Filter the filtrate through a 0.22 μm microporous membrane to obtain the honeysuckle fruit test solution.

[0050] Prepare reference solution: accurately weigh appropriate amounts of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, chlorogenic acid, isochlorogenic acid A, and isochlorogenic acid C, and dissolve them in methanol. At the same time, dissolve luteolin in 70% ethanol to form a concentration of 1.14 mg mL -1 , 2.01mg·mL -1 , 1.58mg·mL -1 , 1.13 mg·mL -1 , 1.18 mg·mL -1 , 1.37 mg·mL -1 , 1.23 mg·mL -1 , 0.13mg·mL -1 8 reference solutions.

[0051] Prepare mixed reference solution: 8 reference solution were measured separately, and methanol with a volume fraction of 75% was added to prepare the neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidyl glycoside, luteolin, isochlorogenic acid A, and isochlorogenic acid C, with the contents of 43.39 μg·mL -1 , 58.11 μg·mL -1 , 98.19 μg·mL -1 , 84.18 μg·mL -1 , 64.07 μg·mL -1 , 4.58 μg·mL -1 , 68.45 μg·mL -1 , 92.71 μg·mL -1 mixed reference solution.

[0052] (2) UPLC detection

[0053] The UPLC test of the Fructus Lonicerae test solution was performed to obtain a UPLC chromatogram of the test sample with 23 characteristic chromatographic peaks, as shown in the attached figure. Figure 1 At the same time, the mixed reference solution was tested by UPLC to obtain a mixed reference UPLC chromatogram, as shown in the attached figure. Figure 2 shown.

[0054] All UPLC detection conditions in the examples of this application are as follows: Thermo Accucore™ C18 column (100 mm × 4.6 mm, 2.6 μm), mobile phase acetonitrile (A)-0.1% phosphoric acid aqueous solution (B), gradient elution, column temperature 30°C, volume flow rate 0.3 mL min -1 The injection volume was 1 μL, and the detection wavelength was 204-328 nm. The gradient elution program was: 0%-8% A (0-7 min); 8%-16% A (7-13 min); 16%-16% A (13-21 min); 16%-17% A (21-26 min); 17%-27% A (26-35 min); 27%-27% A (35-40 min). The detection wavelength dynamic switching program was: 326 nm (0-14.6 min); 246 nm (14.6-17.8 min); 238 nm (17.8-22.0 min); 204 nm (22.0-28.0 min); and 328 nm (28.0-40.0 min).

[0055] In the examples of this application, the precision, repeatability, stability and sample recovery rate of the UPLC detection instrument were tested respectively. The specific experimental process is as follows:

[0056] Precision test: The honeysuckle seed sample solution was injected and measured six times continuously according to the UPLC detection conditions, and the RSD value of the peak area of ​​each component was calculated. The results showed that the relative peak area RSDs of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, tangerinoside, luteolin, isochlorogenic acid A, and isochlorogenic acid C were 0.33%, 0.30%, 0.41%, 0.29%, 0.34%, 0.41%, 0.34%, and 0.25%, respectively. The RSDs of the relative peak areas of each chromatographic peak were less than 3%, indicating that the UPLC detection instrument has good precision.

[0057] Repeatability test: Six samples of honeysuckle fruit from the same batch were used to prepare six honeysuckle fruit test solutions. Each of the six honeysuckle fruit test solutions was subjected to UPLC analysis according to the UPLC detection conditions, and the relative standard deviation (RSD) values ​​of the peak areas of each component were calculated. The results showed that the relative peak area RSDs for neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, tangerinoside, luteolin, isochlorogenic acid A, and isochlorogenic acid C were 0.25%, 0.18%, 0.84%, 0.15%, 0.17%, 0.31%, 0.54%, and 0.21%, respectively. The RSDs for the relative peak areas were less than 3%, indicating good repeatability of the UPLC detection instrument.

[0058] Stability test: The sample solution of honeysuckle seed was injected at 0, 2, 4, 8, 12, and 24 hours according to the UPLC detection conditions, and the RSD value of the peak area of ​​each component was calculated. The results showed that the area RSDs of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, danshin, luteolin, isochlorogenic acid A, and isochlorogenic acid C were 0.62%, 0.46%, 0.47%, 0.39%, 0.41%, 0.47%, 0.35%, and 0.46%, respectively, indicating that each component had good stability within 24 hours.

[0059] Recovery test: Accurately weigh six portions (0.15 g) of known Lonicera japonica seed powder. Add reference substances (neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidinoside, luteolin, isochlorogenic acid A, and isochlorogenic acid C) to each of the six portions of Lonicera japonica seed powder at a 1:1 mass ratio to form a mixed sample. UPLC analysis was performed on the six mixed samples according to the UPLC detection conditions. Calculate the relative standard deviation (RSD) of the peak area for each component and the recovery of the sample. The results showed that the relative peak area RSDs of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidyl glycoside, oligurol glycoside, isochlorogenic acid A and isochlorogenic acid C were 0.34%, 2.14%, 2.28%, 0.87%, 2.56%, 1.70%, 0.94% and 1.69%, respectively, and the sample recoveries were 100.82%, 101.67%, 100.21%, 99.48%, 101.39%, 97.97%, 99.57% and 97.61%, respectively, indicating that the method had good accuracy.

[0060] (3) Construction of UPLC fingerprint of honeysuckle fruit

[0061] The UPLC chromatograms of the test sample and the mixed reference substance were compared, and the common characteristic peaks in the UPLC chromatograms of the test sample and the mixed reference substance were matched according to the retention time to construct the UPLC fingerprint of the honeysuckle fruit. Figure 1 . Figure 1 It can be seen that the UPLC fingerprint of Lonicera japonica includes 23 common characteristic peaks, and 8 qualitative identification characteristic peaks are identified, among which the 8 qualitative identification characteristic peaks are: Peak 1: neochlorogenic acid; Peak 4: chlorogenic acid; Peak 5: cryptochlorogenic acid; Peak 6: caffeic acid; Peak 10: chlorogenic acid; Peak 15: luteolin; Peak 19: isochlorogenic acid A; Peak 21: isochlorogenic acid C.

[0062] Example 2

[0063] The present invention provides a method for quantitatively analyzing the active ingredients in Yinhuazi, which comprises:

[0064] (1) Prepare the test solution and 8 reference solution

[0065] The medicinal material of honeysuckle was collected from Shandong, Henan and Hebei and identified as Lonicera japonica Lonicera japonica The sources of the mature fruits of Thunb. and silver flower seed samples are shown in Table 1 .

[0066] Table 1: Sources of Silver Flower Seed Samples

[0067]

[0068] Prepare the test solution: Grind 13 batches of honeysuckle fruit to be tested and pass them through a 60-mesh sieve to obtain honeysuckle fruit powder. Add 75% methanol by volume to each batch of honeysuckle fruit powder. Ultrasonicate at a power of 512 W and a frequency of 40 kHz for 30 minutes. Filter the filtrate through a 0.22 μm microporous membrane to obtain 13 batches of test solution.

[0069] Prepare reference solution: accurately weigh appropriate amounts of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, chlorogenic acid, isochlorogenic acid A, and isochlorogenic acid C, and dissolve them in methanol. At the same time, dissolve luteolin in 70% ethanol to form a concentration of 1.14 mg mL -1 , 2.01mg·mL -1 , 1.58mg·mL -1 , 1.13 mg·mL -1 , 1.18 mg·mL -1 , 1.37 mg·mL -1 , 1.23 mg·mL -1 , 0.13mg·mL -1 8 reference solutions.

[0070] (2) UPLC detection and drawing of standard curve

[0071] Eight reference solutions were precisely measured and diluted to six different concentrations with 75% methanol. After filtration through a 0.22 μm microporous membrane, UPLC analysis was performed to obtain UPLC chromatograms for each reference. UPLC analysis conditions were: a Thermo Accucore™ C18 column (100 mm × 4.6 mm, 2.6 μm), a mobile phase of acetonitrile (A)-0.1% aqueous phosphoric acid (B), gradient elution, column temperature at 30°C, and a flow rate of 0.3 mL / min. -1, injection volume 1 μL, detection wavelength 204-328 nm. Gradient elution program: 0-7 min, 0%-8% A; 7-13 min, 8%-16% A; 13-21 min, 16%-16% A; 21-26 min, 16%-17% A; 26-35 min, 17%-27% A; 35-40 min, 27%-27% A. Detection wavelength dynamic switching program: 0-14.6 min, 326 nm; 14.6-17.8 min, 246 nm; 17.8-22.0 min, 238 nm; 22.0-28.0 min, 204 nm; 28.0-40.0 min, 328 nm. The injection concentration of the reference substance was μg·mL -1 With the peak area in the UPLC chromatogram as the horizontal coordinate X and the peak area in the UPLC chromatogram as the vertical coordinate Y, the linear regression equation was calculated and the standard curve was drawn to obtain Table 2.

[0072] Table 2: Linear regression equations of 8 active ingredients in Yinhuazi

[0073]

[0074] (3) Determination of the contents of 8 active ingredients in 13 batches of Yinhuazi

[0075] 13 batches of test sample solutions were taken respectively, and the UPLC fingerprints of 13 batches of tested silver flower fruits were obtained according to the determination method and UPLC detection conditions of the above 8 reference solution. Figure 3 According to the UPLC fingerprint of the tested honeysuckle fruit, the peak areas of the eight active ingredients in each batch of honeysuckle fruit were determined, and the peak areas were respectively substituted into the linear regression equation in Table 2 to calculate the contents of the eight active ingredients in each batch of honeysuckle fruit, and Table 3 was obtained.

[0076] Table 3: Contents of 8 active ingredients in 13 batches of Yinhuazi ( , n=3), mg·g -1

[0077]

[0078] Example 3

[0079] The present application provides a method for identifying the quality of silver flower seeds, the method comprising:

[0080] UPLC analysis was performed on 13 batches of honeysuckle fruit, yielding UPLC chromatograms of the tested honeysuckle fruit. The "Traditional Chinese Medicine Fingerprint Similarity Evaluation System" was used to compare the similarity between the tested UPLC chromatograms and the established UPLC fingerprint of honeysuckle fruit, yielding the results shown in Table 4. A similarity greater than 0.90 indicates minimal differences in the main chemical components of the honeysuckle fruit batch, indicating that the product is qualified.

[0081] Table 4: Similarity evaluation results

[0082]

[0083] Example 4

[0084] The present invention provides a method for identifying the origin of silver flower seeds, the method comprising:

[0085] (1) UPLC detection

[0086] UPLC was performed on 13 batches of Fructus Lonicerae to obtain the UPLC chromatogram of Fructus Lonicerae, as shown in the attached figure. Figure 3 As shown. Based on the UPLC chromatograms of 13 batches of Yinhuazi, the peak areas of the eight active ingredients in each batch of Yinhuazi were determined, and the peak areas were substituted into the linear equations shown in Table 2 to calculate the contents of the eight active ingredients in the 13 batches of Yinhuazi. The UPLC detection conditions were as follows: Thermo Accucore™ C18 column (100mm × 4.6mm, 2.6μm), mobile phase acetonitrile (A)-0.1% phosphoric acid aqueous solution (B), gradient elution, column temperature 30°C, volume flow rate 0.3mL·min -1 The injection volume was 1 μL, and the detection wavelength was 204-328 nm. The gradient elution program was: 0%-8% A (0-7 min); 8%-16% A (7-13 min); 16%-16% A (13-21 min); 16%-17% A (21-26 min); 17%-27% A (26-35 min); 27%-27% A (35-40 min). The detection wavelength dynamic switching program was: 326 nm (0-14.6 min); 246 nm (14.6-17.8 min); 238 nm (17.8-22.0 min); 204 nm (22.0-28.0 min); and 328 nm (28.0-40.0 min).

[0087] (2) Cluster analysis

[0088] Will attach Figure 3 The peak area data corresponding to the eight active ingredients in the UPLC chromatograms of 13 batches of honeysuckle seeds were imported into origin 2023b software to establish a cluster heat map analysis model, as shown in the attached figure. Figure 4 As shown. Figure 4 The color differences in the heat map squares visually reveal the differences in the content of the eight active ingredients in different batches of silver flower seeds. Silver flower seeds from different origins are highly distinguishable and exhibit significant differences. Based on the varying content of the eight active ingredients, the 13 batches of silver flower seeds were clustered into three categories: 1-6, 7-9, and 10-13.

[0089] (3) Principal component analysis

[0090] Will attach Figure 3 The peak area data corresponding to the eight active ingredients in the UPLC chromatograms of 13 batches of honeysuckle seeds were imported into SIMCA software as variables, and a principal component analysis (PCA) model was established to obtain the attached Figure 5 . Figure 5 Observe the natural aggregation of silver flower seeds in different batches. Figure 5 As can be seen, four principal components were generated, with a cumulative contribution rate of 99.5%, exceeding 80%. Furthermore, Q2 was 0.951, indicating that the PCA model fit well and had good predictive performance. Based on the PCA analysis results, the 13 batches of silver flower seeds were divided into three categories: 1-6 as category one, 7-9 as category two, and 10-13 as category three. This classification result is consistent with the cluster analysis results, further confirming the reliability of the cluster analysis results and providing more accurate support for quality control and origin identification of silver flower seeds.

[0091] (4) Orthogonal partial least squares discriminant analysis

[0092] Since the PCA analysis method cannot ignore the intra-group error, in order to eliminate the random error irrelevant to the research purpose, the supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model was selected based on PCA for analysis. The established OPLS-DA model is shown in the attached figure. Figure 6 As shown in the attached Figure 6 The OPLS-DA model shown in the figure has OPLS-DA cumulative explanatory power parameters R2X=0.981, R2Y=0.895, and predictive power parameter Q2=0.878, which indicates that the accuracy, stability and predictive power of the OPLS-DA model are good, and the three types of samples are well clustered, which is consistent with the results of cluster analysis and principal component analysis, further confirming the rationality of cluster analysis and PCA analysis and the differences between samples from different origins.

[0093] In order to verify the reliability of the OPLS-DA model, the OPLS-DA model established in the present embodiment was permuted 200 times and the following results were obtained: Figure 7 The test results shown in the attached Figure 7 It can be seen that the R2 value and Q2 value on the left are lower than those on the right, and the intercept of the regression line of Q2 on the right side on the ordinate is less than 0, indicating that the model does not overfit and the OPLS-DA model is reliable.

[0094] (5) Screening of marker components that affect differences

[0095] The variable influenceon projection (VIP) is calculated based on the orthogonal partial least squares discriminant analysis, and the attached Figure 8 VIP diagram shown. According to the VIP diagram, the marker components that affect the difference can be screened out, wherein the larger the VIP value, the greater the contribution rate of the component to the quality of silver flower fruit. Therefore, in this application, active ingredients with VIP>1 are selected as potential quality markers for distinguishing silver flower fruit, and the potential quality markers include chlorogenic acid, luteolin, and isochlorogenic acid A. The origin of silver flower fruit can be determined by the content ratio of chlorogenic acid, luteolin, and isochlorogenic acid A. When the content ratio of chlorogenic acid, luteolin, and isochlorogenic acid A is 1:0.55-0.57:0.52-0.56, the silver flower seeds are from Shandong; when the content ratio of chlorogenic acid, luteolin, and isochlorogenic acid A is 1:2.17-2.23:1.22-1.38, the silver flower seeds are from Hebei; and when the content ratio of chlorogenic acid, luteolin, and isochlorogenic acid A is 1:1.28-1.29:0.63-0.64, the silver flower seeds are from Henan. Therefore, chlorogenic acid, luteolin, and isochlorogenic acid A may be the key components that lead to quality differences in silver flower seeds and are important indicator components for quality identification and origin identification of silver flower seeds.

[0096] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A method for establishing a UPLC fingerprint of Lonicera japonica L., characterized in that: include: preparing a honeysuckle fruit test solution and a mixed reference solution, wherein the mixed reference solution is prepared from neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidyl glycoside, luteolin, isochlorogenic acid A and isochlorogenic acid C; The honeysuckle test solution and the mixed reference solution are respectively subjected to UPLC detection to obtain a test sample UPLC chromatogram and a mixed reference UPLC chromatogram; Comparing the UPLC chromatogram of the test sample with the UPLC chromatogram of the mixed reference sample, matching the common characteristic peaks, and constructing a UPLC fingerprint of the honeysuckle fruit; the UPLC fingerprint of the honeysuckle fruit includes 23 common characteristic peaks and 8 qualitative identification characteristic peaks; The UPLC detection conditions are as follows: Thermo Accucore™ C18 column, mobile phase acetonitrile (A)-0.1% phosphoric acid aqueous solution (B), gradient elution, column temperature 30°C, volume flow rate 0.3 mL min -1 , injection volume 1 μL, detection wavelength 204-328 nm; The gradient elution program is: 0-7 min, 0%-8% A; 7-13 min, 8%-16% A; 13-21 min, 16%-16% A; 21-26 min, 16%-17% A; 26-35 min, 17%-27% A; 35-40 min, 27%-27% A; The dynamic switching program of the detection wavelength is: 0-14.6 min, 326 nm; 14.6-17.8 min, 246 nm; 17.8-22.0 min, 238 nm; 22.0-28.0 min, 204 nm; 28.0-40.0 min, 328 nm.

2. The method for establishing the UPLC fingerprint of the Fructus Lonicerae according to claim 1, wherein: There are 8 qualitative identification characteristic peaks, among which, peak 1: neochlorogenic acid; peak 4: chlorogenic acid; peak 5: cryptochlorogenic acid; peak 6: caffeic acid; peak 10: chlorogenic acid glycoside; peak 15: luteolin; peak 19: isochlorogenic acid A; peak 21: isochlorogenic acid C.

3. A UPLC fingerprint of Lonicera japonica, characterized in that: The method for establishing the UPLC fingerprint of Lonicera japonica fruit according to claim 1 or 2 is constructed.

4. The UPLC fingerprint of the Fructus Lonicerae according to claim 3 is used to identify the quality of the Fructus Lonicerae, and the method for identifying the quality of the Fructus Lonicerae comprises: The UPLC test is performed on the tested honeysuckle fruit to obtain a UPLC chromatogram of the tested honeysuckle fruit, and the similarity between the tested honeysuckle fruit UPLC chromatogram and the honeysuckle fruit UPLC fingerprint is compared. The honeysuckle fruit with a similarity greater than 0.90 is a qualified product.

5. Application of the UPLC fingerprint of the Fructus Lonicerae according to claim 3 in the quantitative analysis of active ingredients in the Fructus Lonicerae.

6. The use according to claim 5, characterized in that The method for quantitatively analyzing the active ingredients in Yinhuazi comprises: Prepare a test solution and 8 reference solution, wherein the 8 reference solution are prepared from neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, arachidyl glycoside, luteolin, isochlorogenic acid A and isochlorogenic acid C, respectively; The reference solution was tested by UPLC, and the linear equation was calculated and the standard curve was drawn with the reference sample concentration as the horizontal axis and the peak area as the vertical axis; The test solution was subjected to UPLC detection, the peak areas of the eight active ingredients were recorded, and the active ingredient content was calculated according to the linear equation; The UPLC detection conditions are as follows: Thermo Accucore™ C18 column, mobile phase acetonitrile (A)-0.1% phosphoric acid aqueous solution (B), gradient elution, column temperature 30°C, volume flow rate 0.3 mL min -1 , injection volume 1 μL, detection wavelength 204-328 nm.

7. Use of the content of active ingredients in the honeysuckle fruit according to claim 5 in identifying the origin of the honeysuckle fruit.

8. The use according to claim 7, characterized in that The method for identifying the origin of silver flower seeds comprises: Different batches of Yinhuazi were tested by UPLC to obtain the contents of 8 active ingredients in Yinhuazi; Cluster analysis, principal component analysis and orthogonal partial least squares discriminant analysis were performed on the Yinhuazi according to the contents of the eight active ingredients in the Yinhuazi, and different batches of Yinhuazi were classified; Screening potential quality markers based on the variable importance projection value in the orthogonal partial least squares discriminant analysis; the potential quality markers include chlorogenic acid, luteolin, and isochlorogenic acid A; The origin of the honeysuckle fruit is determined according to the content ratio of chlorogenic acid, luteolin and isochlorogenic acid A.

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