Dried pear dual-wavelength fingerprint spectrum detection method and control characteristic spectrum thereof

Abstract

The invention relates to the technical field of traditional Chinese medicinal materials, in particular to a detection method for a dual-wavelength fingerprint spectrum of dried pears and a control characteristic chromatogram of the dried pears, and the detection method comprises the following steps: determination of high performance liquid chromatography conditions: detection wavelengths are 280 nm (0-25 min) and 350 nm (26-90 min); preparing a mixed reference substance solution; preparing a dried pear test solution; establishing a dried pear control characteristic spectrum; detecting the quality of the dry pear sample to be detected; and analyzing the quality of the dried pears in combination with a chemometrics analysis method. The dual-wavelength fingerprint spectrum detection method provided by the invention can be used for comprehensively and effectively detecting main chemical components of the dried pears, a scientific evaluation method is provided for quality control of the dried pears, and the method can provide a scientific basis for subsequent development of dried pear medicinal and edible decoction pieces.

Description

Technical Field

[0001] This invention relates to the field of traditional Chinese medicine technology, and in particular to a method for detecting dual-wavelength fingerprint spectrum of dried pear and its control characteristic spectrum. Background Technology

[0002] Pears were first recorded in the "Records of Famous Physicians" and have a long history of medicinal use. They are known for their moisturizing, thirst-quenching, heat-clearing, and phlegm-resolving effects. However, due to their cooling nature, they are not suitable for people with weak spleen and stomach. Dried pears are made from fresh pears after washing, slicing, and drying. The baking process removes the inherent cooling properties of the pear, giving it a refreshing and nourishing effect without any cooling properties. Furthermore, dried pears are easy to transport and store, making them more suitable for development into a medicinal and edible herbal product.

[0003] White pear, sand pear, and autumn pear are listed as medicinal varieties in the "Hunan Provincial Standards for Traditional Chinese Medicine" and the "Hubei Provincial Standards for Traditional Chinese Medicine." These standards mainly specify the source, characteristics, and identification methods of pears, but the quality control standards are not comprehensive.

[0004] Pears are rich in polyphenols and flavonoids, such as arbutin, chlorogenic acid, and rutin. Pharmacological studies have shown that polyphenols have antioxidant, anti-inflammatory, antibacterial, and anti-ulcer effects, and are one of the main effective components of pears. Existing technologies related to pears mainly focus on the determination of total flavonoids, total phenols, or the content of a single component, or on fingerprint analysis under a single wavelength. However, the main effective components of dried pears have complex structures and highly diverse compound properties, with each component exhibiting different ultraviolet absorption characteristics. Single-wavelength fingerprint analysis methods cannot comprehensively and effectively reflect the multi-component information of dried pears. The composition and content of dried pears are similar to, but not entirely the same as, fresh pears. Dried pears retain the nutritional components and medicinal value of fresh pears after being "cooled," making them suitable for a wider range of people. However, there is currently no relevant research data on dried pears. Based on existing research on fresh pears, this study investigates quality control methods for dried pears, establishes a dual-wavelength fingerprinting detection method and its corresponding characteristic spectrum, which can comprehensively reflect the types and quantities of chemical components contained in dried pears. Combined with chemometrics, this allows for a more comprehensive and accurate overall description and evaluation of the quality of dried pears, providing a scientific basis for the subsequent development of dried pears as both food and medicine. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a dual-wavelength fingerprint spectrum detection method for dried pears and its corresponding characteristic spectrum, which can better reflect the types and quantities of chemical components contained in dried pears, establish more comprehensive quality control standards, and thus provide an overall description and evaluation of the quality of dried pears.

[0006] In a first aspect, the present invention provides a method for evaluating the quality of dried pear fingerprint spectra, the method comprising the following steps:

[0007] (1) Chromatographic conditions: Column: Kromasil 100-5-C 18 Specifications: 4.6 × 250 mm, 5 μm; Mobile phase: acetonitrile-0.1% phosphoric acid aqueous solution (V / V), gradient elution; Flow rate: 1.0 mL·min -1 Column temperature: 30℃; Detection wavelength: 280nm (0–25 min) and 350nm (26–90 min); Injection volume: 20 μL; Gradient elution program as follows:

[0008] Time / min Acetonitrile, % 0.1% phosphoric acid aqueous solution, % 0～20 2 98 20～22 2～11 98～89 22～58 11～12 89～88 58～85 12～24 88～76 85～90 24 76

[0009] (2) Solution preparation:

[0010] ① Mixed reference solution: Accurately weigh the reference standards arbutin, chlorogenic acid and rutin, place them in volumetric flasks, dissolve them in 80% methanol and dilute to volume to prepare a mixed reference solution.

[0011] ② Pear Dried Sample Solution: Take dried pear, grind it into powder, accurately weigh 20g, add 40ml of 80% methanol, extract twice by sonication, 15min each time, centrifuge, take the supernatant, evaporate to near dryness in a water bath, dissolve the residue in about 20ml of water, add it to a pretreated D101 macroporous resin column, adsorb, stand, elute with water, elute with 70% ethanol, collect the 70% ethanol eluent, evaporate to dryness in a water bath, dissolve the residue in 80% methanol and make up to 2ml, and the sample is ready.

[0012] (3) Methodological examination:

[0013] ①Precision test: Accurately pipette the same dried pear test solution from step (2), inject it 6 times consecutively under the chromatographic conditions of step (1), record the chromatogram, and use peak 1 as the reference peak to calculate the relative retention time and relative peak area of ​​each common peak in the sample.

[0014] ② Repeatability test: Accurately weigh 6 portions of sample powder, each 20g, prepare the dried pear test solution according to the method in step (2), inject and determine according to the chromatographic conditions in step (1), record the chromatogram, and use peak 1 as the reference peak to calculate the relative retention time and relative peak area of ​​each common peak in the sample.

[0015] ③Stability test: Take the dried pear test solution from step (2), place it at room temperature for 0, 2, 4, 8, 12 and 24 hours respectively, and then inject it according to the chromatographic conditions of step (1) to determine the chromatogram. Record the chromatogram, and use peak 1 as the reference peak to calculate the relative retention time and relative peak area of ​​each common peak in the sample.

[0016] (4) Establishment and analysis of HPLC fingerprint:

[0017] ① Generation of HPLC fingerprint chromatograms: Accurately weigh 20g of each of 20 batches of dried pear samples, prepare dried pear test solutions according to the method in step (2), and then inject and determine according to the chromatographic conditions in step (1), and record the chromatograms; use the "Similarity Evaluation System for Chromatographic Characteristic Spectra of Traditional Chinese Medicine (2012 Edition)" to establish HPLC fingerprint superimposed chromatograms of 20 batches of dried pears, and generate a reference characteristic chromatogram of dried pears;

[0018] ② Identification and related analysis of common peaks: A total of 16 common peaks were identified in the chromatograms of 20 batches of dried pear samples. By comparing with the HPLC chromatograms of the mixed reference solution, peak 1 was identified as arbutin, peak 9 as chlorogenic acid, and peak 10 as rutin. Peak 1 was selected as the reference peak.

[0019] ③ Similarity evaluation: Using the characteristic map of dried pear as a reference, the overall similarity of 20 batches of dried pear samples was evaluated;

[0020] (5) Chemometric analysis:

[0021] ① Cluster analysis: The intergroup linkage method was used, with the peak area of ​​16 common peaks in the HPLC fingerprint of 20 batches of dried pears as the variable and the squared Euclidean distance as the interval. SPSS 26.0 software was used for cluster analysis.

[0022] ② Principal Component Analysis (PCA): The peak area data of the 16 common peaks of dried pears were input into SPSS 26.0 software for dimensionality reduction factor analysis. The first three principal component factors represent most of the information of the 16 common characteristic peaks. Principal component factors 1, 2, and 3 were used as evaluation indicators for dried pears. Common factor scree plots were drawn using the principal component factors as variables. The 16 common characteristic peaks of 20 batches of dried pear samples were selected, and their peak areas were standardized to establish a dried pear quality evaluation model. X1, X2, and X3 represent the three principal components as the information expressed by the components of the 20 batches of dried pear samples. PCA plots of the 20 batches of dried pears were drawn using SIMCA 14.1 software to predict the classification of the 20 batches of dried pear samples.

[0023] ③ Orthogonal Partial Least Squares-Discriminant Analysis (PLS-DA): Based on the PCA classification results, orthogonal partial least squares-discriminant analysis was performed using SIMCA 14.1 software. Two-class and three-class PLS-DA models were established for 20 batches of dried pear samples, and the results were basically consistent with the cluster analysis and PCA results described above. The projected importance (VIP) method was used to screen out six marker components with VIP values ​​greater than 1 for differences in dried pear samples.

[0024] Preferably, the high-performance liquid chromatography (HPLC) detection conditions in step (1) are: detection wavelengths of 280 nm (0–25 min) and 350 nm (26–90 min). Chromatograms at different detection wavelengths were compared. The results showed that arbutin (peak 1) had the maximum UV absorption at 280 nm, and peaks 1–6 all had large peak areas and ideal separation within 0–25 min. Chlorogenic acid (peak 9) and rutin (peak 10) had large UV absorption at 280 nm, but poor separation, and many impurity peaks appeared between 25–29 min. Many peaks were observed between 70 and 90 min, with some inverted peaks appearing. At a wavelength of 350 nm, peaks 1 (arbutin), 2, 3, 4, 5, and 6 did not appear between 0 and 25 min, but chlorogenic acid (peak 9) and rutin (peak 10) showed significant UV absorption at 350 nm. Peaks 9 to 16 all had large peak areas and ideal separation. Furthermore, no impurities or inverted peaks appeared between 26 and 90 min. Therefore, a detection wavelength of 280 nm was selected for analysis between 0 and 25 min, and a detection wavelength of 350 nm was selected for analysis between 26 and 90 min.

[0025] Preferably, the pear sample solution in step (2) is pretreated with a D101 macroporous resin column. The pretreatment method is as follows: take D101 macroporous adsorption resin, soak it in 95% ethanol for 24 hours to fully swell, rinse it with 95% ethanol until a suitable amount of soaking solution is added to water and no white turbidity is observed, take the wet resin, pack it into the column using the wet method (column volume is 20 ml), and rinse it with distilled water until there is no alcohol smell.

[0026] Preferably, the dried pear test solution described in step (2) is added to a pretreated D101 macroporous resin column, and the adsorption rate is 1 mL·min. -1 After standing for 2 hours, elute with 80 mL of water, then elute with 80 mL of 70% ethanol, at a rate of 2 mL / min. -1 Collect the 70% ethanol eluent, evaporate it to dryness in a water bath, dissolve the residue in 80% methanol and make up to 2 ml to obtain the final product.

[0027] Preferably, in step (2), the ultrasonic extraction has an ultrasonic frequency of 35,000 to 45,000 Hz and an extraction time of 15 to 20 min; the centrifugation process has a centrifugation speed of 5,000 to 2,000 rpm and a centrifugation time of 5 to 15 min.

[0028] Preferably, the mixed reference solution in step (2) is prepared by accurately weighing arbutin, chlorogenic acid and rutin reference standards, placing them in 10 mL volumetric flasks, adding methanol solution and making up to volume.

[0029] Preferably, the reason for selecting arbutin (peak 1) as the reference peak (S) in step (4) is that arbutin has a moderate retention time, a large response value, and meets the requirements in terms of symmetry factor and resolution in the chromatogram, and is common to all dried pear samples.

[0030] Preferably, step (5) indicates that the first three principal component factors represent most of the information of the 16 common characteristic peaks because three principal component factors are extracted, with eigenvalues ​​> 1.0 and a cumulative variance contribution rate of 93.870%.

[0031] This invention also relates to a detection method for dual-wavelength fingerprinting of dried pears, as described above, and obtaining a characteristic spectrum of dried pears as a reference. Sixteen common peaks were identified, and peak 1 was identified as arbutin, peak 9 as chlorogenic acid, and peak 10 as rutin. Chemometry analysis indicated that 20 batches of dried pears could be divided into two categories (those from Hebei and those from other regions). Peaks 9 (chlorogenic acid), 4, 5, 8, 13, and 1 (arbutin) were differential markers that had a significant impact on the quality of dried pears and could be used as indicators for evaluating the quality of dried pears.

[0032] Compared with the prior art, the beneficial effects of the present invention are:

[0033] Currently, pears are listed as a medicinal variety in the "Hunan Provincial Standard for Traditional Chinese Medicine" and the "Hubei Provincial Standard for Traditional Chinese Medicine," but these standards only specify their source, characteristics, and identification. Literature research on pears mainly focuses on the determination of total flavonoids, total phenols, or a single component, or on fingerprint analysis at a single wavelength. This invention presents a dual-wavelength fingerprint analysis method for dried pears. This method uses similarity evaluation, cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis to analyze the quality of dried pears from different perspectives. It is the first to use dual-wavelength liquid chromatography to simultaneously detect the types and quantities of chemical components in dried pears and establish a characteristic chromatogram for dried pears. This analytical method provides a scientific basis for the standardized production and quality control of dried pear medicinal materials.

[0034] The present invention compared chromatograms at different detection wavelengths (270, 280, 325, 350 nm). The results showed that at a wavelength of 280 nm, peaks 1-6 had large peak areas and ideal separation from 0 to 25 min, but many impurity peaks and inverted peaks appeared from 26 to 90 min. At a wavelength of 350 nm, peaks 1-6 did not elute from 0 to 25 min, but peaks 9-16 had large peak areas and ideal separation from 29 to 90 min. Therefore, a detection wavelength of 280 nm was selected for analysis from 0 to 25 min, and a detection wavelength of 350 nm was selected for analysis from 26 to 90 min.

[0035] This invention discloses a method for detecting dual-wavelength fingerprint spectroscopy of dried pears and its corresponding characteristic spectroscopy. For the first time, factor analysis is used to analyze the quality of different batches of dried pears, simplifying the 16 common characteristic peaks detected into three principal components as evaluation indicators for dried pears. The contribution rate of each principal component is calculated by analyzing the original data, overcoming the problem of manually determining the weights of each indicator in other comprehensive evaluation methods, resulting in a more objective and impartial evaluation.

[0036] This invention discloses a method for detecting the dual-wavelength fingerprint spectrum of dried pears and its corresponding control characteristic spectrum. Sixteen common peaks were identified from the established control characteristic spectrum, with peak 1 designated as arbutin, peak 9 as chlorogenic acid, and peak 10 as rutin. Chemometric analysis suggests that dried pears can be divided into two main categories (those from Hebei and those from other regions). Peaks 9 (chlorogenic acid), 4, 5, 8, 13, and 1 (arbutin) are differential marker components that significantly influence the quality of dried pears and can be used as quality evaluation indicators. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a high-performance liquid phase fingerprint overlay pattern of dried pears according to the present invention;

[0039] Figure 2 The comparative characteristic spectrum of the dried pear of the present invention (1. arbutin; 9. chlorogenic acid; 10. rutin);

[0040] Figure 3 The chromatogram of the mixed reference standard of the present invention (1. arbutin; 9. chlorogenic acid; 10. rutin);

[0041] Figure 4 This is a cluster analysis dendrogram of the dried pears of the present invention;

[0042] Figure 5 This is a PCA crushed stone diagram of the dried pear of the present invention;

[0043] Figure 6 This is a PCA score chart of the dried pears of the present invention;

[0044] Figure 7 The present invention provides a PLS-DA model for the two categories of dried pears.

[0045] Figure 8 The present invention provides a PLS-DA model for the three categories of dried pears.

[0046] Figure 9 OPLS-DA loading plot of 16 common peaks in pear stem

[0047] Figure 10 VIP value of 16 common peaks in dried pear

[0048] Figure 11 HPLC chromatogram of dried pear (detection wavelength 280 nm)

[0049] Figure 12 HPLC chromatogram of dried pear (detection wavelength 350 nm) Detailed Implementation

[0050] The technical solution of the present invention will be clearly and completely described below with reference to specific embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0051] Example 1

[0052] Reagents: Arbutin reference standard (batch number: 111951-201301, content 99.7%), chlorogenic acid (batch number: 110753-202119, content 96.30%), and rutin (batch number: 100080-202012, content 91.6%) were all obtained from the National Institutes for Food and Drug Control, China; acetonitrile was chromatographic grade, and all other reagents were analytical grade.

[0053] The sources of the dried pear medicinal materials used in this implementation are shown in Table 1.

[0054]

[0055]

[0056] 1. Establishment of fingerprint patterns

[0057] 1.1 Chromatographic conditions

[0058] The chromatographic column was Kromasil 100-5-C. 18 Specifications: 4.6 × 250 mm, 5 μm; Mobile phase: acetonitrile (phase A), 0.1% phosphoric acid aqueous solution (V / V) (phase B); Gradient elution program

[0059]

[0060]

[0061] Flow rate: 1.0 mL·min-1 Column temperature: 30℃; Detection wavelength: 280nm (0~25min) and 350nm (26~90min); Injection volume: 20μL.

[0062] 1.2 Preparation of dried pear test solution

[0063] Soak D101 macroporous adsorption resin in 95% ethanol for 24 hours to allow it to fully swell. Rinse with 95% ethanol until the soaking solution does not turn white and turbid when diluted with water. Crush dried pear herbs and accurately weigh 20g. Add 40mL of 80% methanol solution and extract twice with ultrasound for 15min each time. Centrifuge and collect the supernatant. Evaporate the supernatant to near dryness in a water bath. Dissolve the residue in about 20ml of water and add D101 macroporous adsorption resin. The adsorption rate is 1mL of resin. -1 Let stand for 2 hours, then elute with 80 mL of water, followed by 80 mL of 70% ethanol at a rate of 2 mL / min. -1 Collect the 70% ethanol eluent, evaporate it to dryness in a water bath, dissolve the residue in 80% methanol and make up to 2 ml to obtain the dried pear test solution;

[0064] 1.3 Preparation of mixed reference solution

[0065] Accurately weigh 4.33 mg of arbutin, 19.98 mg of chlorogenic acid, and 1.52 mg of rutin, place them separately in the same 10 mL volumetric flask, and dilute to the mark with 80% methanol to obtain a mixed reference solution.

[0066] 1.4 Precision Test

[0067] One portion of the dried pear test solution was injected six times consecutively under chromatographic conditions. Peak 1 (arbutin) was used as the reference peak. The relative retention time RSD of the total peaks was <1.94%, and the relative peak area RSD was <3.88%, indicating that the method has good precision.

[0068] 1.5 Stability Test

[0069] One sample of dried pear test solution was injected at 0, 2, 4, 8, 12 and 24 h according to the chromatographic conditions. Peak 1 (arbutin) was used as the reference peak. The relative retention time RSD of the total peaks was <2.76% and the relative peak area RSD was <4.14%, indicating that the dried pear sample was relatively stable within 24 h.

[0070] 1.6 Repeatability Test

[0071] Take dried pears and prepare 6 sample solutions of dried pears to be tested according to the method in 1.2. Inject the samples under chromatographic conditions, with peak 1 (arbutin) as the reference peak. The relative retention time of the total peaks RSD < 2.87% and the relative peak area RSD < 3.96%, indicating that the method has good repeatability.

[0072] 1.7 Establishment of Standard Fingerprint Spectrum for Dried Pear

[0073] Twenty batches of dried pears were collected, and pear sample solutions were prepared according to method 1.2. The samples were injected under chromatographic conditions, and the chromatograms were imported into the "Software for Evaluating the Similarity of Chromatographic Characteristic Chromatography of Traditional Chinese Medicine (2012 Edition)". Using L1 as the reference chromatogram, high-performance liquid chromatography fingerprint overlay chromatograms of the 20 batches of samples (L1~L20) were generated (see...). Figure 1 ) and a characteristic atlas of dried pears (see Figure 2 ), and identified 16 common peaks.

[0074] 1.8 Common Peak Identification

[0075] Spectrum of mixed reference standard (see) Figure 3 The peaks were compared, and peak 1 was identified as arbutin, peak 9 as chlorogenic acid, and peak 10 as rutin, with retention times of 6.639, 31.426, and 72.754 min, respectively. Peak 1 (arbutin) had a moderate peak area and ideal separation, so peak 1 was selected as the reference peak.

[0076] 1.9 Similarity Evaluation

[0077] Similarity analysis of fingerprint chromatograms of 20 batches of dried pears with control chromatograms showed that the similarity of dried pears from L1 to L20 was 0.997, 0.972, 0.993, 0.961, 0.970, 0.985, 0.959, 0.988, 0.995, 0.990, 0.981, 0.991, 0.994, 0.991, 0.982, 0.995, 0.996, 0.997, 0.988, and 0.997, respectively. This indicates that the 20 batches of samples have high similarity and relatively stable chemical composition.

[0078] Example 2

[0079] This embodiment provides a chemical pattern recognition analysis method and combines it with the results of feature map analysis to achieve a more objective and comprehensive evaluation of the quality of dried pears.

[0080] 2.1 System Cluster Analysis

[0081] The intergroup linkage method was used, with the peak area of ​​16 common peaks in the HPLC characteristic spectra of 20 batches of dried pears as the variable and the squared Euclidean distance as the interval, and SPSS 26.0 software was used for cluster analysis.

[0082] Test results are as follows Figure 4 As shown, the test results indicate that when the squared Euclidean distance is 5, the 20 batches of dried pears can be clustered into 3 categories: L2 and L5 cluster into 1 category, L4 and L7 cluster into 1 category, and the rest cluster into 1 category.

[0083] When the square Euclidean distance is 10, the 20 batches of dried pears can be grouped into 2 categories: L2, L4, L5, and L7, which are not from Hebei, belong to category 1, and the rest of the Hebei-produced products belong to category 1.

[0084] The results indicate that there are certain differences in the quality of dried pears from different producing areas, while dried pears from the same producing area have a certain degree of quality similarity.

[0085] 2.2 Principal Component Analysis

[0086] The peak area data of the common peaks of the 16 dried pears were entered into SPSS 26.0 software for dimensionality reduction factor analysis.

[0087] The analysis results show that the cumulative variance contribution rate of the first three principal components is 93.870%. Table 2 shows the principal component eigenvalues ​​and variance contribution rates of 20 batches of dried pear samples.

[0088] Table 2 and Figure 5 By combining the abrupt change points of the scree plot, three principal components were extracted for matrix data analysis.

[0089] Table 2. Analysis of principal component eigenvalues ​​and variance contribution rates of 20 batches of dried pear samples.

[0090]

[0091] The results of the three principal component matrices (Table 3) show that peaks 9 (chlorogenic acid), 1 (arbutin), 11, and 10 (rutin) contribute significantly to principal component 1, peaks 3, 7, and 4 contribute significantly to principal component 2, and peaks 2, 7, and 8 contribute significantly to principal component 3.

[0092] Table 3. Composition matrix of 20 batches of dried pear samples

[0093]

[0094]

[0095] Principal component 1 has the largest initial eigenvalue, so the weight values ​​of its variables can reflect the correlation between chemical components and the quality of medicinal materials to the greatest extent. Among them, peak 9 (chlorogenic acid), peak 1 (arbutin), peak 11, and peak 10 (rutin) contribute the most to principal component 1. Therefore, these components are important factors affecting the quality differences of dried pears.

[0096] PCA charts for 20 batches of dried pears were generated using SIMCA 14.1 software, as follows: Figure 6 As shown, the test results indicate that R 2 X(cum) = 0.807, Q 2The cum value (0.600) indicates that the model has good variable explanation and group prediction capabilities. The 20 batches of dried pear samples can be clustered into 2 or 3 groups. When clustered into 3 groups, L2 and L5 cluster into 1 group (upper right side of the score plot), L4 and L7 cluster into 1 group (lower right side of the score plot), and the rest cluster into 1 group (left side of the score plot). When clustered into 2 groups, L2, L4, L5, and L7 cluster into 1 group (right side of the score plot), and the rest cluster into 1 group (left side of the score plot), which is basically consistent with the above cluster analysis results.

[0097] Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) is employed.

[0098] Based on the PCA classification results, PLS-DA analysis was performed using SIMCA 14.1 software.

[0099] PLS-DA models for categories 2 and 3 were established for 20 batches of dried pear samples, respectively. The PLS-DA score chart is shown below. Figure 7 and Figure 8 .

[0100] In the PLS-DA model, the parameters R²X(cum) and R²Y(cum) represent the model's explanatory power for the variables on the X and Y axes, respectively, and the parameter Q... 2 (cum) represents the model's predictive ability for grouping, R 2 X, R 2 Y(cum) and Q 2 The closer (cum) is to 1, the better the model's predictive and explanatory power.

[0101] When 20 batches of dried pears are divided into 2 categories, R 2 X(cum) = 0.846, R 2 Y(cum) = 0.988, Q 2 When (cum) = 0.944, and the classification is divided into 3 categories, R 2 X(cum) = 0.898, R 2 Y(cum) = 0.956, Q 2 (cum) = 0.790, indicating that when divided into two categories, the constructed PLS-DA model has better predictive and explanatory capabilities.

[0102] according to Figure 7 The 20 batches of dried pear samples were divided into two categories: L2, L4, L5, and L7 were divided into one category, and L1, L3, L6, and L8 to L20 were divided into another category, which is basically consistent with the above cluster analysis and PCA results.

[0103] Comparative Example 1

[0104] Compared with Example 1, a single wavelength of 280 nm was used to detect the HPLC fingerprint of dried pears, and the remaining steps were the same as in Example 1.

[0105] The results showed that arbutin (peak 1) had the largest UV absorption at a detection wavelength of 280 nm. Peaks 1-6 had large peak areas and ideal separation in the 0-25 min range. Chlorogenic acid (peak 9) and rutin (peak 10) had large UV absorption at 280 nm in the 26-90 min range, but poor separation and numerous extraneous peaks, including some inverted peaks, were observed. Therefore, a detection wavelength of 280 nm is suitable for the analysis of peak components in the 0-25 min range. Figure 11 .

[0106] Comparative Example 2

[0107] Compared with Example 1, a single wavelength of 350 nm was used to detect the HPLC fingerprint of dried pears, and the remaining steps were the same as in Example 1.

[0108] The results showed that at a detection wavelength of 350 nm, no peaks 1 (arbutin), 2, 3, 4, 5, and 6 were observed in the 0–25 min range. Chlorogenic acid (peak 9) and rutin (peak 10) showed significant UV absorption in the 26–90 min range, with ideal separation. Peaks 9–16 also exhibited large peak areas and ideal separation. Therefore, a wavelength of 350 nm is suitable for the analysis of components eluting in the 26–90 min range. Figure 12 .

[0109] Test results show that

[0110] The present invention has been further described above with reference to specific embodiments. However, it should be understood that the specific description herein should not be construed as limiting the nature and scope of the present invention. Various modifications made to the above embodiments by those skilled in the art after reading this specification are all within the scope of protection of the present invention.

Claims

1. A method for detecting dual-wavelength fingerprints of dried pears, characterized in that, The method includes the following steps: (1) Chromatographic conditions: Column: Kromasil 100-5-C18 (4.6×250mm, 5μm) Detection wavelengths: 280nm (0–25 min) and 350nm (26–90 min); Mobile phase: A: acetonitrile, B: 0.1% (v / v) aqueous phosphoric acid solution. Gradient elution program is as follows: Flow rate: 1.0 mL·min -1 Column temperature: 30℃; Injection volume: 20μL. (2) Solution preparation: ① Mixed reference solution: Accurately weigh the reference standards arbutin, chlorogenic acid and rutin, place them in volumetric flasks, dissolve them in 80% methanol and dilute to volume to prepare a mixed reference solution. ② Pear Dried Sample Solution: Take dried pear, grind it into powder, accurately weigh 20g, add 40ml of 80% methanol, extract twice by sonication, 15min each time, centrifuge, take the supernatant, evaporate to near dryness in a water bath, dissolve the residue in about 20ml of water, add it to a pretreated D101 macroporous resin column, adsorb, stand, elute with water, elute with 70% ethanol, collect the 70% ethanol eluent, evaporate to dryness in a water bath, dissolve the residue in 80% methanol and make up to 2ml, and the sample is ready. (3) Methodological examination: ①Precision test: Accurately pipette the same dried pear test solution from step (2), inject it 6 times consecutively under the chromatographic conditions of step (1), record the chromatogram, and use peak 1 as the reference peak to calculate the relative retention time and relative peak area of ​​each common peak in the sample. ② Repeatability test: Accurately weigh 6 portions of dried pear sample powder, each 20g, prepare dried pear test solution according to the method in step (2), inject and determine according to the chromatographic conditions in step (1), record the chromatogram, and use peak 1 as the reference peak to calculate the relative retention time and relative peak area of ​​each common peak in the sample. ③Stability test: Take the dried pear test solution from step (2), place it at room temperature for 0, 2, 4, 8, 12 and 24 hours respectively, and then inject it according to the chromatographic conditions of step (1) to determine the chromatogram. Record the chromatogram, and use peak 1 as the reference peak to calculate the relative retention time and relative peak area of ​​each common peak in the sample. (4) Establishment and analysis of HPLC fingerprint: ① Generation of HPLC fingerprint chromatograms: Accurately weigh 20g of each of 20 batches of dried pear samples, prepare dried pear test solutions according to the method in step (2), and then inject and determine according to the chromatographic conditions in step (1), and record the chromatograms; use the software "Similarity Evaluation System for Chromatographic Characteristic Spectra of Traditional Chinese Medicine (2012 Edition)" to establish HPLC fingerprint superimposed chromatograms of 20 batches of dried pear, and generate a reference characteristic chromatogram of dried pear; ② Identification and related analysis of common peaks: A total of 16 common peaks were identified in the chromatograms of 20 batches of dried pear samples. By comparing with the HPLC chromatograms of the mixed reference solution, peak 1 was identified as arbutin, peak 9 as chlorogenic acid, and peak 10 as rutin. Peak 1 was selected as the reference peak. ③ Similarity evaluation: Using the characteristic map of dried pear as a reference, the overall similarity of 20 batches of dried pear samples was evaluated; (5) Chemometric analysis: ① Cluster analysis: The intergroup linkage method was used, with the peak area of ​​16 common peaks in the HPLC fingerprint of 20 batches of dried pears as the variable and the squared Euclidean distance as the interval. SPSS 26.0 software was used for cluster analysis. ② Principal Component Analysis (PCA): The peak area data of the 16 common peaks of dried pears were input into SPSS 26.0 software for dimensionality reduction factor analysis. The first three principal component factors represent most of the information of the 16 common characteristic peaks. Principal component factors 1, 2, and 3 were used as evaluation indicators for dried pears. Common factor scree plots were drawn using the principal component factors as variables. The 16 common characteristic peaks of 20 batches of dried pear samples were selected, and their peak areas were standardized to establish a dried pear quality evaluation model. X1, X2, and X3 represent the three principal components as the information expressed by the components of the 20 batches of dried pear samples. PCA plots of the 20 batches of dried pears were drawn using SIMCA 14.1 software to predict the classification of the 20 batches of dried pear samples. ③ Orthogonal Partial Least Squares-Discriminant Analysis (PLS-DA): Based on the PCA classification results, orthogonal partial least squares-discriminant analysis was performed using SIMCA 14.1 software. Two-class and three-class PLS-DA models were established for 20 batches of dried pear samples, and the results were basically consistent with the cluster analysis and PCA results described above. The projected importance (VIP) method was used to screen out six marker components with VIP values ​​greater than 1 for differences in dried pear samples.

2. The method according to claim 1, characterized in that, The high-performance liquid chromatography (HPLC) detection conditions in step (1) were: detection wavelengths of 280 nm (0–25 min) and 350 nm (26–90 min). Chromatograms at different detection wavelengths were compared. The results showed that arbutin (peak 1) had the maximum UV absorption at a detection wavelength of 280 nm. Peaks 1–6 had large peak areas and ideal separation in the 0–25 min range. Chlorogenic acid (peak 9) and rutin (peak 10) had significant UV absorption at 280 nm in the 26–90 min range, but the separation was not ideal. The separation was poor, with many impurities and some inverted peaks. When the detection wavelength was 350 nm, no peaks 1 (arbutin), 2, 3, 4, 5, and 6 were observed in the 0–25 min period. Chlorogenic acid (peak 9) and rutin (peak 10) showed large UV absorption in the 26–90 min period, and the separation was ideal. Peaks 9–16 all had large peak areas and ideal separation. Therefore, the detection wavelength of 280 nm was selected for analysis in the 0–25 min period, and the detection wavelength of 350 nm was selected for analysis in the 26–90 min period.

3. The method according to claim 1, characterized in that, The dried pear test solution described in step (2) and the pretreated D101 macroporous resin column are pretreated as follows: Take D101 macroporous adsorption resin, soak it in 95% ethanol for 24 hours to fully swell, rinse it with 95% ethanol until a suitable amount of soaking solution is added to water and no white turbidity is observed, take the wet resin, pack it into the column using the wet method (column volume is 20 ml), and rinse it with distilled water until there is no alcohol smell, and set it aside for use.

4. The method according to claim 1, characterized in that, The dried pear sample solution described in step (2) was added to a pretreated D101 macroporous resin column, with an adsorption rate of 1 mL·min. -1 After standing for 2 hours, elute with 80 mL of water, then elute with 80 mL of 70% ethanol, at a rate of 2 mL / min. -1 Collect the 70% ethanol eluent, evaporate it to dryness in a water bath, dissolve the residue in 80% methanol and make up to 2 ml to obtain the final product.

5. The method according to claim 1, characterized in that, The dried pear test solution described in step (2) is characterized in that the ultrasonic extraction is performed at a frequency of 35,000 to 45,000 Hz for 15 to 20 min; and the centrifugation is performed at a speed of 5,000 to 20,000 rpm for 5 to 15 min.

6. A comparative feature spectrum of a dual-wavelength fingerprint spectrum of a pear stem, characterized in that, According to any one of claims 1-5, 20 batches of dried pears from different origins were measured to obtain fingerprint chromatograms of the 20 batches of dried pears from different origins. The fingerprint chromatograms of the chromatograms of traditional Chinese medicine were imported into the "Similarity Evaluation System of Chromatographic Characteristic Chromatograms of Traditional Chinese Medicine (2012 Edition)" to determine 16 common peaks of the characteristic chromatogram of dried pears as a reference. Peak 1 was identified as arbutin, peak 9 as chlorogenic acid, and peak 10 as rutin. These common peaks constitute the fingerprint characteristics of dried pears and can be used as the reference characteristic chromatogram of dried pears.

7. The comparative feature map according to claim 1, characterized in that... , characterized in that, According to the method described in any one of claims 1-5, 20 batches of dried pears from different production areas were measured. Combined with cluster analysis, principal component analysis and orthogonal partial least squares-discriminant analysis, the results showed that the 20 batches of dried pears could be divided into two categories (Hebei production area and non-Hebei production area). Peak 9 (chlorogenic acid), peak 4, peak 5, peak 8, peak 13, and peak 1 (arbutin) were differential marker components that had a significant impact on the quality of dried pears and could be used as quality evaluation indicators for dried pears.

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