Preparation method of astragalus mongholicus extracting solution with high antioxidant activity and extracting solution

Abstract

The invention discloses a preparation method of a radix astragali extracting solution with high antioxidant activity and the extracting solution, and aims to solve the problems of low extraction rate of active substances and inaccurate detection of antioxidant activity in the prior art. According to the method, five factors including ethanol content, extracting solution multiple and the like are taken as key variables, U10 * (108) uniform test design is adopted, the DPPH free radical scavenging rate is accurately determined by combining an electron paramagnetic resonance technology, and the contents of astragaloside, general flavone and polysaccharide are synchronously detected. A quantitative model is established through multivariate linear regression analysis, and the optimal process parameters are determined: the ethanol content is 80%, the extracting solution multiple is 4, the temperature is 85 DEG C, the time is 1.5 h, and the extraction time is 1 time. The DPPH free radical scavenging rate of the extracting solution prepared through the technology is larger than or equal to 92.75%, polysaccharide is larger than or equal to 12520 mg / L, total flavone is larger than or equal to 323.77 mg / L, astragaloside is larger than or equal to 257 mg / L, synergistic efficient extraction of multiple components is achieved, and the extracting solution is suitable for industrial production.

Description

Technical Field

[0001] This invention relates to the field of traditional Chinese medicine extraction technology, specifically to a method for preparing a highly antioxidant Astragalus extract and the extract itself. It is particularly suitable for industrial production scenarios where it is necessary to simultaneously increase the content of various antioxidant active substances such as astragaloside A, total flavonoids, and polysaccharides in Astragalus, and to precisely ensure the antioxidant activity of the extract. Background Technology

[0002] Astragalus, a traditional Chinese medicine used in both food and medicine, contains active ingredients such as astragaloside A, total flavonoids, and polysaccharides, which possess significant free radical scavenging capabilities and antioxidant activity, showing broad application prospects in food preservation, pharmaceutical preparations, and cosmetics. Currently, the extraction of active substances from astragalus mainly relies on traditional solvent extraction methods. Extraction parameters are often based on empirical settings, lacking systematic experimental design and data support. This results in low extraction rates of antioxidant active substances and poor product activity stability, making it difficult to meet the quality control requirements of industrial production.

[0003] Existing technologies have two major flaws: First, extraction process optimization often focuses on the extraction rate of a single active substance, such as astragaloside A, neglecting the synergistic antioxidant effect of multiple active ingredients. This limits the overall antioxidant performance of the extract and fails to fully realize the medicinal and health benefits of astragalus. Second, antioxidant activity detection generally uses colorimetric methods, such as ultraviolet spectrophotometry. This method relies on changes in optical density (OD) to reflect the strength of activity. However, the pigments contained in the astragalus extract itself can interfere with the detection signal, leading to inaccurate determination of key indicators such as DPPH free radical scavenging rate, which in turn affects the accuracy of process optimization.

[0004] Therefore, there is an urgent need for a method for preparing Astragalus extract that can achieve accurate detection of antioxidant activity, comprehensively improve the extraction rate of multiple active substances, lock in the optimal process parameters through system optimization, and is suitable for industrial production. Summary of the Invention

[0005] In view of this, the present invention proposes a method for preparing a highly antioxidant Astragalus extract and an extract thereof, aiming to solve the problems of low extraction rate of antioxidant active substances in Astragalus, inaccurate detection, unsystematic process optimization, and poor industrial adaptability in the prior art.

[0006] The technical solution of this invention is achieved as follows: This invention provides a method for preparing a highly antioxidant Astragalus extract, comprising the following steps: establishing an electron paramagnetic resonance (EPR) standard curve for DPPH; determining the dark reaction time between the Astragalus extract and DPPH; conducting single-factor experiments to verify the rationality of the selection of extraction factors; conducting multiple extraction experiments using a uniform experimental design; measuring the core indicators of each group of extracts; establishing a quantitative model through regression analysis; determining the optimal process parameters and preparing a highly antioxidant Astragalus extract; and simultaneously providing the highly antioxidant Astragalus extract prepared by this method.

[0007] In some implementations, when establishing the EPR standard curve for DPPH, a gradient concentration of 0.1-0.5 mmol / L DPPH alcohol solution is prepared using anhydrous ethanol as the solvent. After ultrasonic dissolution at 25°C and 60W for 10 min, the solution is measured using EPR technology to establish the standard curve. The EPR measurement conditions are: frequency 9.792069 GHz, power 5.00 mW, central magnetic field 3487 G, scan width 100 G, modulation amplitude 2.27 G, modulation frequency 86.00 kHz, time constant 40.96, scan time 83.88 s, number of points on the abscissa 512, and receiver gain 3.17 × 10⁻⁶. 3 .

[0008] Gradient concentration DPPH solutions ensure that the standard curve covers the actual detection concentration range, accurate EPR measurement parameters can stably reflect the free radical signal intensity, and ultrasonic dissolution can ensure uniform dispersion of DPPH, avoiding standard curve deviation caused by local concentration differences, thus laying the foundation for subsequent quantitative detection of antioxidant activity.

[0009] In some embodiments, when determining the dark reaction time, Astragalus extract and DPPH ethanol solution are mixed at a volume ratio of 1:5, and the EPR spectrum is scanned once every 2 minutes for a total of 60 scans. The dark reaction time is determined to be 20 minutes by recording the peak height of the third characteristic peak to establish the peak height relationship curve.

[0010] If the dark reaction time is too short, the reaction between DPPH and the active substances in the extract will be insufficient. If it is too long, it may trigger a secondary reaction of free radicals. By dynamically monitoring the changes in peak height, the reaction equilibrium time can be accurately captured, ensuring the accuracy of the scavenging rate measurement and avoiding misjudgments in process optimization due to incomplete reaction.

[0011] In some implementation methods, single-factor experiments used ethanol content of 40%-80%, extraction liquid ratio of 4-8 times, extraction temperature of 65-85℃, extraction time of 1-3h, and extraction times of 1-5 times as the factors to be investigated, and DPPH free radical scavenging rate, astragaloside A content, total flavonoid content, and polysaccharide content as the evaluation indicators.

[0012] The above five factors are all key variables affecting solvent extraction efficiency. Ethanol content determines the dissolution efficiency of lipid-soluble and water-soluble active substances, the extraction solution ratio affects the concentration of active substances and extraction cost, extraction temperature and time are related to solvent diffusion rate and active substance stability, and the number of extractions directly affects production efficiency and energy consumption. The significance of each factor can be verified through single-factor experiments, providing a scientific basis for setting the level of subsequent uniform experiments.

[0013] In some implementations, the uniformity test uses U10*(10 8 The uniform test table sets 10 combinations of process parameters, covering the critical level ranges of all factors.

[0014] The U10*(10 8 The uniformity test table refers to Appendix A of "Uniform Design Test Method" (GB / T34014-2017), specifically U10*(10). 8 The table is generated, and the factor level allocation follows the principle of 'uniform coverage of the level range'. The generation logic of the 10 parameter combinations is as follows: the level range of each factor is divided into 10 gradients at equal intervals, and then uniformly designed using software (such as Mathematic) according to U10*(10 8 The uniformity criteria of the table are used to assign parameters to each group to ensure that factor levels are not repeated and cover the entire interval.

[0015] Compared to orthogonal experiments, uniform experiments can achieve uniform coverage of multiple factors and levels with fewer experimental groups. They are especially suitable for complex systems with five factors, and can comprehensively capture the main effects and interactions of factors. This avoids the limitations of single-factor experiments, which cannot take into account the synergistic effects of variables, and improves the systematicness and reliability of process optimization.

[0016] In some implementations, the DPPH free radical scavenging rate is determined using EPR technology, while the astragaloside A content is simultaneously detected by high performance liquid chromatography, the total flavonoid content by aluminum salt colorimetric method, and the polysaccharide content by phenol-sulfuric acid method. The DPPH free radical scavenging rate is calculated by double integration of the EPR spectrum in the region of 3450±0.01G to 3525±0.01G, using the formula: scavenging rate = (1-As / Ac)×100%, where As is the integral value of the extract group and Ac is the integral value of the blank control group.

[0017] EPR technology can directly detect the resonance signal of free radicals without being affected by the pigment components of Astragalus extract, and has higher accuracy than colorimetric methods. Simultaneous detection of the content of three active substances can achieve dual-dimensional evaluation of antioxidant activity and component content, avoiding component imbalance caused by optimization of a single indicator and ensuring the comprehensive efficacy of the extract.

[0018] In some implementations, data processing software with multiple linear regression capabilities is used to establish regression equations between each indicator and five influencing factors, clarifying the influence weights of the main effects and interactions of the factors on the indicators.

[0019] Regression analysis can quantify the effects of interactions between ethanol content and extraction times, extraction time and extraction times, etc. For example, increased ethanol content can promote the dissolution of active substances, while excessive extraction times can lead to the oxidative decomposition of active substances. Such interactions cannot be observed through intuitive experiments and need to be precisely identified through mathematical modeling to provide a quantitative basis for the selection of optimal parameters.

[0020] In some implementations, based on the regression equation to find the extreme value and combined with the low energy consumption and high efficiency requirements of industrial production, the optimal process parameters are determined as follows: ethanol content 80%, extract volume ratio 4 times, extraction temperature 85℃, extraction time 1.5h, and extraction times 1.

[0021] The 80% high ethanol content can simultaneously improve the solubility of both fat-soluble (astragaloside A, total flavonoids) and water-soluble (polysaccharide) components; the 4x extraction solvent ratio can avoid dilution of active substances due to excessive solvent; the 85℃ extraction temperature can accelerate the solvent diffusion rate without causing degradation of active substances; the 1.5h extraction time can balance dissolution efficiency and stability; and the principle that one extraction is optimal breaks the traditional understanding that more extractions mean higher efficiency. Its core mechanism is that multiple extractions increase the contact time between active substances and air and high-temperature solvents, triggering oxidative decomposition. At the same time, reducing extraction steps can significantly reduce industrial energy consumption.

[0022] In some embodiments, the prepared Astragalus extract with high antioxidant activity has a DPPH free radical scavenging rate ≥92.75%, a polysaccharide content ≥12520mg / L, a total flavonoid content ≥323.77mg / L, and an astragaloside A content ≥257mg / L.

[0023] This indicator system not only reflects the high antioxidant activity of the extract, but also ensures the high content of the three core active substances. Through the synergistic effect of multiple components, the antioxidant performance of the extract is significantly better than that of single-component extracts, meeting the needs of high-value-added application scenarios.

[0024] The present invention has the following advantages over the prior art: (1) Significantly improved accuracy of antioxidant activity detection: The DPPH free radical scavenging rate was determined by EPR technology, which completely eliminated the interference of the color of Astragalus extract on antioxidant activity detection. Combined with standardized spectral integration method and dark reaction time control, the detection results are stable and reliable, providing accurate core evaluation indicators for process optimization and solving the technical pain point of inaccurate detection by traditional colorimetric method. (2) The process optimization is highly scientific: key influencing factors are screened through single-factor experiments, combined with U10*(10 8 Uniform experimental design and multiple linear regression analysis systematically cover the interaction of five factors, quantify the influence weight of each factor on the index, clarify the synergistic effect of extraction times, ethanol content, and extraction time, avoid the blindness of empirical parameter setting, and achieve precise control of process parameters. (3) The synergistic extraction effect of multiple components is outstanding: with antioxidant activity as the core objective, the dissolution efficiency of astragaloside A, total flavonoids and polysaccharides are taken into account at the same time. The synergistic and efficient extraction of the three active substances is achieved through the optimal process parameters. The comprehensive antioxidant performance of the extract is significantly better than the existing single component optimization process, which fully utilizes the medicinal value of Astragalus membranaceus. (4) Excellent industrial adaptability: The optimal process parameters are clear and specific, with only one extraction and an extraction time of 1.5 hours, which greatly reduces production energy consumption and cycle time. Moreover, the process has good stability, with small fluctuation range of core indicators. It can achieve large-scale production without complex equipment, solving the problems of low efficiency, unstable quality and poor adaptability of existing processes. The process of this invention has completed pilot-scale verification: the pilot scale is 10 kg of Astragalus membranaceus raw material, using a 500L stainless steel extraction tank. The extraction equipment parameters are: stirring rate 60 r / min, steam pressure 0.3 MPa, condensation reflux rate 10 L / h. The core indicators of 5 batches of continuous production are: DPPH free radical scavenging rate 92.35%~93.12%, polysaccharide 12480~12650 mg / L, total flavonoids 320.5~326.8 mg / L, astragaloside A 254~260 mg / L, and the relative deviation between batches (RSD) is <0.8%, which is better than the existing process. Attached Figure Description

[0025] 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.

[0026] Figure 1 This is a graph showing the trend of antioxidant active substances (polysaccharides, total flavonoids, astragaloside A) and DPPH free radical scavenging rate of Astragalus extract in Example 1 of the present invention as a function of material-liquid ratio (extract ratio); Figure 2 The graph shows the trend of antioxidant active substances (polysaccharides, total flavonoids, astragaloside A) and DPPH free radical scavenging rate of Astragalus extract in Example 1 of the present invention as a function of extraction times. Figure 3The graph shows the trend of antioxidant active substances (polysaccharides, total flavonoids, astragaloside A) and DPPH free radical scavenging rate of Astragalus extract in Example 1 of the present invention as a function of extraction time. Figure 4 The graph shows the trend of antioxidant active substances (polysaccharides, total flavonoids, astragaloside A) and DPPH free radical scavenging rate of Astragalus extract in Example 1 of the present invention as a function of extraction temperature. Figure 5 This is a graph showing the trend of antioxidant active substances (polysaccharides, total flavonoids, astragaloside A) and DPPH free radical scavenging rate of Astragalus extract in Example 1 of the present invention as a function of ethanol content. Detailed Implementation

[0027] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0028] Example 1 This embodiment provides an example of preparing a highly antioxidant Astragalus extract. 1. Experimental materials and equipment The experimental material was dried Astragalus membranaceus, which was pulverized, passed through a 40-mesh sieve, and dried to constant weight. The reagents included anhydrous ethanol, DPPH with a purity of ≥98%, astragaloside A standard, total flavonoid standard, polysaccharide standard, etc. The equipment used included an electron paramagnetic resonance spectrometer (EPR), a high performance liquid chromatograph, an ultraviolet spectrophotometer, a 60W ultrasonic cleaner, and a constant temperature water bath.

[0029] 2. Preparation steps First, an EPR standard curve for DPPH was established. DPPH alcohol solutions of 0.1 mmol / L, 0.2 mmol / L, 0.3 mmol / L, 0.4 mmol / L, and 0.5 mmol / L were prepared using anhydrous ethanol as the solvent and sonicated for 10 min at 25℃ and 60 W. Subsequently, EPR measurements were performed under the following conditions: frequency 9.792069 GHz, power 5.00 mW, central magnetic field 3487 G, scan width 100 G, modulation amplitude 2.27 G, modulation frequency 86.00 kHz, time constant 40.96, scan time 83.88 s, number of points on the abscissa 512, and receiver gain 3.17 × 10⁻⁶. 3 EPR spectrum Figure 2 A standard curve was constructed using the multiple integral values ​​as the ordinate and the DPPH radical concentration as the abscissa. The correlation coefficient R was calculated. 2 =0.9987.

[0030] Next, the dark reaction time of Astragalus extract and DPPH was determined. 1.0 mL of Astragalus extract and 0.5 mL of DPPH ethanol solution were mixed in a brown stoppered graduated tube and the time was set. After 2 min of mixing and tuning, the EPR measurement was performed immediately under the above-mentioned conditions. The scanning time was 1 h, and the EPR spectrum was scanned once every 2 min for a total of 60 scans. The peak height of the third characteristic peak of each scan was recorded, and the relationship curve of the peak height of the third characteristic peak of DPPH with time was established. The dark reaction time was determined to be 20 min.

[0031] Subsequently, single-factor experiments were conducted to verify the rationality of the selected extraction factors. Ethanol content (40%-80%), extraction solvent ratio (4-8 times), extraction temperature (65-85℃), extraction time (1-3 hours), and extraction frequency (1-5 times) were used as single factors. The contents of astragaloside A, total polysaccharides, total flavonoids, and DPPH free radical scavenging rate were used as indicators to explore the changes in various indicators under different factors. The influence trends of each factor on the indicators are as follows: Figures 1 to 5 As shown, the number of extractions had the most significant impact on all indicators. Figure 2 When the extract volume was 4 times, the performance of each indicator was optimal. Figure 1 This verifies that the above five factors are all key variables affecting the extraction effect.

[0032] U10*(10) 8 Ten sets of experiments were designed using a uniform experimental table, with factor levels shown in Table 1. Ten different combinations of process parameters were used for Astragalus extraction. Relevant indicators were measured for each extract. The DPPH free radical scavenging rate was determined by mixing 100 μL of Astragalus extract with 1 mL of 0.5 mmol / L DPPH alcohol solution in a brown stoppered test tube, allowing it to react in the dark for 20 min, and then measuring it in the resonant cavity of an electron paramagnetic spectrometer. The EPR spectrum was double-integrated within the region of 3450±0.01G to 3525±0.01G, and the measured double integral value was recorded as As. Deionized water was used as a blank control group, and the integral value Ac was obtained under the same operating conditions. The scavenging rate was calculated using the formula "scavenging rate = (1-As / Ac) × 100%". Astragaloside A was detected by high-performance liquid chromatography, total flavonoids were detected by aluminum salt colorimetric method, and polysaccharides were detected by phenol-sulfuric acid method. Specific parameters and results for the ten sets of experiments are shown in Table 2.

[0033] Regression analysis was performed on the experimental data in Table 2 using data processing software with multiple linear regression capabilities, and regression equations were established for each index and the five influencing factors: DPPH clearance rate (Y) = -447.62 + 14.75X1 - 10.49X2 + 92.14X5 - 1.42X1*X5 - 4.41X4*X5 - 0.089X12 (P=0.031332); Polysaccharide (Y) = 8243 - 4X1 + 347X2 + 143X3 - 7771X5 - 30X1*X5 + 1225X5 2 (P=0.0253232); Total flavonoids (Y) = -44.42 + 0.75X1 - 16.69X2 + 4.83X3 - 35.6X5 (P = 0.00914462). Astragaloside A (Y) = 275.84 - 1.77X1 - 14.33X2 + 2.94X3 - 46.12X5 (P = 0.0311509). Where X1 is the ethanol content, X2 is the extraction volume ratio, X3 is the extraction temperature, X4 is the extraction time, and X5 is the number of extractions.

[0034] The specific steps of regression analysis are as follows: ① Data preprocessing: Outliers were removed using the Grubbs method (significance level α=0.05). All data in Table 2 were found to be free of outliers after testing. ② Model selection: The full regression method was used to include all main effect terms (X1-X5) and second-order interaction terms (X1*X2, X1*X5, X4*X5, etc.). Significant terms (P<0.05) were screened by analysis of variance (ANOVA), and finally the terms that had a significant impact on the indicators were retained to form the regression equation. ③ Model validation: The coefficient of determination R of the regression equation 2 The values ​​were: DPPH scavenging rate 0.987, polysaccharide 0.972, total flavonoids 0.965, and astragaloside A 0.958, all greater than 0.95, indicating that the model fit was good and could be used for optimal parameter prediction.

[0035] Based on the regression equation to find the extreme value and combined with the actual production conditions, the optimal process parameters were determined to be 80% ethanol content, 4 times the extraction liquid ratio, 85℃ extraction temperature, 1.5h extraction time, and 1 extraction time. The extraction was repeated 3 times according to the optimal process parameters for verification.

[0036] The EPR spectrum Figure 2 The specific steps for multiple integrals are as follows: ① Spectrum preprocessing: Open the original spectrum using spectrum processing software, select the 'baseline correction' function, use the 3400G~3550G range as the baseline reference, and remove noise after correction (the noise threshold is set to 1% of the original signal strength). ② Characteristic peak identification: The EPR spectrum of DPPH shows a typical triplet. The third characteristic peak is a symmetrical peak on the high field side (high magnetic field value). The magnetic field value at the peak of the peak is 3500±5G as the identification benchmark. ③ Integration operation: Select the integration interval 3450±0.01G~3525±0.01G, select the 'continuous integration' algorithm, and the software will automatically calculate the area enclosed by the spectrum and the baseline within this interval, which is the double integral value.

[0037] The procedure for the blank control group was exactly the same as that for the sample group: 100 μL of deionized water was mixed with 1 mL of 0.5 mmol / L DPPH alcohol solution, and the same volume ratio, dark reaction time (20 min), and EPR measurement conditions were used for detection. The spectrum integration steps were the same as those for the sample group to ensure that the calculation basis of Ac and As was consistent.

[0038] 3. Test Results Table 2 shows the parameters and test results of the 10 groups of uniform experiments. As can be seen from the table, there were significant differences in each index under different combinations of process parameters. Groups 5 and 10, due to having only one extraction cycle, showed significantly higher DPPH free radical scavenging rates and contents of various active substances compared to other groups. The optimal process validation results showed that the DPPH free radical scavenging rate of the extract was 92.75% ± 0.32%, the polysaccharide content was 12520 mg / L ± 156 mg / L, the total flavonoid content was 323.77 mg / L ± 5.8 mg / L, and the astragaloside A content was 257 mg / L ± 4.2 mg / L. The fluctuations in each index were small, indicating good process stability. Figures 1 to 5 Single-factor trend analysis showed that when the extract volume was increased by 4 times, the solvent did not excessively dilute the active substance, thus ensuring extraction efficiency. Figure 1 When extracted once, the active substance did not undergo oxidative decomposition, and the indicators reached their peak. However, multiple extractions led to a significant decrease in all indicators. Figure 2 At an extraction time of 1.5 hours, a balance between sufficient dissolution of active substances and stability was achieved; excessively long extraction times would lead to component degradation. Figure 3 At an extraction temperature of 85℃, the solvent diffusion rate is the fastest, and the active substances do not degrade. Figure 4 When the ethanol content is 80%, it can simultaneously promote the dissolution of both fat-soluble and water-soluble active substances. Figure 5 ).

[0039] Table 1: U10*(10 8 Uniform experimental factor level table

[0040] Table 2: Results of Uniformity Tests (Examples 1-1 to 1-10)

[0041] Comparative Example 1 This comparative example uses colorimetric detection. Preparation steps The preparation steps were completely consistent with those in Example 1, except that the detection method for DPPH radical scavenging rate was replaced with colorimetric method (ultraviolet spectrophotometry) with a detection wavelength of 517 nm. Other experimental materials, equipment, process parameters, and data processing methods were the same as in Example 1. The optimal process after colorimetric optimization was determined by regression analysis, and the extraction was repeated 3 times according to the process for verification.

[0042] Test results The optimal process parameters after colorimetric optimization were: 70% ethanol content, 5 times the extraction volume, 75℃ extraction temperature, 2 hours extraction time, and 2 extractions. The verification results are compared with those of Example 1 in Table 3. As shown in the table, the fluctuation range (RSD) of the colorimetric detection results was significantly greater than that of the EPR method, and all core indicators were lower than those of Example 1. This is mainly because the color of the Astragalus extract itself interfered with the optical density (OD) value measurement by colorimetric analysis, leading to inaccurate detection results. This, in turn, caused the optimal process parameters obtained from regression analysis to deviate from the true optimal range, ultimately affecting the extraction effect. This result is consistent with... Figures 1 to 5 The reflected factors show a consistent trend. For example, the colorimetric method failed to accurately capture the peak value of the index when the extract volume was 4 times and the extraction was performed once, proving that accurate EPR detection is a necessary prerequisite for multi-factor system optimization, and not a replacement for conventional technology.

[0043] Table 3: Comparison of experimental results between Comparative Example 1 and Example 1

[0044] Comparative Example 2 This comparative example aims to optimize the process using orthogonal experimental design. Preparation steps The experimental materials, equipment, testing methods, and data processing methods are completely consistent with those in Example 1, except that the experimental design method is replaced with L18(3). 5 An orthogonal experimental design was used, with the same range of factors as in Example 1 (ethanol content 40%-80%, extract volume 4-8 times, extraction temperature 65-85℃, extraction time 1-3h, extraction times 1-5 times). Each factor was set with 3 levels, for a total of 18 groups of experiments. The optimal process after orthogonal experimental optimization was determined by regression analysis, and the extraction was repeated 3 times according to the process for verification.

[0045] Test results The optimal process parameters after orthogonal experiment optimization were 75% ethanol content, 4 times the extraction volume, 80℃ extraction temperature, 1.5h extraction time, and 2 extractions. The verification results are compared with those of Example 1 in Table 4. As shown in the table, the orthogonal experiment had 8 more experimental groups than Example 1, but the core indicators were still lower than in Example 1. This is mainly because the orthogonal experiment could not fully cover the interaction of the five factors (such as the interaction term X1*X5 between ethanol content and extraction times), while Example 1 used U10*(10... 8 Uniform experiments can achieve a uniform distribution of factor levels with fewer groups, comprehensively capturing interaction effects. This is consistent with the result in the regression equation that "X1*X5 and X4*X5 have a significant impact on DPPH clearance rate." Combined with... Figure 2 It can be seen that the orthogonal experiment failed to accurately identify the optimality of the extraction time of 1, which further proves that the combination of "uniform experiment + regression analysis" in this invention is an innovative optimization scheme for a complex system with 5 factors, and is not a simple application of conventional experimental methods.

[0046] Table 4: Comparison of experimental results between Comparative Example 2 and Example 1

[0047] Comparative Example 3 This comparative study aims to validate the process optimization for a single indicator (astragaloside A). Preparation steps The experimental materials, equipment, detection methods, experimental design, and data processing methods were completely consistent with those in Example 1. Only the content of astragaloside A was used as the sole optimization indicator. During the regression analysis, the regression equation between the content of astragaloside A and the five influencing factors was established based solely on the content of astragaloside A to determine the optimal process. The DPPH free radical scavenging rate, polysaccharide, and total flavonoid content were detected simultaneously, but were not included in the optimization objective. The optimal process was repeated three times for verification.

[0048] Test results The optimal process parameters after single-index optimization were: ethanol content 60%, extract volume ratio 5, extraction temperature 85℃, extraction time 2h, and extraction times 1. The verification results are compared with those of Example 1 in Table 5. As shown in the table, although single-index optimization resulted in a slightly higher astragaloside A content than in Example 1, it significantly reduced the DPPH free radical scavenging rate and the contents of polysaccharides and total flavonoids, with the scavenging rate decreasing by 15.42%. This result confirms the rule in the regression equation that the number of extractions (X5) has a significant impact on all indicators. Furthermore, combined with… Figures 1 to 5 The trend analysis shows that the optimization of a single index ignores the synergistic antioxidant effect of polysaccharides and total flavonoids, resulting in a significant reduction in the overall activity of the extract. This proves that the optimization goal of this invention, which focuses on antioxidant activity and the synergistic effect of multiple components, is a creative design that is different from the existing technology and is not a simple superposition of detection indicators.

[0049] Table 5: Comparison of experimental results between Comparative Example 3 and Example 1

[0050] Comparative Example 4 This comparative example aims to verify the process involving three extractions. Preparation steps The optimal process parameters were completely consistent with those of Example 1, except that the number of extractions was changed from 1 to 3 (the conventional number of extractions in the prior art). Other parameters (ethanol content 80%, extract volume 4 times, extraction temperature 85℃, extraction time 1.5h) as well as the test materials, equipment and detection methods remained unchanged, and the extraction was repeated 3 times for verification.

[0051] Test results The test results are compared with those of Example 1 in Table 6. As shown in the table, after the number of extractions increased to three, all core indicators decreased significantly. Specifically, the DPPH free radical scavenging rate was only 48.99% of that in Example 1, and the polysaccharide content was only 24.78%. This result is consistent with… Figure 2 The trends are completely consistent: Figure 2 The results clearly show that as the number of extractions increases from 1 to 5, all indicators exhibit a significant downward trend, with the indicators reaching their peak at the first extraction. Multiple extractions lead to increased contact time between the active substances and air and high-temperature solvents, triggering oxidative decomposition. This result overturns the conventional understanding that more extractions lead to higher extraction rates, proving that the selection of 1 extraction time in this invention is an unexpected discovery based on systematic experiments and mechanism analysis, rather than a conventional optimization method.

[0052] Simultaneous detection of the content of malondialdehyde (MDA), an oxidative decomposition product in the extract: The thiobarbituric acid (TBA) method was used for detection. The MDA content of Comparative Example 4 (3 extractions) was 18.6±1.2 μmol / L, while the MDA content of Example 1 (1 extraction) was 3.2±0.5 μmol / L. This proves that multiple extractions lead to the oxidative decomposition of active substances, which in turn causes a decrease in the index. This is consistent with the mechanism of 'multiple extractions increase the contact time between active substances and air and high-temperature solvents'.

[0053] Meanwhile, the peak shapes of astragaloside A in Example 1 and Comparative Example 4 were compared by high performance liquid chromatography (HPLC): the astragaloside A peak in Example 1 was symmetrical and without impurity peaks, while the astragaloside A peak in Comparative Example 4 showed tailing and was accompanied by two small molecule impurity peaks (retention times of 8.3 min and 10.1 min, respectively), further verifying that multiple extractions led to the partial degradation of astragaloside A.

[0054] Table 6: Comparison of experimental results between Comparative Example 4 and Example 1

[0055] Example 1 utilizes precise electron paramagnetic resonance (EPR) detection technology combined with U10*(10 8 Using a uniform experimental design and multiple linear regression analysis, the system optimized five key factors, including ethanol content and extraction ratio, to determine the optimal process parameters. This resulted in the synergistic and efficient extraction of astragaloside A, total flavonoids, and polysaccharides, achieving a DPPH free radical scavenging rate of 92.75%. The content of each active substance remained at a high level with good stability. Compared to the colorimetric method in Comparative Example 1, the EPR technology completely eliminated the interference of extract color, providing a reliable basis for process optimization and significantly improving the indicators. Compared to the orthogonal experiment in Comparative Example 2, the uniform experiment, with fewer groups, fully covered the interactions of multiple factors, resulting in better optimization efficiency and effect. While the single-indicator optimization in Comparative Example 3 increased the astragaloside A content, the neglect of synergistic effects led to a decrease in overall antioxidant activity, confirming the inventiveness of the multi-indicator synergistic target of this invention. The multiple extraction scheme in Comparative Example 4, due to the lack of a synergistic effect between high ethanol and single extraction, resulted in indicators far lower than those of this invention. This invention features a scientific process, simple operation, low energy consumption, and is suitable for industrial production, significantly enhancing the application value of astragalus extract.

[0056] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for preparing a highly antioxidant Astragalus extract, characterized in that, Includes the following steps: (1) Establishing the standard curve of electron paramagnetic resonance (EPR) of DPPH: using anhydrous ethanol as solvent, prepare DPPH alcohol solutions with gradient concentrations, dissolve by sonication and then measure by EPR. The standard curve is established with the double integral value of the EPR spectrum as the ordinate and the concentration of DPPH free radicals as the abscissa. (2) Determine the dark reaction time of Astragalus extract and DPPH: Mix Astragalus extract with DPPH ethanol solution, scan the EPR spectrum at intervals and record the peak height of characteristic peaks, establish the peak height change curve with time, and determine the dark reaction time; (3) Single-factor experiment: The single factors were ethanol content of 40%-80%, extract volume of 4-8 times, extraction temperature of 65-85℃, extraction time of 1-3h, and extraction times of 1-5 times. The rationality of the factor selection was verified by using DPPH free radical scavenging rate, astragaloside A content, total flavonoid content, and polysaccharide content as indicators. (4) Uniform experimental design: U10*(10 8 A uniformity test table was used to set up 10 different combinations of process parameters for Astragalus extraction; (5) Index determination: The DPPH free radical scavenging rate of each group of extracts was determined by EPR technology, and the contents of astragaloside A, total flavonoids and polysaccharides were detected simultaneously; among them, the determination of DPPH free radical scavenging rate included: after the extract was reacted with DPPH ethanol solution in the dark, EPR detection was performed, and the EPR spectrum was double integrated in the region of 3450±0.01G~3525±0.01G; (6) Regression analysis: Using data processing software with multiple linear regression function, establish regression equations between each indicator and the five influencing factors; (7) Determine the optimal process parameters: Based on the regression equation, the extreme values ​​are obtained and combined with the actual production conditions. The high antioxidant activity Astragalus extract is obtained according to these parameters.

2. The preparation method according to claim 1, characterized in that, In step (1), the concentration of the DPPH alcohol solution was 0.1-0.5 mmol / L, and the ultrasonic conditions were 25℃, 60W, and 10min; the EPR measurement conditions were: frequency 9.792069GHz, power 5.00mW, central magnetic field 3487G, scan width 100G, modulation amplitude 2.27G, modulation frequency 86.00kHz, time constant 40.96, scan time 83.88s, number of abscissa points 512, and receiver gain 3.17×10⁻⁶. 3 .

3. The preparation method according to claim 1, characterized in that, In step (2), the dark reaction time is 20 min, and the volume ratio of Astragalus extract to DPPH ethanol solution is 1:

5.

4. The preparation method according to claim 1, characterized in that, In step (5), the DPPH free radical scavenging rate is calculated as follows: scavenging rate = (1-As / Ac) × 100%, where As is the double integral value of the EPR spectrum of the extract group and Ac is the double integral value of the EPR spectrum of the blank control group.

5. The preparation method according to claim 1, characterized in that, In step (5), astragaloside A was detected by high performance liquid chromatography, total flavonoids were detected by aluminum salt colorimetric method, and polysaccharides were detected by phenol-sulfuric acid method.

6. The preparation method according to claim 1, characterized in that, In step (7), the optimal process parameters are: ethanol content 80%, extract ratio 4 times, extraction temperature 85℃, extraction time 1.5h, and extraction times 1.

7. The preparation method according to claim 1, characterized in that, The data processing software is software with multiple linear regression functionality.

8. A highly antioxidant Astragalus extract, characterized in that, It is prepared by any of the preparation methods described in claims 1-7.

9. The Astragalus extract with high antioxidant activity according to claim 8, characterized in that, The extract has a DPPH free radical scavenging rate of ≥92.75%, a polysaccharide content of ≥12520mg / L, a total flavonoid content of ≥323.77mg / L, and an astragaloside A content of ≥257mg / L.

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