Method for evaluating flavonoid active ingredients of whole corn silage based on HPLC (High Performance Liquid Chromatography)

Abstract

The invention discloses a method for evaluating flavonoid active ingredients of whole-plant corn silage based on HPLC (High Performance Liquid Chromatography). The method comprises the following steps: S1, collecting and treating a sample; S2, extracting total flavonoids of the sample; S3, preparing before establishment of an HPLC fingerprint spectrum of the active ingredients of the sample; according to the method disclosed by the invention, the chemical characteristic spectrum of the flavonoid active ingredients of the whole corn silage is constructed by adopting a fingerprint spectrum technology and by virtue of multi-dimensional analysis characteristics of the fingerprint spectrum technology, so that the category and content distribution of main effective ingredients in raw materials or finished products can be systematically represented; the whole-plant corn silage flavonoid active ingredients are subjected to integral evaluation and systematic quality control, and the method has the advantages of being good in credibility and high in data accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of silage, in particular to a method for evaluating flavonoid active ingredients in whole-plant corn silage based on HPLC. BACKGROUND

[0002] Whole-plant corn silage is a high-quality roughage made of corn with ears as raw material, which is cut, compacted and sealed for fermentation. Its nutritional value is significantly higher than that of ordinary straw silage. In addition to conventional nutrients such as starch, crude protein and neutral detergent fiber, it also contains flavonoids, organic acids (such as lactic acid and acetic acid), and various vitamins and other active nutrients. Flavonoids are a class of active substances with a relatively high content in whole-plant corn silage, which have antioxidant, anti-inflammatory and immune-regulating functions, and have a significant impact on animal health and production performance.

[0003] At present, the quality evaluation of whole-plant corn silage is mostly based on sensory evaluation or conventional nutrients and fermentation indicators. However, the complexity and dynamic metabolic characteristics of its active nutrients, especially flavonoids, make it difficult to develop a systematic method for quality control of whole-plant corn silage, and there is no unified quality control standard, which cannot meet the needs of modern animal husbandry. SUMMARY

[0004] The present application aims to provide a method for evaluating flavonoid active ingredients in whole-plant corn silage based on HPLC to solve the above problems.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical scheme:

[0006] The present application provides a method for evaluating flavonoid active ingredients in whole-plant corn silage based on HPLC, which comprises the following steps:

[0007] S1, sample collection and processing:

[0008] Collect a large number of whole-plant corn silage samples from different regions with representative, dry and crush them for standby;

[0009] S2, sample total flavonoid extraction process:

[0010] Determine the total flavonoid content in the sample by ultrasonic-assisted ethanol method;

[0011] S3, preparation before establishing the HPLC fingerprint of active ingredients:

[0012] S31, preparation of test solution: accurately weigh a certain amount of each sample obtained in step S1, extract it by the sample total flavonoid extraction process in step S2, and prepare a test solution for standby;

[0013] S32, selection and processing of reference substances: a certain amount of trifolin, isoheteroside, isofraxin, forsythoside, naringenin and kaempferol reference substances were precisely weighed to prepare a mixed reference substance solution;

[0014] S33, construction of chromatographic conditions: the chromatographic conditions for the HPLC fingerprint of the whole corn silage flavonoids were established, and the chromatogram was recorded;

[0015] S34, selection of reference peaks: the mixed reference substance solution of step S32 and the test sample solution of step S31 were mixed and injected for analysis, the chromatographic peaks of each mixed reference substance were identified, and the chromatographic peaks with high resolution and large peak area were selected as reference peaks S;

[0016] S4, establishment of HPLC fingerprint of active ingredients in samples: the test sample solution of each batch of whole corn silage prepared in step S31 was precisely taken, and was injected for analysis according to the chromatographic conditions of the HPLC fingerprint in step S33, the chromatogram was recorded and the control chromatogram was generated; then the common peaks were calibrated, the area of non-common peaks was calculated and the similarity was evaluated; finally, the samples of each batch of whole corn silage were classified through cluster analysis, and the samples of each batch of whole corn silage were classified through principal component factor analysis and calculation of the comprehensive score of the principal components.

[0017] Preferably, in step S2, the ultrasonic-assisted ethanol method process has an ethanol concentration of 50% to 100%, a solid-liquid ratio of 1: (20 to 100), and an ultrasonic extraction time of 30 min to 180 min.

[0018] Preferably, in step S2, the ethanol concentration, solid-liquid ratio and ultrasonic extraction time in the ultrasonic-assisted ethanol method process are optimized through orthogonal test, and the optimal extraction process is obtained as follows: 90% ethanol solution is used as the extracting agent, the solid-liquid ratio is 1:60 W / V, and the ultrasonic extraction time is 120 min.

[0019] Preferably, in step S31, the preparation of the test sample solution has the following specific steps: 5 g of each sample obtained in step S1 is precisely weighed, and is subjected to the sample total flavonoid extraction process in step S2; the obtained extract is evaporated to dryness under reduced pressure by a rotary evaporator; finally, 90% ethanol is used to make up to 5 ml, and the solution is filtered through a 0.45 μm filter for standby use.

[0020] Preferably, in step S32, the selection and processing of reference substances have the following specific steps: 1 mg of trifolin, isoheteroside, isofraxin, forsythoside, naringenin and kaempferol reference substances are precisely weighed, dissolved in methanol and made up to 10 ml in a 10 ml volumetric flask, and then filtered through a 0.45 μm filter to obtain a mixed reference substance solution.

[0021] Preferably, in step S33, the chromatographic conditions of the whole corn silage flavonoids HPLC fingerprint are as follows: methanol-0.5% phosphoric acid aqueous solution or acetonitrile-0.5% phosphoric acid aqueous solution as two mobile phase systems, 0.7ml / min-1.0mL / min of mobile phase flow rate, 25℃-38℃ of column temperature, 330nm or 360nm of detection wavelength, gradient elution, and 0-120min of elution detection time.

[0022] Preferably, in step S33, the chromatographic conditions of the whole corn silage flavonoids HPLC fingerprint are as follows: Extend-C18 as the chromatographic column, 0.5% phosphoric acid aqueous solution as mobile phase A, methanol solution as mobile phase B, 1.0ml / min of mobile phase flow rate, 30℃ of column temperature, 360nm of detection wavelength, gradient elution, and 70min of elution detection time.

[0023] Preferably, in step 4, the specific steps for establishing the sample active ingredient HPLC fingerprint are as follows:

[0024] S41, determination of whole corn silage: precisely pipette the whole corn silage test sample solution prepared in step S31, inject and analyze according to the chromatographic conditions of the HPLC fingerprint in step S33, record the chromatogram, and import it into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Processing Software 2012 Edition" to generate the control chromatogram;

[0025] S42, calibration of common peaks: record the chromatographic peaks with a percentage of total peak area of more than 1% according to the technical parameters of HPLC analysis of each batch of whole corn silage, and obtain the common chromatographic peaks through retention time comparison; calculate the relative retention time and relative peak area of each common peak in the HPLC chromatogram of each batch of test sample;

[0026] S43, calculation of non-common peak area: compare the chromatogram related data of each batch of whole corn silage test sample solution, and calculate the percentage of non-common peak area in total peak area;

[0027] S44, similarity evaluation: import the chromatogram of each batch of whole corn silage into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Processing Software 2012 Edition", take the control chromatogram as the reference, and perform similarity evaluation;

[0028] S45, cluster analysis: based on the common peak area data of each batch of whole corn silage sample obtained in step S42, use SPSS21.0 software to construct a system clustering model; set the average linkage method as the clustering merging strategy, combine the square Euclidean distance to calculate the heterogeneity characteristics of metabolite distribution between different samples, and classify each batch of whole corn silage sample through cluster analysis;

[0029] S46, principal component analysis: based on the common peak area data of each batch of whole corn silage sample obtained in the step S42, an orthogonal linear transformation model is constructed by SPSS21.0 software, each batch is analyzed by principal component factor, and the whole corn silage sample is classified by calculating the principal component comprehensive score.

[0030] The beneficial effects of the present application are:

[0031] (1) The present application is based on the evaluation method of whole corn silage flavonoid active ingredients by HPLC. By using fingerprint technology, the chemical characteristic spectrum of whole corn silage flavonoid active ingredients is constructed by virtue of its multi-dimensional analysis characteristics, which can systematically characterize the category and content distribution of main effective components in raw materials or finished products, and then the whole corn silage flavonoid active ingredients are evaluated and systematically controlled, which has the characteristics of good reliability and high data accuracy.

[0032] (2) The present application is based on the evaluation method of whole corn silage flavonoid active ingredients by HPLC. The screening of core active ingredients in raw materials and its function verification can be systematically evaluated, and a unified quality control standard of flavonoid active ingredients is constructed, which provides theoretical support for the development of active substance omics products, and can meet the quality control needs of modern animal husbandry. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 The total flavonoid extraction rate graph of different ethanol concentrations, solid-liquid ratios and ultrasonic times in the embodiment of the present application;

[0034] Figure 2 The chromatogram of different mobile phases in the embodiment of the present application;

[0035] Figure 3 The chromatogram superposition of different flow rates in the embodiment of the present application;

[0036] Figure 4 The chromatogram superposition of different column temperatures in the embodiment of the present application;

[0037] Figure 5 The chromatogram of two different wavelengths in the embodiment of the present application;

[0038] Figure 6 The chromatogram superposition of different gradient programs in the embodiment of the present application;

[0039] Figure 7 The chromatogram of extending elution to determine the inspection time of 120 min in the embodiment of the present application;

[0040] Figure 8 The HPLC fingerprint of the test sample solution in the embodiment of the present application;

[0041] Figure 9The chromatogram of the mixed standard sample of the embodiment of the present application;

[0042] Figure 10 The superimposed chromatogram of the blank reagent and the sample of the embodiment of the present application;

[0043] Figure 11 The chromatogram of the precision investigation result of the embodiment of the present application;

[0044] Figure 12 The chromatogram of the stability investigation result of the embodiment of the present application;

[0045] Figure 13 The chromatogram of the repeatability investigation result of the embodiment of the present application;

[0046] Figure 14 The superimposed chromatogram of the HPLC fingerprint of 20 batches of whole corn silage of the embodiment of the present application;

[0047] Figure 15 The control HPLC fingerprint of whole corn silage of the embodiment of the present application;

[0048] Figure 16 The system cluster analysis tree diagram of the whole corn silage sample of the embodiment of the present application;

[0049] Figure 17 The principal component fragment stone diagram of the peak area of 7 common peaks of the fingerprint of 20 samples of whole corn silage of the embodiment of the present application. DETAILED DESCRIPTION

[0050] Embodiment 1:

[0051] The present application provides an evaluation method of the flavonoid active ingredient of whole corn silage based on HPLC, which comprises the following steps:

[0052] S1, sample collection and processing: collect representative whole corn silage samples from all over the country, about 500g each, dry at 65℃, crush through a 40 mesh sieve, seal in a bag and store at-20℃, for standby use; the specific sources of the samples are shown in Table 1.

[0053] Table 1, specific sources of samples

[0054] No. Sample source No. Sample source S1 Hefei City, Anhui Province S11 Jinzhou City, Liaoning Province S2 Suzhou City, Anhui Province S12 Shenyang City, Liaoning Province S3 Suzhou City, Anhui Province S13 Bazhuyaner City, Inner Mongolia S4 Guangzhou City, Guangdong Province S14 Hohhot City, Inner Mongolia S5 Shijiazhuang City, Hebei Province S15 Wuzhong City, Ningxia S6 Zhengzhou City, Henan Province S16 Yinchuan City, Ningxia S7 Heihe City, Heilongjiang Province S17 Shanghai S8 Heihe City, Heilongjiang Province S18 Weinan City, Shaanxi Province S9 Changde City, Hunan Province S19 Weifang City, Shandong Province S10 Fuxin City, Liaoning Province S20 Xinjiang Uygur Autonomous Region

[0055] S2, sample total flavonoid extraction process:

[0056] The total flavone content in the sample is determined by using the ultrasonic-assisted ethanol method. The specific steps of the ultrasonic-assisted ethanol method commonly used for extracting flavones at present are as follows: the powder of the whole-plant corn silage sample dried at 65° and crushed is mixed with ethanol in a conical flask at a certain ratio, sealed with a sealing film, and then placed in an ultrasonic cleaner to extract the flavones from the sample by using the ultrasonic-assisted ethanol method.

[0057] In the ultrasonic-assisted ethanol method, the ethanol concentration is 50%, the solid-liquid ratio is 1:60, and the ultrasonic extraction time is 120 min. The total flavone content in the representative whole-plant corn silage samples from various producing areas in China in the S1 step is determined by using the above ultrasonic-assisted ethanol method.

[0058] S3, Preparation before establishing the HPLC fingerprint of the active ingredient of the sample:

[0059] S31, Preparation of the test solution: 5 g of the sample obtained in the S1 step is precisely weighed, and the total flavone extraction process obtained in the S2 step is used to evaporate the obtained extract by using a rotary evaporator under reduced pressure, and finally, the extract is dissolved in 90% ethanol to 5 ml, filtered by using a 0.45 μm filter, and used.

[0060] S32, Selection and treatment of the reference substances: 1 mg of each of the control substances of the alfalfa, isoheteroside, isofraxin, formononetin, and kaempferol is precisely weighed, dissolved in methanol, and dissolved in a 10-ml volumetric flask, and then filtered by using a 0.45 μm filter to obtain a mixed control substance solution.

[0061] S33, Establishment of the chromatographic conditions: 5 μL of the test solution is injected for analysis, the chromatographic conditions of the HPLC fingerprint of the whole-plant corn silage flavones are established, and the specific conditions are as follows: methanol-0.5% phosphoric acid aqueous solution is used as the mobile phase system, the flow rate of the mobile phase is 0.9 mL / min, the column temperature is 30° C, the detection wavelength is 330 nm, the selected gradient elution program I is shown in Table 2, the elution determination time is 80 min, and the chromatogram is recorded.

[0062] Table 2, Gradient elution program I

[0063] Time / min Mobile phase A / % Mobile phase B % 0.00 85 15 5.00 85 15 10.00 70 30 15.00 65 35 18.00 60 40 20.00 55 45 28.00 50 50 48.00 50 50 58.00 30 70 63.00 85 15 70.00 85 15

[0064] S34, Selection of the reference peaks: the mixed control substance solution in the S32 step and the test solution in the S31 step are mixed and injected for analysis, respectively, the chromatographic peaks of each mixed control substance are identified, and the chromatographic peaks with high resolution and large peak area are selected as the reference peaks S.

[0065] S4, Establishment of the HPLC fingerprint of the active ingredient of the sample:

[0066] S41, Determination of 20 batches of whole corn silage: precisely pipette each batch of whole corn silage test solution prepared in step S31, inject and analyze according to the optimal chromatographic conditions in step S33, record the chromatograms of 20 batches of whole corn silage, and import them into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Processing Software 2012 Edition". Take S5 as the reference spectrum, automatically match after multi-point correction, superimpose the 20 fingerprint spectra by the average method, and generate a control spectrum.

[0067] S42, Calibration of common peaks: according to the technical parameters of HPLC analysis of 20 batches of whole corn silage, record the chromatographic peaks with a total peak area percentage of more than 1%, and obtain the common chromatographic peaks by retention time control. Calculate the relative retention time and relative peak area of each common peak in the HPLC chromatogram of 20 batches of test samples.

[0068] S43, Calculation of non-common peak area: by comparing the chromatogram data of 20 batches of whole corn silage test samples, the percentage of non-common peak area to total peak area is calculated.

[0069] S44, Similarity evaluation: import the chromatograms of 20 batches of whole corn silage into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Processing Software 2012 Edition". Take S5 as the reference spectrum, automatically match after multi-point correction, generate a control spectrum by the median method, and evaluate the similarity with the control spectrum as the reference.

[0070] S45, Cluster analysis: based on the common peak area data of 20 batches of whole corn silage, a system clustering model is constructed by SPSS 21.0 software. By setting the between-group average connection method (Between-group linkage) as the clustering merging strategy, combining the squared Euclidean distance (Squared Euclidean distance) to calculate the heterogeneity characteristics of metabolite distribution between different samples, and classifying 20 batches of whole corn silage samples by cluster analysis.

[0071] S46, Principal component analysis: based on the common peak area data of each sample of whole corn silage, an orthogonal linear transformation model is constructed by SPSS 21.0 software, and principal component factor analysis is performed on 20 batches. The principal component comprehensive score of 20 batches of whole corn silage samples is calculated to classify them.

[0072] Example 2:

[0073] This example has five groups, and the evaluation method of whole corn silage flavonoids active ingredients based on HPLC is basically the same as that in Example 1, except that:

[0074] S2 step, in the ultrasonic-assisted ethanol method process, the ethanol concentration of five groups of examples is 60%, 70%, 80%, 90%, 100% respectively.

[0075] Example 3:

[0076] This example has five groups, the evaluation method of the active ingredients of the whole plant corn silage flavonoids based on HPLC, the steps are basically the same as example 1, the difference is that:

[0077] S2 step, in the ultrasonic-assisted ethanol method process, the ethanol concentration of five groups of examples is 60%, 70%, 80%, 90%, 100% respectively.

[0078] Example 4:

[0079] This example has six groups, the evaluation method of the active ingredients of the whole plant corn silage flavonoids based on HPLC, the steps are basically the same as example 1, the difference is that:

[0080] S2 step, in the ultrasonic-assisted ethanol method process, the ethanol concentration of five groups of examples is 60%, 70%, 80%, 90%, 100% respectively.

[0081] In example 1-4, the evaluation of the active ingredients of the whole plant corn silage flavonoids based on HPLC can be carried out. However, in the ultrasonic-assisted ethanol method of S2 step, different ethanol concentration, liquid ratio and ultrasonic extraction time have great influence on the extraction amount of total flavonoids of corn straw silage, and can also affect the accuracy of the evaluation results of the active ingredients of the whole plant corn silage flavonoids.

[0082] In order to explore the optimal extraction process of total flavonoids of whole plant corn silage, single factor experiment and orthogonal experiment are carried out, as follows:

[0083] First, select the whole plant corn silage samples prepared in step S1; then, in step S2, the ethanol concentration is selected at 50%, 60%, 70%, 80%, 90%, and 100% (as shown in Examples 1-2), the solid-liquid ratio (g / mL) is selected at 1:20, 1:40, 1:60, 1:80, and 1:100 (as shown in Example 3), and the ultrasonic extraction time is selected at 30 min, 60 min, 90 min, 120 min, 150 min, and 180 min (as shown in Example 4). The extract obtained under different conditions is centrifuged to obtain the supernatant, which is then transferred to a 100 mL volumetric flask and diluted with 90% ethanol to prepare a flavonoid extract. Finally, the total flavonoid content in the corn straw silage extract is determined by the NaNO2-Al(NO3)3-NaOH colorimetric method and the preparation of a rutin standard curve, and the total flavonoid content of different varieties of corn straw silage is calculated. The total flavonoid content of whole plant corn silage (mg / g) = (total flavonoid content of the test solution * 100 * 5) / the mass of the whole plant corn silage sample.

[0084] The NaNO2-Al(NO3)3-NaOH colorimetric method is as follows: 2 mL of the flavonoid extract of the whole plant corn silage is taken in a 10 mL volumetric flask, supplemented with 60% ethanol to 5 mL, then 0.3 mL of 5% NaNO2 solution is added, mixed and allowed to stand for 6 min, then 0.3 mL of 10% Al(NO3)3 solution is added, mixed and allowed to stand for 6 min, then 4 mL of 4% NaOH solution is added, finally diluted to 10 mL with 60% ethanol, mixed and allowed to stand for 15 min, and the absorbance is measured at 510 nm using a UV spectrophotometer.

[0085] The rutin standard curve is prepared as follows: 10 mg (0.0100 g) of rutin reference substance is accurately weighed, dissolved in 60% ethanol solution and diluted to 50 mL, obtaining a 0.2 mg / mL rutin standard solution. 0 mL, 0.25 mL, 0.5 mL, 1 mL, 2.0 mL, 3.0 mL, 4.0 mL, and 5.0 mL of the rutin standard solution (0.2 mg / mL) are accurately pipetted into a 10 mL volumetric flask, supplemented with 60% ethanol to 5 mL, then 0.3 mL of 5% NaNO2 solution is added, mixed and allowed to stand for 6 min, then 0.3 mL of 10% Al(NO3)3 solution is added, mixed and allowed to stand for 6 min, then 4 mL of 4% NaOH solution is added, finally diluted to 10 mL with 60% ethanol, mixed and allowed to stand for 15 min, and the absorbance is measured at 510 nm using a UV spectrophotometer. The rutin concentration is taken as the abscissa and the absorbance is taken as the ordinate to draw the rutin standard curve. The obtained standard curve is Y = 20.374X (R = 0.9998), and the linear range is 0-0.1 mg / mL.

[0086] The light absorption value of the whole corn silage flavonoid extract obtained by NaNO2-Al(NO3)3-NaOH colorimetric method is combined with the rutin standard curve, that is, the light absorption value of the flavonoid extract is brought into the Y of the rutin standard curve, so that the X value obtained is the total flavonoid content of the test solution, and then the total flavonoid content of the whole corn silage sample is obtained through the conversion of the dilution multiple and the sample quality.

[0087] The column chart of the total flavonoid extraction rate under different ethanol concentrations, different solid-liquid ratios and different ultrasonic times obtained by single factor experiment is shown in Figure 1 As can be seen from Figure 1 , when 90% ethanol is used as the extraction solvent, the total flavonoid yield of the sample is higher, so 80%, 90% and 100% ethanol are selected as the three levels of ethanol concentration in the orthogonal experiment; when the solid-liquid ratio is 1:60, the total flavonoid yield of the sample is higher, so 1:40, 1:60 and 1:80 are selected as the three levels of solid-liquid ratio in the orthogonal experiment; when the ultrasonic time is 150 min, the total flavonoid yield of the sample is higher, so 120 min, 150 min and 180 min are selected as the three levels of ultrasonic time in the orthogonal experiment.

[0088] According to the SPSS experimental design, combined with the single factor experiment results, the ethanol extraction concentration, the solid-liquid ratio and the ultrasonic extraction time are selected as the corresponding factors, the total flavonoid extraction amount of corn straw silage is selected as the response value, and the corresponding analysis of three factors and three levels is set up for experimental design, as shown in Table 3, each factor level is repeated 3 times, and the average value is taken.

[0089] Table 3, L9(3 3 ) factor level table

[0090]

[0091] The orthogonal result table of the total flavonoid extraction process obtained by orthogonal experiment is shown in Table 4; and the variance analysis table of the orthogonal result of the total flavonoid extraction process is shown in Table 5.

[0092] Table 4, orthogonal result table of total flavonoid extraction process

[0093]

[0094] Table 5, variance analysis table of orthogonal result of total flavonoid extraction process

[0095]

[0096] From Table 4, Table 5, the order of the influence of each factor on the total flavonoids extraction rate of whole corn silage is A > C > B, the best level combination is A2B2C2, the verification test result is 7.195 mg / g according to the process, which is greater than any result in the orthogonal test. Therefore, the optimal extraction process of total flavonoids of whole corn silage is: using 90% ethanol solution as the extracting agent, the solid-liquid ratio is 1:60 (W / V), and the ultrasonic extraction time is 120 min.

[0097] The optimal extraction process of total flavonoids of whole corn silage is verified by a verification test, which is as follows:

[0098] Precision: 1.0 g of whole corn silage sample powder is accurately weighed, and the total flavonoids are extracted under the above optimal extraction process. The extraction solution is diluted to 100 mL in a volumetric flask. 2 mL to 10 mL is taken in a volumetric flask, and the absorbance value is measured for 5 times continuously according to the optimal extraction process.

[0099] Repeatability: 1.0 g of whole corn silage sample powder is accurately weighed, and the total flavonoids are extracted under the above optimal extraction process. The extraction solution is diluted to 100 mL in a volumetric flask. 2 mL to 10 mL is taken in a volumetric flask, and the absorbance value is measured according to the optimal extraction process.

[0100] Stability: 1.0 g of whole corn silage sample powder is accurately weighed, and the total flavonoids are extracted under the above optimal extraction process. The extraction solution is diluted to 100 mL in a volumetric flask. 2 mL to 10 mL is taken in a volumetric flask every 20 min, and the absorbance value is measured according to the optimal extraction process.

[0101] The precision, stability and repeatability of the optimal extraction process of total flavonoids of whole corn silage are investigated respectively, and the results are shown in Table 6. The RSD values of each verification test are less than 5%, which proves that the extraction conditions are feasible.

[0102] Table 6, verification test results of the optimal extraction process of total flavonoids of whole corn silage

[0103]

[0104] Example 5:

[0105] This example has two groups, and the evaluation method of whole corn silage flavonoids active ingredients based on HPLC is basically the same as that of Example 1, except that:

[0106] Firstly, in the ultrasonic-assisted ethanol process, the optimal extraction process of total flavonoids of whole corn silage is used, that is, using 90% ethanol solution as the extracting agent, the solid-liquid ratio is 1:60 (W / V), and the ultrasonic extraction time is 120 min.

[0107] Then, S33 step, in the construction of chromatographic conditions, the column temperature is 30 ℃, the detection wavelength is 360 nm, the isocratic elution is selected, and the elution determination inspection time is 70 min. The two groups of comparative examples are different in that methanol-0.5% phosphoric acid aqueous solution (40:60) and acetonitrile-0.5% phosphoric acid aqueous solution (40:60) are used as the mobile phase system, respectively.

[0108] The chromatograms of different mobile phases obtained are shown in Figure 2 As shown in Figure 2 , when methanol-0.5% phosphoric acid aqueous solution is used as the mobile phase, the separation effect of each peak is good, the baseline is smooth and the peak shape is symmetrical, so methanol-0.5% phosphoric acid aqueous solution is selected as the mobile phase.

[0109] Example 6:

[0110] This example has four groups, and the evaluation method of the active ingredient of the whole corn silage flavonoids based on HPLC is basically the same as that of example 1, and the difference is that:

[0111] First, in the ultrasonic-assisted ethanol process, the optimal extraction process of total flavonoids of whole corn silage is used, that is, 90% ethanol solution is used as the extracting agent, the solid-liquid ratio is 1:60 (W / V), and the ultrasonic extraction time is 120 min.

[0112] Then, S33 step, in the construction of chromatographic conditions, methanol-0.5% phosphoric acid aqueous solution is used as the mobile phase system, the column temperature is 30 ℃, the detection wavelength is 360 nm, the gradient elution program III is selected as shown in Table 7, and the elution determination inspection time is 70 min. The four groups of comparative examples are different in that the flow rate of the mobile phase is 0.7 ml / min, 0.8 ml / min, 0.9 ml / min and 1.0 ml / min, respectively.

[0113] Table 7, gradient elution program III

[0114]

[0115]

[0116] The chromatogram superimposed diagram of different flow rates obtained is shown in Figure 3 As shown in Figure 3As shown, flow rate has a significant impact on the separation and retention time of chromatographic peaks. At a flow rate of 0.7 ml / min, the retention times of all chromatographic peaks are prolonged, with poor separation of peaks around 55 min, and some even disappearing. At flow rates of 0.8 ml / min and 0.9 ml / min, the retention times of many chromatographic peaks are prolonged, and the separation of many peaks is poor. At a flow rate of 1.0 ml / min, the chromatographic peak separation is ideal, the retention time is moderate, and the chromatogram information is rich. Therefore, a flow rate of 1.0 ml / min was selected.

[0117] Example 7:

[0118] This example includes five comparative examples. The evaluation method for flavonoid active components in whole-plant maize silage based on HPLC is basically the same as that in Example 1, except that:

[0119] First, in step S2, the optimal extraction process for total flavonoids from whole-plant corn silage is adopted in the ultrasonic-assisted ethanol method, namely, using 90% ethanol solution as the extractant, a material-to-liquid ratio of 1:60 (W / V), and an ultrasonic extraction time of 120 min.

[0120] Then, in step S33, the chromatographic conditions were constructed using a methanol-0.5% phosphoric acid aqueous solution as the mobile phase system, a mobile phase flow rate of 1.0 mL / min, a detection wavelength of 360 nm, gradient elution program III, and an elution determination time of 70 min. The five comparative groups differed in that they used five column temperature levels: 25℃, 28℃, 30℃, 35℃, and 38℃.

[0121] The chromatograms obtained at different column temperatures are shown in the figure. Figure 4 .like Figure 4 As shown, changing the column temperature has a significant impact on the separation of each chromatographic peak. When the column temperature decreases, the retention time of each chromatographic peak is delayed. As shown in the figure, at 25℃, the peak retention time is long, the peak broadening is obvious (low column efficiency), and some peaks are tailed. At 28℃, the signal intensity of each peak is improved, but the baseline noise increases, resulting in a decrease in the signal-to-noise ratio. When the column temperature increases, the elution time of each chromatographic peak is shortened, but the resolution is reduced. As shown in the figure, at 35℃ and 38℃, the retention time of each chromatographic peak is advanced, but the resolution is reduced, and the baseline fluctuation is large. At 30℃, the peak shape of each chromatographic peak is symmetrical, and the resolution and signal-to-noise ratio are optimal. Therefore, the column temperature condition of 30℃ is selected.

[0122] Example 8:

[0123] This example includes two comparative examples. The evaluation method for flavonoid active components in whole-plant maize silage based on HPLC is basically the same as that in Example 1, except that:

[0124] Firstly, S2 step, in the ultrasonic-assisted ethanol method process, the optimal extraction process of total flavonoids of whole corn silage is adopted, that is, 90% ethanol solution is used as the extracting agent, the solid-liquid ratio is 1:60 (W / V), and the ultrasonic extraction time is 120 min.

[0125] Then, S33 step, in the construction of chromatographic conditions, methanol-0.5% phosphoric acid aqueous solution is used as the mobile phase system, the flow rate of the mobile phase is 1.0 mL / min, the column temperature is 30°C, the detection wavelength is 360 nm, and the elution determination inspection time is 70 min, and the three groups of comparative examples are different in that gradient elution program I, gradient elution program II, and gradient elution program III (as shown in Table 7 in Example 6) are used for gradient elution.

[0126] The obtained chromatograms of different gradient programs are shown in Figure 5 As shown in Figure 5 , the signal intensity, peak shape, baseline stability, and common peak coverage of each peak at 330 nm are all better than those at 360 nm, but considering that the peak area at 48.58 min accounts for a large proportion and is the main component of the sample, and the chromatographic peak area at 360 nm is large, 360 nm is selected as the optimal detection wavelength.

[0127] Example 9:

[0128] This example has three groups of comparative examples, and the evaluation method of flavonoid active ingredients of whole corn silage based on HPLC is basically the same as that in Example 1, and the difference is that:

[0129] Firstly, S2 step, in the ultrasonic-assisted ethanol method process, the optimal extraction process of total flavonoids of whole corn silage is adopted, that is, 90% ethanol solution is used as the extracting agent, the solid-liquid ratio is 1:60 (W / V), and the ultrasonic extraction time is 120 min.

[0130] Then, S33 step, in the construction of chromatographic conditions, methanol-0.5% phosphoric acid aqueous solution is used as the mobile phase system, the flow rate of the mobile phase is 1.0 mL / min, the column temperature is 30°C, the detection wavelength is 360 nm, and the elution determination inspection time is 70 min, and the three groups of comparative examples are different in that gradient elution program I, gradient elution program II, and gradient elution program III (as shown in Table 7 in Example 6) are used for gradient elution.

[0131] Table 8, gradient elution program II

[0132] Time / min Mobile phase A / % Mobile phase B % 0.00 85 15 5.00 85 15 10.00 70 30 15.00 60 40 18.00 55 45 20.00 50 50 40.00 30 70 45.00 30 70 50.00 30 70 55.00 85 15 70.00 85 15

[0133] The obtained chromatograms of different gradient programs are shown in Figure 6 . As shown in Figure 6As shown, under the condition of elution gradient program I, each chromatographic peak is dense and there is an overlapping phenomenon; under the condition of elution gradient program II, the separation degree of each peak is slightly better, but there is a baseline drift phenomenon; under the condition of elution gradient program III, the separation degree of each chromatographic peak is good, the peak type is symmetrical and there is no baseline drift phenomenon, so the elution gradient program III is selected as the best elution gradient program.

[0134] Example 10:

[0135] This example has only one group, and the evaluation method of the active ingredients of the whole corn silage flavonoids based on HPLC is basically the same as that in Example 1, and the difference is that:

[0136] Firstly, in the ultrasonic-assisted ethanol process, the optimal extraction process of total flavonoids of whole corn silage is used, that is, 90% ethanol solution is used as the extracting agent, the solid-liquid ratio is 1:60 (W / V), and the ultrasonic extraction time is 120 min.

[0137] Then, in the S33 step, in the construction of the chromatographic condition, methanol-0.5% phosphoric acid aqueous solution is used as the mobile phase system, the flow rate of the mobile phase is 1.0 mL / min, the column temperature is 30°C, the detection wavelength is 360 nm, and gradient elution is carried out by using gradient elution program III. The detection time is extended to 120 min.

[0138] The chromatogram obtained by extending the detection time to 120 min is shown in Figure 7 As shown in Figure 7 , after 70 min, basically no new chromatographic peak appears. Therefore, the detection time is determined to be 70 min.

[0139] From Examples 5-10, the optimal chromatographic condition of the whole corn silage flavonoids HPLC fingerprint is: chromatographic column-Extend-C18 (250x4.6mm, 5um); mobile phase-A is 0.5% phosphoric acid aqueous solution, mobile phase-B is methanol solution; flow rate-1.0ml / min; column temperature-30°C; detection wavelength-360nm; injection volume-5ul; gradient elution program III is selected; and the detection time is 70 min.

[0140] Example 11:

[0141] The evaluation method of the active ingredients of the whole corn silage flavonoids based on HPLC provided by the present application comprises the following steps:

[0142] S1, the sample collection and treatment are the same as in Example 1.

[0143] S2, the sample total flavonoids extraction process is basically the same as in Example 1, and the difference is that:

[0144] In the ultrasonic-assisted ethanol method process, the optimal extraction process of total flavonoids from corn silage is as follows: 90% ethanol solution as the extracting agent, the ratio of material to liquid is 1:60 (W / V), and the ultrasonic extraction time is 120 min.

[0145] The total flavonoid content of the corn silage samples from different regions in S1 step is determined by the ultrasonic-assisted ethanol method process, and the data obtained are shown in Table 9. The data obtained by statistical analysis of the data in Table 9 are shown in Table 10.

[0146] Table 9, total flavonoid content of corn silage samples from different regions

[0147] No. Total flavonoid content (mg / g) No. Total flavonoid content (mg / g) S1 7.1900 S11 6.8028 S2 6.8440 S12 7.0443 S3 7.2872 S13 6.4101 S4 6.1269 S14 6.3890 S5 6.1549 S15 5.5100 S6 5.0481 S16 6.8352 S7 8.5535 S17 6.1122 S8 8.7258 S18 6.7800 S9 5.6189 S19 9.3663 S10 5.8295 S20 7.2431

[0148] Table 10, statistical data table of total flavonoid content of corn silage samples from different regions

[0149] No. Total flavonoid content (mg / g) Average 6.7936 Standard deviation (SD) % 1.0666 Coefficient of variation (CV) % 15.70

[0150] As shown in Table 9, the total flavonoid content of corn silage samples from different regions has a large coefficient of variation and a wide range. The total flavonoid content of samples from S7, S8 and S19 is relatively high, which is 8.5535 mg / g, 8.7258 mg / g and 9.3663 mg / g, respectively. The total flavonoid content of samples from S6, S9 and S15 is relatively low, which is 5.0481 mg / g, 5.6189 mg / g and 5.5100 mg / g, respectively. Table 10 is a statistical data table of total flavonoid content of corn silage samples from different regions. As shown in Table 10, the coefficient of variation of total flavonoid content of the collected corn silage samples is moderate. This variation level indicates that the flavonoid content of corn silage samples from different regions has a quantifiable natural difference, which is suitable for constructing an active ingredient fingerprint for distinguishing different sources.

[0151] S3, sample active ingredient HPLC fingerprint establishment preparation:

[0152] S31 and S32 steps are the same as in Example 1.

[0153] S33, construction of chromatographic conditions:

[0154] In the construction of chromatographic conditions, the optimal chromatographic conditions for the HPLC fingerprint of corn silage flavonoids are used, which are as follows: chromatographic column—Extend-C18 (250×4.6 mm, 5 μm); mobile phase—A is 0.5% phosphoric acid aqueous solution, mobile phase—B is methanol solution; flow rate—1.0 ml / min; column temperature—30℃; detection wavelength—360 nm; injection volume—5 μL; gradient elution program III is selected; and the elution determination check time is 70 min.

[0155] The test sample solution of step S31 was passed through the optimal chromatographic conditions of step S33, and the HPLC fingerprint of the test sample solution and the theoretical plate number of each chromatographic peak were as shown in Table 10 and Table 11. Figure 8 and Table 11.

[0156] Table 11, Theoretical plate number of each chromatographic peak

[0157]

[0158] S34, Selection of reference peak:

[0159] The mixed control sample solution of step S32 was passed through the optimal chromatographic conditions of step S33, and the HPLC fingerprint of the mixed control sample solution, i.e., the mixed standard chromatogram, was as shown in Table 12. Figure 9

[0160] By comparison, the four control samples were respectively controlled against peaks 2, 3, 5 and 6 of the HPLC fingerprint of whole corn silage, wherein peaks 2, 3, 5 and 6 were respectively formononetin, isohomosaligenin, isofukinol and tricin. Peak 6 had a larger peak area and a high degree of separation, which was conducive to the evaluation and identification of the characteristic peaks of the fingerprint, so peak 6 (tricin) was selected as the reference peak (S) of the HPLC fingerprint of whole corn silage. Figure 9 Figure 8 S35, Methodology verification:

[0161] (1) Blank test

[0162] (1) Blank test

[0163] In order to investigate whether the mobile phase and test sample reagent interfere with the chromatographic results, methanol and 90% ethanol were respectively taken, filtered through a 0.45 μm filter membrane, and the chromatogram was determined under the optimal chromatographic conditions of step S33.

[0164] The superimposed chromatogram of the two reagents, methanol and 90% ethanol, and the test sample is shown in Table 13. Figure 10 As shown in Table 13, neither the mobile phase nor the test sample reagent affected the sample analysis results. Figure 10

[0165] (2) Precision investigation

[0166] 5 g of the sample obtained in step S1 was weighed, and the test sample solution was prepared according to the method of step S31. The chromatogram was determined under the optimal chromatographic conditions of step S33, and the sample was continuously injected for 6 times. The RSD of the relative retention time and the relative peak area of the common peaks was calculated.

[0167] The superimposed chromatogram of the precision investigation results is shown in Table 14. Figure 11 ​​​The RSD results of the relative retention time and relative peak area of each common peak are shown in Table 12 and Table 13. According to the above results, the RSD of the relative retention time of each common peak is less than 0.1%, and the RSD of the relative peak area is less than 0.1%, which meet the requirements of the fingerprint spectrum establishment, indicating that the method has good precision.

[0168] Table 12, Precision of relative retention time

[0169]

[0170] Table 13, Precision of relative peak area

[0171]

[0172]

[0173] (3) Stability test

[0174] 5g of the sample obtained in step S1 was weighed, and a test sample solution was prepared according to the method of step S31. The test sample solution was detected at 0h, 2h, 4h, 8h, 12h and 24h under the optimal chromatographic conditions of step S33, and the chromatogram was recorded. With the reference of the chromatographic peak of the control sample, the RSD values of the relative retention time and relative peak area of the common peaks in the results of 6 analyses were calculated.

[0175] The chromatogram superimposition chart of the stability test results is shown in Figure 12 , and the RSD values of the relative retention time and relative peak area of the common peaks are shown in Table 14 and Table 15. According to the above results, the RSD of the relative retention time of each common peak with respect to the peak No. 6 is less than 0.05%, and the RSD of the relative peak area is less than 0.48%, which meet the requirements of the fingerprint spectrum, indicating that the HPLC detection of the test sample is stable and reliable within 24h.

[0176] Table 14, Stability of relative retention time

[0177]

[0178] Table 15, Stability of relative peak area

[0179]

[0180]

[0181] (4) Reproducibility test

[0182] Take 5 g of the sample obtained in step S1, and prepare 6 portions of the sample solution according to the method in step S31. Then, sequentially detect under the optimal chromatographic conditions in step S33, and record the chromatograms. Take the chromatographic peak of the reference substance as the reference, and calculate the RSD values of the relative retention time and the relative peak area of the common peaks in the 6 analysis results.

[0183] The chromatographic superimposition chart is shown in Figure 13 The RSD values of the relative retention time and the relative peak area of the common peaks are shown in Table 16 and Table 17. According to the above results, the RSD value of the relative retention time of each common peak is less than 0.06%, and the RSD value of the relative peak area is less than 0.55%. The method meets the requirements of the fingerprint, and has good repeatability.

[0184] Table 16, repeatability investigation of relative retention time

[0185]

[0186] Table 17, repeatability investigation of relative peak area

[0187]

[0188] S4, establishment of HPLC fingerprint of active ingredients of the sample:

[0189] S41, determination of 20 batches of whole corn silage:

[0190] Precisely take each batch of whole corn silage sample solution prepared according to the method in step S31, and analyze by sample injection according to the optimal chromatographic conditions in step S33. Record the chromatograms of 20 batches of whole corn silage, and import them into the “Traditional Chinese Medicine Chromatographic Fingerprint Similarity Processing Software 2012 Edition”. Take S5 as the reference chromatogram, and automatically match after multi-point correction. Then, superimpose 20 fingerprint chromatograms by the average method, and generate the reference chromatogram.

[0191] The HPLC fingerprint superimposition chart of 20 batches of whole corn silage is shown in Figure 14 The generated reference HPLC fingerprint of whole corn silage is shown in Figure 15 Figure 15 The meanings of the numbers in the table are as follows: 1-undetermined, 2-summer sweet, 3-isohorsin, 4-undetermined, 5-isofukinol, 6(S)-tricin, and 7-undetermined.

[0192] S42, identification of common peaks:

[0193] According to the technical parameters of HPLC analysis of 20 batches of whole corn silage, record the chromatographic peaks with a total peak area percentage of more than 1%. Then, obtain the common chromatographic peaks by retention time control. Calculate the relative retention time and the relative peak area of each common peak in the HPLC chromatograms of 20 batches of sample.​

[0194] The HPLC chromatogram of the 7 common peaks screened out is shown in the control HPLC fingerprint of whole corn silage Figure 15 The relative retention time and relative peak area of the 7 common peaks in the HPLC chromatogram of each batch of test sample are summarized in Table 18 and Table 19.

[0195] Table 18, Relative retention time of common peaks in 20 batches of samples

[0196]

[0197] Table 19, Relative peak area of common peaks in 20 batches of samples

[0198]

[0199]

[0200] As shown in Table 18 and Table 19, the HPLC chromatogram of the flavonoids in 20 batches of whole corn silage has certain commonality, the retention time of the 7 common peaks is basically consistent, and the RSD is within 0.13%, which meets the standard of less than 3%. However, the relative peak area has large difference, which also indicates that the fermentation level and processing technology of whole corn silage in different producing areas have great influence on the content of components.

[0201] S43, Calculation of non-common peak area:

[0202] By comparing the chromatogram data of 20 batches of whole corn silage test samples, the percentage of non-common peaks in the total peak area was calculated. As shown in Table 20, the percentage of non-common peak area in 20 batches of whole corn silage samples is within the range of 0.22% to 8.95%, which meets the requirement of less than 10% of the non-common peak area ratio in the fingerprint.

[0203] Table 20, Non-common peak area of 20 batches of whole corn silage test samples

[0204]

[0205]

[0206] S44, Similarity evaluation:

[0207] The chromatogram of 20 batches of whole corn silage was imported into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Processing Software 2012 Edition", and S5 was taken as the reference spectrum. After multi-point correction, the control spectrum was automatically matched by the median method, and the similarity evaluation was carried out by taking the control spectrum as the reference.

[0208] The similarity value of the obtained fingerprint spectrum was evaluated, and the results are shown in Table 21.

[0209] Table 21, Similarity of HPLC fingerprint of 20 batches of whole corn silage

[0210] No. Similarity No. Similarity S1 0.962 S11 0.994 S2 0.895 S12 0.425 S3 0.888 S13 0.865 S4 0.918 S14 0.632 S5 0.975 S15 0.996 S6 0.976 S16 0.910 S7 0.658 S17 0.801 S8 0.964 S18 0.966 S9 0.982 S19 0.969 S10 0.976 S20 0.979

[0211] As shown in Table 21, the similarity of the components of 20 batches of whole corn silage is between 0.425 and 0.996, and the components of whole corn silage from different origins have large differences, which may be related to the differences in the distribution and metabolic product accumulation of nutrients (such as fiber, soluble carbohydrates, and lactic acid bacteria activity) caused by different planting conditions (such as soil fertility, climate environment, and planting density) and processing technology (such as harvesting period, fermentation time, and additive type) of the raw materials of whole corn silage. In-depth correlation analysis can be carried out in combination with agronomy and microbial fermentation mechanism.

[0212] S45, Cluster analysis:

[0213] Based on the common peak area data of 20 batches of whole corn silage, a system clustering model was constructed using SPSS21.0 software. By setting the between-group linkage as the clustering merging strategy, combined with the calculation of the heterogeneity characteristics of metabolite distribution between samples from different origins by squared Euclidean distance, the 20 batches of whole corn silage samples were classified by cluster analysis.

[0214] Based on the common peak area data of different whole corn silage in Table 19, a system clustering model was constructed using SPSS21.0 software, and the system clustering analysis dendrogram was finally generated as shown in Figure 16 . As shown in Figure 16 , the whole corn silage samples were divided into two categories according to the dendrogram obtained by cluster analysis, S1, S5, S8, S10, S14, S18-S20 were in one category, and this category of samples contained relatively rich flavonoids; S2-S4, S6, S7, S9, S11-S13, S15-S17 were in another category, and this category of samples contained relatively low flavonoids.

[0215] S46, Principal component analysis:

[0216] Based on the common peak area data of each sample of whole corn silage, an orthogonal linear transformation model was constructed by SPSS21.0 software, and principal component factor analysis was performed on 20 batches, and the 20 batches of whole corn silage samples were classified by calculating the principal component comprehensive score. The results are shown in Tables 22, 23, 24 and Figure 17The Kaiser criterion (eigenvalue > 1) and the cumulative contribution rate threshold requirement (usually ≥ 70%) were met. The inflection point characteristics of the broken stone diagram further verified the rationality of the number of principal components, and the slope change showed that the first three principal components had fully extracted the structural characteristics of the multidimensional data. Specifically, the first principal component (PC1) explained 43.557% of the original data variation, the second and third principal components contributed 30.868% and 16.362% of the variance, respectively, and the three together covered 90.787% of the spectral peak characteristic information in the data set.

[0217] As shown in Table 23, the initial factor loading matrix component analysis table showed that the coefficient distribution of each common peak on different principal components was different. Peaks 1, 2, 4, and 5 had higher loadings on principal component 1, i.e., principal component 1 mainly reflected the information of these four common peak indicators; peaks 3, 6, and 7 had higher loadings on principal component 2; and principal component 3 mainly reflected the information of peaks 4, 6, and 7.

[0218] The scores of the 20 samples on the three principal components and the comprehensive scores (F1*variance contribution rate 1+F2*variance contribution rate 2+F3*variance contribution rate 3) were calculated, and the results are shown in Table 24. The higher the score, the better the quality of the sample in the principal component analysis. The 20 samples were divided into two categories based on the average of the comprehensive scores (0) as the boundary. S1, S5, S8, S10, S12, S14, and S20 were in the higher score category, of which S14 (Hohhot, Inner Mongolia) had the highest score; S2-S4, S6, S7, S9, S11, S13, S15-S19 were in the lower score category, of which S9 (Changde, Hunan Province) had the lowest score.

[0219] Figure 17 The broken stone diagram of the 7 common peak peak areas of the fingerprint of the 20 whole corn silage samples is shown in Table 24. Figure 17 The inflection point characteristics of the broken stone diagram further verified the rationality of the number of principal components, and the slope change showed that the first three principal components had fully extracted the structural characteristics of the multidimensional data.

[0220] Table 22, Eigenvalues and variance contribution rates of 3 principal components

[0221]

[0222] Table 23, Initial factor loading matrix component

[0223]

[0224] Table 24, Principal component scores and comprehensive scores of 20 whole corn silage samples

[0225]

[0226]

[0227] Therefore, based on the common peak area data of each sample, 20 samples are divided into two categories by cluster analysis, the content of flavonoids in S1, S5, S8, S10, S14, S18-S20 is relatively rich; the content of flavonoids in S2-S4, S6, S7, S9, S11-S13, S15-S17 is relatively low. The 20 samples are divided into two categories by the average score of the comprehensive principal component, S1, S5, S8, S10, S12, S14 and S20 are the higher score category, and S14 has the highest score; S2-S4, S6, S7, S9, S11, S13, S15-S19 are the lower score category, and S9 has the lowest score.

[0228] The application is based on the evaluation method of the whole corn silage flavonoid active ingredient by HPLC, by using the fingerprint technology, and by virtue of the multi-dimensional analysis characteristics, the chemical characteristic spectrum of the whole corn silage flavonoid active ingredient is constructed, which can systematically represent the category and content distribution of the main effective components in the raw materials or finished products, and then the whole corn silage flavonoid active ingredient is overall evaluated and systematically controlled, which has the characteristics of good credibility and high data accuracy. The application is based on the evaluation method of the whole corn silage flavonoid active ingredient by HPLC, which can systematically evaluate the screening and function verification of the core active ingredient in the raw materials, construct a unified quality control standard of the flavonoid active ingredient, provide theoretical support for the development of active substance omics products, and meet the quality control needs of modern animal husbandry.

[0229] The above is an exemplary description of the application, and it is obvious that the specific implementation of the application is not limited by the above method. As long as the method concept and technical scheme of the application are used for such non-essential improvements, or the concept and technical scheme of the application are directly applied to other occasions without improvement, they are within the protection scope of the application.

Claims

1. A method for evaluating the active flavonoid components of whole-plant corn silage based on HPLC, characterized by, It comprises the following steps: S1, sample collection and processing: Collect a large number of whole plant corn silage samples from different regions, dry and crush them for standby; S2, sample total flavonoid extraction process: Determine the total flavonoid content in the sample by ultrasonic-assisted ethanol method; S3, sample active ingredient HPLC fingerprint establishment preparation: S31, preparation of test solution: Precisely weigh a certain amount of each sample obtained in step S1, extract it by the sample total flavonoid extraction process in step S2, and prepare a test solution for standby; S32, selection and processing of reference materials: Precisely weigh a certain amount of each of the following reference materials: alfalfa, isoheterophyllous glycoside, isofraxin glycoside, sophoraflavone glycoside, naringenin and kaempferol, and prepare a mixed reference solution; S33, construction of chromatographic conditions: Establish the chromatographic conditions of the whole plant corn silage flavonoid HPLC fingerprint, and record the chromatogram; S34, selection of reference peaks: Mix the mixed reference solution in step S32 and the test solution in step S31, respectively, and analyze them by injection, identify the chromatographic peaks of each mixed reference, and select the chromatographic peaks with high resolution and large peak area as reference peaks S; S4, establishment of sample active ingredient HPLC fingerprint: Precisely take each batch of whole plant corn silage test solution prepared in step S31, analyze it by injection according to the HPLC fingerprint chromatographic conditions in step S33, record its chromatogram and generate a control chromatogram; then calibrate the common peaks, calculate the area of non-common peaks and evaluate the similarity; finally, classify each batch of whole plant corn silage sample through cluster analysis, and classify it through principal component factor analysis of each batch of whole plant corn silage sample and calculation of its principal component comprehensive score.

2. The method for evaluating the active components of corn silage flavonoids from whole plant based on HPLC according to claim 1, characterized in that, In step S2, the ultrasonic-assisted ethanol method process has an ethanol concentration of 50% to 100%, a solid-liquid ratio of 1:(20-100), and an ultrasonic extraction time of 30 minutes to 180 minutes.

3. The method for evaluating the active components of corn silage flavonoids from whole plant based on HPLC according to claim 2, characterized in that, In step S2, the ethanol concentration, solid-liquid ratio and ultrasonic extraction time in the ultrasonic-assisted ethanol method process are optimized by orthogonal test, and the optimal extraction process is obtained as follows: 90% ethanol solution is used as the extracting agent, the solid-liquid ratio is 1:60 W / V, and the ultrasonic extraction time is 120 minutes.

4. The method for evaluating the active components of corn silage flavonoids from whole plant based on HPLC according to claim 1, characterized in that, In step S31, the preparation of the test solution comprises the following specific steps: precisely weigh 5g of each sample obtained in step S1, extract it by the sample total flavonoid extraction process in step S2, evaporate the obtained extract by rotary evaporation under reduced pressure, finally dilute it to 5ml with 90% ethanol, filter it with a 0.45μm filter membrane, and standby.

5. The method for evaluating the active components of corn silage flavonoids from whole plant based on HPLC according to claim 1, characterized in that, In step S32, the selection and processing of reference materials comprises the following specific steps: precisely weigh 1mg of each of the following reference materials: alfalfa, isoheterophyllous glycoside, isofraxin glycoside, sophoraflavone glycoside, naringenin and kaempferol, dissolve them in methanol and dilute them to 10ml in a volumetric flask, and filter them with a 0.45μm filter to obtain a mixed reference solution.

6. The method for evaluating the active components of corn silage flavonoids from whole plant based on HPLC according to claim 1, characterized in that, In step S33, the chromatographic conditions of the whole corn silage flavonoids HPLC fingerprint are as follows: two mobile phase systems of methanol-0.5% phosphoric acid aqueous solution or acetonitrile-0.5% phosphoric acid aqueous solution, a flow rate of 0.7 ml / min-1.0 mL / min, a column temperature of 25-38°C, a detection wavelength of 330 nm or 360 nm, gradient elution, and an elution detection time of 0-120 min.

7. The method for evaluating the active components of corn silage flavonoids from whole plant based on HPLC according to claim 1, characterized in that, In step S33, the chromatographic conditions of the whole corn silage flavonoids HPLC fingerprint are as follows: a chromatographic column of Extend-C18, a mobile phase of A being 0.5% phosphoric acid aqueous solution and B being methanol solution, a flow rate of 1.0 ml / min, a column temperature of 30°C, a detection wavelength of 360 nm, gradient elution, and an elution detection time of 70 min.

8. The method for evaluating the active components of corn silage flavonoids from whole plant based on HPLC according to claim 1, characterized in that, In step 4, the HPLC fingerprint of the active ingredients of the sample is established, and the specific steps are as follows: S41, determination of whole corn silage: Precisely take the whole corn silage test sample solution prepared in step S31, and analyze it by injection according to the chromatographic conditions of the HPLC fingerprint in step S33, record the chromatogram, and import it into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Processing Software 2012 Edition" to generate a control chromatogram; S42, calibration of common peaks: According to the technical parameters of HPLC analysis of each batch of whole corn silage, record the chromatographic peaks with a percentage of total peak area of more than 1%, and obtain the common chromatographic peaks by retention time control; calculate the relative retention time and relative peak area of each common peak in the HPLC chromatogram of each batch of test sample; S43, calculation of non-common peak area: By comparing the chromatogram data of each batch of whole corn silage test sample solution, the percentage of non-common peak area to total peak area is calculated; S44, similarity evaluation: Import the chromatogram of each batch of whole corn silage into the "Traditional Chinese Medicine Chromatographic Fingerprint Similarity Processing Software 2012 Edition", take the control chromatogram as a reference, and perform similarity evaluation; S45, cluster analysis: Based on the common peak area data of each batch of whole corn silage sample obtained in step S42, a system clustering model is constructed using SPSS21.0 software; by setting the intergroup average connection method as the clustering merging strategy, combining the square Euclidean distance calculation of the metabolite distribution heterogeneity characteristics between different samples, and through cluster analysis, each batch of whole corn silage sample is classified; S46, principal component analysis: Based on the common peak area data of each batch of whole corn silage sample obtained in step S42, an orthogonal linear transformation model is constructed by SPSS21.0 software, and the principal component factor analysis of each batch is performed, and the principal component comprehensive score of each batch of whole corn silage sample is calculated for classification.

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