CN108241033B - Method for rapidly detecting content of 6 quality index substances in radix ophiopogonis alcohol extract and application - Google Patents
Method for rapidly detecting content of 6 quality index substances in radix ophiopogonis alcohol extract and application Download PDFInfo
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
- G01N30/02—Column chromatography
- G01N30/88—Integrated analysis systems specially adapted therefor, not covered by a single one of the groups G01N30/04 - G01N30/86
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- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/33—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using ultraviolet light
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Abstract
The invention discloses a method for rapidly detecting the content of 6 quality index substances in an alcohol extract of dwarf lilyturf tuber, belonging to the field of quality monitoring in the production process of traditional Chinese medicines. The method comprises the following steps: (1) collecting a correction set sample; (2) determining the content of fructose, glucose, sucrose, radix Ophiopogonis total saponin, radix Ophiopogonis methyl dihydrohomoisoflavone A and radix Ophiopogonis methyl dihydrohomoisoflavone B in the calibration sample by conventional method; (3) measuring the ultraviolet absorption spectrum of the correction set sample; (4) establishing a correction model; (5) verifying the correction model; (6) and calculating the contents of 6 quality index substances of the radix ophiopogonis alcohol extract to be detected. The method is simple to operate, and compared with the traditional analysis method, the total determination time is shortened by more than 50 times. The ultraviolet characteristic spectrum and the contents of 6 substances with different quality indexes have good correlation, the completion quality of the extraction process is ensured by monitoring the quality indexes in real time, and the quality of the final product is further ensured.
Description
Technical Field
The invention relates to the field of quality monitoring in the production process of traditional Chinese medicines, in particular to a method for rapidly detecting the content of 6 quality index substances in an alcohol extract of dwarf lilyturf tuber and application thereof in simultaneously determining 6 quality indexes in an alcohol extract unit intermediate of dwarf lilyturf tuber in the production process of Shenmai injection.
Background
The Shenmai injection is a quick-acting Chinese medicine preparation developed on the basis of "Shengmai powder" as ancient Chinese medicine recipe and is prepared with red ginseng and ophiopogon root through alcohol extraction and water precipitation. Clinically, the Shenmai injection is mainly used for treating cardiovascular diseases such as heart failure, arrhythmia and the like, and is also commonly used as an auxiliary medicament of an anti-tumor medicament. With the wide application of Shenmai injection, people pay more and more attention to the quality control level of the Shenmai injection in the production process.
The saponins and homoisoflavonoids in radix Ophiopogonis are important material basis for preventing and treating cardiovascular diseases, and have physiological activities of resisting myocardial ischemia, lowering blood sugar, resisting aging, inhibiting tumor, regulating immunity, etc. However, radix ophiopogonis contains a large amount of monosaccharides, disaccharides and oligosaccharides, and the existence of the saccharides brings great risks to the stability, safety and quality control of the Shenmai injection, and directly influences parameters such as osmotic pressure, solid amount and the like of the injection. In conclusion, the improvement of the quality control level of the substances has important significance for improving the overall quality control level of the production process of the Shenmai injection.
In the production process of the ginseng and dwarf lilyturf tuber injection, saponins, flavonoids, monosaccharides, disaccharides and other components in dwarf lilyturf tuber can be extracted by an ethanol reflux extraction process unit of dwarf lilyturf tuber, the components of an alcohol extract are complex, the quality control value of the alcohol extract is focused and researched, in the actual production process, the determination methods of the saponins, the flavonoids and the saccharides in the dwarf lilyturf tuber in an intermediate are different, a patent document with the application publication number of CN105004830A discloses a high performance liquid chromatography method for simultaneously determining 5 saponin components in the dwarf lilyturf tuber, the 5 saponin components comprise Ophiojaponin-C, deacetylated Ophiojaponin-A, 3-O- α -L-rhamnose- (1 → 2) - β -glucose ophiopogonin, ophiopogonin-D and ophiopogonin-D, the application publication number of CN 105301130A discloses a high performance liquid chromatography method for detecting the content of flavonoids in the dwarf lilyturf tuber, the patent with the application publication number of CN 102133333A discloses a quality control method for detecting the fingerprint of the ginseng and the quality of a ginseng and the ginseng injection by using a liquid chromatography detector as a liquid chromatography method for detecting the similarity of the fingerprint of a ginseng and a red ginseng product, and calculating the similarity of the quality of the ginseng product by using a liquid chromatography method for detecting the fingerprint method for detecting the quality.
The method has high analysis precision, but needs a great deal of time for an analyst to analyze, is complex in analysis operation, long in instrument time, troublesome in pretreatment, high in requirements for the instrument and the analyst, and is not suitable for real-time analysis and monitoring of the process.
Disclosure of Invention
The invention aims to provide a method for simultaneously and rapidly detecting the contents of 6 quality index substances, namely fructose, glucose, sucrose, total saponins of radix ophiopogonis, methyl ophiopogon root isoflavanone A and methyl ophiopogon root isoflavanone B in an alcohol extract of radix ophiopogonis, and the method is applied to real-time monitoring of 6 quality indexes in an ethanol reflux extraction unit of radix ophiopogonis in the production process of Shenmai injection and online monitoring of the alcohol extraction process of radix ophiopogonis.
In order to achieve the purpose, the invention adopts the following technical scheme: a method for rapidly detecting the content of 6 quality index substances in an alcohol extract of radix ophiopogonis, wherein the 6 quality index substances are fructose, glucose, sucrose, total saponins of radix ophiopogonis, methyl ophiopogon root isoflavanone A and methyl ophiopogon root isoflavanone B, and is characterized by comprising the following steps:
(1) collecting a correction set sample: selecting different batches of radix ophiopogonis, and taking radix ophiopogonis alcohol extract collected at different stages of the radix ophiopogonis alcohol reflux extraction process as a correction set sample;
(2) and 6 quality index substance reference values of the correction set sample are determined: a. determining the content of fructose, glucose and sucrose by high performance liquid chromatography and evaporative light scattering detector; b. determining the content of the total saponins of the dwarf lilyturf root by adopting a perchloric acid color development method; c. measuring contents of methyl ophiopogon root isoflavanone A and methyl ophiopogon root isoflavanone B by high performance liquid chromatography-ultraviolet light detection method;
(3) and (3) measurement of ultraviolet absorption spectrum of the calibration set sample: placing the calibration set sample diluent in an ultraviolet visible spectrometer for full-wavelength scanning by adopting a quartz cuvette with an optical path of 10mm, wherein the wavelength scanning range is 190-800 nm, the scanning precision is 1nm, water is used as a blank solution, each sample is subjected to 3 times of parallel scanning, and average spectral data is taken as ultraviolet visible absorption spectral data of the sample to obtain ultraviolet visible absorption spectral data of a calibration set sample;
(4) establishing a correction model: establishing a mathematical model of the relation between the contents of 6 quality index substances in a correction set sample and corresponding ultraviolet-visible absorption spectra by adopting a multivariate data analysis method, wherein the correlation coefficient of the correction model is more than or equal to 0.9;
(5) verifying the correction model: performing internal verification on the correction model established in the step (4) by adopting a leave-one-out method in a crossed manner, wherein the verification method comprises the steps of taking the alcohol extract of the radix ophiopogonis to be detected, measuring the ultraviolet visible absorption spectrum of the alcohol extract, inputting the ultraviolet visible absorption spectrum into the correction model of each quality index substance, calculating the content of the corresponding quality index substance, and comparing the content of the corresponding quality index substance with the content of each quality index substance measured by the alcohol extract of the radix ophiopogonis according to the method in the step (2), wherein the measurement error is required to be less than or;
(6) calculating the contents of 6 quality index substances of the radix ophiopogonis alcohol extract to be detected: taking winter wheat extract samples with 6 quality index substance contents to be detected, collecting ultraviolet visible absorption spectrum information of the samples according to the same ultraviolet spectrum collection method as the correction set samples, inputting the spectrum information into the correction model of each quality index substance, and calculating the content of the corresponding quality index substance in the samples to be detected.
In the step (4), the multivariate data analysis method is a principal component regression method or a partial least squares method.
According to the invention, representative alcohol extract of radix ophiopogonis is collected as a correction set sample, and an ultraviolet-visible absorption spectrogram of the correction set sample is obtained by scanning in a certain collection mode. The method comprises the steps of measuring the content of fructose, glucose, sucrose, total saponins of radix ophiopogonis, methyl ophiopogon homoisoflavonoid A and methyl ophiopogon homoisoflavonoid B in a correction set sample by using a traditional quantitative method as reference values, establishing a multivariate correction model of the relation between the ultraviolet spectrum of the radix ophiopogonis alcohol extract and the quality index of the radix ophiopogonis alcohol extract by using a PCR (polymerase chain reaction) method and a PLS (partial least squares) method in a multivariate data analysis technology, measuring the ultraviolet spectrum of the radix ophiopogonis extract to be measured by using the same method, and rapidly calculating by using the established correction model to obtain each quality index value.
Compared with the prior art, the invention has the following beneficial effects:
(1) the method for rapidly determining 6 quality indexes of the intermediate of the alcohol extraction unit of the radix ophiopogonis in the production process of the Shenmai injection by using the ultraviolet spectrum is simple and rapid to operate and simple to pretreat. Compared with the traditional analysis method, the method shortens the determination time by more than 50 times, does not need a large amount of organic solvent, and accords with the concept of green manufacturing.
(2) The ultraviolet visible absorption spectrum and the contents of 6 substances with different quality indexes have good correlation, the problem that the contents of various components in the alcohol extract of radix ophiopogonis are difficult to rapidly measure can be effectively solved, the process is monitored in real time by monitoring the quality indexes in real time, the completion quality of an extraction process is ensured, the quality of a final product is further ensured, and the method can be popularized and applied in the production of Chinese medicinal preparations.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
FIG. 2 is a UV spectrum of a calibration set of alcohol extracts of Ophiopogon japonicus.
FIG. 3 is a spectrum of a sample of a calibration set of an alcoholic extract of Ophiopogon japonicus after SG smoothing and first-order derivation pretreatment.
FIG. 4 is a correlation diagram between the reference value and the predicted value of the PCR quantitative model of the total saponins content in Ophiopogon japonicus in the Ophiopogon japonicus alcohol extract verification set and the correction set.
FIG. 5 is a correlation diagram between the reference value and the predicted value of the PCR quantitative model for the content of isoflavanone A in radix Ophiopogonis methyl in the radix Ophiopogonis alcoholic extract validation set and the calibration set samples.
FIG. 6 is a correlation diagram between the reference value and the predicted value of the PCR quantitative model of the content of the methylophiopogonin B in the alcohol extract of radix Ophiopogonis and the samples in the calibration set.
FIG. 7 is a correlation diagram between the reference value and the predicted value of the PCR quantitative model of fructose content in the samples of the radix Ophiopogonis ethanol extract validation set and the correction set.
FIG. 8 is a correlation diagram between the reference value and the predicted value of the PCR quantitative model of glucose content of the samples of the validation set and the calibration set of the alcoholic extractive solution of radix Ophiopogonis.
FIG. 9 is a correlation diagram between the reference values and the predicted values of the PCR quantitative model of sucrose content in the samples of the radix Ophiopogonis ethanol extract validation set and the calibration set.
FIG. 10 is a spectrogram of a radix Ophiopogonis ethanol extractive solution calibration set sample subjected to SG smoothing and second derivative pretreatment.
FIG. 11 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model calibration set sample of the total saponins content in Ophiopogon japonicus extracted with alcohol.
FIG. 12 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model calibration set sample of the content of liriope dihydrohomoisoflavone A in an alcoholic extract of radix Ophiopogonis.
FIG. 13 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model calibration set sample of the content of liriope dihydrohomoisoflavone B in an alcoholic extract of radix Ophiopogonis.
FIG. 14 is a graph showing the correlation between the reference value and the predicted value of a sample of a PLS quantitative model correction set of fructose content in an alcoholic extract of radix Ophiopogonis.
FIG. 15 is a graph showing the correlation between the reference value and the predicted value of the PLS quantitative model calibration set sample of the alcohol extract of Ophiopogon japonicus.
FIG. 16 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model calibration set sample of radix Ophiopogonis ethanol extract.
FIG. 17 is a graph showing the correlation between the reference value and the predicted value of the PLS quantitative model validation set of total saponins content in Ophiopogon japonicus extracted with alcohol.
FIG. 18 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model validation set sample of the content of liriope dihydrohomoisoflavone A in an alcoholic extract of radix Ophiopogonis.
FIG. 19 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model validation set sample of the content of liriope dihydrohomoisoflavone B in an alcoholic extract of radix Ophiopogonis.
FIG. 20 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model validation set sample of ethanol extract of Ophiopogon japonicus.
FIG. 21 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model validation set sample of Ophiopogon japonicus alcohol extract.
FIG. 22 is a graph showing the correlation between the reference value and the predicted value of a PLS quantitative model validation set sample of radix Ophiopogonis ethanol extract.
In fig. 4 to 9, the data points of samples 1, 9 and 16 in the figures are verification set samples, and the rest are correction set samples.
In fig. 11 to 16, data points of samples md2, md3, md4, md5, md6, md7, md8, md10, md11, md12, md13, md14, md15, and md17 in the figures are correction set samples.
In fig. 17 to 22, the data points of the samples md1, md9, and md16 in the figures are verification set samples.
Detailed Description
The following is further described with reference to the drawings and examples, but the present invention is not limited thereto.
Example 1:
the method flow is shown in figure 1.
1. Collection of correction set samples:
accurately weighing 30g of radix Ophiopogonis decoction pieces, placing in an extraction tank with a glass jacket, adding alcohol solution as extraction solvent, heating and reflux-extracting for a period of time, collecting filtrate, repeating the above steps, reflux-extracting one decoction piece for 2 times, wherein the ethanol dosage, alcohol concentration and single extraction time of ethanol reflux-extracting radix Ophiopogonis in different batches are different. Extracting solution is irregularly sucked from the reflux extraction process of 10 batches of radix ophiopogonis with ethanol, and 14 correction set samples are obtained in total;
2. determination of correction set sample fructose, glucose and sucrose content reference value
Determining the contents of fructose, glucose and sucrose in the calibration set sample by adopting a high performance liquid chromatography and evaporative light scattering detector combined method (HPLC-ELSD method);
(1) the analysis conditions comprise that a chromatographic column is Grace Prevail Carbohydrate ES (4.6mm × 250mm,5 mu m), a mobile phase is acetonitrile-water (70:30), the flow rate is 1mL/min, the column temperature is 30 ℃, the sample injection amount is 10 mu L, the ELSD detector conditions are that the nitrogen flow rate is 2.0L/min, the drift tube temperature is 100 ℃, the gain is 2.0, and a collider is closed;
(2) preparation of control solutions: precisely weighing fructose, glucose and sucrose reference substances in a volumetric flask, diluting with 50% chromatographic grade methanol to scale, and preparing into solution containing fructose 10.66mg/mL, glucose 4.24mg/mL and sucrose 4.04mg/mL as No. 1 mixed reference substance solution; accurately transferring 5.0mL, 2.5mL, 2.0mL and 1.0mL of the reference substance solution 1 into 10mL volumetric flasks, and diluting with 50% chromatographic grade methanol to scale to obtain mixed reference substance solutions No. 2, No. 3, No. 4 and No. 5;
(3) and (3) standard curve determination: respectively injecting No. 1-5 standard substance solutions into a high performance liquid chromatograph, measuring according to the conditions in the step (1), performing linear regression by using the logarithm value of the chromatographic peak area A and the logarithm value of the sample injection quality m of a reference substance, and respectively drawing standard curves of fructose, glucose and sucrose, wherein the standard curves of saccharides are shown in Table 1;
TABLE 1 regression analysis Standard Curve, correlation coefficient and Linear Range of saccharides
(4) And (3) determining the content of fructose, glucose and sucrose: and (3) taking a calibration set sample, filtering by using a 0.45-micron microporous filter membrane, injecting subsequent filtrate into a liquid chromatograph, measuring according to the conditions in the step (1), and calculating the content of three saccharides according to an external standard method to be used as reference values.
3. Determination of total saponin content reference value of correction set sample
Determining the content of the radix ophiopogonis total saponins in the calibration set sample by adopting a perchloric acid color development method, wherein the content of the radix ophiopogonis total saponins is calculated by ruscogenin;
(1) preparation of control solutions: taking a proper amount of ruscogenin reference substance, precisely weighing, and adding methanol to obtain solution containing 120 μ g per 1 mL;
(2) preparation of a standard curve: precisely measuring a reference substance solution by 0.2mL, 0.5mL, 1.0mL, 2.0mL, 3.0mL and 4.0mL, respectively placing the reference substance solution in a test tube with a plug, volatilizing a solvent in a water bath, precisely adding 10mL of perchloric acid, shaking up, keeping the temperature in hot water for 15 minutes, taking out, cooling with ice water, measuring absorbance at 397nm by using a corresponding reagent as a blank according to an ultraviolet-visible spectrophotometry (appendix V A of Chinese pharmacopoeia 2015 edition), and drawing a standard curve by using absorbance A to concentration c, wherein the formula of the standard curve is as follows:
A＝12.994c-0.0193，R20.9957, linear range 0.0012-0.0480 mg/mL;
(3) the determination method comprises the following steps: placing the sample in a dry test tube with a plug, measuring absorbance by the method from 'volatilizing solvent in water bath', reading out the amount of ruscogenin in the calibration set sample from the standard curve, and calculating to obtain the final product.
4. Determination of content of methyl ophiopogon root dihydrohomoisoflavone A and methyl ophiopogon root dihydrohomoisoflavone B in correction sample
Measuring contents of methyl ophiopogon root isoflavanone A and methyl ophiopogon root isoflavanone B in the calibration set sample by adopting a high performance liquid chromatography and ultraviolet detector combined method (HPLC-UV method);
(1) the analysis conditions are that a chromatographic column is Agilent Zorbax C18(4.6mm × 250mm,5 mu m), a mobile phase is acetonitrile-0.1% phosphoric acid solution (58: 42), the flow rate is 1.0mL/min, the column temperature is 30 ℃, the sample injection volume is 10 mu L, and the detection wavelength is 280 nm;
(2) preparation of a standard substance: precisely weighing two reference substances respectively, and adding methanol to obtain mixed reference substance solution containing 20.4 μ g/mL of radix Ophiopogonis dihydrohomoisoflavone A and 33.8 μ g/mL of radix Ophiopogonis dihydrohomoisoflavone B per 1 mL;
(3) preparation of a standard curve: the mixed control solution was injected at 1. mu.L, 2. mu.L, 5. mu.L, 10. mu.L, 15. mu.L, and 20. mu.L, respectively, and a linear regression was performed on the peak area A of the chromatogram in the amount of m (. mu.g) to plot a standard curve of the two compounds, the information of the standard curve being shown in Table 2.
TABLE 2 regression analysis Standard Curve, correlation coefficient and Linear Range of homoisoflavonoids
(4) Measuring the content of the ophiopogon japonicus isoflavanone A and the ophiopogon japonicus isoflavanone B: and (3) taking a calibration set sample, filtering by using a 0.45-micrometer microporous filter membrane, taking a subsequent filtrate, injecting the subsequent filtrate into a liquid chromatograph, and calculating the contents of the two compounds by peak areas according to an external standard method to serve as reference data.
5. Calibration set sample spectral data acquisition
Diluting the collected correction set sample by ten times with pure water, and scanning by using an ultraviolet-visible spectrophotometer (Cary60, Agilent company, USA) to obtain an ultraviolet full-wavelength spectrum of the 190-800 nm range of the correction sample set; taking water as a blank solution, performing 3 times of parallel scanning on each sample, and taking average spectrum data as ultraviolet-visible characteristic absorption spectrum data of the sample. The collection mode is a transmission method, the used cuvette is a quartz cuvette with an optical path of 10mm, and the scanning precision is 1 nm. The collected sample is shown in FIG. 2 as the original spectrogram of radix Ophiopogonis extract.
6. Establishment of correction model
Processing the original data by using a calculation software BWIQTM (B & W Tek Opto-Electronics in America), performing pretreatment method and waveband selection optimization on the spectrum, and processing the original data by using an optimal waveband range and a sample pretreatment method to obtain the characteristic spectrum information of the radix ophiopogonis alcohol extract. And (3) establishing a quantitative regression model of 6 quality indexes by using a PCR method, and performing internal verification alternately by using a leave-one-out method.
(1) Modeling and optimizing by different spectrum preprocessing methods: the SG smoothing, first derivative and second derivative pretreatment methods are respectively used for processing full-wave-band ultraviolet original spectra, and the numerical value of the ophiopogon japonicus total saponin is taken as an example for carrying out PCR method modeling, and the result is shown in Table 3. By a correlation coefficient R2The Root Mean Square Error (RMSE) is used as the judgment basis of the model robustness, and the result shows that the model performance is the best after the smoothing and first derivative processing, namely the correlation coefficient is the highest (R)20.888), the root mean square error (RMSE ═ 1.882 μ g/mL) is minimal. The spectra after SG smoothing and first derivative processing are shown in fig. 2.
TABLE 3 optimization results of the establishment of the radix Ophiopogonis total saponins model by PCR method with different spectrum pretreatment methods
(2) Modeling and optimizing spectral data of different wave bands: the PCR method modeling is performed by respectively using the four wave bands of the full wavelength of the sample set, 190-350nm, 190-450nm and 190-600nm, and the results are shown in Table 4. The results show that: the radix ophiopogonis total saponin quantitative model established by selecting the 190-450nm wave band has the best performance, namely the correlation coefficient (R)20.969) and the root mean square error (RMSE 0.987 μ g/mL) is minimal.
TABLE 4 optimization results of prediction model for total saponins of radix Ophiopogonis established by PCR method in different wave band ranges
(3) Establishing a correction model: SG smoothing method and first derivative method preprocessing are carried out on the ultraviolet absorption spectrum data of the sample set with the wave band of 190-450nm, a PCR method is used for establishing a correction model between the characteristic spectrum information of the radix ophiopogonis extracting solution and 6 quality indexes, and the interior intersection of the leave-one method is adopted for verification. The correlation coefficients and cross-validation error root mean square RMSECV values for the 6 quantitative calibration models are shown in table 5.
TABLE 5 quantitative results of PCR regression model for 6 quality indexes of radix Ophiopogonis ethanol extractive solution sample set
The characteristic spectrum of the radix ophiopogonis extracting solution has better correlation with 6 quality indexes. The correlation graphs between the content of 6 quality indexes of the radix ophiopogonis extract predicted by the quantitative correction model and the reference value measured by the traditional method are shown in fig. 4 to fig. 9, wherein the quantitative regression model graphs of the content of the total saponins of radix ophiopogonis, the content of the dihydro-homoisoflavone A of radix ophiopogonis methyl, the content of the dihydro-homoisoflavone B of radix ophiopogonis methyl, the content of fructose, glucose and sucrose are sequentially shown in fig. 4, fig. 5, fig. 6, fig. 7, fig. 8 and fig. 9, and the correlation between the predicted value and the reference value of the models is good and the models have good performance as can be seen from fig. 4 to fig. 9.
7. Verification of correction models
Selecting 3 radix Ophiopogonis extracts (the content of each component is required to fall within the content range of the corresponding component in the correction set) with known quality index as a verification set, and performing ultraviolet absorption spectrum scanning according to the same ultraviolet spectrum collection method of the correction set. And after the same spectrum pretreatment is carried out, inputting the spectrum characteristic value into a correction model, and calculating to obtain the quality index content of the sample of the verification set. The predicted data were compared to reference values and the results are shown in Table 6.
TABLE 6 predicted values, reference values and RMSEP values of 6 quality index quantitative correction models of PCR method radix Ophiopogonis extract
The root mean square RMSEP of the prediction errors of the predicted values and the reference values of the total saponins of dwarf lilyturf root, the dihydrohomoisoflavone A of dwarf lilyturf root, the dihydrohomoisoflavone B of dwarf lilyturf root, fructose, glucose and sucrose contents are acceptable prediction errors.
8. Determination of quality indexes of radix ophiopogonis ethanol reflux extraction unit in production process of Shenmai injection
Collecting the intermediate of the radix ophiopogonis ethanol reflux extraction unit in a certain batch of large-scale production of Shenmai injection, collecting ultraviolet absorption spectrum data of a sample according to the same ultraviolet spectrum collection method of a correction set sample, inputting a characteristic spectrum into a quantitative correction model after the same spectrum pretreatment, and quickly calculating to obtain the content value of the corresponding quality index in the extracting solution. The content values of 6 quality indexes obtained by the correction model are as follows: the total saponins of radix Ophiopogonis is 10.28 μ g/mL, the dihydrohomoisoflavone A of radix Ophiopogonis is 0.0131 μ g/mL, the dihydrohomoisoflavone B of radix Ophiopogonis is 0.0109 μ g/mL, the fructose is 6037 μ g/mL, the glucose is 921 μ g/mL, and the sucrose is 508 μ g/mL. Compared with the actual value measured by HPLC, the difference is not large, and the spectrum rapid detection method is verified to be reliable.
Example 2:
the method of example 1 was followed, except that a quantitative calibration model of 6 quality indicators in the alcoholic extract of Ophiopogon japonicus was established using PLS method in exchange for the calculation software Simca-P +12.0 (Umetrics, Sweden).
1. The same calibration set samples and their reference values, uv spectra, as in example 1 were used.
2. Establishment of correction model
And processing the original data by using Simca, performing pretreatment method and waveband selection optimization on the spectrum, and processing the original data by using the optimal waveband range and sample pretreatment method to obtain the characteristic spectrum information of the radix ophiopogonis alcohol extract. And (3) establishing a quantitative regression model of 6 quality indexes by using a PLS method, and performing internal verification by adopting a leave-one-out method in a crossed manner.
(1) Modeling and optimizing by different spectrum preprocessing methods: the SG smoothing, first derivative and second derivative preprocessing methods are respectively used for processing full-wave-band ultraviolet original spectra, the numerical value of the ophiopogon japonicus total saponin is taken as an example for modeling by the PLS method, and the results are shown in Table 7. With R2The RMSE is used as the decision basis of the model robustness, and the result shows that the model after the smoothing and second derivative processing has the best performance, namely the highest correlation coefficient (R)20.997), the root mean square error of cross-validation (RMSECV 2.11 μ g/mL) was small. The spectra after SG smoothing and second derivative processing are shown in fig. 10.
TABLE 7 optimization results of establishing radix Ophiopogonis total saponin model by PLS method with different spectrum pretreatment methods
(2) Modeling and optimizing spectral data of different wave bands: the PLS method modeling is performed by respectively using the sample set full wavelength, 190-350nm, 190-450nm and 190-600nm, and the results are shown in Table 8. Comprehensive consideration R2And after RMSECV, R is selected2The highest 190-600nm wave band is used as a wave band for modeling.
TABLE 8 PLS method for establishing radix Ophiopogonis total saponin prediction model optimization results in different wave band ranges
(3) Establishing a correction model: SG smoothing and first derivative method preprocessing are carried out on the ultraviolet absorption spectrum data of the sample set with the 190-ion 600nm wave band, a PLS method is used for establishing a correction model between the characteristic spectrum information of the radix ophiopogonis extracting solution and 6 quality indexes, and the interior intersection of the leave-one method is adopted for verification. The correlation coefficients and cross-validation error root mean square RMSECV values for the 6 quantitative calibration models are shown in table 9.
TABLE 9 quantitative results of PLS regression model for six quality indexes of radix Ophiopogonis ethanol extractive solution sample set
The characteristic spectrum of the radix ophiopogonis extracting solution has better correlation with 6 quality indexes. The correlation graphs between the 6 quality index contents of the radix ophiopogonis extract predicted by the quantitative correction model and the reference values measured by the traditional method are shown in fig. 11-16, wherein the quantitative regression model graphs of the total saponins of radix ophiopogonis, the dihydrohomoisoflavone A of radix ophiopogonis, the dihydrohomoisoflavone B of radix ophiopogonis, fructose, glucose and sucrose contents are sequentially shown in fig. 11, fig. 12, fig. 13, fig. 14, fig. 15 and fig. 16, and the graphs from fig. 11 to fig. 16 show that the correlation between the predicted values and the reference values of the models is good and the models have good performance.
3. Verification of correction models
Selecting 3 radix Ophiopogonis extracts (the content of each component is required to fall within the content range of the corresponding component in the correction set) with known quality index as a verification set, and performing ultraviolet absorption spectrum scanning according to the same ultraviolet spectrum collection method of the correction set. And after the same spectrum pretreatment is carried out, inputting the spectrum characteristic value into a correction model, and calculating to obtain the quality index content of the sample of the verification set. The predicted data were compared with reference values and the results are shown in Table 10.
TABLE 10 predicted value, measured value and RMSEP value of the quantitative calibration model for six quality indexes of radix Ophiopogonis extract by PLS method
The correlation graphs of the predicted values and the reference values of the ophiopogon japonicus total saponin, the ophiopogon japonicus dihydrohomoisoflavone A, the ophiopogon japonicus dihydrohomoisoflavone B, the fructose, the glucose and the sucrose content are respectively shown in the figure 17, the figure 18, the figure 19, the figure 20, the figure 21 and the figure 22, and the root mean square RMSEP of the predicted values and the reference values of the ophiopogon japonicus total saponin, the ophiopogon japonicus dihydrohomoisoflavone A, the ophiopogon japonicus dihydrohomoisoflavone B, the fructose, the glucose and the sucrose content is acceptable prediction errors.
4. Determination of quality indexes of radix ophiopogonis ethanol reflux extraction unit in production process of Shenmai injection
Collecting the intermediate of the radix ophiopogonis ethanol reflux extraction unit in a certain batch of large-scale production of Shenmai injection, collecting ultraviolet absorption spectrum data of a sample according to the same ultraviolet spectrum collection method of a correction set sample, inputting a characteristic spectrum into a quantitative correction model after the same spectrum pretreatment, and quickly calculating to obtain the content value of the corresponding quality index in the extracting solution. The content values of 6 quality indexes obtained by the correction model are as follows: the total saponins of radix Ophiopogonis is 10.59 μ g/mL, the dihydrohomoisoflavone A of radix Ophiopogonis is 0.0140 μ g/mL, the dihydrohomoisoflavone B of radix Ophiopogonis is 0.0112 μ g/mL, the fructose is 6087 μ g/mL, the glucose is 946 μ g/mL, and the sucrose is 504 μ g/mL. Compared with the actual value measured by HPLC, the difference is not large, and the spectrum rapid detection method is verified to be reliable.
Claims (3)
1. A method for rapidly detecting the content of 6 quality index substances in an alcohol extract of radix ophiopogonis, wherein the 6 quality index substances are fructose, glucose, sucrose, total saponins of radix ophiopogonis, methyl ophiopogon root isoflavanone A and methyl ophiopogon root isoflavanone B, and is characterized by comprising the following steps:
(1) collecting a correction set sample: selecting different batches of radix ophiopogonis, and taking radix ophiopogonis alcohol extract collected at different stages of the radix ophiopogonis alcohol reflux extraction process as a correction set sample;
(2) and 6 quality index substance reference values of the correction set sample are determined: a. determining the content of fructose, glucose and sucrose by high performance liquid chromatography and evaporative light scattering detector; b. determining the content of the total saponins of the dwarf lilyturf root by adopting a perchloric acid color development method; c. measuring contents of methyl ophiopogon root isoflavanone A and methyl ophiopogon root isoflavanone B by high performance liquid chromatography-ultraviolet light detection method;
(3) and (3) measurement of ultraviolet absorption spectrum of the calibration set sample: placing the calibration set sample diluent in an ultraviolet visible spectrometer for full-wavelength scanning by adopting a quartz cuvette with an optical path of 10mm, wherein the wavelength scanning range is 190-800 nm, the scanning precision is 1nm, water is used as a blank solution, each sample is subjected to 3 times of parallel scanning, and average spectral data is taken as ultraviolet visible absorption spectral data of the sample to obtain ultraviolet visible absorption spectral data of a calibration set sample;
(4) establishing a correction model: establishing a mathematical model of the relation between the contents of 6 quality index substances in a correction set sample and corresponding ultraviolet-visible absorption spectra by adopting a multivariate data analysis method, wherein the correlation coefficient of the correction model is more than or equal to 0.9;
(5) verifying the correction model: performing internal verification on the correction model established in the step (4) by adopting a leave-one-out method in a crossed manner, wherein the verification method comprises the steps of taking the alcohol extract of the radix ophiopogonis to be detected, measuring the ultraviolet visible absorption spectrum of the alcohol extract, inputting the ultraviolet visible absorption spectrum into the correction model of each quality index substance, calculating the content of the corresponding quality index substance, and comparing the content of the corresponding quality index substance with the content of each quality index substance measured by the alcohol extract of the radix ophiopogonis according to the method in the step (2), wherein the measurement error is required to be less than or;
(6) calculating the contents of 6 quality index substances of the radix ophiopogonis alcohol extract to be detected: taking winter wheat extract samples with 6 quality index substance contents to be detected, collecting ultraviolet visible absorption spectrum information of the samples according to the same ultraviolet spectrum collection method as the correction set samples, inputting the spectrum information into the correction model of each quality index substance, and calculating the content of the corresponding quality index substance in the samples to be detected.
2. The method for rapidly detecting the content of the 6 quality index substances in the alcohol extract of radix ophiopogonis as claimed in claim 1, wherein the multivariate data analysis method in the step (4) is a principal component regression method or a partial least squares method.
3. The use of the method for rapidly detecting the content of 6 mass index substances in an alcohol extract of radix Ophiopogonis as claimed in claim 1, in the determination of the content of 6 mass index substances in an intermediate of an alcohol extract unit of radix Ophiopogonis in the production of SHENMAI injection.
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