CN102768194A - Method for quickly detecting adenosine content of cordyceps mycelia powder - Google Patents
Method for quickly detecting adenosine content of cordyceps mycelia powder Download PDFInfo
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- CN102768194A CN102768194A CN2012102268468A CN201210226846A CN102768194A CN 102768194 A CN102768194 A CN 102768194A CN 2012102268468 A CN2012102268468 A CN 2012102268468A CN 201210226846 A CN201210226846 A CN 201210226846A CN 102768194 A CN102768194 A CN 102768194A
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Abstract
The invention discloses a method for quickly detecting adenosine content of cordyceps mycelia powder. The method comprises the following steps of: taking a cordyceps mycelia powder sample, and measuring the adenosine content; acquiring and pre-processing a near infrared spectrum of the cordyceps mycelia powder sample, and establishing a correcting model between the adenosine content of the cordyceps mycelia powder sample and the pre-processed near infrared spectrum by adopting partial least squares (PLS); acquiring and pre-processing a near infrared spectrum of a sample to be detected, and calculating the adenosine content of the sample to be detected through the correcting model, wherein the spectral scanning bands for acquiring the near infrared spectrums are 4,902.49-4,817.64cm<-1> and 4,740.49-4,107.91cm<-1>. By modeling with characteristic bands, the method is low in operation quantity and high in modeling speed; and the established PLS regression model is high in reliability and good in predicting effect, and can realize quick, accurate and nondestructive detection of the adenosine content of the cordyceps mycelia powder.
Description
Technical field
The present invention relates to cordyceps composition detection field, relate in particular to a kind of cordyceps adenosine content method for quick.
Background technology
Because the natural cs producing region has limitation, output is rare, adds that unauthorized and excessive mining for a long time causes ecological disruption serious, and wild Chinese caterpillar fungus can not satisfy the growing market demand far away.Fermentation cordyceps is to separate from the Chinese medicine protection kind of Chinese caterpillar fungus parasitical fungi through the biotechnology fermenting and producing; Also be a kind of important function health food simultaneously, be rich in adenosine, D-sweet mellow wine, several amino acids isoreactivity material, have important biomolecules such as antitumor, antifatigue and raising immunity and learn function (Pan B S; LinC Y; Huang B M.Evid Based Complement Alternat Med, 2011,2011:750468.; Wang Z-M, Peng X, Lee K-L D, et al.Food Chemistry, 2011,125 (2): 637-643.).Cordyceps sinensis belongs to Ascomycetes, Clavicipitaceae, Cordyceps, and a kind of in the Chinese caterpillar fungus is the distinctive famous and precious strong tonic Chinese medicine material of China.The fermentation Chinese caterpillar fungus bacterium powder is that first class national new drug and Chinese medicine are protected kind for from fresh Cordyceps sinensis, separating the fungi asexual generation bacterial classification obtain through the mycelial dried powder of liquid fermentation and culture gained.
At present, mainly adopt modern analytical technique such as high performance liquid chromatograph that the index adenosine content of reflection quality in the fermentation cordyceps (comprising the fermentation Chinese caterpillar fungus bacterium powder) is detected (Li SP, Li P; Dong TT; Et al.Electrophoresis, 2001,22 (1): 144-150.; Yang F Q, Li D Q, Feng K, et al.J Chromatogr A, 2010,1217 (34): 5501-5510.).The patent of invention of notification number CN100483131C discloses a kind of Chinese caterpillar fungus quality evaluating method of characterization natural Cordyceps sinensis characteristic, wherein discloses to adopt the HPLC analytic approach to detect the content and the ratio of adenosine composition in the natural cordyceps extract.The patent of invention of notification number CN101822765B discloses the detection method of content of a kind of invigorating function of kidney and strengthening bone, enriching blood and replenishing vital essence compound Chinese medicinal preparation; Compound Chinese medicinal preparation by prepared rhizome of rehmannia, stir-baked CORTEX EUCOMMIAE, the fruit of Chinese wolfberry, the fruit of glossy privet, the stir-fry seed of Chinese dodder, stir-baked RHIZOMA DIOSCOREAE, Poria cocos, fermentation cordyceps, lotus seeds, Gorgon fruit, calcined oyster shell etc. ten simply bulk drug form, disclose in this patent documentation and adopted high performance liquid chromatography to detect the adenosine content in the compound Chinese medicinal preparation.These traditional chemical detection methods need be destroyed sample, and pre-service and mensuration process are very time-consuming, only can carry out sampling Detection, can't realize that enterprise requires the requirement that product quality information is obtained on a large scale.
Got into since 21 century, (Near Infrared Spectroscopy, NIRS) analytical technology is increasing to the research of the detection of various compositions in food, agricultural byproducts, the oil etc. and product quality influence factor to utilize near infrared spectrum.Domestic researcher Wang Di etc. utilizes content of effective in the near infrared fast measuring Cordyceps militaris (WANG Di, ZHANG Yuan-li, MENG Qin-fan.Acta OpticaSinica, 2009 (10): 2795-2799.).Cheng Yi space seminar also uses Artificial Neural Network fermentation cordyceps to be carried out quantitative detecting analysis (the YANG Nan-lin of amino acid and sweet mellow wine; CHENYi-yu.analytical chemistry (analytical chemistry), 2003 (06): 664-668.; ZHAOChen, QU Hai-bin, CHEN Yi-yu.Spectro scopy and Spectral Analysis, 2004 (01): 50-53.).But these researchs all only use NIRS to active component carry out simple quantitatively, and about the NIRS detection by quantitative of adenosine in the fermentation cordyceps as yet the someone relate to, and also nobody further carries out analyses such as wavelength selection.
The difference of adenosine index is to estimate its quality and the different main foundation of fixing a price in the fermentation cordyceps.If can solve the problem of detection by quantitative quick and precisely, the quality control in the high volume production process is had crucial meaning.
Summary of the invention
The invention provides a kind of cordyceps adenosine content method for quick, be used for the cordyceps adenosine content fast, harmless, accurately detect, solved problems such as existing detection method complex operation, consuming time, consumption power, cost height, contaminated environment.
A kind of cordyceps adenosine content method for quick comprises:
(1) gets the cordyceps sample, measure adenosine content;
(2) gather the near infrared spectrum of cordyceps sample and carry out pre-service, adopt PLS to set up the calibration model between the adenosine content and pretreated near infrared spectrum in the cordyceps sample;
(3) gather the near infrared spectrum of sample to be tested and carry out pre-service, calculate the adenosine content of sample to be tested through calibration model;
Wherein, the spectral scan wave band of collection near infrared spectrum is 4902.49-4817.64cm
-1And 4740.49-4107.91cm
-1
In the electromagnetic wavelength 800-2500nm scope is the frequency multiplication and the combined spectral band of material molecule vibrational spectrum, thereby has comprised the abundant information of material composition and molecular structure, can be used for the quantitative measurement of component content.Containing hydrogen group has very strong absorption to light wave, through the near infrared spectrum of scanning samples, can obtain the characteristic information of adenosine group in the sample, is used for the quantitative of adenosine.
In the step (1); Described cordyceps can (comprise separate sources bacterial classification such as cordyceps sinensis (Berk) sacc for artificial ferment cordyceps sinensis bacterium filament; Paecilomyces hepiali Chen &Dai; Cephalosporiun sinensis.Chen.Sp.nov, Mortierella SP, Cordyceps militaris kind [Cordyceps militaris (L.Fr) Link]) through powder dry, that obtain after pulverizing; Also can for natural cs through powder dry, that obtain after pulverizing.Natural cs is different Chinese caterpillar fungus Pseudomonas fungies infect bat moth (Lepidoptera Hepialidae bat Hepialus insect) through variety of way a larva; Carry out parasitic life with the organic substance in its body as the nutrient energy source; Final mycelium kink and formation stroma stretch out host's shell, the biosome of a kind of special entomogenous fungi symbiosis of formation.Natural cs has been Duoed the composition of polypide than ferment cordyceps sinensis, but the content difference of the content of adenosine polypide in the different places of production is bigger, produces 0.3g/100g like Qinghai; 0.1g/100g is produced in Tibet; Sichuan product 0.2g/100g (Li Shaoping, Li Ping, Ji Hui etc. Acta Pharmaceutica Sinica, 2001,36 (6): 436-439), the concentration gradient that forms content is easier to quantitative modeling.
When adopting artificial fermentation's method; Described cordyceps is a fermentation cordyceps; Can prepare through following method: activated Chinese caterpillar fungus strain is inoculated into carries out fermented and cultured in the fluid nutrient medium; Separate obtaining mycelium after the fermented and cultured, mycelium obtains fermentation cordyceps after drying, pulverizing; Also the commercially available prod be can be, ferment cordyceps sinensis mycelium powder raw material, capsule preparations content, Cordyceps militaris mycelium powder etc. comprised.
Cordyceps sinensis is a kind of in the Chinese caterpillar fungus, and described fermentation cordyceps is preferably the fermentation Chinese caterpillar fungus bacterium powder; The fermentation Chinese caterpillar fungus bacterium powder of Zhongmei Huadong Pharmaceutical Co., Ltd. Hangzhou's production more preferably; This product is for separating the fungi asexual generation bacterial classification obtain through the mycelial dried powder of liquid fermentation and culture gained from fresh Cordyceps sinensis; Be to prepare through special fermentation, drying process; Mycelium and fermentation liquor are more thorough discretely, the higher and steady quality of active component content, and adenosine content difference is less.
The particle diameter of described cordyceps is preferably the 80-100 order, and the calibration model prediction effect of structure is better.
Sample size is big more, and the reliability of constructed model is high more; But crossing conference, sample size increases working strength.The quantity of described cordyceps sample is preferably more than 162.
In order to make up calibration model and to predict, can evenly extract total sample 2/3 as calibration set, all the other are remaining 1/3 as forecast set, and guarantee that the forecast set CONCENTRATION DISTRIBUTION is even, and scope is no more than calibration set.
The fermentation Chinese caterpillar fungus bacterium powder steady quality that Zhongmei Huadong Pharmaceutical Co., Ltd. Hangzhou produces, adenosine content difference is less between sample, and promptly the sample gradient is narrower, is unfavorable for model construction.But adopt method of the present invention, can obtain prediction effect model preferably.The maximal value of described cordyceps sample adenosine content and the difference between the minimum value can be more than 0.08%.
The method of measuring adenosine content can be high performance liquid chromatography, carries out according to the record in the Pharmacopoeia of the People's Republic of China 2000 version (two ones) " appendix V D high performance liquid chromatography ".
In the step (2), adopt ft-nir spectrometer when gathering near infrared spectrum; Preferably, adopt the multi-functional ft-nir spectrometer of MPA type, spectral range: liquid transmission, fibre-optical probe, integrating sphere (12800-4000cm
-1), solid passes through diffusion (12800-5700cm
-1), resolution: 2cm
-1(0.3nm 1,250nm place), wave number accuracy: be superior to 0.05cm
-1, wave number precision: be superior to 0.1cm
-1, transmittance precision: be superior to 0.1%T.Adopt this near infrared spectrometer, can gather 2203 wavelength information, be beneficial to modeling.
Gathered the influence that factors such as fashionable dress appearance difference, sample is inhomogeneous are brought in order to reduce spectroscopic data, described pre-service can be adopted one or more in level and smooth (S-G the is level and smooth) processing of Savitzky-Golay convolution, normalization (normalization) processing, polynary scatter correction (MSC), baseline correction (baseline) and the standard normal variable conversion (SNV).Can simplify, strengthen model through pre-service, wherein, the S-G smoothing processing comes down to a kind of method of weighted mean, is to eliminate the most frequently used a kind of method of noise; Normalization often is used to proofread and correct the spectrum change that is caused by small light path difference.MSC is mainly used in and eliminates the diffuse transmission influence that distribution of particles is inhomogeneous and grain size produces; Baseline correction is mainly used in the deduction instrumental background or drifts about to the influence of signal; The purpose of SNV and MSC is basic identical, mainly is to be used for eliminating the influence to spectrum of solid particle size, surface scattering and change in optical path length.
Preferably, Savitzky-Golay convolution smoothing processing is adopted in described pre-service.This preprocess method is adopted in evidence, and calibration model is best to the prediction effect of adenosine content in the sample.
Can adopt a kind of in PLS (PLS), PCA (PCR) and the artificial neural network method (ANN) when setting up calibration model.The present invention adopts described PLS can use full spectrum or partial spectrum data; And data matrix decomposes and recurrence is combined into a step alternately; The feature value vector that obtains is relevant with tested component or character; Rather than relevant with the variable of variation maximum in the data matrix, relatively be applicable to the small sample multivariate data analysis, can be used in complicated analysis system.
Set up in the PLS calibration model process, carry out validation-cross, when checking collection root-mean-square error (RMSEV) reaches minimum and r through leaving-one method
2Employed main gene number is considered to optimum during maximal value.They as input variable, are set up the PLS calibration model, predict.The foundation of calibration model can adopt Unscramber software to carry out.
Can adopt all band scanning when gathering near infrared spectrum data, the spectral scan wave band can be 12493.45-3999.91cm
-1(instrument parameter is 4000-12500cm
-1, be that the MPA instrument can collect full spectral limit parameter).In order effectively to select the wave band that includes characteristic information, improve arithmetic speed, can adopt related coefficient and regression coefficient combined techniques to carry out choosing of characteristic wave bands, characteristic wavelength choose the detection effect that can influence composition to be measured largely.
Correlation coefficient process is in polynary correction, and through the reflectivity vector that each wavelength is corresponding in the spectrum battle array is carried out correlation calculations with concentration vector to be measured, bigger its information of corresponding related coefficient is corresponding many more.Among the present invention, according to the PLS regression coefficient figure under all band, it is needed characteristic wavelength greater than 0.2 wavelength that adenosine content is set the related coefficient absolute value, and selected wave band is 8088.54-7286.24cm
-1, 4902.49-4817.64cm
-1And 4740.49-3999.91cm
-1
The regression coefficient method is in the index of regretional analysis metrics dependent variable to the interdependent degree of independent variable; It is multinomial coefficient or function parameters when the function through polynomial expression or other band parameter reaches the best-fit degree to independent variable and dependent variable, can select the higher wavelength of interdependent degree in view of the above.Among the present invention,, be 6 * 10 to the adenosine content setting threshold according to the PLS regression coefficient figure under all band
-5, selected wave band is 5126.21-4104.05cm
-1Wave band.
Characteristic wave bands when choosing the crossing part of these several spectrum ranges as modeling, the spectral scan wave band of promptly gathering near infrared spectrum is 4902.49-4817.64cm
-1And 4740.49-4107.91cm
-1Adopt this characteristic wave bands, can not only effectively improve prediction effect, and can significantly reduce the operand in the modeling, improve modeling speed, and foundation is provided for the exploitation of detecting instrument.
The quality of model performance is a standard with the accurate differentiation rate to the forecast set sample, can adopt prediction related coefficient (r), predicted root mean square error (RMSEP), remaining predicted deviation (RPD) evaluation model performance.The r value is high more, and the RMSEP value is more little, explains that model performance is good more; The RPD value is the ratio of chemical score standard deviation and RMSEP, and its value is considered to high value and the low value that model can be distinguished variable between 1.5～2.0, shows 2.0～2.5 and can carry out quantitative forecast, surpasses 2.5 and shows that good precision of prediction is arranged.
The factor number of described calibration model adopts the leaving-one method cross validation, i.e. get one of them variable in the process of modeling at every turn and be used as checking, remaining modeling.
In the step (3), described near infrared spectra collection and preprocess method can be with reference to the associative operations in the step (2).
The present invention adopts near-infrared spectrum analysis to combine stoichiometry to learn a skill adenosine content in the cordyceps have been carried out quantitative test, with the Savitzky-Golay smoothing processing near infrared spectrum has been carried out pre-service, and choose 4902.49-4817.64cm
-1And 4740.49-4107.91cm
-1Two characteristic wave bands have been set up the PLS regression model.
The inventive method is applicable to the sample that concentration gradient is narrow, carries out modeling through selected characteristic wave bands, and operand is little in the modeling process, and modeling speed is fast; And the PLS regression model validity of being set up is good, reliability is high, and is good to the prediction effect of adenosine content in the sample to be tested, can realize quick, accurate, Non-Destructive Testing to adenosine content in the cordyceps.The inventive method can realize the integrated management of analysis data and the real-time monitoring of production run through integrating with Process Control System; Spectral instrument through optical fiber joint detection probe, can be used for the real-time detection of sample in the fermentation cordyceps production run in conjunction with this method, for the near infrared online detection in the production practices lays the foundation.
Description of drawings
Fig. 1 is a full spectrum samples averaged spectrum curve map among the embodiment 1;
Fig. 2 is adenosine regression coefficient and related coefficient figure among the embodiment 1, and wherein, figure (a) is adenosine PLS regression coefficient figure, and figure (b) is the related coefficient figure of adenosine;
Fig. 3 is a full spectrum samples averaged spectrum curve map among the embodiment 2.
Embodiment
Adenosine content detects in the embodiment 1 fermentation Chinese caterpillar fungus bacterium powder
1, specimen preparation
162 fermentations of random collecting Chinese caterpillar fungus bacterium powder sample is used to set up whole data set.More representative and the diversity for the sample that makes collection, the different batches that sample provides from Zhongmei Huadong Pharmaceutical Co., Ltd. Hangzhou respectively (20 batches) fermentation Chinese caterpillar fungus bacterium powder makes institute's established model have better adaptability and robustness.Sample is preserved with the temperature of (4 ± 1 ℃); Each sample is placed in the unified plastic package bag, and whole experiment is carried out under room temperature 18-20 ℃.
2, adopt the chemical gauging adenosine content
Carry out according to the Pharmacopoeia of the People's Republic of China 2000 version (two ones) " appendix V D high performance liquid chromatography "; Measured value is the content value (g) in the 100 gram samples.Measure the result and see table 1.
Sort 2/3 (amounting to 108) that the back evenly extracts gross sample as calibration set according to the adenosine measured value, all the other be left 1/3 as forecast set, guarantee that the forecast set CONCENTRATION DISTRIBUTION is even, and scope is no more than calibration set.
The adenosine content of table 1 modeling collection and forecast set (g/100g)
3, based on full wave PLS (PLS) modeling
The multi-functional ft-nir spectrometer of MPA type (BRUKER, Germany), spectral range: liquid transmission, fibre-optical probe, integrating sphere (12800-4000cm
-1), solid passes through diffusion (12800-5700cm
-1), resolution: 2cm
-1(0.3nm 1,250nm place), wave number accuracy: be superior to 0.05cm
-1, wave number precision: be superior to 0.1cm
-1, transmittance precision: be superior to 0.1%T.All stoichiometry analytic approachs are carried out by Unscrambler version 9.6 (CAMO PROCESS AS, Norway) and MATLAB 7.1 (The Math Works, Natick, the U.S.).OPUS 5.5 softwares (BRUKER, Germany).
(1) spectral measurement and chemometrics application
The spectrum of each sample is the mean value of continuous 32 scannings.The spectral absorption value of all samples is averaged, obtain the curve of spectrum as shown in Figure 1.The one-level frequency multiplication of N-H key stretching vibration generally appears at 6666cm
-1Near, the combination frequency of stretching vibration and flexural vibrations is at 4650cm
-1Near.The one-level frequency multiplication of c h bond vibration appears at 6250-5555cm
-1Between, the secondary frequency multiplication is at 9090-8333cm
-1Between, first makes up the present 5000-4160cm that occurs frequently
-1Between, bands of a spectrum strong (Chu Xiaoli. chemometrics method and Molecular Spectral Analysis technological [M]. the .2011.7:1259-307 of Chemical Industry Press).Use following 5 kinds of preprocessing procedures, comprise Savitzky-Golay smoothing processing (S-G smoothing processing), normalization processing (normalization), polynary scatter correction (MSC), baseline calibration (baseline) and variable standardization (SNV).
(2) all band modeling
After pre-service, set up the PLS model of spectroscopic data and fermentation Chinese caterpillar fungus bacterium powder adenosine content.
The full spectrum PLS of adenosine content model result in the table 2 fermentation Chinese caterpillar fungus bacterium powder
Adenosine just can reach comparatively desirable predicting the outcome without any processing; (WANG Di such as this and Wang Di; ZHANG Yuan-li; MENG Qin-fan.Acta Optica Sinica, 2009 (10): 2795-2799.) the observed result of content of effective is consistent in the fast measuring Cordyceps militaris.The spectrum pre-service does not only have to improve to decrease on the contrary to the adenosine content prediction effect; Such reason as a result occurs and be likely less because of the content of adenosine in the fermentation cordyceps; Its functional group is not very strong to the response of spectrum, has weakened Useful Information after the pre-service on the contrary.
4, based on PLS (PLS) modeling of characteristic wave bands
The MPA spectrometer is gathered altogether has 2203 wavelength information, in order effectively to select the wave band that includes characteristic information, improves arithmetic speed, adopts regression coefficient and related coefficient combined techniques, carries out choosing of characteristic wave bands.
Can obtain the PLS regression coefficient figure (see the figure a Fig. 2, v is a wave number, and Reg is a related coefficient) of adenosine from all band modeling, at wave number 4107.91-3999.91cm
-1And 9025.83-12493.45cm
-1Noise is bigger in these two wave bands, does not choose the wavelength in these two wave bands.According to regression coefficient figure, be 6 * 10 to the adenosine setting threshold
-5, selected wave band is 5126.21-4104.05cm
-1Wave band.
In Matlab, adenosine content is carried out correlation analysis, obtain related coefficient figure (see the figure b among Fig. 2, v is a wave number, and Rel is a related coefficient).According to result of calculation, it is needed characteristic wavelength greater than 0.2 wavelength that adenosine content is set the related coefficient absolute value, knows that by figure have 3 spectrum ranges to meet this setting threshold, they are respectively 8088.54-7286.24cm
-1, 4902.49-4817.64cm
-1And 4740.49-3999.91cm
-1
Characteristic wave bands when only choosing part that these several spectrum ranges intersect and being modeling is 4902.49-4817.64cm
-1And 4740.49-4107.91cm
-1Two wave bands are set up the PLS model, and it is listed like table 3 to predict the outcome.
Table 3 selects wavelength to carry out adenosine PLS model prediction result after the different pre-service
Concerning the adenosine original spectrum, use characteristic wavelength modeling effect is more effective than all band modeling.The same with all band modeling is just can reach comparatively desirable predicting the outcome without any pre-service, and the level and smooth pre-service of process Savitzky-Golay convolution to be with close without any pretreated prediction effect.
After utilizing adenosine selected characteristic wavelength to set up the PLS model; No matter whether adopt pre-service; Its prediction effect all has raising in various degree than all band PLS model: (r=0.7882, RMSEP=0.000134 RPD=1.6407) bring up to (r=0.8290 to the optimum during by all band; RMSEP=0.001250, RPD=1.8476).
Adenosine content detects in embodiment 2 fermentation cordyceps
1, specimen preparation
162 fermentation cordyceps samples of random collecting are used to set up whole data set.Sample is respectively from Jiangxi Guoyao Co.,Ltd and Changxing Pharmaceutical Co., Ltd's different batches (20 batches) fermentation cordyceps.Sample experiment condition and preservation are all with reference to embodiment 1.
2, adopt the chemical gauging adenosine content
The mensuration of calibration set and forecast set setting, adenosine is measured the result and is seen table 4 all with reference to embodiment 1.
The adenosine content of table 4 modeling collection and forecast set (g/100g)
3, utilize the characteristic wave bands of selecting to carry out PLS (PLS) modeling
Near infrared spectroscopy instrument and use software are all with reference to embodiment 1.
(1) spectral measurement and chemometrics application
The spectrum of each sample is the mean value of continuous 32 scannings.The spectral absorption value of all samples is averaged, obtain the curve of spectrum as shown in Figure 3.
(2) characteristic wave bands modeling
Utilize characteristic wave bands that spectrum is not carried out pre-service and pre-service respectively and set up the PLS model, utilize same characteristic features wave band 4902.49-4817.64cm among the embodiment 1
-1And 4740.49-4107.91cm
-1Two wave bands are set up the PLS model of spectroscopic data and fermentation cordyceps adenosine content.
Table 5 selects wavelength to carry out adenosine PLS model prediction result after the different pre-service
After utilizing the selected characteristic wavelength of adenosine to set up the PLS model, no matter whether adopt pre-service, its prediction effect is all fine: optimum be (r=0.9743, RMSEP=0.01234, RPD=6.2391).Explain that this characteristic wave bands is applicable to the prediction of adenosine content in the fermentation cordyceps.
Claims (9)
1. cordyceps adenosine content method for quick comprises:
(1) gets the cordyceps sample, measure adenosine content;
(2) gather the near infrared spectrum of cordyceps sample and carry out pre-service, adopt PLS to set up the calibration model between the adenosine content and pretreated near infrared spectrum in the cordyceps sample;
(3) gather the near infrared spectrum of sample to be tested and carry out pre-service, calculate the adenosine content of sample to be tested through calibration model;
Wherein, the spectral scan wave band of collection near infrared spectrum is 4902.49-4817.64cm
-1And 4740.49-4107.91cm
-1
2. cordyceps adenosine content method for quick according to claim 1 is characterized in that described cordyceps is a fermentation cordyceps.
3. cordyceps adenosine content method for quick according to claim 2 is characterized in that, described cordyceps is the fermentation Chinese caterpillar fungus bacterium powder.
4. cordyceps adenosine content method for quick according to claim 1 is characterized in that the particle diameter of described cordyceps is the 80-100 order.
5. cordyceps adenosine content method for quick according to claim 1 is characterized in that the quantity of described cordyceps sample is more than 162.
6. cordyceps adenosine content method for quick according to claim 5 is characterized in that the maximal value of described cordyceps sample adenosine content and the difference between the minimum value are more than 0.08%.
7. cordyceps adenosine content method for quick according to claim 1 is characterized in that, in the step (1), the method for measuring adenosine content is a high performance liquid chromatography.
8. cordyceps adenosine content method for quick according to claim 1; It is characterized in that; In step (2) or (3), one or more in Savitzky-Golay convolution smoothing processing, normalization processing, polynary scatter correction, baseline correction and the standard normal variable conversion are adopted in described pre-service.
9. cordyceps adenosine content method for quick according to claim 8 is characterized in that, Savitzky-Golay convolution smoothing processing is adopted in described pre-service.
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| CN103558161A (en) * | 2013-11-12 | 2014-02-05 | 劲牌有限公司 | Near infrared detection method for cordycepic acid content of cordyceps sinensis |
| CN103868914A (en) * | 2014-02-17 | 2014-06-18 | 南昌大学 | Aptamer-based method for detecting adenosine through nanogold and hydroxylamine amplification chemiluminiscence |
| CN103983605A (en) * | 2014-05-28 | 2014-08-13 | 河北大学 | Method for rapidly and nondestructively detecting sporoderm-breaking rate of reishi shell-broken spore powder |
| CN105334186A (en) * | 2015-12-10 | 2016-02-17 | 山东大学 | Infrared spectral analysis method |
| CN108872135A (en) * | 2018-08-31 | 2018-11-23 | 天津科技大学 | A method of utilizing polymalic acid content near infrared ray fermentation liquid |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103558161A (en) * | 2013-11-12 | 2014-02-05 | 劲牌有限公司 | Near infrared detection method for cordycepic acid content of cordyceps sinensis |
| CN103868914A (en) * | 2014-02-17 | 2014-06-18 | 南昌大学 | Aptamer-based method for detecting adenosine through nanogold and hydroxylamine amplification chemiluminiscence |
| CN103983605A (en) * | 2014-05-28 | 2014-08-13 | 河北大学 | Method for rapidly and nondestructively detecting sporoderm-breaking rate of reishi shell-broken spore powder |
| CN103983605B (en) * | 2014-05-28 | 2016-04-13 | 河北大学 | A kind of method of Fast nondestructive evaluation ganoderma spove powder sporoderm-broken rate |
| CN105334186A (en) * | 2015-12-10 | 2016-02-17 | 山东大学 | Infrared spectral analysis method |
| CN108872135A (en) * | 2018-08-31 | 2018-11-23 | 天津科技大学 | A method of utilizing polymalic acid content near infrared ray fermentation liquid |
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