CN105181637A - Method for rapidly determining content of quality indexes of red ginseng by using near infrared diffuse reflection spectrum - Google Patents
Method for rapidly determining content of quality indexes of red ginseng by using near infrared diffuse reflection spectrum Download PDFInfo
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Abstract
The invention discloses a method for rapidly determining the respective content of water, carbohydrate components and ginsenoside of red ginseng by using a near infrared diffuse reflection spectrum. The method comprises the following steps: carrying out a routine analysis process to obtain the references of all quality control index components in red ginseng samples and obtain near infrared spectrum data of all red ginseng powder samples, carrying out mathematical modeling to make all the routine analysis references of the index components and the near infrared spectrum data compose a database, and carrying out modeling optimization by using a full factor test analysis process to respectively obtain quantitative correction models of all the indexes; and collecting the near infrared spectrum of an unknown red ginseng powder sample, and determining the content of every index component by using the quantitative correction models. The method has the characteristics of rapid and simple analysis, no pollution in the analysis process, and simultaneous determination of various index components, and allows whether sugar is added or not to be rapidly discriminated especially through determining the carbohydrate components in order to maximally guarantee the quality of the red ginseng.
Description
Technical field
The present invention relates to medicine analysis detection field, be specifically related to the content utilizing the multiple red ginseng powder quality index of near-infrared diffuse reflection spectrum Rapid Simultaneous Determination.
Background technology
The quality index of Chinese Pharmacopoeia (2010 editions) red ginseng is mainly moisture and ginsenoside Rg1, Re and Rb1, and wherein moisture adopts the method for loss on drying to detect, and the method is more time-consuming; The detection of ginsenoside adopts high performance liquid chromatography, and the method sample pre-treatments relates to the steps such as surname extraction, ultrasonic extraction, evaporate to dryness, redissolution, and whole analytic process is more loaded down with trivial details; The organic solvent used in simultaneously analyzing can be unfavorable for the health of human body to environment.
It is simple that near infrared spectroscopic method has sample pre-treatments, and analyzing the advantages such as quick, is the free of contamination analytical approach of a kind of environmental protection.At present, there are reports both at home and abroad starts trial near-infrared spectrum technique and carries out fast mass evaluation to red ginseng, but the index analyzed is often more single, the overall inherent quality of red ginseng can not be reflected effectively all sidedly, such as the simply qualitative True-false distinguish that carries out (is applied near-infrared spectrum technique and is differentiated red ginseng medicinal material, Chinese herbal medicine, 2008, 39 (3): 428-440), determination of moisture is (a kind of based near infrared red ginseng quality of medicinal material fast appraisement method, Chinese herbal medicine, 2005, 36 (6): 912-915), measuring content of ginsenoside (DevelopmentofNearInfraredSpectroscopyforRapidQualityAsse ssmentofRedGinseng, CHEM.RES.CHINESEUNIVERSITIES2009, 25 (5), 633-637).
In addition, because current Chinese Pharmacopoeia does not carry out quality control to red ginseng carbohydrate content, the phenomenon of therefore mixing sugar (particularly sucrose) in the market in red ginseng is general, has had a strong impact on the quality of red ginseng raw material and relevant final product.The analytical approach of traditional carbohydrate content is mainly chemical staining method, high performance liquid chromatography etc., but there is the problems such as sample pre-treatments complexity, com-parison and analysis be time-consuming equally.
Summary of the invention
In order to overcome the single problem of the time-consuming, loaded down with trivial details of traditional analysis and pollution problem, existing near infrared spectroscopy index components and the carbohydrate content content problem that cannot effectively control at present, the invention provides a kind of method of near-infrared diffuse reflection spectrum Rapid Simultaneous Determination red ginseng moisture, carbohydrate content and content of ginsenoside, described method mainly comprises the steps:
(1) detection method specified according to red ginseng quality standard in Chinese Pharmacopoeia (2010 editions) detects moisture, content of ginsenoside in the red ginseng sample of different batches, and detects total sugar content by high performance liquid chromatography; Described total sugar content refers to the total content of sucrose and maltose in red ginseng pressed powder; Described content of ginsenoside comprises the total content of Rg1 and Re and the content of Rb1 in red ginseng drying solid powder;
(2) above-mentioned red ginseng sample is carried out near-infrared diffuse reflection spectrum detection respectively, the scanning wavelength scope of near-infrared diffuse reflection spectrum is respectively 10000-4000cm
-1and 10000-4250cm
-1two wave bands, obtain the near infrared spectrum data of 2 wave bands of every increment product, the moisture of the different samples that step (1) measures, content of ginsenoside, total sugar content forms the moisture database of 2 wave bands respectively with the near infrared spectrum data of its 2 wave bands respectively, the ginsenoside Rg_1 and Re total content database of 2 wave bands, ginsenoside Rb1's content data storehouse of 2 wave bands, the total sugar content database of 2 wave bands, then Pretreated spectra and regression modeling is carried out respectively, preprocessing procedures has three kinds: multiplicative scatter correction (MSC), standard normal variable change (SNV) or first order derivative (1-Der), regression model has three kinds of methods: partial least squares regression (PLSR), principal component regression (PCR) or multiple linear regression (MLR) method, total divisor analysis of experiments method is adopted to each database, namely each database adopts different preprocessing procedures and regression model, modeling 9 times respectively, Unscrambler software (9.8 editions) is used to carry out the foundation of model, obtain 18 moisture model group, 18 Rg1 and Re total content model group, 18 Rb1 content model group, 18 total sugar content model group respectively, with the coefficient of determination (R
2) and correct mean square deviation (RMSECV) be model-evaluation index, choose R in each model group respectively
2closest to 1 and RMSECV closest to the model of 0, obtain quantitative correction moisture model, quantitative correction Rg1 and Re total content model, quantitative correction Rb1 content model and quantitative correction total sugar content model, quantitative correction moisture model, quantitative correction Rg1 and Re total content model, quantitative correction Rb1 content model and quantitative correction total sugar content model are set with specific wavelength band, preprocessing procedures and regression modeling method respectively separately,
(3) get unknown red ginseng sample, carry out near-infrared diffuse reflection spectrum detection according to step (2) similarity condition, the scanning wavelength scope of near-infrared diffuse reflection spectrum is respectively 10000-4000cm
-1and 10000-4250cm
-1two wave bands, obtain the near infrared spectrum data of 2 wave bands of unknown sample, then according to the wavelength band set respectively in quantitative correction moisture model, quantitative correction Rg1 and Re total content model, quantitative correction Rb1 content model and quantitative correction total sugar content model, the near infrared spectrum data of corresponding wave band is inputted in Unscrambler software 9.8 editions, calculate according to respective quantitative calibration models, obtain the moisture of unknown red ginseng sample, Rg1 and Re total content, Rb1 content and total sugar content.
In described step (1), the detection method that moisture and content of ginsenoside specify according to red ginseng quality standard in Chinese Pharmacopoeia (2010 editions) detects, wherein moisture dry weight-loss method measures, generally measure according to Chinese Pharmacopoeia 2010 editions one annex Ⅸ H first method, content of ginsenoside high performance liquid chromatography measures, and can measure according to the regulation in the assay item in Chinese Pharmacopoeia 2010 editions red ginseng quality standards;
Total sugar content high performance liquid chromatography measures.
Described red ginseng sample includes but not limited to: whole red ginseng, go must red ginseng, red ginseng ginseng must, red ginseng reed is first-class.
Described red ginseng sample is red ginseng fine powder, is generally the powder of No. six sieves.
In described step (1), the red ginseng sample of different batches at least chooses 20, preferably 50 ~ 200.
In described step (2), the condition that near-infrared diffuse reflection spectrum detects is generally: detected temperatures is 23 ~ 27 DEG C, and detecting humidity is 50 ~ 60%, and spectral scan scope is 10000-4000cm
-1and 10000-4250cm
-1two wave bands, generally can scan 10000-4000cm
-1wave band, then chooses 10000-4000cm respectively
-1and 10000-4250cm
-1the data of two wave bands.The scanning times that instrument single detects is 32 times, resolution 8cm
-1.General each sample duplicate detection three times, takes from the near infrared spectrum data of the dynamic average spectral data generated as sample.
Described each database adopts total divisor analysis of experiments method, namely each database adopts different preprocessing procedures and regression model, modeling 9 times respectively, this refers to and preprocessing procedures and regression model is divided into 2 factors, for each factor, preprocessing procedures has 3 kinds of levels, i.e. multiplicative scatter correction (MSC), standard normal variable change (SNV) or first order derivative (1-Der); Regression model also has 3 kinds of levels, i.e. partial least squares regression (PLSR), principal component regression (PCR) and multiple linear regression (MLR) method, then according to total divisor test method(s), each database needs modeling 3
2secondary, namely 9 times.
The invention has the beneficial effects as follows, compare with traditional conventional method of analysis, application near infrared spectrum can realize more quick, easy, free of contamination analysis in conjunction with mathematical modeling; Single different from existing red ginseng near-infrared analysis index, the NIR Analysis that the present invention sets up can carry out assay to sample moisture, ginsenoside and carbohydrate content simultaneously.By the Simultaneously test to carbohydrate content, whether can also mix sugar by rapid identification sample, thus ensure red ginseng quality most possibly.In addition, use multiple index quick detecting method provided by the invention, effectively can solve the representative not enough problem of pharmaceutical manufacturer's production scene red ginseng raw material pick test, ensure finished product quality further.
Accompanying drawing explanation
Fig. 1 is the near-infrared diffuse reflection spectrum figure of 60 red ginseng fine powder samples.
Fig. 2 is moisture quantitative calibration models predicted value and actual value correlogram.
Fig. 3 is total sugar content quantitative calibration models predicted value and actual value correlogram.
Fig. 4 is ginsenoside Rg_1 and Re total content quantitative calibration models predicted value and actual value correlogram.
Fig. 5 is ginsenoside Rb1's content quantitative calibration model predicted value and actual value correlogram.
Embodiment
Describe the present invention in detail below in conjunction with embodiment, this embodiment should not be construed as limitation of the present invention.
Embodiment 1: red ginseng raw material near infrared Fast Measurement
Red ginseng is the important composition of multiple Chinese patent drug and other Related products as bulk drug, and only the quality of guaranteed bulk drug just can guarantee the safe and reliable of final products, and therefore the detection of bulk drug is most important.The detection of pharmaceutical manufacturer's traditional raw material medicine is normally extracted sample segment and is carried out conventional chemical analysis, and there is the representative not enough problem of pick test, be difficult to the quality ensureing all batches, conventional method of analysis is simultaneously usual also more loaded down with trivial details time-consuming.Near infrared spectroscopy can address these problems well, realizes the quick detection to all batch sample.
Set up the method for each index content of near-infrared diffuse reflection spectrum Rapid Simultaneous Determination red ginseng, mainly comprise the steps:
1, the foundation of near infrared correction:
(1) red ginseng preparation of samples
Get the red ginseng fine powder totally 60 parts (all red ginseng samples are provided by Zhengda Qingchunbao Pharmaceutical Co., Ltd) produced with different lot number.
(2) near infrared spectra collection
Get each red ginseng fine powder sample and join (sample accounts for the half of vial volume) in 50mL vial in right amount respectively, use the silent portable fiber-optic collected specimens near infrared spectrum flying AntarisMX Fourier near infrared spectrometer of match.Near infrared spectrometer start preheating is after 1 hour, inserted by portable fiber-optic in sample powder, the Result software supporting with instrument carries out near-infrared diffuse reflection spectrum collection, and detected temperatures is 23 ~ 27 DEG C, detecting humidity is 50 ~ 60%, and spectral scan scope is 10000 to 4000cm
-1, each detection scanning times is 32 times, resolution 8cm
-1.Each sample detects three times automatically, takes from the dynamic averaged spectrum generated and carries out modeling.The red ginseng fine powder near-infrared diffuse reflection spectrum of 60 samples as shown in Figure 1.
(3) each index components conventional method of analysis measures
The content of moisture measures according to Chinese Pharmacopoeia 2010 editions one annex Ⅸ H first method.Get test sample 2g, be laid in and be dried in the flat measuring cup of constant weight, accurately weighed, open bottle cap 100 ~ 105 DEG C of dryings 5 hours, bottle cap is built, in dislocation exsiccator, cool 30 minutes, accurately weighed, again said temperature drying 1 hour, cooling, weighs, to double difference of weighing is no more than 5mg.According to the weight of less loss, calculate water cut (%) in test sample
Ginsenoside measures according to the assay item in Chinese Pharmacopoeia 2010 editions red ginseng quality standards.Get this product powder and be about 1g, accurately weighed, put in apparatus,Soxhlet's, add methenyl choloride appropriate, add hot reflux 3 hours, discard methenyl choloride liquid, the dregs of a decoction volatilize solvent, move in tool plug conical flask together with filtration paper cylinder, precision adds water-saturated n-butanol 50ml, close plug, placement is spent the night, ultrasonic process (power 250W, frequency 50kHz) 30 minutes, filters.Precision measures subsequent filtrate 25ml, puts evaporate to dryness in evaporating dish, and residue adds methyl alcohol and dissolves, and is transferred in 5ml measuring bottle, adds methyl alcohol to scale, shake up, and filters, gets subsequent filtrate, obtain test sample.Accurate absorption reference substance solution 10 μ L and need testing solution 20 μ L respectively, injection liquid chromatography, measures content.
Ginsenoside Rg1's reference substance, ginsenoside Re's reference substance, ginsenoside Rb1's reference substance are got in the preparation of reference substance solution respectively, add methyl alcohol and make the mixed solution containing ginsenoside Rg1 0.5mg, ginsenoside Re 0.3mg, ginsenoside Rb1 0.5mg in every 1ml, to obtain final product.
[assay] measures according to " high performance liquid chromatography test stone running program ".
Chromatographic condition and system suitability take octadecylsilane chemically bonded silica as filling agent; Be mobile phase A with acetonitrile, take water as Mobile phase B, the regulation according to the form below carries out gradient elution; Determined wavelength is 203nm.Number of theoretical plate calculates should be not less than 6000 by ginsenoside Rg1 peak.
Table 1:
The assay method of carbohydrate content is specific as follows: get 0.5g red ginseng fine powder, be placed in 50mL conical flask, add 30mL purified water, slight wobble makes powder dispersion open, ultrasonic extraction 30min, pause 10min, slight wobble, more ultrasonic 15min, the then centrifugal rear 0.45um membrane filtration mistake of extract, get subsequent filtrate, obtain total reducing sugar extract, accurately take sucrose and maltose reference substance (in phosphorus pentoxide vacuum drying apparatus dry more than 12 hours) appropriate, add water and make the reference substance solution of every 1ml containing sucrose 7mg and maltose 3mg, shake up, be diluted to the hybrid standard product solution of a series of concentration, analyze with Agilent1200 liquid chromatograph, chromatographic column is AlltechPrevailCarbohydrateES5u (4.6 × 250mm), mobile phase is acetonitrile-aqueous solution (75:25, V/V), flow velocity is 1.0ml/min, column temperature remains on 25 DEG C, detecting device is evaporative light-scattering detector, each sample feeding amount is 10uL, measure the sucrose in variable concentrations hybrid standard product solution and maltose content, obtain the typical curve of sucrose and maltose respectively, sucrose and maltose content in the liquid chromatographic detection total reducing sugar extract of then similarity condition, with standard curve control, calculate sucrose and maltose content in red ginseng sample.
The content statistics of all 60 parts of each index components of red ginseng fine powder sees the following form 2:
Table 2
| Index components | Minimum value (%) | Maximal value (%) | Mean value (%) | Standard deviation (%) |
| Water | 4.44 | 8.28 | 6.41 | 0.84 |
| Sucrose | 5.06 | 35.23 | 22.84 | 10.36 |
| Maltose | 0.60 | 22.26 | 6.71 | 3.74 |
| Total reducing sugar | 14.77 | 40.07 | 29.55 | 7.91 |
| Rg1 | 0.11 | 0.46 | 0.22 | 0.10 |
| Re | 0.18 | 1.20 | 0.30 | 0.19 |
| Rg1+Re | 0.30 | 1.59 | 0.52 | 0.26 |
| Rb1 | 0.34 | 1.55 | 0.56 | 0.23 |
(4) model is set up
All 60 parts of red ginseng fine powder samples are divided into two groups at random, and wherein one group of 50 increment product is as calibration set, for the foundation of calibration model; As test set, the model set up is verified and evaluated for other one group 10 parts.The parameter of Optimized model mainly comprises the selection of wavelength coverage, preprocessing procedures and regression model, mutually has impact between these parameters, therefore needs systematically to optimize.Its medium wavelength range paper examines 10000-4000cm
-1and 10000-4250cm
-1two wave bands because for gather near infrared spectrum optical fiber this in 4250-4000cm
-1there is certain absorption, therefore need the absorption investigating optical fiber whether to have impact to model; Every increment product are divided into the near infrared spectrum data of 2 wave bands to analyze.
Uneven or the particulate interspaces of red ginseng fine particle size can cause scattering phenomenon, and Pretreated spectra is mainly used for eliminating near infrared spectrum baseline wander because scattering phenomenon causes and noise signal thus improves accuracy and the stability of model.
By the moisture of the calibration set sample that step (3) measures, content of ginsenoside, total sugar content forms the moisture database of 2 wave bands respectively with the near infrared spectrum data of each sample 2 wave bands respectively, the ginsenoside Rg_1 and Re total content database of 2 wave bands, ginsenoside Rb1's content data storehouse of 2 wave bands, the total sugar content database of 2 wave bands, then Pretreated spectra and regression modeling is carried out respectively, preprocessing procedures comprises multiplicative scatter correction (MSC), standard normal variable change (SNV) or first order derivative (1-Der), regression model adopts partial least squares regression (PLSR), principal component regression (PCR) or multiple linear regression (MLR) method, total divisor analysis of experiments method is adopted to each database, namely each database adopts different preprocessing procedures and regression model, modeling 9 times respectively, Unscrambler software (9.8 editions) is used to carry out the foundation of model, obtain 18 moisture model group, 18 Rg1 and Re total content model group, 18 Rb1 content model group, 18 total sugar content model group respectively, with the coefficient of determination (R
2) and correct mean square deviation (RMSECV) be model-evaluation index, choose R in each model group respectively
2closest to 1 and RMSECV closest to the model of 0, obtain quantitative correction moisture model, quantitative correction Rg1 and Re total content model, quantitative correction Rb1 content model and quantitative correction total sugar content model, quantitative correction moisture model, quantitative correction Rg1 and Re total content model, quantitative correction Rb1 content model and quantitative correction total sugar content model are set with specific wavelength band, preprocessing procedures and regression modeling method respectively separately,
Through systematically optimizing, finally determine that the modeling conditions of each index components is as shown in table 3 below:
Table 3
The quantitative calibration models of moisture, total sugar content, ginsenoside Rg_1 and Re total content, Determination of Content of Ginsenoside Rg_1 is shown in Fig. 2 ~ 5 respectively.Fig. 2-5 shows the actual value of calibration set sample and the correlativity figure of predicted value that participate in modeling.
2, the mensuration of each index components content in red ginseng sample:
Unscrambler software is used to be inputed to by the near infrared spectrum of the sample of 10 parts of test sets in the quantitative calibration models of each index components, then the near infrared spectrum data of corresponding wave band is inputted according to the wavelength band set respectively in each quantitative calibration models, calculate according to respective quantitative calibration models, predict the content of each index components, and will predict the outcome and to compare with actual value, concrete outcome sees the following form 4:
Table 4
Predicting the outcome of 10 parts of each index components of red ginseng fine powder sample is substantially close with actual value, and overall prediction relative deviation is about 10%, and prediction effect is better.Result illustrates that can substitute loaded down with trivial details time-consuming conventional method carries out quality assessment with fast and convenient near infrared spectroscopy to red ginseng raw material, and this evaluation result has higher confidence level.
Embodiment 2: the red ginseng sample near infrared Fast Measurement of Different sources and different parts
Current Chinese Pharmacopoeia does not carry out quality control to red ginseng carbohydrate content, and the phenomenon of therefore mixing sugar (particularly sucrose) in the market in red ginseng gets more and more, and has had a strong impact on the quality of red ginseng raw material and relevant final product.Example of the present invention collects the red ginseng totally 8 parts in 4 places of production, wherein comprises sample that is possible sugary and sugar-free, with each index components content of near infrared Fast Measurement; Have collected separately red ginseng reed head and ginseng palpus each 1 part of sample in addition, with each index components content of near infrared Fast Measurement sample.
1, the foundation of near infrared correction: with embodiment 1; Adopt the quantitative calibration models of embodiment 1.
2, the mensuration of each index components content in red ginseng sample:
(1) red ginseng sample preparation
Collect 8 parts, red ginseng sample altogether from 4 Different sources, comprise 2 parts, the place of production, Jingyu, wherein 1 part is denoted as sugar-free; Totally 4 parts, the ten thousand good places of production, wherein 1 part is denoted as sugar-free, and other 3 parts are denoted as a, b, c respectively; 1 part, the place of production, Jian, is denoted as sugar-free; Prolong 1 part, the place of production, limit, be denoted as sugar-free.Red ginseng reed head and ginseng must each 1 part of samples in addition.
After red ginseng sample is cleaned, pulverize after drying at 40 DEG C, cross No. six sieves.Then get each red ginseng fine powder sample and join (sample accounts for the half of vial volume) in 50mL vial in right amount respectively, use the silent portable fiber-optic collected specimens near infrared spectrum flying AntarisMX Fourier near infrared spectrometer of match.Near infrared spectrometer start preheating is after 1 hour, inserted by portable fiber-optic in sample powder, the Result software supporting with instrument carries out near-infrared diffuse reflection spectrum collection, and detected temperatures is 23 ~ 27 DEG C, detecting humidity is 50 ~ 60%, and spectral scan scope is 10000 to 4000cm
-1, it is 32 times that single detects scanning times, resolution 8cm
-1.Each sample detects three times automatically, takes from the dynamic averaged spectrum generated and analyzes.
(2) index components content prediction verifying
Use Unscrambler software to be inputed in each index components quantitative calibration models by the near infrared spectrum of above-mentioned 10 parts of red ginseng samples, predict the content of each index components; Meanwhile, use conventional method of analysis measure the actual value of each index components and compare with predicted value, concrete outcome sees the following form 5:
Table 5
The overall prediction effect of all 10 increment product is better, and each index mean relative deviation is all within 10%; In the red ginseng in simultaneously visible 4 places of production, the sample total reducing sugar being denoted as sugar-free predicts the outcome and is starkly lower than other samples, and this method effectively can distinguish the height of sugared content in red ginseng sample.The content of the ginsenoside at red ginseng reed head and ginseng palpus position is apparently higher than main root part, and the index components of this method to these two positions predicts the outcome better, illustrates that this method is applicable to the mensuration of red ginseng each position index components content.
Claims (4)
1. a method for near-infrared diffuse reflection spectrum Rapid Simultaneous Determination red ginseng moisture, carbohydrate content and content of ginsenoside, is characterized in that described method comprises the steps:
(1) detection method specified according to red ginseng quality standard in Chinese Pharmacopoeia 2010 editions detects moisture, content of ginsenoside in the red ginseng sample of different batches, and detects total sugar content by high performance liquid chromatography; Described total sugar content refers to the total content of sucrose and maltose in red ginseng pressed powder; Described content of ginsenoside comprises the total content of Rg1 and Re and the content of Rb1 in red ginseng drying solid powder;
(2) above-mentioned red ginseng sample is carried out near-infrared diffuse reflection spectrum detection respectively, the scanning wavelength scope of near-infrared diffuse reflection spectrum is respectively 10000-4000cm
-1and 10000-4250cm
-1two wave bands, obtain the near infrared spectrum data of 2 wave bands of every increment product, the moisture of the different samples that step (1) measures, content of ginsenoside, total sugar content forms the moisture database of 2 wave bands respectively with the near infrared spectrum data of its 2 wave bands respectively, the ginsenoside Rg_1 and Re total content database of 2 wave bands, ginsenoside Rb1's content data storehouse of 2 wave bands, the total sugar content database of 2 wave bands, then Pretreated spectra and regression modeling is carried out respectively, preprocessing procedures has three kinds: multiplicative scatter correction, standard normal variable change or first order derivative, regression model has three kinds of methods: partial least squares regression, principal component regression or multiple linear regression analysis method, total divisor analysis of experiments method is adopted to each database, namely each database adopts different preprocessing procedures and regression model, modeling 9 times respectively, Unscrambler software 9.8 editions is used to carry out the foundation of model, obtain 18 moisture model group, 18 Rg1 and Re total content model group, 18 Rb1 content model group, 18 total sugar content model group respectively, with coefficient of determination R
2with correction mean square deviation RMSECV be model-evaluation index, choose R in each model group respectively
2closest to 1 and RMSECV closest to the model of 0, obtain quantitative correction moisture model, quantitative correction Rg1 and Re total content model, quantitative correction Rb1 content model and quantitative correction total sugar content model, quantitative correction moisture model, quantitative correction Rg1 and Re total content model, quantitative correction Rb1 content model and quantitative correction total sugar content model are set with specific wavelength band, preprocessing procedures and regression modeling method respectively separately,
(3) get unknown red ginseng sample, carry out near-infrared diffuse reflection spectrum detection according to step (2) similarity condition, the scanning wavelength scope of near-infrared diffuse reflection spectrum is respectively 10000-4000cm
-1and 10000-4250cm
-1two wave bands, obtain the near infrared spectrum data of 2 wave bands of unknown sample, then according to the wavelength band set respectively in quantitative correction moisture model, quantitative correction Rg1 and Re total content model, quantitative correction Rb1 content model and quantitative correction total sugar content model, the near infrared spectrum data of corresponding wave band is inputted in Unscrambler software 9.8 editions, calculate according to respective quantitative calibration models, obtain the moisture of unknown red ginseng sample, Rg1 and Re total content, Rb1 content and total sugar content.
2. the method for claim 1, it is characterized in that in described step (1), the detection method that moisture and content of ginsenoside specify according to red ginseng quality standard in Chinese Pharmacopoeia 2010 editions detects, wherein moisture dry weight-loss method measures, and content of ginsenoside high performance liquid chromatography measures;
Total sugar content high performance liquid chromatography measures.
3. the method for claim 1, is characterized in that, in described step (1), the red ginseng sample of different batches at least chooses 20.
4. the method for claim 1, is characterized in that in described step (2), and the condition that near-infrared diffuse reflection spectrum detects is: detected temperatures is 23 ~ 27 DEG C, and detecting humidity is 50 ~ 60%, and spectral scan scope is 10000-4000cm
-1and 10000-4250cm
-1two wave bands, the scanning times that instrument single detects is 32 times, resolution 8cm
-1, each sample duplicate detection three times, takes from the near infrared spectrum data of the dynamic average spectral data generated as sample.
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