CN109765200A - A kind of binary based near infrared spectrum and Chemical Measurement mixes pseudo- Radix Angelicae Sinensis quantitative analysis method - Google Patents
A kind of binary based near infrared spectrum and Chemical Measurement mixes pseudo- Radix Angelicae Sinensis quantitative analysis method Download PDFInfo
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Abstract
The present invention relates to a kind of binary based near infrared spectrum and Chemical Measurement to mix pseudo- Radix Angelicae Sinensis quantitative analysis method.The specific steps are first buy Radix Angelicae Sinensis and similar product it is several, the Radix Angelicae Sinensis for preparing certain amount mixes pseudo- sample；The near-infrared diffusing reflection spectrum of pseudo- sample is mixed in acquisition；Using KS packet mode, data set is divided into training set and forecast set；Determine Partial Least-Squares Regression Model because of subnumber；Again, the pretreating effect for investigating SG exponential smoothing, multiplicative scatter correction, standard normal variable, first derivative, second dervative, continuous wavelet transform and combinations thereof, obtains best preprocess method；Finally, mixing pseudo- Radix Angelicae Sinensis quantitative analysis to binary using best pretreatment-PLSR modeling method.It is fast and convenient the present invention is based near infrared spectrum and Chemical Measurement, lossless sample.The present invention is suitable for the quantitative analysis that binary mixes pseudo- Radix Angelicae Sinensis.
Description
Technical field
The invention belongs to the quantitative analysis tech of Analysis of Chinese Traditional Medicine field Radix Angelicae Sinensis, are related to a kind of based near infrared spectrum and chemistry
The binary of meterological mixes pseudo- Radix Angelicae Sinensis quantitative analysis method.
Background technique
When being classified as Umbellales umbelliferae, it is distributed mainly on high and cold rainy mountain area.Radix Angelicae Sinensis can not only replenishing and activating blood, and
And promoting menstruation dredging collateral, and it is widely used in all various aspects such as weak anaemia, asthenia cold abdominalgia, rheumatism paralysis, menstruction regulating and pain relieving.However due to medicine
The problems such as object scarcity of resources, drug price are higher and demand is big, it is commonplace to mix pseudo- phenomenon for Radix Angelicae Sinensis in market.Common Radix Angelicae Sinensis
Adulterant has Radix Angelicae Pubescentis, Rhizoma Chuanxiong, Rhizoma Atractylodis Macrocephalae etc., and form is approximate and is difficult to the naked eye distinguish, misuses that will lead to curative effect undesirable, or even meeting
Health of human body is threatened, therefore corresponding detection and identification technology is also come into being.
Common TCD identificafion method has chromatography, spectroscopic methodology, differential thermal analysis, random amplification DNA method, scanning electron microscope skill
Art and electrophoresis etc..Wherein, reproducibility is poor when thin-layered chromatography is simple and efficient but complicated component, ultraviolet spectroscopy high sensitivity
But some difficulties are distinguished to Chinese medicine similar in relationship.Near infrared spectrum (NIRS) technology has quick analysis, low cost, without dirt
Dye, being not necessarily to the advantages that pre-treatment and simultaneous determination of multiponents, (China, State of Zhao, Liu Jia, Zhao Qiushuan, the food based near infrared spectrum are mixed
False starch rapid assay methods and system, Chinese invention patent, 2014, CN201410271077.2).NIRS is able to reflect Chinese medicine
Whole difference between material system.Therefore, qualitative analysis is the important branch that NIRS is applied in the field of Chinese medicines, is answered extensively
The true and false for Chinese medicine identifies (Zang Hengchang, Zeng Yingzi, Nie Lei, Yang Hailong, Hu Tian, Yu Hongliang, based on NIR technology
The Radix Codonopsis true and false identify and the place of production determine method, Chinese invention patent, 2015, CN201510141871.X).
Due to the overlapping seriousness and discontinuity of atlas of near infrared spectra, so needing by polynary in Chemical Measurement
Bearing calibration carries out quantitative analysis.Multivariate calibration methods mainly have principal component regression (PCR), Partial Least Squares Regression (PLSR),
Artificial neural network (BP-ANN), support vector regression (SVR) and extreme learning machine (ELM) etc..Wherein PLSR predictive ability is strong
And it is simple to model needs, become one of the multivariate calibration methods being most widely used.Reliable Radix Angelicae Sinensis mixes puppet in order to obtain
Analysis is as a result, the pretreatment of spectrum is very important.Preprocess method mainly has SG smooth, first derivative (1stDer), second order
Derivative (2ndDer), continuous wavelet transform (CWT), multiplicative scatter correction (MSC), standard normal variable (SNV) etc..SG is smooth, one
Order derivative and second dervative are using window number as its important parameter, if window number is too low, it is undesirable to will lead to smooth effect, mistake
Height, which will lead to, relatively to be idealized, and is lost and caused to be distorted compared with multi information.Wavelet transformation there are two important parameter it needs to be determined that, i.e.,
Wavelet function and decomposition scale, the two parameters are directly related to the quality of Pretreated spectra result.So which kind of pretreatment side
Method effect is best, and combination processing effect is needed to choose.
Summary of the invention
The purpose of the present invention is in view of the above problems, using near infrared spectrum as means of testing, by suitable
Preprocess method pre-processes spectrum, models in conjunction with PLSR, and providing a kind of accurately and rapidly binary, to mix pseudo- Radix Angelicae Sinensis quantitative
Analysis method.
The technical scheme comprises the following steps provided by realize the present invention:
1) sample is prepared
From more pharmacy's purchase Radix Angelicae Sinensis and its several batches of adulterant, Chinese medicine is crushed with pulverizer, crosses 120 mesh later
The fine and smooth powder of collection is put into paper bag dry and prepare binary by a certain percentage and mixes pseudo- sample, wherein same match by sieve
Pseudo- sample is mixed with different Radix Angelicae Sinensis 3 Radix Angelicae Sinensis of preparation than lower, seals bottle, number.
2) near infrared spectrum of sample is acquired
The relevant parameter of near-infrared is set and the performance of instrument is tested, acquires the near infrared spectrum of sample.
3) data grouping
Using KS packet mode, data set is divided into training set and forecast set.
4) the optimum factor number of Partial Least-Squares Regression Model is determined
According to cross validation root-mean-square error (RMSECV) with the optimum factor for determining PLSR because of the variation of subnumber (LV)
Number, RMSECV minimum value are corresponding because subnumber is the optimum factor number of PLSR.
5) compare different pretreatments method and extremely combine effect to Pretreated spectra, obtain best preprocess method
SG smooth, first derivative and second order are determined with the variation of window size by predicted root mean square error (RMSEP)
The best window number of derivative, the corresponding window number of RMSEP minimum value are best window number.With wavelet function and divided according to RMSEP
The variation of scale is solved to determine the Optimum wavelet function and decomposition scale of wavelet transformation (CWT).
Under optimal parameter, investigates SG exponential smoothing, standard normal variable (SNV), multiplicative scatter correction (MSC), single order and lead
Number (1stDer), second dervative (2ndDer), the preprocess methods such as CWT and its combination of two carry out pretreated effect to spectrum,
The corresponding preprocess method of RMSEP minimum value is best preprocess method.
6) best pretreatment combines PLSR modeling method to predict unknown sample
PLSR modeling method is combined to predict the constituent content in forecast set sample using best pretreatment.
Pretreated effect is carried out to spectrum the invention has the advantages that comparing different pretreatments method, and then is selected best pre-
Then processing method resettles Partial Least-Squares Regression Model, to realize the accurate identification for mixing binary pseudo- Radix Angelicae Sinensis.
Detailed description of the invention
Fig. 1 is the atlas of near infrared spectra that 81 Radix Angelicae Sinensis Radix Angelicae Pubescentis binary mix pseudo- sample
Fig. 2 is the RMSECV of PLSR modeling with the variation diagram because of subnumber
Fig. 3 is RMSEP with smooth (b) first derivative (c) second dervative of variation diagram (a) SG of window size
Fig. 4 is the RMSEP of wavelet transformation with wavelet function and decomposition scale variation diagram
Fig. 5 is that optimal pretreatment combines PLSR to model to the predicted value of forecast set and relational graph (a) Radix Angelicae Sinensis of true value
SNV-CWT-PLSR modeling；(b) Radix Angelicae Pubescentis MSC-PLSR is modeled
Specific embodiment
To be best understood from the present invention, the present invention will be described in further detail with reference to the following examples, but of the invention
Claimed range is not limited to range represented by embodiment.
Embodiment:
The present embodiment is the quantitative analysis that pseudo- sample is mixed applied to Radix Angelicae Sinensis Radix Angelicae Pubescentis binary, uses near infrared spectrum combinationization
The method for learning meterological.Specific steps are as follows:
1) sample is prepared
From 40, Tianjin, different pharmacies buys 40 batch of Radix Angelicae Sinensis, 39 batch of Radix Angelicae Pubescentis.First by Chinese medicine pulverizer
It crushes, crosses 120 meshes later, the fine and smooth powder of collection is put into paper bag and is dried.By the adulterant Radix Angelicae Pubescentis and Radix Angelicae Sinensis of Radix Angelicae Sinensis
Powder is uniformly mixed according to different proportion, and obtained binary mixes pseudo- sample, wherein the Radix Angelicae Pubescentis to match in every group with Radix Angelicae Sinensis is all pure
Product.Radix Angelicae Sinensis, Radix Angelicae Pubescentis concentration range 0-100% are wherein divided between 1%, 5-95% between being divided into 5%, 97-100% between 0-3% and are divided into
1%, three groups of samples prepared according to same ratio of all useful different sterlings in 27 configuration proportions, so being set in the experiment
In meter, the binary of Radix Angelicae Sinensis mixes puppet and shares 81 samples.Drug is put into plastic bottle later, and marks sample number into spectrum 1-81.Often
A sample theory gross mass is 10g, calculates the Theoretical Mass of each sample each component, after weighing, it is each to record each sample
The actual mass of component, component actual mass obtain the mass percent of each component in sample divided by gross mass, as each group
The target value divided.
2) near infrared spectrum of sample is acquired
Before starting test sample, opens optically focused generation and reach near-infrared spectrometers, first preheat 0.5-1 hours, and to the property of instrument
It can be carried out self-test, wave-length coverage 1000-1800nm is spaced 1nm, then is tested for the property with white correcting plate and reference plate.It
The sample prepared is moved into loading ware with spoon afterwards, the surface of loading ware is smeared smoothly with angle square, makes its uniform fold ware
Face and the sample residue for wiping ware edge, in order to avoid pollution apparatus measures environment.Each sample setting pendulous frequency is 3 times, is turned
Disk carries object ware and rotates together, exports 3 spectrum automatically.In measurement process, white reference plate is utilized to carry out every other hour
Reference guarantees result accurately without generating deviation.Fig. 1 is the atlas of near infrared spectra that Radix Angelicae Sinensis and Radix Angelicae Pubescentis binary mix pseudo- sample.
3) data grouping
Using KS group technology, 2/3 is training set, and 1/3 is forecast set.The instruction of 54 samples is obtained after 81 sample groupings
Practice collection, the forecast set of 27 samples.
4) the optimum factor number of Partial Least-Squares Regression Model is determined
According to cross validation root-mean-square error (RMSECV) with the optimum factor for determining PLSR because of the variation of subnumber (LV)
Number, RMSECV minimum value are corresponding because subnumber is the optimum factor number of PLSR.Fig. 2 shows cross validation root-mean-square error
(RMSECV) with the variation because of subnumber, the RMSECV minimum value of Radix Angelicae Sinensis and Radix Angelicae Pubescentis component is corresponding because subnumber is respectively 15 Hes
The optimum factor number of 14, as PLSR.
5) compare different pretreatments method and extremely combine effect to Pretreated spectra, obtain best preprocess method
SG smooth, first derivative and second order are determined with the variation of window size by predicted root mean square error (RMSEP)
The best window number of derivative, the corresponding window number of RMSEP minimum value are best window number.Fig. 3 (a), (b), (c) are respectively SG flat
Cunning, first derivative, second dervative RMSEP with window size variation diagram.It can thus be concluded that Radix Angelicae Sinensis and Radix Angelicae Pubescentis component SG are smooth
Best window number is respectively 29 and 3, and the best window number of first derivative is 9, and the best window number of second dervative is respectively 17
With 19.
The Optimum wavelet function of wavelet transformation (CWT) is determined with the variation of wavelet function and decomposition scale according to RMSEP
With decomposition scale.Wavelet function include Haar, db2, db3, db4, db5, db6, db7, db8, db9, db10, db11, db12,
db13、db14、db15、db16、db17、db18、db19、db20、coif1、coif2、coif3、coif4、coif5、sym2、
sym3、sym4、sym5、sym6、sym7、sym8、bior1.1、bior1.3、bior1.5、bior2.2、bior2.4、
Bior2.6, bior2.8, bior3.1, bior3.3, bior3.5, bior3.7, bior3.9, bior4.4, bior5.5 and
Bior6.8, decomposition scale are divided into 1 from 1 to 60, calculate different wavelet functions and the corresponding RMSEP value of decomposition scale.RMSEP
The corresponding wavelet function of minimum value and decomposition scale are Optimum wavelet function and decomposition scale.Fig. 4 shows RMSEP with small echo letter
The variation of several and decomposition scale.Radix Angelicae Sinensis is respectively with decomposition scale with Radix Angelicae Pubescentis component Optimum wavelet function as can be drawn from Figure 4
Coif1 and 49, db2 and 52.
Under optimal parameter, investigates SG exponential smoothing, standard normal variable (SNV), multiplicative scatter correction (MSC), single order and lead
Number (1stDer), second dervative (2ndDer), the preprocess methods such as CWT and its combination of two carry out pretreated effect to spectrum,
The corresponding preprocess method of RMSEP minimum value is best preprocess method.Table 1 is different pretreatments method combination PLSR prediction
RMSEP and R.As can be seen from Table 1, the best pretreatment mode of the corresponding Radix Angelicae Sinensis of RMSEP minimum value and Radix Angelicae Pubescentis is SNV- respectively
CWT-PLSR and MSC-PLSR, the corresponding related coefficient of both best preprocess methods are also the peak in all methods.
The prediction result of 1 different pretreatments method combination PLSR of table modeling
6) best pretreatment combines PLSR modeling method to predict unknown sample
PLSR modeling method is combined to predict the constituent content in forecast set sample using best pretreatment.Fig. 5
(a), (b) is respectively the relationship of Radix Angelicae Sinensis and Radix Angelicae Pubescentis using the SNV-CWT-PLSR and MSC-PLSR predicted value modeled and true value
Figure.As can be seen that predicted value and the linear relationship of true value are fine, related coefficient is all 0.97 or more.Therefore, best pretreatment
It is modeled in conjunction with PLSR, the accurate quantitative analysis of component may be implemented.
Claims (2)
1. a kind of binary based near infrared spectrum and Chemical Measurement mixes pseudo- Radix Angelicae Sinensis quantitative analysis method, it is characterised in that: first
It buys Radix Angelicae Sinensis and similar product is several, the Radix Angelicae Sinensis for preparing certain amount mixes pseudo- sample；The near-infrared that pseudo- sample is mixed in acquisition diffuses
Spectrum；Using KS packet mode, data set is divided into training set and forecast set；Determine the factor of Partial Least-Squares Regression Model
Number；Again, the pretreating effect for investigating different pretreatments method, obtains best preprocess method；Finally, using best pre- place
Reason-PLSR modeling method mixes pseudo- Radix Angelicae Sinensis quantitative analysis to binary.
2. a kind of binary based near infrared spectrum and Chemical Measurement according to claim 1 mixes pseudo- Radix Angelicae Sinensis quantitative analysis
Method, it is characterised in that: the different pretreatments method includes SG exponential smoothing, multiplicative scatter correction, standard normal variable, single order
Derivative, second dervative and continuous wavelet transform and their combination.
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| CN110376310A (en) * | 2019-08-20 | 2019-10-25 | 陕西中医药大学 | The detection method of Radix Angelicae Sinensis quality |
| CN110376310B (en) * | 2019-08-20 | 2021-10-01 | 陕西中医药大学 | Method for detecting quality of angelica sinensis |
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Application publication date: 20190517 |