CN103364362A - Method for identifying Chinese herbal medicines by using THz-TDS combined with chemometrics - Google Patents
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Abstract
The invention relates to a method for identifying Chinese herbal medicines by using THz-TDS combined with chemometrics, which mainly comprises the following steps: carrying out detection on a Chinese herbal medicine sample by using the THz-TDS so as to obtain a terahertz time domain spectroscopy, and after the terahertz time domain spectroscopy is subjected to Fourier transform and calculated by using Timothy and Duvillaret methods, obtaining an absorption coefficient spectrum, and dividing the absorption coefficient spectrum into a training-set sample and a validating-set sample absorption coefficient spectrum; carrying out preprocessing on the training-set sample and the validating-set sample absorption coefficient spectrum by using an orthogonal signal correction method; establishing a qualitative analysis model by using the least squares support vector machine (SVM) method according to the training-set sample and the validating-set sample absorption coefficient spectrum so as to carry out identification on the Chinese herbal medicine sample. The method disclosed by the invention is simple, pollution-free, capable of rapidly and accurately carrying out nondestructive identification on the Chinese herbal medicines, and applicable to the quality control in the process of Chinese herbal medicine production, and the identification accuracy of the method can reach 97.84+ /-1.62%.
Description
Technical field
The present invention relates to a kind of THz-TDS of utilization identifies Chinese herbal medicine in conjunction with Chemical Measurement method, belong to evaluation and the analysis technical field of Chinese herbal medicine.
Background technology
Along with the traditional Chinese medical science and tcm theory are gone abroad gradually as being paid close attention in the world, people are more and more stronger to the exploration desire of the traditional Chinese medical science and Chinese medicine principle, and research means is also abundant gradually.Be full of in market but increasing Chinese herbal medicine product of poor quality also occurred thereupon, not only affect the restriction that result for the treatment of also further develops for traditional Chinese medicine.In recent years, along with producing the growth of actual needs and developing rapidly of modern science, discriminating means to Chinese herbal medicine also become better and approaching perfection day by day, mainly concentrate on diagnostic characteristics and the chemical composition of studying Chinese herbal medicine, and identify the true and false and the quality of Chinese herbal medicine with this, and then guarantee the curative effect of Chinese herbal medicine and patient's drug safety.At present, for the discriminating of Chinese herbal medicine, more employing traditional Chinese medicine fingerprint technology purpose quick to realize, the precise Identification Chinese herbal medicine.The traditional Chinese medicine fingerprint technology is a kind of technology that marks the total peak of Chinese medicine characteristic with analysis means, comprises various chromatograms, spectral technique and gene fingerprint technology.But above-mentioned various Fingerprint of traditional Chinese medicine technology all needs pre-service such as sample flood, separates, concentrates, and analysis time is long, complex operation, and after detecting end, medicinal material can not be used again, and therefore, above-mentioned fingerprint pattern technology only is suitable for carrying out Chinese herbal medicine is spot-check detection.
Along with deeply reaching extensively of research, some medium-height grass the effective elements of the medicine and molecular structure have been studied clear whole or in part, yet also has the more Chinese herbal medicine of multicomponent complexity, its effective constituent and molecular structure and then adopt prior art to be difficult to said herbal medicine is effectively identified also under study for action.This wherein differentiates difficult point and the study hotspot that more becomes Chinese herbal medicine discriminating field to the true and false of rheum officinale.
Rheum officinale specifically refers to polygonaceae plant, is that a kind of component portion is unknown and form very complicated Chinese herbal medicine, thereby is the difficult problem that the personage generally acknowledges in the industry to the evaluation of rheum officinale always.Wherein, pharmacopeia has been included three kinds of genuine rhubarbs, comprises sorrel, the ancient especially big Huang of Tang and Rheum officinale, the dry root and rhizome of above-mentioned three kinds of genuine rhubarbs, bitter cold in nature, have heat and toxic materials clearing away, clearing heat-fire, removing pattogenic heat from the blood and toxic material from the body, by the stasis of blood stimulate the menstrual flow, the effect of dampness removing removing jaundice.In recent years, widespread use along with rheum officinale, occurred on the market the root of the adulterant rheum officinales such as North China rheum officinale, Radix Rhei emodi, Rheum hotaoense C. Y. Cheng et C. T. Kao and rhizome are sneaked into situation in the genuine rhubarb, but the discharge function of these adulterant rheum officinales is far away from genuine rhubarb, some in addition may cause stomachache.But widely used discrimination method but can't be realized the discriminating to authenticity of Chinese rhubarb in the prior art, also becomes the puzzlement on the middle medical drugs.
Terahertz emission refers to frequency at 0.1THz-10THz, the electromagnetic wave of wavelength between 0.03-3mm, its wave band between microwave and infrared ray, be macroelectronics to the zone of microcosmic photonics transition, in electromagnetic spectrum, occupy very special position.Develop gradually the method for utilizing terahertz emission in the prior art to differentiate the method for Chinese herbal medicine.Compare with additive method, the THz radiation is used for Study of Medicinal Herbs to have the following advantages: low-frequency vibration or the rotation mode of the contained biomacromolecule of (1) most of Chinese herbal medicines are in the THz wave band, therefore different Chinese herbal medicines have corresponding characteristic spectrum, can effectively distinguish various traditional Chinese medicine ingredients; (2) photon energy of THz radiation is lower, can not produce harmful ionising radiation to Chinese herbal medicine, and the Chinese herbal medicine after the discriminating still can use; (3) the THz radiation has the coherence, can directly measure amplitude and the phase place of electric field, can extract easily refractive index and the absorption coefficient of Chinese herbal medicine sample, and infrared spectrum can only obtain the strength information of a certain frequencies of light; (4) THz pulses of radiation width to the femtosecond magnitude, can carry out time-resolved transient state spectral investigation in psec to Chinese herbal medicine, and by the sampled measurements technology, the interference of energy establishment background radiation obtains the very high Time Domain Spectrum of signal to noise ratio (S/N ratio).
Based on this, Chinese patent CN1614391A discloses a kind of quick nondestructive analytical approach to the Chinese herbal medicine true and false and quality discrimination, it may further comprise the steps: (1) utilizes the THz-TDS device to measure respectively the THz-TDS spectrogram of known and Chinese herbal medicine to be measured, through Fourier transform, ordinate is taken the logarithm, the fingerprint that obtains Chinese herbal medicine absorbs collection of illustrative plates again; (2) fingerprint of contrast said herbal medicine absorbs collection of illustrative plates, and the fingerprint absorption peak collection of illustrative plates of identical wave band is close, and then Chinese herbal medicine to be measured is true medicinal material, and a little less than the absorption peak, then chemical composition content reduces in the Chinese herbal medicine to be measured, if collection of illustrative plates is different, then is judged to the counterfeit drug material.Above-mentioned analytical approach utilizes the finger-print of effective constituent in the Chinese herbal medicine sample to carry out fast, nondestructively detect and differentiate, but the discriminating of the method is to depend on the fingerprint of the Chinese herbal medicine of having set up to absorb collection of illustrative plates, but for the rheum officinale that many Chinese herbal medicine samples that does not have obvious characteristic fingerprint pattern especially characteristic fingerprint pattern extremely are difficult for identification, then also inapplicable.
In order to address the above problem, Chinese patent literature CN102590135A discloses a kind of herbicide discrimination method based on least square method supporting vector machine, mainly may further comprise the steps: at first use the terahertz time-domain spectroscopy system training sample sets is detected, obtain terahertz time-domain spectroscopy; Then through Fourier transform and terahertz optics parameter extraction model, calculate the absorption coefficient spectrum, and utilize inclined to one side two Theravada's methods to extract the validity feature vector, differentiate model database take the validity feature vector as the Foundation herbicide; Recycling terahertz time-domain spectroscopy system detection validation sample sets, obtain terahertz time-domain spectroscopy, then through Fourier transform and terahertz optics parameter extraction model, calculating absorption coefficient spectrum, and utilize partial least square method to extract the validity feature vector, call at last the herbicide of having set up and differentiate model database, utilize least square method supporting vector machine to determine the classification of verification sample collection.Finished fast and accurately discriminating to herbicide although utilize THz-TDS spectrum in the said method in conjunction with chemometrics method, but because herbicide itself is comprised of several known compounds, not only composition is simple for it, and differentiate that the target substance feature is clear, the characteristic of this and medicinal herb components complexity and composition the unknown is far from each other, therefore, for complicated component and unknown Chinese herbal medicine especially rheum officinale, said method still is difficult to realize discriminating and the analysis of sample.
Summary of the invention
Technical matters to be solved by this invention is to utilize the THz-TDS device to be difficult to complicated component and unknown Chinese herbal medicine are differentiated and analyzed in the prior art, and then provides a kind of THz-TDS of utilization to identify that in conjunction with Chemical Measurement Chinese herbal medicine especially differentiates the method for the rheum officinale true and false.
For solving the problems of the technologies described above, the THz-TDS that utilizes of the present invention is in conjunction with the method for Chemical Measurement evaluation Chinese herbal medicine, and its technical scheme is:
A kind of method of utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement, it comprises the steps:
(1) utilize the THz-TDS spectrometer that the Chinese herbal medicine sample is tested, obtain terahertz time-domain spectroscopy, and after Fourier transform and Timothy and the calculating of Duvillaret method, obtain the absorption coefficient spectrum of sample, and described absorption coefficient spectrum is divided into training set sample and described checking collection sample absorption coefficient spectrum;
(2) adopt the reinforcement Orthogonal Signal Correction that described training set sample and described checking collection sample absorption coefficient spectrum are carried out pre-service, the specific algorithm of described reinforcement Orthogonal Signal Correction is as follows:
B＝null(M) （2）
Q＝USV
T （4）
Wherein, described M is covariance matrix, and described X is the data matrix that test obtains, and is described
Be the average data matrix, described Y is the output matrix with binary coding representation, and is described
It is average binary coded matrix, described B is the kernel matrix of described covariance matrix M, the p that described B is comprised of p-k eigenwert characteristic of correspondence vector of the minimum of M * (p-k) ties up transformation matrix, described Q is the subspace of being opened by B, and described Q also is the complementary subspace with matrix Y quadrature;
Described U is a row matrix, and V is a column matrix, and S is the diagonal matrix take the singular value of Q as diagonal element, described I
PRefer to that dimension is the unit matrix of p;
Described
That matrix D is the transition matrix that will seek through the corrected data matrix of reinforcement Orthogonal Signal Correction Analyze method;
(3) described training set sample and described checking collection sample absorption coefficient spectrum adopts the least square method supporting vector machine method to set up qualitative analysis model, so that the Chinese herbal medicine sample is identified.
Described Chinese herbal medicine is rheum officinale.
In described step (1), utilize self-service Latin partition method that described absorption coefficient spectrum is divided and obtain described training set sample and described checking collection sample absorption coefficient spectrum.
Utilizing described self-service Latin partition method to select the partition number when absorption coefficient spectrum is divided is 4, gets wherein 3/4 as training set sample absorption coefficient spectrum, and 1/4 as checking collection sample absorption coefficient spectrum.
When utilizing described self-service Latin partition method that described absorption coefficient spectrum is divided, repeat partition and calculate 10 times.
In the described step (1), the test condition of described THz-TDS is: chamber Warm (25 ℃ time), and with nitrogen as a reference, the scanning step motor of spectrometer scanning system interval is 24.6-27.6mm, step-length is 0.01mm.
In the described step (2), the absorption coefficient of described training set sample and described checking collection sample spectrum also comprises first described training set sample and described checking collection sample absorption coefficient spectrum through automatically adjusting or the step of 5 cubic polynomial smoothing processing of Savitzky-Golay before adopting the EOSC method to carry out pre-service.
When adopting described automatic adjustment to carry out pre-service in conjunction with described reinforcement Orthogonal Signal Correction in the described step (2), proofreading and correct the main cause subnumber is 4; When adopting 5 cubic polynomials of described Savitzky-Golay smoothly to carry out pre-service in conjunction with the EOSC method, proofreading and correct the main cause subnumber is 11.
The least square method supporting vector machine method that described step (3) adopts is processed described training set sample and described checking collection sample absorption coefficient spectrum first through least square, the recycling support vector machine method is identified.
Described Chinese herbal medicine sample is thin slice or Powdered.
Technique scheme of the present invention has the following advantages compared to existing technology:
(1) method of utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement of the present invention, adopt reinforcement Orthogonal Signal Correction Analyze (EOSC) method that training set sample and the described checking collection sample absorption coefficient spectrum of described Chinese herbal medicine sample are carried out pre-service, described reinforcement Orthogonal Signal Correction Analyze is by utilizing change of variable to make measure spectrum transform to an orthogonal intersection space from measurement space, basic thought based on useful signal in orthogonal intersection space and noise and other irrelevant signal quadrature, keep useful information by orthogonal calculation, remove noise and other irrelevant information, thereby not only can effectively remove the impact of measuring the Noise and Interference signal, also further solved Chinese herbal medicine in the prior art owing to containing multiple not principal component and not having obvious characteristic fingerprint pattern, can't carry out accurately, effectively identify the problem with identification; When adopting the method for the invention that Chinese herbal medicine is identified that especially the higher rheum officinale of difficulty is identified, identify accuracy rate up to 97.84 ± 1.62%, discriminating and the evaluation of rheum officinale had high directive significance.
(2) method of utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement of the present invention, before employing least square method supporting vector machine method is identified sample, utilize self-service Latin partition method (Bootstrappd Latin-Partitions) that described training set and described checking collection sample absorption coefficient spectrum are divided, realization is to the evaluation of disaggregated model predictive ability and stability, this be because: described self-service Latin partition method is a kind of modelling verification method that is based upon on cross validation and the random sampling checking basis, utilize self-service Latin partition can realize uniform random sampling checking, every enforcement once, each sample is used for and only is used for once prediction, guaranteed that true and false Chinese herbal medicine sample is concentrated with same ratio appearance at training set and checking, thereby realize the nothing of institute's established model predictive ability is estimated partially, make and identify that model is more reliable, analysis result has more statistical significance.
When (3) the present invention adopts described self-service Latin partition method to divide in terahertz time-domain spectroscopy, select 3/4 to compose as training set sample absorption coefficient, 1/4 as checking collection sample absorption coefficient spectrum, repeating partition calculates 10 times, setting can avoid in the single modeling selecting the different and distortion that causes of sample like this, utilizes self-service Latin partition to divide training set and checking collection sample makes the model that obtains more reliable.
(4) method of utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement of the present invention, the spectrum of Terahertz absorption coefficient described in its step (2) is before adopting the EOSC method to carry out pre-service, the first automatic adjustment of process or 5 cubic polynomial smoothing processing of Savitzky-Golay are to remove the impact of partial noise in the spectrum, so that qualification result is more accurate credible.
Description of drawings
For content of the present invention is more likely to be clearly understood, below in conjunction with accompanying drawing, the present invention is further detailed explanation.Wherein:
Fig. 1 is the evaluation accuracy and the graph of a relation of proofreading and correct the main cause subnumber of rheum officinale sample among the embodiment 1.
Fig. 2 is the evaluation accuracy and the graph of a relation of proofreading and correct the main cause subnumber of rheum officinale sample among the embodiment 2.
Embodiment:
Embodiment 1
The present embodiment utilize THz-TDS in conjunction with Chemical Measurement to the identifying of rheum officinale, wherein adopt automatically to adjust in conjunction with the EOSC method described absorption coefficient spectrum carried out pre-service, it comprises that step is as follows:
(1) adopt Beijing Science Institute of joint-stock company of Tongrentang to provide 41 rheum officinale samples to set up model, wherein 17 is genuine rhubarb, and 24 is non-genuine rhubarb; The preparation method of 41 rheum officinale samples is identical, and the preparation process of each rheum officinale sample is: (a) described rheum officinale sample is ground into 60 purpose powder after drying; (b) after described powder carries out vacuum drying again, get a certain amount of sample and be transferred to grind in the agate mortar and obtain fine powder; (c) last, under the pressure of 6.5t, described fine powder is made the thin slice of diameter 13mm, thickness 0.9-1.2mm as rheum officinale sample to be measured, described thin slice two surfaces are parallel, smooth surface and do not have the crack; Described thin slice is being guaranteed to distinguish under the prerequisite of certified products and non-certified products, be numbered successively and be 1-41, to be measured.
(2) utilize Z-3 transmission-type THz-TDS system (Zomiga company), the MVDS-400controller software kit under the room temperature (25 ℃), with nitrogen as a reference, measures the terahertz time-domain spectroscopy of the rheum officinale sample to be measured of described numbering 1-41.The terahertz light spectrometry is usually at 1-10THz(0.03-3mm) carry out in the scope.The frequency range of the Z-3THz-TDS system that uses in the present embodiment is 0.1-3.0THz.The scanning step motor interval of the tera-hertz spectra scanning system of using in experiment is 24.6-27.6mm, and step-length is 0.01mm.The THz time-domain spectroscopy signal that needs first witness mark during measurement, the then position of mobile example, each sample is successively got 3 different points and is measured, and the mean value of the THz time-domain spectroscopy signal of last sample thief is used for subsequent analysis.
(3) the terahertz time-domain spectroscopy signal of the rheum officinale sample of described numbering 1-41 is obtained the frequency domain spectra of rheum officinale sample after Fourier transform, in frequency domain spectra, extract its absorption coefficient and calculate absorption coefficient with Timothy and Duvillaret method and compose; Then, adopt self-service Latin partition method that the absorption coefficient spectrum of rheum officinale sample is divided, selecting the partition number is 4, get wherein 3/4 as training set sample absorption coefficient spectrum, 1/4 as checking collection sample absorption coefficient spectrum, is specially: at first sample to be tested is divided into 4 parts, select wherein 1 part of conduct checking collection sample, all the other 3 parts as the training set sample, repeats partition 10 times, namely repeats this process 10 times; Need to prove, in each calculating, each sample only is used for once prediction checking.
Described Timothy and Duvillaret method are to be proposed by people such as Timothy and Duvillaret, and its circular is as follows:
E
s/E
r＝T(n)exp(-αd/2+inωd/c) （7）
E wherein
sAnd E
rRespectively signal (through sample) and the frequency domain spectra amplitude that obtains through Fourier transform with reference to the time-domain spectroscopy of (without sample).α (ω) and n (ω) are respectively absorption coefficient and the refractive index of sample, and ω represents frequency, d representative sample thickness,
The phase differential of representative sample signal and reference signal, the amplitude ratio of A representative sample signal and reference signal.
The computing formula of absorption of sample coefficient and refractive index is:
(4) adopt automatically adjustment in conjunction with the EOSC method described absorption coefficient spectrum to be carried out pre-service.Concrete processing is as follows: at first, training set sample and the described checking collection sample absorption coefficient spectrum of rheum officinale sample are adjusted automatically; Then, select different correction main cause subnumbers, use the EOSC method that the absorption coefficient spectrum of rheum officinale sample is carried out pre-service.
Described EOSC method is to eliminate the important step of noise and other irrelevant signal in the THz-TDS spectrum, also is to utilize THz-TDS to the key of rheum officinale authenticity, and the algorithm of described EOSC is specific as follows:
1) core of EOSC method is based on following relation:
B＝null(M) （2）
Wherein, described M is covariance matrix, and described X is the data matrix that test obtains, and namely the data matrix of described training set sample and described checking collection sample absorption coefficient spectrum is described
Be the average data matrix, described Y is the output matrix with binary coding representation, and is described
It is average binary coded matrix, described B is the kernel matrix of described covariance matrix M, the p that described B is comprised of p-k eigenwert characteristic of correspondence vector of the minimum of M * (p-k) tie up transformation matrix, described Q is the subspace of being opened by B, described Q also is the subspace with the Y quadrature.Because described B space and M are complementary space, then the B space comprises the remaining order except M in the total space.The information of matrix B will weed out from X, that is to say that described subspace B has comprised ground unrest.Q has then served as a bridge of linking up kernel and spectroscopic data here.The ground unrest that checking is concentrated is present in the B space equally, still, and to some extent difference in the fluctuation meeting of verifying the ground unrest of concentrating and training set.
2) Q is carried out svd, obtains lower relation of plane:
Q＝USV
T （4）
Wherein, described U is a row matrix, V is a column matrix, S is the diagonal matrix take the singular value of Q as diagonal element, described relational expression (4) is used for the contrary component number of Computation of Pseudo, determine the degree of correction to data, its objective is by svd and find a transition matrix, be used for calibration samples.
Wherein
Be the data after proofreading and correct through reinforcement Orthogonal Signal Correction Analyze method, matrix D is the transition matrix that will seek; Described I
PRefer to that dimension is the unit matrix of p.
Sample for the checking collection:
Wherein
Through strengthening the corrected checking collection of Orthogonal Signal Correction Analyze method sample.
In the terahertz light spectrometry, measured signal is the hybrid system of various signals, adopts existing preprocessing procedures directly to carry out Signal Pretreatment and is difficult to useful signal is effectively extracted.Described reinforcement Orthogonal Signal Correction Analyze is by utilizing change of variable to make measure spectrum transform to an orthogonal intersection space from measurement space, basic thought based on useful signal in orthogonal intersection space and noise and other irrelevant signal quadrature, keep useful information by orthogonal calculation, remove noise and other irrelevant information, thereby, adopt Orthogonal Signal Correction Analyze to have higher evaluation accuracy rate compared to existing preprocessing procedures.
(5) described training set sample and described checking collection sample absorption coefficient spectrum adopts least square method supporting vector machine (LS-SVM) method to set up qualitative analysis model, so that the Chinese herbal medicine sample is identified, namely at first with described training set sample and described checking collection sample absorption coefficient spectrum process Least Square in Processing, proofread and correct main cause subnumber and its proper vector to extract, the recycling support vector machine is to the sample evaluation of classifying.In model construction of SVM, the nuclear parameter σ of radial basis kernel function (RBF)
210
-6-1, γ is at 1-10 for the regression error weight
3All can obtain satisfactory result in the scope.
Described authentication method specifically describes:
In a binary classification device, establish training sample set
x
k∈ R
n, y
k∈ R, x
kThe input data, y
kThe output classification, the problem below the classification problem in weights ω space (luv space) can be described as finding the solution:
Constraint condition is:
Wherein, φ () is nonlinear function, weight vector ω ∈ R
n(luv space), error variance e
k∈ R, b are departures.Loss function J is error sum of squares and regularization amount sum, and γ is the weight of regression error.The purpose of nonlinear function is to extract feature from luv space, and the sample in the luv space is mapped as a vector in the high-dimensional feature space, to solve the problem in the luv space.According to (1) formula, the definable Lagrangian function:
Wherein, Lagrange multiplier is α
kFollowing formula is optimized, can gets following matrix equation:
Wherein,
Y=[y
1; ..; y
N], I=[1; ...; I], α=[α
1; ...; α
N], use the mercer condition and arrive
K, l=1 .., N.Obtain at last disaggregated model:
After the present embodiment adopts self-service Latin partition method to divide, automatically adjust in conjunction with the EOSC method described training set sample and described checking collection sample absorption coefficient spectrum to be carried out pre-service, adopt the least square method supporting vector machine method that described training set sample and the described checking collection sample absorption coefficient spectrum of sample are set up qualitative analysis model so that sample is identified, calculate and obtain different evaluation accuracy of proofreading and correct under the main cause subnumber.Be illustrated in figure 1 as the evaluation accuracy and the graph of a relation of proofreading and correct the main cause subnumber of the present embodiment rheum officinale sample, wherein, solid line has shown the evaluation accuracy of actual measurement with the situation of change of proofreading and correct the main cause subnumber, and dotted line has shown the evaluation accuracy fiducial interval that degree of confidence obtains when being 95%.As seen from the figure, when correction main cause subnumber is 4, identify that accuracy is 97.84 ± 1.62% to the maximum.
The described computing method of accuracy of identifying are: in the modeling of rheum officinale sample and identifying, the desired output of at first specifying the genuine rhubarb sample is 1, the desired output of non-genuine rhubarb sample is-1, to calculate output valve 0 as threshold value, identify correctly if the result of calculation of genuine rhubarb is namely thought greater than 0, otherwise think the evaluation mistake; In like manner, if less than 0, namely thinking, the calculating output valve of non-genuine rhubarb identifies correctly, otherwise for identifying mistake.The self-service Latin partition method of each employing is divided rear calculating, and it identifies accuracy, and the repetition partition is calculated altogether afterwards 10 times for 10 times and averaged as final evaluation accuracy.
As shown in table 1 for the present embodiment method is 4 o'clock at the correction factor number, identify the related data of accuracy.Described evaluation accuracy is calculated according to the following formula: identify the correct sample number of accuracy (%)=qualification result/evaluation total number of samples * 100%.
Table 1 is with automatically adjusting in conjunction with the result (main cause subnumber=4) after the EOSC processing
The present embodiment adopts the preprocess method identical with embodiment 1, identical self-service Latin partition method is divided, identical least square method supporting vector machine method is set up qualitative analysis model, to utilize THz-TDS in conjunction with Chemical Measurement identifying rheum officinale, difference only is that embodiment 1 adopts automatically adjustment in conjunction with the EOSC method described training set sample and described checking collection sample absorption coefficient spectrum to be carried out pre-service, and the present embodiment adopts 5 cubic polynomials of Savitzky-Golay level and smooth (claiming that also S-G is level and smooth) in conjunction with the EOSC method described absorption coefficient spectrum to be carried out pre-service.
Interpretation of result, be illustrated in figure 2 as the evaluation accuracy and the graph of a relation of proofreading and correct the main cause subnumber of the present embodiment rheum officinale sample, wherein, solid line has shown the evaluation accuracy of actual measurement with the situation of change of proofreading and correct the main cause subnumber, and dotted line has shown the evaluation accuracy fiducial interval that degree of confidence obtains when being 95%.As seen from the figure, when correction main cause subnumber was 11, the evaluation accuracy reached and is 87.45 ± 3.03% to the maximum.
As shown in table 2 for the present embodiment method is 11 o'clock at the correction factor number, identify the related data of accuracy.
Result (main cause subnumber=11) after table 2 is smoothly processed in conjunction with EOSC with S-G
Embodiment 3
The present embodiment adopts the preprocess method identical with embodiment 1, identical qualitative analysis model, to utilize THz-TDS in conjunction with Chemical Measurement identifying rheum officinale, difference is: (1) embodiment 1 adopts 41 samples to set up model and finishes sample identification, finishes sample identification and adopt 11 samples to set up model in the present embodiment; (2) embodiment 1 adopts self-service Latin partition method that the absorption coefficient spectrum of rheum officinale sample is divided, and the present embodiment adopts random device of the prior art that the absorption coefficient spectrum of rheum officinale sample is divided, the result shows, when correction main cause subnumber was 12, it identified that accuracy is 91.82 ± 2.61% to the maximum.
As shown in table 3 for the present embodiment method is 12 o'clock at the correction factor number, identify the related data of accuracy.
Result (main cause subnumber=12) after table 3 is processed with random device
The present embodiment adopts that the self-service Latin partition method identical with embodiment 1 divided, identical least square method supporting vector machine method is set up qualitative analysis model, to utilize THz-TDS in conjunction with Chemical Measurement identifying rheum officinale, difference only is that embodiment 1 adopts automatically adjustment in conjunction with the EOSC method described training set sample and described checking collection sample absorption coefficient spectrum to be carried out pre-service, and the present embodiment adopts the EOSC method independently to carry out pre-service, the result shows, when correction main cause subnumber was 12, it identified that accuracy is 81.50% ± 3.54 to the maximum.
As shown in table 4 for the present embodiment method is 12 o'clock at the correction factor number, identify the related data of accuracy.
Result (main cause subnumber=12) after table 4 is processed with EOSC
Need to prove that the method for utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement of the present invention at first, is divided described absorption coefficient spectrum by adopting self-service Latin partition method; Secondly, adopt automatically adjustment or 5 cubic polynomials of Savitzky-Golay smoothly in conjunction with the EOSC method described training set sample and described checking collection sample absorption coefficient spectrum to be carried out pre-service; At last, adopt the least square method supporting vector machine method to set up qualitative analysis model at described training set sample and described checking collection sample absorption coefficient spectrum, thereby finished evaluation and analysis to the Chinese herbal medicine sample.Described self-service Latin partition method, automatic adjusting method, S-G smoothing method, EOSC method, least square method supporting vector machine method all belong to the Chemical Measurement field.
As the embodiment that can select, the EOSC preprocess method can automatically adjust as described with other preprocessing procedures or the S-G smoothing method is united use, also can use separately.
Further, the present invention describes as an example of rheum officinale class Chinese herbal medicine example, because rheum officinale is a kind of complicated component and unknown Chinese herbal medicine, thereby is suitable for differentiating that the analytical approach of rheum officinale also is applicable to the evaluation of other various Chinese herbal medicines in principle.In addition, the sample of Chinese herbal medicine described in the embodiment of the invention is thin slice, and as the embodiment that can select, the inventive method also can be identified Powdered Chinese herbal medicine sample.
Obviously, above-described embodiment only is for example clearly is described, and is not the restriction to embodiment.For those of ordinary skill in the field, can also make other changes in different forms on the basis of the above description.Here need not also can't give all embodiments exhaustive.And the apparent variation of being extended out thus or change still are among the protection domain of the invention.
Claims (10)
1. a method of utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement is characterized in that, comprises the steps:
(1) utilize the THz-TDS spectrometer that the Chinese herbal medicine sample is tested, obtain terahertz time-domain spectroscopy, and after Fourier transform and Timothy and the calculating of Duvillaret method, obtain the absorption coefficient spectrum of sample, and described absorption coefficient spectrum is divided into training set sample and described checking collection sample absorption coefficient spectrum;
(2) adopt the reinforcement Orthogonal Signal Correction that described training set sample and described checking collection sample absorption coefficient spectrum are carried out pre-service, the specific algorithm of described reinforcement Orthogonal Signal Correction is as follows:
B＝null(M) （2）
Q＝USV
T （4）
Wherein, described M is covariance matrix, and described X is the data matrix that test obtains, and is described
Be the average data matrix, described Y is the output matrix with binary coding representation, and is described
It is average binary coded matrix, described B is the kernel matrix of described covariance matrix M, the p that described B is comprised of p-k eigenwert characteristic of correspondence vector of the minimum of M * (p-k) ties up transformation matrix, described Q is the subspace of being opened by B, and described Q also is the complementary subspace with matrix Y quadrature;
Described U is a row matrix, and V is a column matrix, and S is the diagonal matrix take the singular value of Q as diagonal element, described I
PRefer to that dimension is the unit matrix of p;
Described
That matrix D is the transition matrix that will seek through the corrected data matrix of reinforcement Orthogonal Signal Correction Analyze method;
(3) described training set sample and described checking collection sample absorption coefficient spectrum adopts the least square method supporting vector machine method to set up qualitative analysis model, so that the Chinese herbal medicine sample is identified.
2. the method for utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement according to claim 1 is characterized in that, described Chinese herbal medicine is rheum officinale.
3. the THz-TDS that utilizes according to claim 1 and 2 is in conjunction with the method for Chemical Measurement evaluation Chinese herbal medicine, it is characterized in that, in described step (1), utilize self-service Latin partition method that described absorption coefficient spectrum is divided and obtain described training set sample and described checking collection sample absorption coefficient spectrum.
4. the THz-TDS that utilizes according to claim 3 is in conjunction with the method for Chemical Measurement evaluation Chinese herbal medicine, it is characterized in that, utilizing described self-service Latin partition method to select the partition number when the absorption coefficient spectrum is divided is 4, get wherein 3/4 as training set sample absorption coefficient spectrum, 1/4 as checking collection sample absorption coefficient spectrum.
5. according to claim 3 or the 4 described methods of utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement, it is characterized in that, when utilizing described self-service Latin partition method that described absorption coefficient spectrum is divided, repeat partition and calculate 10 times.
6. arbitrary described THz-TDS that utilizes is in conjunction with the method for Chemical Measurement evaluation Chinese herbal medicine according to claim 1-5, it is characterized in that, in the described step (1), the test condition of described THz-TDS is: in the time of 25 ℃, with nitrogen as a reference, the scanning step motor interval of spectrometer scanning system is 24.6-27.6mm, and step-length is 0.01mm.
7. arbitrary described THz-TDS that utilizes is in conjunction with the method for Chemical Measurement evaluation Chinese herbal medicine according to claim 1-6, it is characterized in that, in the described step (2), the absorption coefficient of described training set sample and described checking collection sample spectrum adopt strengthen Orthogonal Signal Correction and carry out pre-service before, also comprise first described training set sample and described checking collection sample absorption coefficient spectrum through automatically adjusting or the step of 5 cubic polynomial smoothing processing of Savitzky-Golay.
8. the THz-TDS that utilizes according to claim 7 is in conjunction with the method for Chemical Measurement evaluation Chinese herbal medicine, it is characterized in that, when adopting described automatic adjustment to carry out pre-service in conjunction with described reinforcement Orthogonal Signal Correction in the described step (2), proofreading and correct the main cause subnumber is 4; When adopting 5 cubic polynomials of described Savitzky-Golay smoothly to carry out pre-service in conjunction with the EOSC method, proofreading and correct the main cause subnumber is 11.
9. arbitrary described THz-TDS that utilizes is in conjunction with the method for Chemical Measurement evaluation Chinese herbal medicine according to claim 1-8, it is characterized in that, the least square method supporting vector machine method that described step (3) adopts, first described training set sample and described checking collection sample absorption coefficient spectrum are processed through least square, the recycling support vector machine method is identified.
10. arbitrary described method of utilizing THz-TDS to identify Chinese herbal medicine in conjunction with Chemical Measurement is characterized in that according to claim 1-9, and described Chinese herbal medicine sample is thin slice or Powdered.
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