CN108802251A - The method for quickly measuring chiral material based on limitation Alternating trilinear decomposition algorithm and HPLC-DAD instruments - Google Patents
The method for quickly measuring chiral material based on limitation Alternating trilinear decomposition algorithm and HPLC-DAD instruments Download PDFInfo
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Abstract
The present invention discloses a kind of method based on limitation Alternating trilinear decomposition algorithm and HPLC-DAD Instrument measuring chiral materials：Prepare calibration set sample respectively first, verification collection sample and forecast set sample, sample is detected using HPLC-DAD instruments, then it establishes calibration model and does regression analysis, i.e. first by calibration set sample, the HPLC-DAD data composition three-dimensional data battle array X of verification collection sample and forecast set sample, vector subspace projection is recycled to determine system because of subnumber in conjunction with Monte-Carlo Simulation Method, and three-dimensional data battle array is decomposed using limitation Alternating trilinear decomposition algorithm, establish calibration model, and regression analysis is carried out to the concentration of chiral material in verification sample and pre- sample, finally measure the concentration of chiral material in system；The problem of present invention can be total to eluting peak with effective solution chirality object avoids the waste plenty of time from screening chiral column column type and mobile phase, has the characteristics that quick, green, environmental protection.
Description
Background technology
Chirality is the essential attribute of nature substance, and active Difference In Toxicity is notable between chiral pesticide enantiomers, and this difference
It is different closely related with local environment.There are about 40% it is chiral material in the currently used pesticide of China, and not with labyrinth
Disconnected to introduce, which is in the trend gradually increased.Therefore, Chiral pesticide rapid detection method is established, agriculture not only can be effectively reduced
The production cost of medicine can also reduce input amount of the pesticide into natural ecosystems, and then pesticide is alleviated or avoided to ecology
The harm of environment and animals and plants.
Chiral material analysis method common at present, including chemical resolution method, enzyme or microbial method and Chromatographic resolution method,
Wherein, Chromatographic resolution method have many apparent superiority, can meet it is various under the conditions of Chiral Separation and measure want
It asks, simple and rapid qualitative and quantitative analysis can be carried out, can also carry out the separation and microdetermination of preparative-scale.Chromatographic resolution
Method can be divided into chiral derivation method, chiral mobile phases and Chiral Stationary Phases.Wherein, the color based on Chiral Stationary Phases
It is most commonly seen to compose Split Method.It is temporary non-that Chiral Stationary Phases are that the chiral selector based on sample and fixed phase surface is formed
The energy difference exclusive or stability of enantiomer complex is different and reaches chiral separation, can be without being transformed into the straight of diastereomer
Connect fractionation.The flowing phase composition of this method is simple, and favorable reproducibility is easy to operate, and application range is extremely extensive.But chirality is fixed
There is phase method very strong specificity, a type of stationary phase can only split a kind of or a few class enantiomers, develop at present
Many chiral columns with different function.Therefore, high performance liquid chromatography-diode array UV detector instrument is utilized
(HPLC-DAD) method detects Chiral pesticide, both needs to take a significant amount of time to screen suitable column type and mobile phase so that hand
Property object has separating effect on chiral column；Even if chiral object has separating effect on a certain chiral column, it is also necessary to when long
Between explore suitable apparatus method chiral material be kept completely separate on chiral column, and cannot be in the chromatography delivery time
Unknown disturbances are overlapped, just can be with accurate quantitative analysis.Therefore, general based on HPLC-DAD instrument developments, quick chiral compound detection
Method has become urgent technical problem to be solved in the field.
Invention content
In view of the above-mentioned problems, the present invention is based on " mathematics separation " enhancing " chromatographic isolation " thinking, for the analysis of chiral object
Special system develops limitation Alternating trilinear decomposition algorithm (RATLD), and combines the HPLC-DAD instruments based on chiral column
Fast quantitative analysis is carried out to the chiral material in complex sample.The technology of the present invention method is realized by the following method：
1) preparation of calibration set sample：Buy chiral object substance mark product to be measured, and suitable organic solvent (such as hexane) point
Not Pei Zhi chiral object working solution, the chiral material mixed solution of different gradient concentrations is prepared in the concentration range of linearity, as
Calibration set sample, wherein concentration proportioning can according to the methods of this field conventional orthorhombic experimental design and uniform test design into
Row setting is (such as reference《Analytical chemistry handbook (second edition) ten fascicles-Chemical Measurement》, Chemical Industry Press)；
For measuring R- dinotefuran and the S- dinotefuran in rice sample, R- dinotefuran is dissolved respectively using n-hexane
With S- dinotefuran mark product, then the working solution for a concentration of 10.0mg/L being configured to utilizes working solution to prepare 6 groups of differences dense
The chiral object mixed solution of gradient is spent as correction sample, and n-hexane is used in combination to be settled to 1mL, after constant volume in 6 calibration set samples,
R- dinotefuran concentrations are followed successively by 4.0,2.0,1.0,0.5,0.2,0.0mg/L, S- dinotefuran concentrations are followed successively by 0.0,0.2,0.5,
1.0、2.0、4.0mg/L。
2) preparation of verification collection sample：The sample to be tested without chiral material is weighed, a certain amount of chiral object to be measured is added
Standard solution, according to this field conventional sample processing method (such as document《Liquid-phase chromatographic analysis technical standard collects》, China
Standard publishing house) sample to be tested is extracted, it is ensured that sample to be tested extracting solution meets chromatographic apparatus sample introduction standard.Wherein, it tests
The concentration for demonstrate,proving sample extracting solution should be in calibration set sample in the concentration range of chiral object.
For measuring R- dinotefuran and the S- dinotefuran in rice sample, takes not by dinotefuran Polluted Paddy, food is used in combination
Product smash pulp grinder to pieces and crush simultaneously mixing, accurate to claim 1.0g in disposable plastic pipe with cover 5mL, are separately added into a certain amount of hand
Property object standard solution, make two chiral objects addition concentration be respectively 0.1mg/kg, 0.5 mg/kg and 1.5mg/kg, 5.0mL be added
Acetonitrile vibrates 30min, and 1.0g sodium chloride, vortex 1min is added to centrifuge 10min with 5000r/min rotating speeds, take supernatant liquor
In 5mL disposable plastic pipes 30mg graphitic carbon blacks are added, mono- propyl ethylenediamines (PSA) of 100mgN, 100mg is anhydrous in 2.5mL
Magnesium sulfate, vortex 1min centrifuge 5min with 8000r/min rotating speeds, then take supernatant liquor 1mL, and after nitrogen drying, 1mL is being added just
Hexane dissolves, and after 0.22 μm of organic membrane filtration, that is, obtains the verification collection sample to be measured；
3) preparation of forecast set sample：Sample to be tested is consistent with the verification collection processing step of sample in forecast set, but does not add
Add chiral object standard items.
4) based on chiral column of the HPLC-DAD instruments screening with separating effect and mobile phase, (chiral object is on chiral column
Need not be kept completely separate), and correction sample, verification sample and pre- test sample are detected.
In the embodiment of the present invention using Daicel bonded chiral chromatographic column (IB-3), efficient liquid phase
Chromatographic parameter setting is as follows：Instrument：High performance liquid chromatograph；Chromatographic column：Daicel IB-3；Mobile phase：N-hexane (A)-ethyl alcohol
(B)；Flow velocity：0.6mL/min；Sample size：30uL；Detector：Diode array detector (DAD), scanning range 230-
400nm is spaced 2nm.Under this condition, it measures R- dinotefuran and S- dinotefuran there are problems that flowing out altogether.
5) calibration model foundation and regression analysis：First by calibration set sample, verification collection sample and forecast set sample
HPLC-DAD data form three-dimensional data battle array X, and vector subspace projection is recycled to determine system in conjunction with Monte-Carlo Simulation Method
Number of components, and the limitation Alternating trilinear decomposition algorithm utilized decomposes three-dimensional data battle array, finally calibration set is utilized to establish correction
Model, and regression analysis is carried out to the concentration of chiral material in verification sample and pre- sample.
In step 5), the HPLC-DAD data of the calibration set sample, verification collection sample and forecast set sample are two dimension
Data matrix, size are I × J, and wherein I is time dimension, and size is time dimension gathered data point number；J ties up for spectrum
Degree, size are spectral Dimensions gathered data point number.The 2-D data of each sample is stacked up and just constitutes three dimensions
According to battle arrayX, size is I × J × K, and wherein K is sample dimension, and the value of K is sample number.
In step 5), is projected using vector subspace and determine process of the system because of subnumber in conjunction with Monte-Carlo Simulation Method
It is as follows：
A) in three-dimensional data battle arrayXIn, obtain a pseudo- sample battle array R along the directions I1：
In above formula, Xi..For three-dimensional data battle arrayXI-th of slice matrix along the directions I；
wiIt is the random data generated by Monte-Carlo Simulation Method, size utilizes singular value point between 0 to 1
Solution (SVD) method takes X..kTop n principal component build sample battle array M..k：
[U, S, V]=svds (X..k,N) (2)
M..k=USVT (3)
Wherein, X..kFor three-dimensional data battle array X matrix is sliced along the directions K k-th；
B) pseudo- matrix R2 is built：
Wherein, wiWith the w in equation (1)iIt is identical；
Then singular value decomposition is utilized to handle two pseudo- matrix R1And R2：
[U1,S1,V1]=svd (R1) (5)
[U2,S2,V2]=svd (R2) (6)
U is calculated according to following equation1And U2In corresponding vector projection residual errors：
In above formula, DI(n)Indicate projection residual errors, U1(n)And U2(n)It is U respectively1And U2N-component column vector, IJIndicate size
For the unit matrix of J × J, subscript+It is Moore-Penrose generalized inverse matrix, DI is that its vectorial size is 1 × N；||.||FFor
The F norms or Frobenius moulds of matrix；
C) at least 50 groups of w are randomly generated using Monte-Carlo Simulation MethodiNumerical value carries out repeating step a)-b), calculate phase
Answer the average value DI of projection residual errorsN(DINFor vector, its size is 1 × N), because of subnumber criterion：When because subnumber is more than true
When system component number, corresponding projection residual errors numerical value can jump to a relatively large numerical value from a very small numerical value,
And the projection residual errors numerical value of the factor behind is also all bigger, so this jumping point is corresponding because of subnumber NIIt is exactly pre-estimation
System component number；
D) projection residual errors DJ is found out along the directions JNAnd estimate another number of components NJ；From NIAnd NJIt is middle to judge final system
Number of components；
Vector subspace projection can be refering to document (Yong Li, et in conjunction with the specific steps of Monte-Carlo Simulation Method
al.Estimating the chemical rank of three-way fluorescence data by vector
subspace projection with Monte Carlo simulation.Chemometrics and Intelligent
Laboratory Systems,2014,136:15-23)。
The 5 of step) in, limitation alternating projection new method (RATLD) is based on limitation trilinear model exploitation.
For chiral object system, although there is steric hindrance difference between chiral object, its ultraviolet spectra is almost the same, exists serious
Therefore synteny can not parse correct result using conventional second order correction method.It is therefore desirable to develop more steady method
To handle the type data.According to two substance chiral systems, according to the thinking of trilinear model, it can propose that limitation three is linear
Model：
Wherein, xijkIt is three-dimensional data battle arrayXIn element,XSize be I × J × K；ain、bjnAnd cknIt is size respectively
For the element in the chromatography matrix A of I × N, the spectrum matrix B that size is J × N, the relative concentration Matrix C that size is K × N；
eijkIt is three-dimensional residual error battle arrayEIn element；N is represented because of subnumber, it is the components of interest and interference and the back of the body for having physical significance
The summation of scape ingredient.Based on limitation trilinear model, following equation is to set up：
Xi..=[B(:,1),B(:,1),B(:,3:N)]diag(A(i,:))CT+Ei..(i=1,2 ..., I) (17)
X.j.=Cdiag ([B(j,1),B(j,1),B(j,3:N)])AT+E.j.(j=1,2 ..., J) (18)
X..k=Adiag (C(k,:))[B(:,1),B(:,1),B(:,3:N)]T+E..k(k=1,2 ..., K) (19)
Wherein, Xi..、X.j.、X..kRespectivelyXSlice matrix along tri- directions i, j, k；Ei..、E.j.、E..kThe respectively edges E
I, the slice matrix in tri- directions j, k；B(:,n)For the n-component column vector of B；B(:,3:N)For by the 3rd a row to the end of matrix B
The matrix that vector is formed, if N=3, B(:,3:N)For the 3rd column vector of B；A(i,:)For i-th of column vector of A；C(k,:)
For k-th of column vector of C；diag(A(i,:)) and diag ([B(j,1),B(j,1),B(j,3:N)]) it is diagonal matrix, diagonal element
Respectively with A(i,:)[B(j,1),B(j,1),B(j,3:N)] corresponding；SubscriptTFor matrix transposition operation.Based on limitation trilinear model,
Limitation Alternating trilinear decomposition algorithm (RATLD) can be built, object function structure is as follows：
Wherein | | | |FThe F norms or Frobenius moulds of matrix.B(:,1)It, can for the ultraviolet spectrogram of homochiral substance
It is obtained with to pure material directly measure by HPLC-DAD.A, B can be solved according to object above function(:,3:N)
And C：
A(i,:)=diagm ([B(:,1),B(:,1),B(:,3:N)]+Xi..(CT)+) (i=1,2 ..., I) (10)
Wherein diagm () extracts the element on matrix diagonals, and is arranged into a column vector.RATLD algorithm meters
Calculation process is as follows：
A) chiral object ultraviolet spectra B is measured(:,1), and be normalized；
B) random initializtion matrix A and B(:,3:N)；
C) C is calculated according to formula (12), nonnegativity restrictions is carried out to C
D) A is calculated according to formula (10), nonnegativity restrictions is carried out to A, and normalization by column is carried out to A；
E) B is calculated according to formula (11)(:,3:N), to B(:,3:N)Nonnegativity restrictions is carried out, and to B(:,3:N)One is advised by column
Change；
F) C is calculated according to formula (12), nonnegativity restrictions is carried out to C；
G) step d)-f are repeated) until meeting convergence：
In above formula, m is current iteration number, and SSR is residual sum of squares (RSS), and the maximum value of m is 1000.
After obtaining chromatography matrix A, spectrum matrix B and concentration matrix C, the chromatogram and spectrum of chiral material to be measured are utilized
Figure determines the position of chiral material to be measured in a matrix, then carries out regression analysis successively to two chiral materials.
Regression analysis is such as carried out by taking R- dinotefuran as an example：First determining position of the R- dinotefuran in parsing matrix (for example is
First row), the parsing concentration C of calibration set sample is determined in parsing concentration matrix1, utilize C1With actual concentration vector C0It establishes
Calibration model：
C0=C1*b (15)
Wherein b is regression coefficient, least square method can be utilized to obtain；After obtaining calibration model, then verification collection
Parse concentration C2With the parsing concentration C of forecast set sample3It brings into calibration model and collects and R- in forecast set sample to get to verification
The concentration of dinotefuran.
Compared with prior art, the chiral column of the present invention and mobile phase selection require relatively low, it is only necessary to which there are separating effects
, chiral material need not be made to be kept completely separate on chiral column.The present invention may be implemented specific in the case where unknown disturbances coexist
The quick detection of chiral material.The invention avoids the conventional method waste plenty of time to screen chiral column column type and mobile phase,
Have the characteristics that quick, green, environmentally friendly.
Description of the drawings
Fig. 1 R- dinotefuran and S- dinotefuran chromatograms.
Fig. 2 HPLC-DAD measure the ultraviolet spectrogram of R- dinotefuran and S- dinotefuran.
The projection of Fig. 3 vector subspaces combines Monte-Carlo Simulation Method to carry out number of components estimation to HPLC-DAD data：
(a) it is I direction projection residual errors；(b) it is J direction projection residual errors.
Fig. 4 RATLD analysis results when number of components is selected as 3：(a) it is chromatogram；(b) it is spectrogram.
Specific implementation mode
Inventive technique scheme is described further with reference to specific embodiment：
Involved reagent in following embodiment：
S- dinotefuran and R- dinotefuran are that analysis is pure, are bought in Guangzhou Yao Bo chemical research Co., Ltd.Sodium chloride
(A.R., Xilong Chemical Co., Ltd)；Acetonitrile (HPLC, German Merck companies)；(HPLC, German Merck are public for n-hexane
Department)；Ethyl alcohol (HPLC, German Merck companies)；(mono- propyl ethylenediamines of N (Agela Technologies companies)；Anhydrous slufuric acid
Magnesium (A.R., Chengdu Ke Long chemical reagents factory), 550 DEG C of baking 5h, cooling are for use；
Embodiment 1S- dinotefuran and the detection and analysis of R- dinotefuran
A. prepare calibration set sample：It dissolves S- dinotefuran and R- dinotefuran mark product respectively using n-hexane, is made into a concentration of
10mg/L working solutions, and mixed by 1 concentration of table,
R- dinotefuran and S- dinotefuran concentrations in 1 calibration set sample of table
B. prepare verification collection sample：
It takes not by dinotefuran Polluted Paddy, being used in combination food to smash to pieces, pulp grinder crushes and mixing, accurate title 1.0g are with cover in 5mL
Disposable plastic pipe in, be separately added into a certain amount of chiral object standard solution, make the two chiral objects addition concentration be respectively
5.0mL acetonitriles are added in 0.1mg/kg, 0.5mg/kg and 1.5mg/kg, vibrate 30min, add 1.0g sodium chloride, vortex 1min, with
5000r/min rotating speeds centrifuge 10min, take supernatant liquor 2.5mL in 5mL disposable plastic pipes, and 30mg graphitic carbon blacks are added,
Mono- propyl ethylenediamines (PSA) of 100mgN, 100mg anhydrous magnesium sulfates, vortex 1min centrifuge 5min with 8000r/min rotating speeds, then
Take supernatant liquor 1mL, after nitrogen drying, be added 1mL n-hexane dissolutions, after 0.22 μm of membrane filtration, that is, obtain described in wait testting
Card collection sample, each concentration level are repeated 3 times；
C. prepare forecast set sample：
Rice plant sample to be measured is taken, being used in combination food to smash to pieces, pulp grinder crushes and mixing, accurate title 1.0g are with cover in 5mL
In disposable plastic pipe, 5.0mL acetonitriles are added, vibrates 30min, adds 1.0g sodium chloride, vortex 1min, with 5000r/min rotating speeds
10min is centrifuged, takes supernatant liquor 2.5mL in 5mL disposable plastic pipes, 30mg graphitic carbon blacks, mono- propyl second of 100mgN is added
Diamines (PSA), 100mg anhydrous magnesium sulfates, vortex 1min centrifuge 5min with 8000r/min rotating speeds, then take supernatant liquor 1mL,
After nitrogen drying, 1mL n-hexane dissolutions are added and obtains the pre- test sample to be measured after 0.22 μm of filter membrane filter, each waits for test sample
Three Duplicate Samples are arranged in product.
D. instrument and chromatographic condition
Based on HPLC-DAD instruments screening with separating effect chiral column and mobile phase (chiral object on chiral column not
Need to be kept completely separate), and correction sample, verification sample and pre- test sample are detected.
High performance liquid chromatography parameter setting is as follows：Instrument is high performance liquid chromatograph (Agilent 1260)；Chromatographic column is selected
For Daicel IB-3, (solvent-resisting chiral column, Silica Surface are covalently bonded with (3, the 5- dimethylphenylamino first of cellulose-three
Acid esters)；Mobile phase is selected as n-hexane (A)-ethyl alcohol (B)；Flow rate set is 0.6mL/min；Column oven temperature is 40 DEG C；Sample introduction
Amount is 30uL.
Detector is diode array detector (DAD), and scanning range 230-400nm is spaced 2nm.
Before sample introduction, sample is first with 0.22 μm of organic membrane filtration.
Chromatography testing result is as shown in Figure 1, it is seen that the chromatography delivery time of S- dinotefuran is 11.3-11.9min (Fig. 1
(a)), the chromatography delivery time of R- dinotefuran is 11.4-12.0min (Fig. 1 (b)), so, when two chiral objects detect simultaneously
When, there are problems that serious overlap of peaks, at this point, conventional method is to need to grope instrument condition again or attempt other chiralitys
Chromatographic column and mobile phase make two chiral objects be kept completely separate, but this process is fairly time consuming laborious, moreover, when unknown dry
Disturb object similarly also influences its quantitative result in chiral object delivery time appearance.But " the number based on Chemical Measurement second order correction
Credit from " enhancing " chromatographic isolation " thinking can be very good to solve chromatographic peak overlap problem, and may be implemented in unknown disturbances
The fast quantitative analysis of the lower substances of interest of eluting peak interference altogether.
E. calibration model foundation and regression analysis：First by calibration set sample, verification collection sample and forecast set sample
HPLC-DAD data form three-dimensional data battle array X, and vector subspace projection is recycled to determine the system factor in conjunction with Monte Carlo simulation
Number, and the limitation Alternating trilinear decomposition algorithm utilized parses three-dimensional data battle array, finally establishes straightening die using calibration set
Type, and regression analysis is carried out to S- dinotefuran in verification sample and pre- sample and R- dinotefuran concentrations.
In step e, the HPLC-DAD data that each sample measures are 2-D data battle array, and size is I × J, and wherein I is
Time dimension, size are time dimension gathered data point number；J is spectral Dimensions, and size is spectral Dimensions gathered data
Point number.The 2-D data of each sample is stacked up and just constitutes three-dimensional data battle arrayX, size is I × J × K, wherein K
Value for sample dimension, K is sample number.
Using vector subspace projection combine Monte-Carlo Simulation Method (VSPMCS) determine system because subnumber process such as
Under：
A) in three-dimensional data battle arrayXIn, obtain a pseudo- sample battle array R along the directions I1：
In above formula, Xi..For three-dimensional data battle arrayXI-th of slice matrix along the directions I；
wiIt is the random data generated by Monte-Carlo Simulation Method, size utilizes singular value point between 0 to 1
Solution (SVD) method takes X..kTop n principal component build sample battle array M..k：
[U, S, V]=svds (X..k,N) (2)
M..k=USVT (3)
Wherein, X..kFor three-dimensional data battle array X matrix is sliced along the directions K k-th；
B) pseudo- matrix R2 is built：
Wherein, wiWith the w in equation (1)iIt is identical；
Then singular value decomposition is utilized to handle two pseudo- matrix R1And R2：
[U1,S1,V1]=svd (R1) (5)
[U2,S2,V2]=svd (R2) (6)
U is calculated according to following equation1And U2In corresponding vector projection residual errors：
In above formula, DI(n)Indicate projection residual errors, U1(n)And U2(n)It is U respectively1And U2N-component column vector, IJIndicate size
For the unit matrix of J × J, subscript+It is Moore-Penrose generalized inverse matrix, DI is that its vectorial size is 1 × N；
C) at least 50 groups of w are randomly generated using Monte-Carlo Simulation MethodiNumerical value carries out repeating step a)-b), calculate phase
Answer the average value DI of projection residual errorsN(DINFor vector, its size is 1 × N), to DINThe jumping point to change from small to big suddenly is corresponding
Because of subnumber NIThe as system component number of pre-estimation；
D) projection residual errors DJ is found out along the directions JNAnd estimate another number of components NJ；From NIAnd NJIt is middle to judge final system
Number of components；
Vector subspace projection can be refering to document (Yong Li, et in conjunction with the specific steps of Monte-Carlo Simulation Method
al.Estimating the chemical rank of three-way fluorescence data by vector
subspace projection with Monte Carlo simulation.Chemometrics and Intelligent
Laboratory Systems,2014,136:15-23)。
Fig. 3 is that vector subspace projection combines Monte-Carlo Simulation Method to system component number estimated result, it is found that
First three projection residual errors is equal to 0 or increases suddenly close to the projection residual errors of 0, the 4th factor, this explanation is in system component
Number should be estimated as 3.
In step e, based on limitation trilinear model, limitation alternating projection method (RATLD) can be built,
Object function structure is as follows：
Wherein | | | |FThe F norms or Frobenius moulds of matrix；
B(:,1)For the ultraviolet spectrogram of homochiral substance, can by HPLC-DAD to pure material carry out directly measurement come
It obtains, A, B can be solved according to object above function(:,3:N)And C：
A(i,:)=diagm ([B(:,1),B(:,1),B(:,3:N)]+Xi..(CT)+) (i=1,2 ..., I) (10)
Element on wherein diagm () extraction matrix diagonals is arranged into a column vector；
RATLD algorithm calculating process is as follows：
A) chiral object ultraviolet spectra B is measured(:,1), and be normalized；
B) matrix A and B are initialized(:,3:N)；
C) C is calculated according to formula (12), nonnegativity restrictions is carried out to C
D) A is calculated according to formula (10), nonnegativity restrictions is carried out to A, and normalization by column is carried out to A；
E) B is calculated according to formula (11)(:,3:N), to B(:,3:N)Nonnegativity restrictions is carried out, and to B(:,3:N)One is advised by column
Change；
F) C is calculated according to formula (12), nonnegativity restrictions is carried out to C；
G) step d)-f are repeated) until meeting convergence：
In above formula, m is current iteration number, and SSR is residual sum of squares (RSS), and the maximum value of m is 1000；
After obtaining chromatography matrix A, spectrum matrix B and concentration matrix C, the color of component to be measured (R- and S- dinotefuran) is utilized
Spectrogram and spectrogram determine the position of component to be measured in a matrix, then carry out regression analysis successively to two components.With R-
Regression analysis is carried out for dinotefuran：It first determines position (for example be first row) of the R- dinotefuran in parsing matrix, is parsing
The parsing concentration C of calibration set sample is determined in concentration matrix1, utilize C1With actual concentration vector C0Establish calibration model：
C0=C1*b (15)
Wherein b is regression coefficient, least square method can be utilized to obtain；After obtaining calibration model, then verification collection
Parse concentration C2With the parsing concentration C of forecast set sample3It brings into calibration model and collects and R- in forecast set sample to get to verification
The concentration of dinotefuran.The concentration of S- dinotefuran in collection and forecast set can be similarly verified.Specific separate regression steps can be refering to
Document (Fundamentals and analytical applications of multi-way calibration,
Alejandro C.Olivieri,Graciela M.Escandar, C.Goicoechea,Arseniooz de
laA, Editors.2015, Chapter 4-Practical Analytical Applications of Multiway
Calibration Methods Based on Alternating Multilinear Decomposition)。
Fig. 3 is the factor when being 3, the chromatogram and spectrogram that RATLD arithmetic analysis goes out, and thus figure is as can be seen that RATLD
It parses S- dinotefuran and R- dinotefuran chromatogram and true color spectra figure is substantially overlapping, qualitative results are satisfied.In addition RATLD
Also an interfering substance is parsed, illustrates that the interested quick measurement in the case where unknown disturbances coexist may be implemented in RATLD algorithms.
, the average recovery rate results contrast of S- and R- dinotefuran as shown in table 2 to the prediction result of verification collection sample using calibration model
It is satisfied, prove that development approach is feasible.In pre- sample, the chiral object a concentration of 0.7 of S- dinotefuran and R- dinotefuran is measured
± 0.1mg/kg and 1.0 ± 0.1mg/kg.
2 forecast sample concentration of table and average recovery rate
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, several improvement can also be made without departing from the principle of the present invention, these improvement also should be regarded as the present invention's
Protection domain.
Claims (2)
1. a kind of method based on limitation Alternating trilinear decomposition algorithm and HPLC-DAD Instrument measuring chiral materials, specific steps
It is as follows：
1) prepare calibration set sample：The mixed solution for preparing the chiral material of gradient concentration, as calibration set sample；
2) prepare verification collection sample：Chiral object mark product are added in the sample to be tested without chiral object, according to this field routine sample
Product processing method extracts sample to be tested；
3) prepare forecast set sample：Except not adding chiral object standard items, the processing of sample to be tested and verification collection sample in forecast set
Step is consistent；
4) based on chiral column of the HPLC-DAD instruments screening with separating effect and mobile phase, (chiral object does not need on chiral column
It is kept completely separate), and calibration set sample, verification collection sample and forecast set sample are detected.
5) calibration model foundation and regression analysis：First by calibration set sample, the HPLC- of verification collection sample and forecast set sample
DAD data form three-dimensional data battle arrayX, vector subspace projection is recycled to determine system component in conjunction with Monte-Carlo Simulation Method
Number, and three-dimensional data battle array is decomposed using limitation Alternating trilinear decomposition algorithm, calibration model finally is established using calibration set, and
Regression analysis is carried out to the concentration of chiral material in verification sample and pre- sample；
5.1) described projected using vector subspace determines that system is as follows because of the process of subnumber in conjunction with Monte-Carlo Simulation Method：
5.1.1) in three-dimensional data battle arrayXIn, obtain a pseudo- sample battle array R along the directions I1：
In above formula, Xi..For three-dimensional data battle arrayXI-th of slice matrix along the directions I；
wiIt is the random data generated by Monte-Carlo Simulation Method, size utilizes singular value decomposition between 0 to 1
(SVD) method takes X..kTop n principal component build sample battle array M..k：
[U, S, V]=svds (X..k,N) (2)
M..k=USVT (3)
Wherein, X..kFor three-dimensional data battle arrayXK-th of slice matrix along the directions K；
5.1.2 pseudo- matrix R) is built2：
Wherein, wiWith the w in equation (1)iIt is identical；
Then singular value decomposition is utilized to handle two pseudo- matrix R1And R2：
[U1,S1,V1]=svd (R1) (5)
[U2,S2,V2]=svd (R2) (6)
U is calculated according to equation (7)1And U2In corresponding vector projection residual errors：
In above formula, DI(n)Indicate projection residual errors, U1(n)And U2(n)It is U respectively1And U2N-component column vector, IJExpression size be J ×
The unit matrix of J, subscript+It is Moore-Penrose generalized inverse matrix, DI is that its vectorial size is 1 × N；||.||FFor matrix
F norms；
5.1.3 at least 50 groups of w) are randomly generated using Monte-Carlo Simulation MethodiNumerical value carries out repeating step 5.1.1) -5.1.2),
Calculate the average value DI of homolographic projection residual errorN, DINFor vector, DINValue be 1 × N, and obtain the system component number of pre-estimation
NI；
5.1.4) projection residual errors DJ is found out along the directions JNAnd estimate another number of components NJ；From NIAnd NJIt is middle to judge final system group
Score；
5.2) the object function structure of the limitation Alternating trilinear decomposition algorithm is as follows：
Wherein, Xi..、X.j.RespectivelyXSlice matrix along the directions i and j；A is the chromatography matrix that size is J × N；[B(:,1),
B(:,1),B(:,3:N)] it is the relative spectral matrix B that size is K × N；C is the relative concentration matrix that size is K × N；B(:,n)For B's
N-component column vector；B(:,3:N)For by the 3rd matrix that a column vector is formed to the end of matrix B；A(i,:)For A arrange for i-th to
Amount；diag(A(i,:)) and diag ([B(j,1),B(j,1),B(j,3:N)]) be diagonal matrix, diagonal element respectively with A(i,:)With
[B(j,1),B(j,1),B(j,3:N)] corresponding；SubscriptTFor matrix transposition operation；B(:,1)For the ultraviolet spectrogram of homochiral substance；Root
A, B are solved according to object above function(:,3:N)And C：
A(i,:)=diagm ([B(:,1),B(:,1),B(:,3:N)]+Xi..(CT)+) (i=1,2 ..., I) (10)
Wherein diagm () extracts the element on matrix diagonals, and is arranged into a column vector；
5.3) the limitation Alternating trilinear decomposition algorithm calculating process is as follows：
5.3.1 chiral object ultraviolet spectra B) is measured(:,1), and be normalized；
5.3.2) random initializtion matrix A and B(:,3:N)；
5.3.3 C) is calculated according to formula (12), nonnegativity restrictions is carried out to C；
5.3.4 A) is calculated according to formula (10), nonnegativity restrictions is carried out to A, and normalization by column is carried out to A；
5.3.5 B) is calculated according to formula (11)(:,3:N), to B(:,3:N)Nonnegativity restrictions is carried out, and to B(:,3:N)One is advised by column
Change；
5.3.6 C) is calculated according to formula (12), nonnegativity restrictions is carried out to C；
5.3.7 step 5.3.4-5.3.6) is repeated until meeting following convergence：
In above formula, m is current iteration number, and SSR is residual sum of squares (RSS), and the maximum value of m is 1000.Final acquisition chromatography matrix A,
Spectrum matrix B and concentration matrix C.
5.4) after obtaining chromatography matrix A, spectrum matrix B and concentration matrix C, using the chromatogram and spectrogram of chiral material come really
Determine the position of chiral material in a matrix, regression analysis is then carried out successively to two kinds of chiral materials；5.4.1) establish straightening die
Type：
C0=C1*b (15)
Wherein, C0For actual concentration vector, C1For the parsing concentration of calibration set sample, b is regression coefficient；
5.4.2) by the parsing concentration C of verification collection2With the parsing concentration C of forecast set sample3It brings into calibration model to get to testing
The concentration of chiral material in card collection and forecast set sample.
2. according to claim 1 based on limitation Alternating trilinear decomposition algorithm and HPLC-DAD Instrument measuring chiral materials
Method, which is characterized in that calibration set sample described in step 5, verification collect sample and the HPLC-DAD data of forecast set sample are
2-D data battle array, size are I × J, and wherein I is time dimension, and the value of I is time dimension gathered data point number；J is light
Dimension is composed, the value of J is spectral Dimensions gathered data point number；The 2-D data of each sample is stacked up and just constitutes three
Dimension data battle arrayX, size is I × J × K, and wherein K is sample dimension, and the value of K is sample number.
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