CN102087212B - Pueraria lobata starch adulteration identification method based on principal component analysis - Google Patents
Pueraria lobata starch adulteration identification method based on principal component analysis Download PDFInfo
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Abstract
The invention relates to an identification method of an infrared spectrum, in particular to a pueraria lobata starch adulteration identification method based on principal component analysis (PCA). The method specifically comprises the following steps: tabletting pueraria lobata starch or starch composition mixed with other starch in the pueraria lobata starch to prepare samples and carrying out intermediate infrared scanning under the condition that the wavelength range is 4000-500cm<-1> to obtain the infrared spectrum; carrying out PCA after carrying out baseline adjustment, smoothing processing and vector normalization processing on the infrared spectrum to obtain the principal component score; and carrying out discriminant analysis (DA) on the obtained principal component score and judging pueraria lobata starch adulteration from the DA result. The method has the following beneficial effects: the infrared spectrum of starch is introduced into study; in combination with the chemical analysis and meterage method, the method is simple and easy to operate, has the advantages of rapidness and accuracy; and the correction recognition rate is 100%.
Description
Technical field
The present invention relates to the authentication method of infrared spectrum, particularly kudzuvine root starch is mingled discrimination method.
Background technology
The root of kudzu vine be the legume Pueraria lobota (
Pueraria lobata Ohwi) root, be a kind of medicine, the dual-purpose natural plant resource of food.The kudzuvine root starch that with the root of kudzu vine is raw material production is a kind of wild plant starch of high-quality, not only is rich in each seed amino acid and calcium, iron, zinc, the selenium and other trace elements of needed by human, also contains materials such as isoflavones, Puerarin, have clearing heat and detoxicating, effect such as promote the production of body fluid to quench thirst.Illegal retailer in the market mingles in pure kudzuvine root starch such as cheap potato starch such as sweet potato powder, dehydrated potato powder in order to earn profit in large quantities, attempts to mix the genuine with the fictitious, mix the spurious with the genuine.This makes the consumer suffer deception undoubtedly, and market prestige is had a greatly reduced quality.Kudzuvine root starch detection technique commonly used comprises proterties comparison, microscope comparison and liquid chromatography etc.They exist such as similar performance between the starch, can't accurately detect; Shortcoming and restrictions such as instrumentation is complicated, and is expensive.Therefore, the kudzuvine root starch trade market presses for a kind of quick, accurate and economic true and false authentication technique.
Infrared spectrum (infrared spectroscopy, IRS) not only can decision making to the chemical constitution of material, and can set up the characteristic fingerprint pattern of sample by technology.And fast with its analysis speed, efficient is high; Sample does not generally need pre-service; Analysis cost is low, and is pollution-free; Be convenient to on-line analysis; Advantage such as easy and simple to handle becomes the research focus of food security and field of quality control.Gurdeniz G etc. utilizes Pure Olive Oil and mingles the infrared spectrum of sample, and combines principal component analysis (PCA) to differentiate.The result shows that the ratio of in olive oil, mixing sunflower oil, rapeseed oil, cottonseed oil is higher than 5%, mingles sample and can successfully be differentiated.Cozzolino D etc. carry out conventional physics and chemistry to organic and non-organic red wine and detect and middle infrared scan, and combine principal component analysis (PCA) to distinguish.Find that through contrast organic red wine and the distributed areas of non-organic red wine in two-dimentional major component distribution plan there are differences, and use this method successfully the two to be differentiated.Combination fourier transform such as Paradkar M M and Raman spectrum scan honey, and through principal component analysis (PCA) to mixing beet sugar in the honey and cane suger is differentiated.The result shows that nectar is mingled sample and can successfully be distinguished, and correct recognition rata is higher than 95%.Karoui R etc. extract the characteristic light spectral coverage in the mid infrared spectrum of the cheese of two kinds of different cultivars, in conjunction with principal component analysis (PCA) and discriminatory analysis sample is differentiated.The result shows, at characteristic light spectral coverage 2 800～3 000cm
-1With 900～1 500cm
-1The accurate discrimination that obtains is respectively 90.9% and 90.5%.At present, for using infrared spectrum to differentiate that the kudzuvine root starch true and false yet there are no report.In the prior art; The discriminating of pueraria starch and adulterated product thereof only can depend on the shared characteristics such as ratio of long-chain short chain in ratio and the amylopectin of form, size, structure, component, straight chain and amylopectin of various plant amylums, and is also rare based on the IR spectroscopy study of identification.
Summary of the invention
In view of this, the object of the present invention is to provide a kind of kudzuvine root starch based on principal component analysis to mingle discrimination method, this method is to realize that through the principal component analysis (PCA) to infrared spectrum its discrimination is high, and is simple to operate.
For realizing above-mentioned purpose, technical scheme of the present invention is:
Kudzuvine root starch based on principal component analysis is mingled discrimination method, specifically may further comprise the steps:
Obtaining of A, standard infared spectrum: the starch composites compressing tablet that mixes other starch in kudzuvine root starch or the kudzuvine root starch is processed sample, is 4000～500cm in wavelength coverage
-1Carry out middle infrared scan under the condition, get the standard infared spectrum;
B, standard principal component analysis: steps A gained standard infared spectrum is carried out carrying out principal component analysis after baseline adjustment, smoothing processing and vector normalization are handled, and the standard of acquisition master composition score;
C, discriminatory analysis: step B gained standard master composition score is carried out discriminatory analysis, get discriminant function;
D, mingle judgement: unknown sample to be detected is carried out obtaining of infared spectrum and principal component analysis, and as a result in the substitution discriminant function, unknown sample gained functional value the maximum is corresponding group, and then kudzuvine root starch is mingled with its principal component analysis.
Further, in the steps A, or/and to mix weight ratio in the kudzuvine root starch be that the composition grouping compressing tablet of starch from sweet potato/potato starch of 7:3,5:5,3:7 and 0:10 is processed sample, every group of sample number>=5 are 4000～500cm in wavelength coverage with kudzuvine root starch
-1Carry out middle infrared scan under the condition, get the standard infared spectrum;
Further, among the step C, step B gained standard master composition score is carried out the Fisher discriminatory analysis, gets following discriminant function:
Mix starch from sweet potato in the kudzuvine root starch:
f
Kudzuvine root starch=-3.757X
1+ 8.731X
2+ 1.290X
3-0.0012;
f
Starch from sweet potato=0.970X
1+ 0.517X
2-0.041X
3-171.963;
f
30% mingles=0.641X
1-1.248X
2-0.324X
3-34.801;
f
50% mingles=0.503X
1-1.982X
2-0.164X
3-60.753;
f
70% mingles=0.357X
1-1.876X
2-0.180X
3-59.225.
Mix farina in the kudzuvine root starch:
f
Kudzuvine root starch=0.399X
1-0.188X
2+ 0.272X
3-56.476;
f
Farina=-0.235X
1+ 0.124X
2+ 0.895X
3-30.675;
f
30% mingles=0.165X
1+ 0.035X
2-0.635X
3-17.834;
f
50% mingles=0.034X
1-0.031X
2+ 0.824X
3-18.599;
f
70% mingles=-0.264X
1+ 0.042X
2+ 0.549X
3-24.581;
Wherein, X
1,
,X
2And X
3Main respectively composition score comes preceding 3 main composition successively.
Beneficial effect of the present invention is: this law is introduced research with the infrared spectrum of starch, through combining the stoichiometry analytical approach, obtains simple and easy, the kudzuvine root starch discrimination method fast and accurately of a kind of operation, and its correct recognition rata is 100%.
Description of drawings
In order to make the object of the invention, technical scheme and advantage clearer, will combine accompanying drawing that the present invention is made further detailed description below, wherein:
Fig. 1 mingles the infared spectrum of sweet potato powder for kudzuvine root starch;
Fig. 2 mingles the infared spectrum of dehydrated potato powder for kudzuvine root starch;
Fig. 3 mingles the principal component analysis (PCA) figure of sweet potato powder for kudzuvine root starch;
Fig. 4 mingles the principal component analysis (PCA) figure of dehydrated potato powder for kudzuvine root starch.
Embodiment
In order to make the object of the invention, technical scheme and advantage clearer, below the preferred embodiments of the present invention are described in detail.
In order to make the object of the invention, technical scheme and advantage clearer, the preferred embodiments of the present invention are described in detail below in conjunction with accompanying drawing.
1 materials and methods
1.1 experiment material and specimen preparation
Kudzuvine root starch: one-level, treasure peak, Chongqing biological products Ltd (development of Food Science institute of Southwestern University); Starch from sweet potato: Jiangbei District, Chongqing City crossdrift two brother Bean Products Factories; Farina: gold field, Chongqing agricultural development company limited.Sample places exsiccator to be cooled to room temperature through the dry 2h of baking oven (105 ℃) then.Take by weighing sample by table 1 through the accurate essence of electronic balance.Prepare 110 in sample altogether, 55 are used for modeling, and 45 are used for checking.Sample powder is ground in the ratio of 1:50 with the potassium bromide powder, and each mensuration accurately takes by weighing 0.1g and carries out compressing tablet, and measures infrared spectrum.
Table 1 kudzuvine root starch and the preparation of mingling kudzuvine root starch
1.2 experimental apparatus
The Spectrum GX of Perkin-Elmer company FTIS, DTGS detecting device, spectral resolution 4 cm
-1, sweep limit 4 000～400cm
-1, scanning times 16 times, immediate removal moisture content and CO during scanning
2Background interference.The Spectrum 2.0 function softwares collection and the processing infared spectrum that adopt infrared spectrometer to carry.
1.3 data processing
Through measuring, obtain the infrared spectrogram of sample powder.With the sample is object, is index with different wave number sections and absorbance thereof.Former spectrum data imported among the Unscrambler 7.8 as data source with the JCAMP-DX form carry out principal component analysis (PCA).After obtaining the principal component scores value, use SPSS 16.0 softwares to carry out discriminatory analysis.
Result and analysis
2.1 kudzuvine root starch compares with the infrared spectrum of mingling kudzuvine root starch
The infared spectrum that among Fig. 1 and Fig. 2 is three kinds of starch does not have too big-difference, all at 2800～3100cm
-1The place occurred-the stretching vibration absorption peak of CH; At 3500～3000cm
-1Occurred in the scope-the stretching vibration absorption peak of OH; At 1000cm
-1About C-C stretching vibration absorption peak in the sugar ring appears; At 1634 cm
-1Near the stretching vibration district of C=O or C=C appears.Infrared spectrogram concentrated expression has gone out some essential informations of three kinds of starch constituents.Therefore can find out that all there are very big similarity in the peak shape at spectral absorption peak and peak position, need to combine multivariate statistical analysis that the infrared spectrum that obtains is handled, to set up kudzuvine root starch and to mingle the discriminating model of kudzuvine root starch.
2.2 principal component analysis (PCA)
(principal component analysis PCA) can become one group of new variable with original variable linear combination, and promptly one group of major component only just can be expressed the main information of original variable with the part major component in principal component analysis (PCA).Utilize this characteristic, can realize the linear dimensionality reduction Projection Display of ir data, thereby can from two dimension or three-dimensional image, observe the key property and the cluster situation of spectrum intuitively.Kudzuvine root starch with mingle image data in the kudzuvine root starch sample, totally 55 groups.With carrying out principal component analysis (PCA) among the gained data importing Unscrambler 7.8, make the PC scatter diagram of sample.Fig. 3,4 is kudzuvine root starch and the 1st, the 2nd principal component scores figure that mingles false kudzuvine root starch.Horizontal ordinate is represented the score value that gets of the 1st major component, and ordinate is represented the score value that gets of the 2nd major component.Simultaneously, to kudzuvine root starch with mingle kudzuvine root starch and carry out area dividing, obtain sample major component two-dimensional distribution separately.Can find out to be in the collection of illustrative plates of horizontal stroke, the longitudinal axis with PC1 and PC2, the distributed areas of mingling kudzuvine root starch and kudzuvine root starch are at a distance of more obvious, and the interior degree of polymerization of each sample is better among Fig. 3.
Through principal component analysis (PCA), obtain the contribution rate of accumulative total of variance of the major component of 55 samples, as shown in table 2.The contribution rate of accumulative total of mingling preceding 5 major components of mingling dehydrated potato powder in sweet potato powder and the kudzuvine root starch in the kudzuvine root starch has all surpassed 99%.Explain that preceding 5 major components have enough represented the important information of 55 samples.
The contribution rate of accumulative total of variance of table 2 major component
2.3 discriminatory analysis
2.3.1 set up discriminant function
(discriminant analysis, variable DA) is not The more the better, when the variable number is too much, not only can increase calculated amount, and can have influence on final differentiation effect owing to the interference of the not strong variable of differentiation power to be used for discriminatory analysis.Can find out that from table 3 preceding 5 major components of two models can represent the information of former wavelength variable more than 99%.Therefore, we choose preceding 5 major components of two models as the discriminatory analysis variable, adopt Fisher differentiation carrying out discriminatory analysis among the SPSS 16.0.At first, all variablees are done variance analysis, verify whether selected variable reaches the level of signifiance.As shown in table 3, when the Sig value less than 0. 05, the expression significant difference.
Table 3 variable The results of analysis of variance
By knowing in the table 3, two kinds of first three major components of mingling model have all reached the level of signifiance, can keep as the variable of setting up the discriminant function relational expression.It is following to set up two kinds of discriminant function relational expressions of mingling model:
Kudzuvine root starch is mingled sweet potato powder:
f
Kudzuvine root starch=-3.757X
1+ 8.731X
2+ 1.290X
3-0.0012;
f
Starch from sweet potato=0.970X
1+ 0.517X
2-0.041X
3-171.963;
f
30% mingles=0.641X
1-1.248X
2-0.324X
3-34.801;
f
50% mingles=0.503X
1-1.982X
2-0.164X
3-60.753;
f
70% mingles=0.357X
1-1.876X
2-0.180X
3-59.225.
Kudzuvine root starch is mingled dehydrated potato powder:
f
Kudzuvine root starch=0.399X
1-0.188X
2+ 0.272X
3-56.476;
f
Farina=-0.235X
1+ 0.124X
2+ 0.895X
3-30.675;
f
30% mingles=0.165X
1+ 0.035X
2-0.635X
3-17.834;
f
50% mingles=0.034X
1-0.031X
2+ 0.824X
3-18.599;
f
70% mingles=-0.264X
1+ 0.042X
2+ 0.549X
3-24.581.
2.3.2 differentiation effect
At first can utilize self checking of discriminatory analysis modeling sample is returned to declare, to verify the differentiation effect with validation-cross.The utilization cross verification often can draw than the higher False Rate of self proof method, and the confidence level that the result is declared in its time is higher.This experiment is carried out self checking and validation-cross to 55 modeling samples.Its differentiation the results are shown in Table 4,5.
Table 4 kudzuvine root starch is mingled returning of sweet potato powder and is declared the result
Self verifies accuracy rate 93.3% in the table 4, and the validation-cross accuracy rate is 86.7%; Bracket inner digital is actual sample number before judging.
Table 5 kudzuvine root starch is mingled returning of dehydrated potato powder and is declared the result
Self verify in
table 5 that accuracy rate is 100%, the validation-cross accuracy rate is 92%; Bracket inner digital is actual sample number before judging
Discriminatory analysis finally utilizes the discriminant function of its gained that unknown sample is carried out identification and classification.To three kinds of pure starch and mingle sample, each more every group prepare 5 samples (totally 45).Sample major component value is brought among the discriminant function fi.Sample gained functional value the maximum shows and belongs to corresponding one type.
Table 6 kudzuvine root starch is mingled the external certificate result of sweet potato powder
External certificate accuracy rate 96% in
table 6; Bracket inner digital is actual sample number before judging.
Table 7 kudzuvine root starch is mingled the external certificate result of dehydrated potato powder
In the table 7, external certificate accuracy rate 92%; Bracket inner digital is actual sample number before judging
External certificate shows that kudzuvine root starch is in full accord with differentiation result and the actual conditions of mingling kudzuvine root starch, and the discriminating of the kudzuvine root starch true and false can realize.Explain that selected variable is suitable to the discriminant function kudzuvine root starch of discerning the false from the genuine.Therefore, use this method to differentiate that the kudzuvine root starch true and false is successful.
Conclusion
Using infrared spectrum technology combines principal component analysis (PCA) and discriminatory analysis that the kudzuvine root starch true and false is carried out Study on Identification.Major component through extracting sample is as the input value of discriminatory analysis, and then obtains to differentiate the discrimination model of the kudzuvine root starch true and false.Through discriminatory analysis draw mingle in the kudzuvine root starch mingle in sweet potato powder and the kudzuvine root starch dehydrated potato powder self the checking accuracy rate be respectively 93.3% and 100%; The validation-cross accuracy rate is respectively 86.7% and 92%.Preparation is mingled sample and is carried out external certificate in addition, and accurately discrimination is respectively 96% and 92%, has obtained desirable precision of prediction.This paper uses Infrared Spectrum Technology to combine principal component analysis (PCA), techniques of discriminant analysis to differentiate the kudzuvine root starch true and false first.This method can be used character, the characteristic of known sample to set up kudzuvine root starch to mingle model of cognition, reach the purpose of the quick discriminating kudzuvine root starch true and false.For the fast detecting of the kudzuvine root starch true and false provides a kind of new method.Said method is not only applicable to the evaluation of kudzuvine root starch and sweet potato powder/mealy potato, is applicable to the evaluation of kudzuvine root starch and other starch yet.
Explanation is at last; Above embodiment is only unrestricted in order to technical scheme of the present invention to be described; Although through invention has been described with reference to the preferred embodiments of the present invention; But those of ordinary skill in the art should be appreciated that and can make various changes to it in form with on the details, and the spirit and scope of the present invention that do not depart from appended claims and limited.
Claims (1)
1. mingle discrimination method based on the kudzuvine root starch of principal component analysis, it is characterized in that, specifically may further comprise the steps:
Obtaining of A, standard infared spectrum: process sample with mixing the starch from sweet potato that weight ratio is 7:3,5:5,3:7 and 0:10 or the composition grouping compressing tablet of farina in kudzuvine root starch and the kudzuvine root starch, every group of sample number>=5 are 4000～500cm in wavelength coverage
-1Carry out middle infrared scan under the condition, get the standard infared spectrum;
B, standard principal component analysis: steps A gained standard infared spectrum is carried out carrying out principal component analysis after baseline adjustment, smoothing processing and vector normalization are handled, and the standard of acquisition master composition score;
C, discriminatory analysis: step B gained standard master composition score is carried out the Fisher discriminatory analysis, get following discriminant function:
Mix starch from sweet potato in the kudzuvine root starch:
f
Kudzuvine root starch=-3.757X
1+ 8.731X
2+ 1.290X
3-0.0012;
f
Starch from sweet potato=0.970X
1+ 0.517X
2-0.041X
3-171.963;
f
30% mingles=0.641X
1-1.248X
2-0.324X
3-34.801;
f
50% mingles=0.503X
1-1.982X
2-0.164X
3-60.753;
f
70% mingles=0.357X
1-1.876X
2-0.180X
3-59.225;
Mix farina in the kudzuvine root starch:
f
Kudzuvine root starch=0.399X
1-0.188X
2+ 0.272X
3-56.476;
f
Farina=-0.235X
1+ 0.124X
2+ 0.895X
3-30.675;
f
30% mingles=0.165X
1+ 0.035X
2-0.635X
3-17.834;
f
50% mingles=0.034X
1-0.031X
2+ 0.824X
3-18.599;
f
70% mingles=-0.264X
1+ 0.042X
2+ 0.549X
3-24.581;
Wherein, X
1,
,X
2And X
3Be respectively that main composition score comes preceding 3 main composition successively;
D, mingle judgement: unknown sample to be detected is carried out obtaining of infared spectrum and principal component analysis, and as a result in the substitution discriminant function, unknown sample gained functional value the maximum is corresponding group with its principal component analysis, and then judges that kudzuvine root starch mingles.
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| CN110826615A (en) * | 2019-10-31 | 2020-02-21 | 南方电网科学研究院有限责任公司 | Method, device, equipment, medium and data acquisition system for classifying pollutants |
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