CN106706545A - Method for analyzing functional group atlas of potato powder and flour mixture - Google Patents
Method for analyzing functional group atlas of potato powder and flour mixture Download PDFInfo
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- 244000061456 Solanum tuberosum Species 0.000 title claims abstract description 51
- 235000002595 Solanum tuberosum Nutrition 0.000 title claims abstract description 51
- 239000000843 powder Substances 0.000 title claims abstract description 39
- 235000013312 flour Nutrition 0.000 title claims abstract description 27
- 125000000524 functional group Chemical group 0.000 title claims abstract description 16
- 238000000034 method Methods 0.000 title claims abstract description 14
- 239000000203 mixture Substances 0.000 title claims abstract description 13
- 238000001228 spectrum Methods 0.000 claims abstract description 62
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 23
- 230000001360 synchronised effect Effects 0.000 claims abstract description 15
- 238000002156 mixing Methods 0.000 claims abstract description 11
- 230000008859 change Effects 0.000 claims abstract description 10
- 238000010219 correlation analysis Methods 0.000 claims abstract description 4
- 238000004458 analytical method Methods 0.000 claims description 13
- 230000003595 spectral effect Effects 0.000 claims description 10
- 230000000694 effects Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 5
- 238000009835 boiling Methods 0.000 claims description 4
- 238000002360 preparation method Methods 0.000 claims description 4
- 238000004140 cleaning Methods 0.000 claims description 3
- 230000003068 static effect Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 230000006698 induction Effects 0.000 claims description 2
- 235000013305 food Nutrition 0.000 abstract description 10
- 230000003993 interaction Effects 0.000 abstract description 2
- 238000011156 evaluation Methods 0.000 abstract 1
- 238000004519 manufacturing process Methods 0.000 abstract 1
- 235000015097 nutrients Nutrition 0.000 abstract 1
- 230000000875 corresponding effect Effects 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 8
- 229920002472 Starch Polymers 0.000 description 5
- 235000013339 cereals Nutrition 0.000 description 5
- 235000019698 starch Nutrition 0.000 description 5
- 239000008107 starch Substances 0.000 description 5
- 239000000463 material Substances 0.000 description 4
- 235000016709 nutrition Nutrition 0.000 description 4
- 230000035764 nutrition Effects 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 238000004566 IR spectroscopy Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004445 quantitative analysis Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 241000208340 Araliaceae Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000005100 correlation spectroscopy Methods 0.000 description 1
- 239000013078 crystal Substances 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 235000005911 diet Nutrition 0.000 description 1
- 230000000378 dietary effect Effects 0.000 description 1
- 235000006694 eating habits Nutrition 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 239000000796 flavoring agent Substances 0.000 description 1
- 235000019634 flavors Nutrition 0.000 description 1
- 235000008434 ginseng Nutrition 0.000 description 1
- 235000011868 grain product Nutrition 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 235000012149 noodles Nutrition 0.000 description 1
- 229920000642 polymer Polymers 0.000 description 1
- 238000012805 post-processing Methods 0.000 description 1
- 102000004169 proteins and genes Human genes 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000007873 sieving Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000001845 vibrational spectrum Methods 0.000 description 1
- 238000007704 wet chemistry method Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
- G01N2021/3572—Preparation of samples, e.g. salt matrices
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Abstract
The invention discloses a method for analyzing a functional group atlas of a potato powder and flour mixture. The method comprises the following steps of preparing a plurality of varieties of potato powder and flour mixing samples, and collecting infrared spectrums of each potato powder and flour mixing sample under the condition of temperature outer disturbance; calculating the dynamic spectrum of the infrared spectrum of the mixing sample induced by the temperature outer disturbance; performing two-dimensional correlation analysis on the dynamic spectrum of each sample, and obtaining the corresponding synchronous two-dimensional correlation spectrum; analyzing the functional group atlas of the synchronous two-dimensional correlation spectrum of each sample. The method has the advantages that the molecular structure change and the interaction of the potato powder and flour mixture are studied, the change rule of functional groups of potato powder and flour of different varieties under different mixing ratios is disclosed, and a reference is provided for the optimizing and improving of potato staple food manufacturing and processing, and the evaluation of nutrients and efficiencies of potato staple food.
Description
Technical field
The present invention relates to the use of infrared light test or analysis of material detection method, and in particular to a kind of potato full-powder
With functional group's atlas analysis method of flour blend.
Background technology
China starts potato staple food grainization strategy at the beginning of 2015, selected, clean, go with fresh potato as raw material
Skin, cut into slices, rinse, precooking, cooling down, boiling, the technical process such as smash mud, dehydrate potato full-powder is obtained.Potato full-powder
Easily storage, and maintains the distinctive nutrition of potato and local flavor, it is mixed with flour by a certain percentage post-processing be made steamed bun,
The staple food of suitable Chinese's eating habit such as noodles, this will substantially improve and enrich the dietary nutrition structure of China resident, meet
The need for human body is to nutrition-allocated proportion.But there is potato full-powder specific breed shortage in current potato staple food grain progradation,
Potato full-powder mixed proportion is relatively low in potato staple food grain, the problems such as potato staple food grain product price is high.
Some technologies detected for farina, potato full-powder and its product are occurred in that in recent years, it is such as near
Infrared spectrum modeling analysis.Research based near infrared spectrum is mainly for the nutrition such as reduced sugar, protein in potato full-powder
Composition has carried out quantitative analysis, and also scholar has carried out quantitative analysis to dry, starch etc..Many near-infrared model prediction knots
Fruit precisely, but models required sample size greatly, and model failure has to be solved.
Two-dimensional correlation spectra technology is that the spectrum by script in the one-dimensional space is extended to two-dimensional space, to reach enhanced spectrum
The effect of resolution ratio, two-dimensional correlation spectra technology is often used together with reference to infrared spectrum detection technique, and infrared spectrogram is divided into spy
Frequency zones and fingerprint region are levied, the absworption peak number in characteristic frequency area is few, but with very strong characteristic, in group identification work
On it is very valuable.Fingerprint region peak is more complicated, does not have strong characteristic, but when molecular structure is slightly different, area's absworption peak
Nuance will be produced, the fingerprint region compound similar for difference structure is helpful.So two-dimensional correlation spectra technology
After with reference to infrared spectrum technology, so that it may by determining the influence of infrared vibrational spectra caused by the corresponding perturbation of each group of intramolecular,
The dynamic spectrum for obtaining process with mathematical correlation analysis technology and obtains two-dimensional correlation infrared spectrum spectrogram, using more high-resolution
The difference of the position of automatic peak and related peak-to-peak cluster, quantity and intensity etc., can not only identify each spectral peak on the two-dimentional spectrogram of rate
Specific ownership, additionally provide the information of micro-variations between each material molecule, and then obtain the information of molecule structure change.It is right
Studied in the discriminating of complex system, with certain practical significance.Current the method has been widely used in physics, has changed
The every field such as, material, biology, medical science, but yet there are no application in potato staple food grain field.
The content of the invention
For problem and shortage present in background technology, it is an object of the invention to provide a kind of potato full-powder and face
Functional group's atlas analysis method of powder blend, be gathering under sample is disturbed outside temperature one under decay is totally reflected drainage pattern
Row infrared spectrum, further obtains synchronous two-dimensional correlation spectra, and then difference between different sample two-dimensional correlations synchronously spectrum is carried out
Analysis, discloses the change rule of different cultivars potato full-powder and flour corresponding each functional group between them under the different mixing proportion
Rule, had both solved the shortcomings of traditional wet chemistry method testing cost is high, and environment is unfriendly, also effectively compensate near infrared spectrum
The deficiency of modeling analysis method model failure.
The step of the technical solution adopted by the present invention, is as follows:
1) potato full-powder and the biased sample of flour of multiple kinds, the potato full-powder and flour of multiple kinds are prepared
Biased sample ratio be respectively 30%, 35%, 40%, 45% or 50%;Then the horse of lower multiple kinds is disturbed outside collecting temperature
The infrared spectrum of the biased sample of the full powder of bell potato and flour;
2) calculation procedure 1) in biased sample infrared spectrum by disturbed outside temperature t induction dynamic spectrum, dynamic spectrumIt is expressed as:
In formula, y (v, t) is the light that perturbation is at t variations per hours v in whole perturbation process (from t=-T/2 to t=T/2)
Spectral intensity;It is reference spectra, the selection of reference spectra is set by static spectrum or time averaged spectrum, is defined as:
3) dynamic spectrum to each sample carries out Two-dimensional Correlation Analysis, obtains corresponding synchronous two-dimensional correlation spectra;
Under perturbation t effects, m data point is measured at equal intervals and (the infrared of sample is measured such as when equal temperature is spaced
Spectrum) dynamic spectrum then from t=-T/2 to t=T/2 is represented by:
Synchronous two-dimensional correlation spectra represents two variable v1And v2Locate the similar of the change that spectral intensity is produced with perturbation t
Property, the synchronous spectrum intensity φ (v of synchronous two-dimensional correlation spectra1, v2) computing formula be:
4) the synchronous two-dimensional correlation spectra to each biased sample carries out the atlas analysis of functional group's change.
The step 1) in, potato full-powder preparation method is:Fresh potato-cleaning peeling-slice thickness 8mm- exists
The 20min- that precooked at 70 DEG C coolings-boiling 15min- smashs mud processed-mesh of vacuum drying-crushing 100 to pieces and sieves-take sieve at 100 DEG C
Lower thing.
The step 1) in, spectra collection pattern is totally reflected for decay, pick-up slip during all samples collection infrared spectrum
Part is consistent:Spectral region is 4000~400cm-1, spectral resolution 8cm-1, acquisition time 3s, each spectrum is 16 scanning
Averaged spectrum.
The invention has the advantages that:
1) present invention use two-dimensional correlated spectroscopy combination infrared spectrum detection technique, by compare potato full-powder and
Difference condition between the Two-Dimensional Correlation IR Spectroscopy of flour different mixing proportion sample, sample is disturbed outside lower each material molecule it
Between micro-variations information be analyzed.The method is not only simple, quickly, without being separated to testing sample, the pre- place such as purifying
Reason, and it is environment-friendly, it is less demanding to operating personnel without chemical reagent pollution, while also compensate near infrared spectrum modeling
The problem of the model failure run into method.
2) present invention is using Two-Dimensional Correlation IR Spectroscopy research potato full-powder and the molecule structure change of flour blend
And the interaction between them, disclose different cultivars potato full-powder and flour under the different mixing proportion between them
The Changing Pattern of corresponding each functional group, is the making process for preferably optimizing potato staple food grain, is more effectively evaluated
The nutrition of potato staple food grain and effect provide reference.
Brief description of the drawings
Fig. 1 is potato full-powder preparation method.
Fig. 2 is the acquisition schematic diagram of two-dimensional correlation spectra.
Fig. 3 is that Atlantic Ocean content increases to 50% potato full-powder and the two-dimensional correlation collection of illustrative plates of flour blend from 30%.
Specific embodiment
The present invention is further illustrated with reference to the accompanying drawings and examples.
In the present embodiment, prepared sample includes:
Potato:Totally 4 kinds, the respectively Atlantic Ocean, Xia Bodi, Ji potato 8 and gram new, harvest from the dam of Hebei
Zhangbei County.
As shown in figure 1, potato full-powder preparation method is:Fresh potato-cleaning peeling-slice thickness 8mm- is at 70 DEG C
Under precook 20min- cooling-boiling 15min- smashs the mesh sieving of mud-vacuum drying-crushing processed 100-extracting screen underflow to pieces at 100 DEG C.
The blend of potato full-powder and flour:Mixing potato full-powder ratio is respectively 30%, 35%, 40%,
45%th, 50%
As shown in Fig. 2 being the acquisition schematic diagram of two-dimensional correlation spectra.
Step 1:Gather a series of infrared spectrums
Five kinds of mixed proportion samples of potato full-powder and flour are respectively placed on temperature control annex, it is then attached using temperature control
Part controls temperature, and an infrared spectrum is gathered from 35~95 DEG C every 10 DEG C.Pick-up slip during all samples collection infrared spectrum
Part is consistent:Drainage pattern is totally reflected for decay, and blank spectrum is the infrared spectrum of the air for not placing sample collection, spectrum
Scope is 4000~400cm-1, spectral resolution 8cm-1, acquisition time 3s, each spectrum is 16 averaged spectrums of scanning.
Step 2:The dynamic spectrum of the infrared spectrum being calculated
Dynamic spectrum can be calculated by following formula:
In formula, y (v, t) be under the effect of disturbing outside-T/2 to spectral intensity in T/2 regions;It is reference spectra, ginseng
The selection for examining spectrum is generally set by static spectrum or time averaged spectrum, is defined as:
If under extraneous variable t effects, the m groups data of acquisition its dynamic spectrums can also be expressed by formula 3.
Step 3:Calculate synchronous two-dimensional correlation spectra:
Shown in synchronous two-dimensional correlation spectra computing formula such as formula (4);
Step 4:Mixing according to the synchronous two-dimensional correlation spectra figure (as shown in Figure 3) for obtaining to potato full-powder and flour
Sample carries out functional group's mutation analysis.Automatic peak is occurred in that on the close position of diagonal as we can see from the figure, but
Automatic peak there are different combinations and relative intensity is also variant, that is to say, that potato full-powder mixing ratio different with flour
The intramolecule environment residing for functional group in example system corresponding to automatic peak is different, and corresponding molecular structure is to external temperature
The sensitivity of perturbation is also different.Additionally, these automatic peaks are in 1047cm-1、1022cm-1And 994cm-1Place occurs most strong
Peak, 1047cm-1It is the architectural feature in starch crystals area, corresponding to the ordered structure in starch accumulation state structure, 1022cm-1Then
It is the architectural feature of starch unformed area, corresponding to the random coil structure of starch polymer.In each feature of diagonal both sides
Peak also all occurs in that intersection peak each other, and is posivtive spike, shows under the influence of outside perturbation, each characteristic peak dynamic
The direction of change is consistent.
Above-mentioned specific embodiment is used for illustrating the present invention, rather than limiting the invention, of the invention
In spirit and scope of the claims, any modifications and changes made to the present invention both fall within protection model of the invention
Enclose.
Claims (3)
1. a kind of functional group's atlas analysis method of potato full-powder and flour blend, it is characterised in that comprise the following steps:
1) potato full-powder and the biased sample of flour of multiple kinds, the potato full-powder of multiple kinds and mixing for flour are prepared
Close sample ratio and be respectively 30%, 35%, 40%, 45% or 50%;Then the potato of lower multiple kinds is disturbed outside collecting temperature
The infrared spectrum of the biased sample of full powder and flour;
2) calculation procedure 1) in biased sample infrared spectrum by disturbed outside temperature t induction dynamic spectrum, dynamic spectrum
It is expressed as:
In formula, y (v, t) be in whole perturbation process (from t=-T/2 to t=T/2) perturbation be t variations per hours v at spectrum it is strong
Degree;It is reference spectra, the selection of reference spectra is set by static spectrum or time averaged spectrum, is defined as:
3) dynamic spectrum to each sample carries out Two-dimensional Correlation Analysis, obtains corresponding synchronous two-dimensional correlation spectra;
Under perturbation t effects, m data point (infrared spectrum of sample is measured such as when equal temperature is spaced) is measured at equal intervals
Then the dynamic spectrum from t=-T/2 to t=T/2 is represented by:
Synchronous two-dimensional correlation spectra represents two variable v1And v2The similitude of the change that place's spectral intensity is produced with perturbation t, together
Walk the synchronous spectrum intensity φ (v of two-dimensional correlation spectra1, v2) computing formula be:
4) the synchronous two-dimensional correlation spectra to each biased sample carries out the atlas analysis of functional group's change.
2. functional group's atlas analysis method of a kind of potato full-powder according to claim 1 and flour blend, it is special
Levy and be:The step 1) in, potato full-powder preparation method is:Fresh potato-cleaning peeling-slice thickness 8mm- is 70
The 20min- that precooked at DEG C coolings-boiling 15min- smashs mud processed-mesh of vacuum drying-crushing 100 to pieces and sieves-take under sieve at 100 DEG C
Thing.
3. functional group's atlas analysis method of a kind of potato full-powder according to claim 1 and flour blend, it is special
Levy and be:The step 1) in, spectra collection pattern is totally reflected for decay, acquisition condition during all samples collection infrared spectrum
Unanimously:Spectral region is 4000~400cm-1, spectral resolution 8cm-1, acquisition time 3s, each spectrum is 16 scanning
Averaged spectrum.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107044967A (en) * | 2017-04-18 | 2017-08-15 | 江苏大学 | A kind of method of potato starch near infrared spectrum quick discriminating |
CN110749575A (en) * | 2019-10-17 | 2020-02-04 | 夏永刚 | Traditional Chinese medicine polysaccharide two-dimensional infrared spectrum identification prediction model and construction method and application thereof |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5258825A (en) * | 1991-11-13 | 1993-11-02 | Perten Instruments North America, Inc. | Optical compositional analyzer apparatus and method for detection of ash in wheat and milled wheat products |
CN102435575A (en) * | 2011-09-05 | 2012-05-02 | 中山市中健药业有限公司 | Method for detecting near-infrared two-dimensional correlation spectra |
CN102661929A (en) * | 2012-03-12 | 2012-09-12 | 中国林业科学研究院木材工业研究所 | Identification method of bamboo raw fiber based on infrared and two-dimensional correlation spectra |
CN104251839A (en) * | 2014-09-04 | 2014-12-31 | 塔里木大学 | Spectrum separation detection method of compositions of south-Xinjiang red date sample for south-Xinjiang red date modeling |
CN105136737A (en) * | 2015-09-29 | 2015-12-09 | 贵州省马铃薯研究所 | Method for fast measuring content of potato flour in steamed buns based on near infrared spectrums |
CN105158194A (en) * | 2015-09-23 | 2015-12-16 | 中国人民解放军第二军医大学 | Method for identifying whether ephedrine and/or pseudo ephedrine are/is added to weight-reducing type traditional Chinese medicine or health care products |
CN105842186A (en) * | 2016-03-23 | 2016-08-10 | 浙江大学 | Doped meat paste qualitative and quantitative detection method based on two-dimensional correlation infrared spectroscopy |
CN105928897A (en) * | 2016-06-03 | 2016-09-07 | 通化师范学院 | Synchronous separation and analysis multi-stage macroscopic fingerprint identification method for traditional Chinese medicinal material infrared spectrum |
-
2016
- 2016-11-29 CN CN201611072128.4A patent/CN106706545A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5258825A (en) * | 1991-11-13 | 1993-11-02 | Perten Instruments North America, Inc. | Optical compositional analyzer apparatus and method for detection of ash in wheat and milled wheat products |
CN102435575A (en) * | 2011-09-05 | 2012-05-02 | 中山市中健药业有限公司 | Method for detecting near-infrared two-dimensional correlation spectra |
CN102661929A (en) * | 2012-03-12 | 2012-09-12 | 中国林业科学研究院木材工业研究所 | Identification method of bamboo raw fiber based on infrared and two-dimensional correlation spectra |
CN104251839A (en) * | 2014-09-04 | 2014-12-31 | 塔里木大学 | Spectrum separation detection method of compositions of south-Xinjiang red date sample for south-Xinjiang red date modeling |
CN105158194A (en) * | 2015-09-23 | 2015-12-16 | 中国人民解放军第二军医大学 | Method for identifying whether ephedrine and/or pseudo ephedrine are/is added to weight-reducing type traditional Chinese medicine or health care products |
CN105136737A (en) * | 2015-09-29 | 2015-12-09 | 贵州省马铃薯研究所 | Method for fast measuring content of potato flour in steamed buns based on near infrared spectrums |
CN105842186A (en) * | 2016-03-23 | 2016-08-10 | 浙江大学 | Doped meat paste qualitative and quantitative detection method based on two-dimensional correlation infrared spectroscopy |
CN105928897A (en) * | 2016-06-03 | 2016-09-07 | 通化师范学院 | Synchronous separation and analysis multi-stage macroscopic fingerprint identification method for traditional Chinese medicinal material infrared spectrum |
Non-Patent Citations (2)
Title |
---|
覃方丽: ""二维相关光谱研究及应用"", 《中国优秀硕士学位论文全文数据库 基础科学辑》 * |
陈建波: ""二维相关红外光谱差异分析方法及其应用研究"", 《中国优秀硕士学位论文全文数据库 工程科技I辑》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107044967A (en) * | 2017-04-18 | 2017-08-15 | 江苏大学 | A kind of method of potato starch near infrared spectrum quick discriminating |
CN110749575A (en) * | 2019-10-17 | 2020-02-04 | 夏永刚 | Traditional Chinese medicine polysaccharide two-dimensional infrared spectrum identification prediction model and construction method and application thereof |
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