CN108344709A - A method of quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique - Google Patents
A method of quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique Download PDFInfo
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- CN108344709A CN108344709A CN201810092311.3A CN201810092311A CN108344709A CN 108344709 A CN108344709 A CN 108344709A CN 201810092311 A CN201810092311 A CN 201810092311A CN 108344709 A CN108344709 A CN 108344709A
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- 244000061456 Solanum tuberosum Species 0.000 title claims abstract description 120
- 235000002595 Solanum tuberosum Nutrition 0.000 title claims abstract description 120
- 238000000034 method Methods 0.000 title claims abstract description 61
- 238000002329 infrared spectrum Methods 0.000 title claims abstract description 34
- 238000001514 detection method Methods 0.000 claims abstract description 5
- 238000001228 spectrum Methods 0.000 claims description 22
- 238000004458 analytical method Methods 0.000 claims description 21
- 238000012795 verification Methods 0.000 claims description 18
- 238000010239 partial least squares discriminant analysis Methods 0.000 claims description 9
- 230000003595 spectral effect Effects 0.000 claims description 6
- 238000012937 correction Methods 0.000 claims description 5
- 238000011156 evaluation Methods 0.000 claims description 3
- 239000002184 metal Substances 0.000 claims description 3
- 238000002203 pretreatment Methods 0.000 claims description 2
- 238000012512 characterization method Methods 0.000 claims 1
- 230000003993 interaction Effects 0.000 claims 1
- 230000001681 protective effect Effects 0.000 abstract description 3
- 238000010276 construction Methods 0.000 abstract description 2
- 238000007689 inspection Methods 0.000 abstract description 2
- 230000035784 germination Effects 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 235000013339 cereals Nutrition 0.000 description 2
- 239000012141 concentrate Substances 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 235000013305 food Nutrition 0.000 description 2
- 235000013573 potato product Nutrition 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 206010000087 Abdominal pain upper Diseases 0.000 description 1
- 206010007247 Carbuncle Diseases 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 240000007594 Oryza sativa Species 0.000 description 1
- 235000007164 Oryza sativa Nutrition 0.000 description 1
- 241000207763 Solanum Species 0.000 description 1
- 235000002594 Solanum nigrum Nutrition 0.000 description 1
- 240000002307 Solanum ptychanthum Species 0.000 description 1
- 235000021307 Triticum Nutrition 0.000 description 1
- 244000098338 Triticum aestivum Species 0.000 description 1
- 240000008042 Zea mays Species 0.000 description 1
- 235000005824 Zea mays ssp. parviglumis Nutrition 0.000 description 1
- 235000002017 Zea mays subsp mays Nutrition 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- RXVGBQCEAQZMLW-UHFFFAOYSA-N alpha-solanine Natural products CC1CCC2C(C)C3C(CC4C5CC=C6CC(CCC6(C)C5CCC34C)OC7OC(CO)C(O)C(OC8OC(CO)C(O)C(O)C8O)C7OC9OC(CO)C(O)C(O)C9O)N2C1 RXVGBQCEAQZMLW-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 235000008429 bread Nutrition 0.000 description 1
- 238000009395 breeding Methods 0.000 description 1
- 230000001488 breeding effect Effects 0.000 description 1
- 150000001720 carbohydrates Chemical class 0.000 description 1
- 229920002678 cellulose Polymers 0.000 description 1
- 239000001913 cellulose Substances 0.000 description 1
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- 239000003814 drug Substances 0.000 description 1
- 229930008677 glyco alkaloid Natural products 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 229910052500 inorganic mineral Inorganic materials 0.000 description 1
- 231100000567 intoxicating Toxicity 0.000 description 1
- 230000002673 intoxicating effect Effects 0.000 description 1
- 239000011707 mineral Substances 0.000 description 1
- 210000005036 nerve Anatomy 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 235000008935 nutritious Nutrition 0.000 description 1
- 238000011017 operating method Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000035479 physiological effects, processes and functions Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000004321 preservation 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
- 238000011160 research Methods 0.000 description 1
- 235000009566 rice Nutrition 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- ZGVSETXHNHBTRK-OTYSSXIJSA-N solanine Chemical compound O([C@H]1[C@@H](O)[C@@H](CO)O[C@H]([C@@H]1O[C@@H]1[C@@H]([C@H](O)[C@@H](O)[C@H](C)O1)O)O[C@@H]1CC2=CC[C@H]3[C@@H]4C[C@@H]5N6C[C@@H](C)CC[C@@H]6[C@H]([C@@H]5[C@@]4(C)CC[C@@H]3[C@@]2(C)CC1)C)[C@@H]1O[C@H](CO)[C@@H](O)[C@H](O)[C@H]1O ZGVSETXHNHBTRK-OTYSSXIJSA-N 0.000 description 1
- 229940031352 solanine Drugs 0.000 description 1
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- 238000012360 testing method Methods 0.000 description 1
- 231100000331 toxic Toxicity 0.000 description 1
- 230000002588 toxic effect Effects 0.000 description 1
- 238000009423 ventilation Methods 0.000 description 1
- 229940088594 vitamin Drugs 0.000 description 1
- 229930003231 vitamin Natural products 0.000 description 1
- 235000013343 vitamin Nutrition 0.000 description 1
- 239000011782 vitamin Substances 0.000 description 1
Classifications
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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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Abstract
The invention belongs to agricultural product quality detection technique fields, and in particular to a method of quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique.The method of Rapid identification potato sprouting characteristic of the present invention, since some physiological changes can occur after potato sprouting, these variations can have significant embodiment near infrared region, therefore, near-infrared spectrum technique can be used to judge potato sprouting characteristic, realize the quick discriminating of potato sprouting characteristic, have many advantages, such as quick, efficient, environmentally protective, meanwhile this method can effectively reduce model construction cost, improve model inspection efficiency.
Description
Technical field
The invention belongs to agricultural product quality detection technique fields, and in particular to one kind is quickly reflected based on near-infrared spectrum technique
The method of other potato sprouting characteristic.
Background technology
Potato, nickname potato, potato, potato etc., Solanaceae Solanum, annual herb plant is 15-80 centimetres high, hairless
Or by thin pubescence.Potato is rich in a variety of nutriments, is capable of providing the carbohydrate, protein, minerals of necessary for human
And vitamins and other nutritious components, it is known as the title of " underground apple " and " the second bread "；Potato is stem tuber breeding, can be used as medicine,
Flat property and sweet taste can treat for stomachache, the diseases such as Zha ribs, carbuncle swells.Potato nutritional value is high, adaptive faculty is strong, yield is big, is China five
One of big staple food, and it is only second to the fourth-largest cereal crops in the world of rice, wheat and corn.Potato have both grain dish, it is feeding,
The multiple uses such as light industry raw material, by the extensive favor of people.
In recent years, with the adjustment of food configuration, potato product is gradually diversified, and emerging potato product exploitation
The development for more having driven potato deep process technology has pushed greatly developing for potato agricultural product.But the thing followed, Ma Ling
The quality security problem of potato also highlights.It is well known that potato belongs to seasonal form product, harvest time Relatively centralized and
Period is shorter, needs to carry out deep processing processing to it in a short period of time, otherwise can cause edible more difficult.Therefore, such as
What carries out rational preservation and freshness with regard to very necessary to potato.Under normal conditions, during storage of potato, if temperature compared with
Height, ventilation are poor, then potato can be promoted germination phenomenon occur, and the black nightshade cellulose content meeting that the potato after germinateing contains is a large amount of
Increasing, solanine is a kind of toxic glycoalkaloid, there is larger harm to nerve system of human body, if eaten by mistake, Qing Zhehui
There is intoxicating phenomenon, severe one then can be dead.Therefore, while reasonable shelf potato, enter market with greater need in potato
Find its Germinating status as early as possible before, in order to avoid bring edible harm.But in the prior art, even unsuitable technology is to Ma Ling
The germination characteristic of potato quickly detect and identify.
Near-infrared spectral analysis technology is a kind of fast in the optical characteristics of near infrared spectrum using organic chemicals
The method of speed estimation sample information variation characteristic, and have the advantages that it is quick, conveniently, it is accurate.Therefore, by means of near infrared spectrum
Analytical technology is detected and differentiates to the germination characteristic of potato, and the Early Identification of only potato disease evil does not provide a kind of new
Method and thinking, and then lay a good foundation for efficient, the high-quality development of Potato Industry, there is important theory significance and work
Journey application value.
Invention content
For this purpose, quickly differentiating horse based on near-infrared spectrum technique technical problem to be solved by the present invention lies in one kind is provided
The method of bell potato germination characteristic, to solve the problems, such as that potato sprouting characteristic is difficult to detect in the prior art.
In order to solve the above technical problems, the invention discloses near-infrared spectrum techniques quickly to differentiate potato sprouting characteristic
Application in method.
A kind of method quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique of the present invention, including such as
Lower step：
(1) healthy potato and budded potato sample are collected, respectively by healthy potato and budded potato sample point
Collect for calibration collection and verification, and acquire the near infrared light spectrum signal of each healthy potato and budded potato sample respectively, obtains
Calibration collection spectral signal and verification collection spectral signal；
(2) the near infrared light spectrum signal of the healthy potato of acquisition and budded potato sample is pre-processed；
(3) by by based on pretreated data, establishing Partial Least Squares discriminant analysis (PLS-DA) model, and right
Constructed discriminant analysis model is evaluated；
(4) under the identical acquisition condition with step (1), the near infrared light spectrum information of potato sample to be measured is acquired, and
It is input in the discriminant analysis model established in step (3) and carries out discriminant analysis, with Rapid identification potato sample to be measured
Germination characteristic.
In the step (1), the near infrared spectra collection ranging from 12000-4000cm-1, resolution ratio is 4 or 8cm-1, scanning times are 32 or 64 times.
In the step (1), in the near infrared spectra collection step, potato sample is hidden using opaque metal box
It covers, and at least four difference is selected to be acquired, calculate and obtain its averaged spectrum curve.
In the step (1), the quantitative proportion that the calibration collects and verification integrates is 3-4：1.
In the step (2), the mode of the pre-treatment step be selected from baseline correction, weighted least-squares baseline correction,
Go at least one of trend, MSC, SNV, standardization, method for normalizing.
In the step (3), described the step of establishing partial least squares discriminant analysis model, uses and stays a cross verification.
In the step (3), the step of evaluating the discriminant analysis model is to the discriminant analysis model
Precision is evaluated.
The precision of the discriminant analysis model uses discrimination and reject rate for evaluation index, the discrimination and reject rate
For 0.85-1.00 when, the discriminant analysis model is effective, and the discrimination and reject rate are closer to 1.00, the discriminant analysis
The precision of model is higher.
In the step (4), the step of the near infrared light spectrum information of acquisition potato sample to be measured, be with step
(1) it is carried out under identical acquisition condition.
The invention also discloses described quickly to differentiate that the method for potato sprouting characteristic exists based on near-infrared spectrum technique
Application in potato quality detection field.
The method of Rapid identification potato sprouting characteristic of the present invention, since some physiology can occur after potato sprouting
Variation, these variations can have significant embodiment near infrared region, therefore, near-infrared spectrum technique can be used to potato sprouting spy
Property is judged, the quick discriminating of potato sprouting characteristic is realized, have many advantages, such as it is quick, efficient, environmentally protective, meanwhile,
This method can effectively reduce model construction cost, improve model inspection efficiency.
The method of Rapid identification potato sprouting characteristic of the present invention, is detected based on near-infrared spectrum technique, by
It is the spectral signal for obtaining sample in near-infrared analysis, can be even measured, not need other in former container sometimes
Therefore reagent not will produce any pollution in entire test process, have the characteristics that it is environmentally protective, meanwhile, the structure of the model
It builds, is also beneficial to budded potato and differentiates special instrument exploitation, new way is provided for the Rapid identification of potato sprouting characteristic
Diameter has great importance.
Description of the drawings
In order to make the content of the present invention more clearly understood, it below according to specific embodiments of the present invention and combines
Attached drawing, the present invention is described in further detail, wherein
Fig. 1 is the primary light spectrogram of healthy potato samples and budded potato sample, and healthy potato sample is dark color, germination
Potato sample is light color；
Fig. 2 is the near infrared spectrum through the pretreated spectrogram of SNV methods；
Fig. 3 is that the germination characteristic of present invention verification potato samples judges result figure.
Specific implementation mode
Embodiment 1
The present embodiment carries out Rapid identification using near-infrared spectrum technique to the Germination Characteristics of potato samples, due to Ma Ling
Potato, can be along with certain physiological change in germination process, these variations can have significant embodiment near infrared region, specific to grasp
Include the following steps as method：
(1) sample collection
The potato research sample that the present embodiment is chosen is 204 parts total, wherein 102 parts are healthy potato, 102 parts are hair
The potato of bud.It is divided into a manner of taking one every three by the healthy potato sample and budded potato sample are random respectively
Healthy potato samples are 1,2,3,5,6,7,9,10,11 ... to set by randomly ordered middle number by calibration collection and verification collection
It is set to calibration collection, and numbers the verification that is set as being 4,8,12 ... and collect, same operating method is suitable for budded potato.It obtains
Calibration to concentrate healthy potato samples be 77, budded potato sample is 77, and verification concentrates the healthy potato samples to be
25, budded potato sample is 25.Then above-mentioned healthy potato samples and budded potato sample are carried out respectively close
Infrared spectrum acquires, the healthy potato samples of acquisition and the primary light spectrogram of budded potato sample as shown in Figure 1, with this point
Collection spectrum and verification collection spectrum Huo get not be calibrated, respective numbers are respectively included in the calibration collection spectrum and verification collection spectrum
Healthy potato spectrum and budded potato spectrum.
Near infrared spectrum detection is carried out using German Brooker MPA Fourier Transform Near Infrared instruments to potato samples
Spectra collection is carried out, near infrared spectrometer is opened at 25 DEG C and preheats 30min, is swept every time before sample using air spectrum as bias light
Spectrum, near infrared spectrometer acquisition mode are diffusing reflection, spectra collection ranging from 12000-4000cm-1, resolution ratio 4cm-1, sweep
It is 64 times to retouch number, and sample is covered using opaque metal box, selects 4 differences to be acquired, seeks its averaged spectrum curve.
(2) spectral signal acquired is pre-processed
Using Matlab softwares (R2012a, Mathworks companies of the U.S.), to the healthy potato acquired in step (1)
And the near infrared light spectrum signal of budded potato sample is pre-processed.
The pretreatment mode be baseline correction, weighted least-squares baseline correction, go trend, MSC, SNV, standardization,
At least one of method for normalizing method.It is pre-processed using SNV methods in the present embodiment, specific preprocessing process is as schemed
Shown in 2.
(3) foundation and evaluation of Partial Least Squares discrimination model
By being inputted based on pretreated data in above-mentioned steps (2), and uses and a cross verification is stayed to build
Vertical Partial Least Squares discriminant analysis (PLS-DA) model, and what is obtained divides gained differentiation based on Model Identification rate and reject rate
The precision of analysis model is evaluated, and when the discrimination and reject rate are 0.85-1.00, the discriminant analysis model is effective,
Closer to 1.00, the precision of the discriminant analysis model is higher for the discrimination and reject rate.
Sample identification rate=itself class specimen discerning number/such sample class sum × 100%；
Reject rate=other classes sample refusal sum/other class total sample number × 100%.
The present embodiment obtains the discrimination of discriminant analysis (PLS-DA) model and reject rate data see the table below 1.
1 Partial Least Squares of table differentiates (PLS-DA) Model Identification rate and reject rate
(4) verification and identification of Partial Least Squares discrimination model
In addition 50 potato samples are selected to verify constructed partial least squares discriminant analysis model.Described 50
In a potato sample, wherein healthy potato 25, budded potato 25.Above-mentioned 50 potato samples are carried out close red
External spectrum detects, and acquires its near infrared spectrum data, the same step of gatherer process (1).
The partial least squares discriminant analysis model of the near infrared spectrum data input gained of acquisition is verified, sample is obtained
This discrimination and reject rate data is shown in Table 2, and the discrimination and reject rate of the sample are 1.00, it was demonstrated that structure model
Precision is higher.
The verification of table 2 collection sample identification rate and reject rate
| Sample class | Discrimination | Reject rate |
| Budded potato | 1.00 | 1.00 |
| Healthy potato | 1.00 | 1.00 |
And the results are shown in Figure 3 for the germination characteristic judgement for the potato samples verified, top half is health Ma Ling in figure
Lower half portion is budded potato sample in potato sample, figure, and in figure, sample (upper and lower part) from left to right is calibration respectively
The healthy potato of collection, calibration collection budded potato, the healthy potato of verification collection, verification collection budded potato.
Number in Fig. 3 is it was demonstrated that the present invention is based on near-infrared spectrum techniques to be detected to potato sprouting characteristic, this method
Whole discrimination it is higher, effective discriminating of potato sprouting can be met.
Obviously, the above embodiments are merely examples for clarifying the description, and does not limit the embodiments.It is right
For those of ordinary skill in the art, can also make on the basis of the above description it is other it is various forms of variation or
It changes.There is no necessity and possibility to exhaust all the enbodiments.And it is extended from this it is obvious variation or
It changes still within the protection scope of the invention.
Claims (10)
1. application of the near-infrared spectrum technique in quickly differentiating potato sprouting Characterization method.
2. a kind of method quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique, which is characterized in that including as follows
Step：
(1) healthy potato and budded potato sample are collected, it is fixed to be respectively divided into healthy potato and budded potato sample
Mark collection and verification collection, and the near infrared light spectrum signal of each healthy potato and budded potato sample is acquired respectively, it is calibrated
Collect spectral signal and verification collection spectral signal；
(2) the near infrared light spectrum signal of the healthy potato of acquisition and budded potato sample is pre-processed；
(3) by by based on pretreated data, establishing Partial Least Squares discriminant analysis (PLS-DA) model, and to institute's structure
The discriminant analysis model built is evaluated；
(4) under the identical acquisition condition with step (1), the near infrared light spectrum information of potato sample to be measured is acquired, and is inputted
To discriminant analysis is carried out in the discriminant analysis model established in step (3), with the hair of Rapid identification potato sample to be measured
Bud characteristic.
3. the method according to claim 2 for quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique, special
Sign is, in the step (1), the near infrared spectra collection ranging from 12000-4000cm-1, resolution ratio is 4 or 8cm-1, scanning times are 32 or 64 times.
4. the method according to claim 3 for quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique, special
Sign is, in the step (1), in the near infrared spectra collection step, potato sample is covered using opaque metal box,
And at least four difference is selected to be acquired, it calculates and obtains its averaged spectrum curve.
5. quickly differentiating the side of potato sprouting characteristic based on near-infrared spectrum technique according to claim 2-4 any one of them
Method, which is characterized in that in the step (1), the quantitative proportion that the calibration collects and verification integrates is 3-4：1.
6. quickly differentiating the side of potato sprouting characteristic based on near-infrared spectrum technique according to claim 2-5 any one of them
Method, which is characterized in that in the step (2), the mode of the pre-treatment step is selected from baseline correction, weighted least-squares baseline
It corrects, go at least one of trend, MSC, SNV, standardization, method for normalizing.
7. quickly differentiating the side of potato sprouting characteristic based on near-infrared spectrum technique according to claim 2-6 any one of them
Method, which is characterized in that in the step (3), described the step of establishing partial least squares discriminant analysis model uses and stays an interaction
Proof method.
8. the method according to claim 7 for quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique, special
Sign is, in the step (3), the step of evaluating the discriminant analysis model is the essence to the discriminant analysis model
Degree is evaluated.
9. the method according to claim 8 for quickly differentiating potato sprouting characteristic based on near-infrared spectrum technique, special
Sign is that the precision of the discriminant analysis model uses discrimination and reject rate for evaluation index, the discrimination and reject rate
For 0.85-1.00 when, the discriminant analysis model is effective, and the discrimination and reject rate are closer to 1.00, the discriminant analysis
The precision of model is higher.
10. the method that claim 2-9 any one of them quickly differentiates potato sprouting characteristic based on near-infrared spectrum technique
Application in potato quality detection field.
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| CN109520966A (en) * | 2018-11-20 | 2019-03-26 | 中国农业科学院农业质量标准与检测技术研究所 | A method of vitamin A content is quickly detected based on near-infrared spectrum technique |
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