CN108548792A - A kind of fast non-destructive detection method of peanut kernel soluble sugar content - Google Patents
A kind of fast non-destructive detection method of peanut kernel soluble sugar content Download PDFInfo
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- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
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Abstract
The invention discloses a kind of fast non-destructive detection methods of peanut kernel soluble sugar content, inventor utilizes near-infrared spectrum technique for the first time, establish a kind of fast non-destructive detection method of reliable peanut kernel soluble sugar content, this method can realize the quick detection of peanut kernel soluble sugar, the shortcomings that overcoming conventional method, time-consuming, destruction seed benevolence.Near infrared detection of the present invention only needs 5s from dress sample to testing result is gone out; and it realizes and Intact peanut kernel is carried out non-destructive testing; save a large amount of human and material resources and financial resources; and reduce many processes; it improves work efficiency; pollution of the pernicious gas to environment and the injury to experiment operator are reduced, new approach is opened for follow-up quickly detection peanut kernel soluble sugar content.Soluble sugar content in unknown peanut kernel sample is quickly measured with the near-infrared calibration model that the present invention is set up, testing result is reliable, accuracy of detection is high, reproducible.
Description
Technical field
The present invention relates to a kind of fast non-destructive detection methods of peanut kernel soluble sugar content, and in particular to a kind of use
The method of soluble sugar content near infrared ray peanut kernel.
Background technology
Peanut is important oil crops, in addition to for extracting oil or the important source material of food industry.As people live
Horizontal continuous improvement, peanut breeding target is also turned to by early stage based on high yield is laid equal stress on yield and quality, thus also right
The quality of peanut kernel gives more concerns.Peanut kernel sweet taste main source is the soluble sugar in peanut kernel, and sweet tea
Taste is character that can be hereditary.Research shows that the related coefficient between the sugariness and flavouring quality of peanut kernel reaches 0.88.Due to
The quality of many breeding materials is detected in peanut kernel quality-improving, especially in low stage generation, in quality trait
On assay method other than requiring that simple and efficient a large amount of samples can be handled, used Quality Detection technology is preferably non-destructive
, and it is of low cost.But the method generally use Phenol sulfuric acid procedure and anthrone colorimetry of traditional test soluble sugar content, this
A little methods due to the testing time is long, sample dosage is big, experimentation is cumbersome, has certain toxicity and pollution etc., it is difficult into
The large-scale analysis of row.In addition, traditional analysis needs to destroy seed benevolence, it is difficult to reality less because of grain weight in the early generation of breeding
It applies.It is peanut seed therefore, it is necessary to find a kind of method of detection peanut soluble sugar content that is quick, accurate, not destroying seed benevolence
The evaluation of benevolence flavouring quality provides foundation.
Near infrared spectroscopic method be using substance in the specific absorption characteristic of near infrared spectrum is come determination sample certain
The detection method of one or more chemical composition contents, have quickly, it is accurate, efficiently, low cost and can detect simultaneously it is a variety of at
The advantages that dividing (at most up to six kinds of components), has been widely used in a variety of agricultures such as rice, wheat, rape, soybean and cotton at present
In the attributional analysis of crop.However, in terms of the related soluble sugar content using Near Infrared Spectroscopy for Rapid peanut kernel
Report also seldom see.
Invention content
In view of the deficiencies of the prior art, the object of the present invention is to provide it is a kind of accurate, quickly, be not necessarily to pretreated peanut seed
The fast non-destructive detection method of benevolence soluble sugar content.
To achieve the goals above, the technical solution adopted in the present invention is：
A kind of fast non-destructive detection method of peanut kernel soluble sugar content, includes the following steps：
1) representative peanut kernel sample is collected；
2) spectral scan is carried out to the sample of collection；
3) accurate soluble sugar content analysis is carried out to the sample after spectral scan and analysis result is input to spectrum
In file；
4) extraordinary sample is removed, determines calibration sample collection；
5) with bearing calibration that spectral information is associated with the chemical measurements of component, establish calibration model；
6) estimated performance for the sample the set pair analysis model for being not engaged in calibration with one group is verified.
The method of step 2) is：To the sample of collection after fully drying, its moisture is made to be down to 3-6%, used
The DA7200 near-infrared spectrometers of Perten companies production, take full peanut kernel sample to be uniformly fitted into specimen cup,
It shakes up, makes surfacing, sample is scanned in the range of wavelength is 950-1650nm, acquire near infrared light spectrum information, generate light
Compose file.
Before carrying out soluble sugar content analysis, sample is dried, is peeled, degreasing, specific method is：Sample is existed
50 DEG C of baking ovens dry 48h, remove kind of a skin, after being ground with grinder, weigh 2g samples in 50mL centrifuge tubes, add 20mL n-hexanes de-
Fat extracts 2-4h on shaking table, is then centrifuged for 3min, outwells supernatant, is deposited in draught cupboard and air-dries, and it is spare to cross 80 mesh sieve.
Soluble sugar content analysis method is：The accurate sample for weighing 0.100g degreasings, is respectively put into 3 15mL by totally 3 parts
In centrifuge tube, be added 80% ethyl alcohol of 5mL, extract 2 times, each 30min in 80 DEG C of water-baths, merging extracting solution, 11000rpm from
Heart 5min takes supernatant in 50mL test tubes after centrifugation, being positioned in boiling water makes extracting solution evaporate into 2-3mL, adds distilled water fixed
Hold to 25mL, be stored at room temperature 60min, sample liquid is made；0.2mL sample liquids are drawn in test tube, add distilled water 1.8mL, then
9% phenol solution of 1mL mass fractions is in vitro added, shakes up, then the 5mL concentrated sulfuric acids are added in 5-20s from pipe liquid front, shakes
Even, total volume 8mL places 30min at room temperature, colour developing；Then using blank as reference, the colorimetric estimation under 485nm wavelength,
Using soluble sugar content as abscissa, optical density is ordinate, draws standard curve, finds soluble sugar by standard curve and contain
Amount, and soluble sugar content in sample is calculated, soluble sugar content result is input in spectrum file.
The calculation formula of soluble sugar content is in sample：
Soluble sugar content (%)=[from standard curve check in amount (μ g) × sample constant volume (mL) of soluble sugar ×
Extension rate]/[reaction solution volume (mL) × example weight (g) × 106]×100。
Step 4) uses principal component analysis PCA methods, and extraordinary sample is removed according to mahalanobis distance or correlation.Extraordinary sample picks
Except limit is 3.0.
The specific method of step 5) is：By foundation between the spectral information of acquisition and the result that conventional chemical measures it is related close
System establishes the near-infrared analysis model of soluble sugar content with the Partial Least Squares Return Law, utilizes " SNV+De-trending/
2,4,4, regression equation is established in the combination of 1/PLS ", and it is maximum with crosscheck standard to find out crosscheck coefficient of determination 1-VR values
SECV value minimums are missed, as optimal scaling model.
Optimal scaling model is：
Advantageous effect of the present invention：
1, current peanut quality research focuses primarily upon protein, crude fat, fatty acid component etc., and to peanut taste shadow
The concern for ringing larger soluble sugar content is inadequate, and research is less, while to the detection method of peanut kernel soluble sugar content
Rare report is studied, and what the existing detection means to soluble sugar content mostly used is destructive larger chemical method.This
It invents inventor and utilizes near-infrared spectrum technique for the first time, establish a kind of quick nondestructive of reliable peanut kernel soluble sugar content
Detection method opens new approach for follow-up quickly detection peanut kernel soluble sugar content.
2, the sample that the present invention collects is domestic and international good edible peanut resource, is measured using phenol-sulfuric acid and colorimetric method,
Measurement result distribution is 6.344%~16.728%, average value 10.177%, the coefficient of variation of soluble sugar content compared with
Greatly, distribution is wider, has preferable representativeness, can be used for calibrating near infrared spectrum predictive equation.
3, the pre-treating method of chemical assay of the present invention uses n-hexane degreasing, simpler relative to soxhlet type method
Just, easy to operate.
4, the present invention realizes the quick detection of peanut kernel soluble sugar, and overcoming conventional method, time-consuming, destroys seed
The shortcomings that benevolence, near infrared detection of the present invention only needs 5s from dress sample to testing result is gone out, and realizes and carried out to Intact peanut kernel
Non-destructive testing saves a large amount of human and material resources and financial resources, and reduces many processes, improves work efficiency, reduces
Pollution of the pernicious gas to environment and the injury to experiment operator.
5, the present invention substantially increases the screening efficiency of the breeding material in peanut quality breeding work, and due to not breaking
Cur's, can screen early generation breeding material, accelerate breeding process.
6, the near-infrared calibration model set up with the present invention is quickly measured soluble sugar in unknown peanut kernel sample and contained
Amount, testing result is reliable, accuracy of detection is high, reproducible.Therefore, which can be promoted.
Description of the drawings
The specific implementation mode of the present invention is described in further detail below in conjunction with attached drawing.
Fig. 1 is the near-infrared primary light spectrogram of soluble sugar content in peanut kernel.
Fig. 2 is the related figure between verification collection soluble sugar NIR predicted values and actual value.
Specific implementation mode
The specific implementation mode of the present invention is described in further detail with reference to embodiments.
Embodiment
The fast non-destructive detection method of peanut kernel soluble sugar content, includes the following steps：
1) sample is collected：
72, representative peanut kernel sample is collected, sample source is provided in high-quality edible peanut germplasm both at home and abroad
Source；
2) infrared analysis：
To the sample of collection after fully drying, its moisture is made to be down to 5% or so, using the production of Perten companies
DA7200 near-infrared spectrometers take full peanut kernel sample to be uniformly fitted into specimen cup, shake up, make surfacing,
Sample is scanned in the range of wavelength is 950-1650nm, acquires near infrared light spectrum information.Every part of sample in triplicate, to spectrum
It is averaged, generates averaged spectrum file (see Fig. 1)；As seen from Figure 1, the sample of collection is in the range of wavelength 950-1650nm
There is apparent absorption peak, for each sample there are many places absorption peak, different sample rooms are apparent in the peak value difference of same absorption peak.
Illustrate that the near-infrared absorption spectrum of peanut kernel may be used as the qualitative and quantitative analysis of soluble sugar content.
3) soluble sugar content measures
Sample after spectral scan is dried, is peeled, after degreasing, soluble sugar content in determination sample, specific side
Method is：Representational peanut kernel sample is collected, 48h is dried in 50 DEG C of baking ovens, goes kind of a skin, after being ground with grinder, weigh 2g
Sample adds 20mL n-hexane degreasings, 3.5h is extracted on shaking table, is then centrifuged for 3min, outwells supernatant in 50mL centrifuge tubes, sinks
It forms sediment and is air-dried in draught cupboard, it is spare to cross 80 mesh sieve.
The accurate sample for weighing 0.100g degreasings, is respectively put into 3 15mL centrifuge tubes totally by 3 parts, and 5mL 80% is added
(v/v) ethyl alcohol extracts 2 times, each 30min in 80 DEG C of water-baths, merges extracting solution, and 11000rpm centrifuges 5min, taken after centrifugation
For supernatant in 50mL test tubes, being positioned in boiling water makes extracting solution evaporate into 2-3mL, and distilled water is added to be settled to 25mL, and room temperature is quiet
60min is set, sample liquid is made；0.2mL sample liquids are drawn in test tube, adds distilled water 1.8mL, 1mL is then in vitro added
9% phenol solution of mass fraction, shakes up, then the 5mL concentrated sulfuric acids are added in 5-20s from pipe liquid front, shakes up, total volume 8mL,
30min is placed at room temperature, is developed the color；Then using blank as reference, the colorimetric estimation under 485nm wavelength, with soluble sugar content
For abscissa, optical density is ordinate, draws standard curve, finds soluble sugar content by standard curve, and calculate in sample
Soluble sugar content result is input in spectrum file by soluble sugar content.
Soluble sugar content (%)=[from standard curve check in amount (μ g) × sample constant volume (mL) of soluble sugar ×
Extension rate]/[reaction solution volume (mL) × example weight (g) × 106]×100
4) calibration sample collection is determined
Using principal component analysis PCA methods, extraordinary sample is removed according to mahalanobis distance or correlation, usually extraordinary sample is rejected
It is limited to 2-3 times of SEC.It is 3.0 that extraordinary sample, which rejects limit, in the present invention.Calibration sample collection is shown in Table 1.
Spectroscopic data is compressed to and is decomposed into principal component and score square using principal component analysis technology (Clustering Analysis Technology)
Battle array data.Then score matrix data are utilized, the difference between each sample spectrum and the difference between certain sample and main group product group are compared
It is different, so that it is determined that participating in the best sample of calibration.
Soluble sugar content chemical assay range of variation in 1 shelled peanut of table
| Character | Average value/% | Minimum value/% | Maximum value/% | Standard deviation | Standard error | The coefficient of variation/% |
| Soluble sugar content | 10.177 | 6.344 | 16.728 | 1.681 | 0.198 | 16.5 |
5) foundation of calibration model
Correlativity will be established between the spectral information of acquisition and the result of conventional chemical measurement.In near-infrared analysis,
Due to the spectrum overlapping of each component, then add the influence of the complex background spectrum of the uneven generation of sample granularity, in order to filter off
Noise in initial data improves signal-to-noise ratio, and the present invention is using partial least-squares regression method (PLS) as founding mathematical models
Chemometrics method establishes the near-infrared analysis model of soluble sugar content, passes through Variance and Correlation (R)
As the foundation of optimal wavelength, utilize " standard normal variable conversion (SNV)+trend converter technique (De-trending)/2,4,4,
Regression equation is established in the combination of 1/PLS ".It finds out maximum 1-VR (the crosscheck coefficient of determination) values and minimum SECV (intersects
Test stone is missed) value, as optimal scaling model.
Gained model result is as shown in table 2.Following information can be obtained after correction：Correct the coefficient of determination (RSQ), school
Positive standard error (SEC), crosscheck standard error (SECV), cross-checking the coefficient of determination (1-VR), these are to weigh near-infrared model
Major parameter.According to the precision and grade of fit of RSQ, 1-VR, SEC and SECV inspection data.
The near-infrared scaling parameter of soluble sugar content in 2 peanut kernel of table
6) verification of calibration model
After calibration equation foundation, verified with the estimated performance of verification sample set pair equation.Verification sample collection sample
Should have good representativeness, ingredient that should cover certain range, traditional experiment room reference data must be accurate and reliable, with
Just rational verification result is provided.Validation obtain prediction result and conventional method measurement result and its deviation (being shown in Table 3) with
And the results of analysis of variance (being shown in Table 4) of chemical score and near-infrared value.The result shows that near-infrared prediction peanut kernel soluble sugar contains
For amount with conventional method result without significant difference, institute's established model is accurately and reliably for the detection of peanut kernel soluble sugar content.
The coefficient of determination between the near-infrared predicted value and chemical analysis value of the soluble sugar content of inspection set sample is
0.796.Illustrate also to have between the chemical measurements of soluble sugar content and near-infrared measured value preferable linearly related.From mould
The relevance degree and standard deviation of type can be assumed that near infrared spectroscopic method can also rapidly detect solvable in shelled peanut
Property sugared content, the scatter plot (see Fig. 2) between the chemical measurements and near-infrared measured value of soluble sugar content also can be intuitively
Illustrate linear relationship between the two.Therefore, the soluble sugar content in shelled peanut can be carried out effectively with near-infrared model
Estimate on ground.
3 peanut kernel soluble sugar content NIR predicted values of table and conventional method measured value results contrast
4 near-infrared predicted value of table and chemical measurements variance analysis
| Difference source | Soluble sugar | Degree of freedom | Standard deviation | F values | P values |
| Between group | 0.575196 | 1 | 0.575196 | 0.244748 | 0.621562 |
| In group | 333.7223 | 142 | 2.350157 | ||
| It amounts to | 334.2975 | 143 |
The foregoing is merely the embodiments that the present invention is best, and for those skilled in the art, the present invention can have
Various modifications and variations.All within the spirits and principles of the present invention, any modification, equivalent replacement, improvement and so on, should all
It is included within protection scope of the present invention.
Claims (9)
1. a kind of fast non-destructive detection method of peanut kernel soluble sugar content, which is characterized in that include the following steps：
1) representative peanut kernel sample is collected；
2) spectral scan is carried out to the sample of collection；
3) accurate soluble sugar content analysis is carried out to the sample after spectral scan and analysis result is input to spectrum file
In；
4) extraordinary sample is removed, determines calibration sample collection；
5) with bearing calibration that spectral information is associated with the chemical measurements of component, establish calibration model；
6) estimated performance for the sample the set pair analysis model for being not engaged in calibration with one group is verified.
2. the fast non-destructive detection method of peanut kernel soluble sugar content according to claim 1, which is characterized in that step
Rapid method 2) is：To the sample of collection after fully drying, its moisture is made to be down to 3-6%, is produced using Perten companies
DA7200 near-infrared spectrometers, take full peanut kernel sample to be uniformly fitted into specimen cup, shake up, keep surface flat
It is whole, sample is scanned in the range of wavelength is 950-1650nm, acquires near infrared light spectrum information, generates spectrum file.
3. the fast non-destructive detection method of peanut kernel soluble sugar content according to claim 1, which is characterized in that
Before carrying out soluble sugar content analysis, sample is dried, is peeled, degreasing, specific method is：Sample is dried in 50 DEG C of baking ovens
48h removes kind of a skin, after being ground with grinder, weighs 2g samples in 50mL centrifuge tubes, adds 20mL n-hexane degreasings, on shaking table
2-4h is extracted, 3min is then centrifuged for, outwells supernatant, draught cupboard is deposited in and air-dries, it is spare to cross 80 mesh sieve.
4. the fast non-destructive detection method of peanut kernel soluble sugar content according to claim 3, which is characterized in that can
Dissolubility sugared content analysis method is：The accurate sample for weighing 0.100g degreasings, is respectively put into 3 15mL centrifuge tubes totally by 3 parts,
80% ethyl alcohol of 5mL is added, is extracted 2 times, each 30min in 80 DEG C of water-baths, merges extracting solution, 11000rpm centrifuges 5min, from
Take supernatant in 50mL test tubes after the heart, being positioned in boiling water makes extracting solution evaporate into 2-3mL, and distilled water is added to be settled to 25mL,
It is stored at room temperature 60min, sample liquid is made；0.2mL sample liquids are drawn in test tube, add distilled water 1.8mL, are then in vitro added
Enter 9% phenol solution of 1mL mass fractions, shake up, then the 5mL concentrated sulfuric acids are added in 5-20s from pipe liquid front, shakes up, total volume
For 8mL, 30min is placed at room temperature, is developed the color；Then using blank as reference, the colorimetric estimation under 485nm wavelength, with solubility
Sugared content is abscissa, and optical density is ordinate, draws standard curve, finds soluble sugar content by standard curve, and calculate
Soluble sugar content result is input in spectrum file by soluble sugar content in sample.
5. the fast non-destructive detection method of peanut kernel soluble sugar content according to claim 4, which is characterized in that sample
The calculation formula of soluble sugar content is in product：
Soluble sugar content (%)=[amount (μ g) × sample constant volume (mL) × dilution of soluble sugar is checked in from standard curve
Multiple]/[reaction solution volume (mL) × example weight (g) × 106]×100。
6. the fast non-destructive detection method of peanut kernel soluble sugar content according to claim 1, which is characterized in that step
It is rapid 4) to use principal component analysis PCA methods, extraordinary sample is removed according to mahalanobis distance or correlation.
7. the fast non-destructive detection method of peanut kernel soluble sugar content according to claim 6, which is characterized in that super
It is 3.0 that normal sample, which rejects limit,.
8. the fast non-destructive detection method of peanut kernel soluble sugar content according to claim 1, which is characterized in that step
Rapid specific method 5) is：Correlativity will be established between the spectral information of acquisition and the result of conventional chemical measurement, with partially most
The small square law Return Law establishes the near-infrared analysis model of soluble sugar content, utilize " SNV+De-trending/2,4,4,1/
Regression equation is established in the combination of PLS ", find out crosscheck coefficient of determination 1-VR values it is maximum and cross-check standard error SECV values
Minimum, as optimal scaling model.
9. the fast non-destructive detection method of peanut kernel soluble sugar content according to claim 8, which is characterized in that most
Good calibration model is：
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