CN106908408A - A kind of assay method of Itanlian rye crude protein content - Google Patents
A kind of assay method of Itanlian rye crude protein content Download PDFInfo
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- CN106908408A CN106908408A CN201710115574.7A CN201710115574A CN106908408A CN 106908408 A CN106908408 A CN 106908408A CN 201710115574 A CN201710115574 A CN 201710115574A CN 106908408 A CN106908408 A CN 106908408A
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Classifications
-
- 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
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- 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
- G01N2021/3595—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using FTIR
Abstract
The invention discloses a kind of assay method of the Itanlian rye crude protein content that can quickly determine Itanlian rye crude protein content.The assay method provides a kind of forecast model of crude protein real content in Itanlian rye based on near-infrared spectrum technique, on the basis of known a large amount of sample real contents, gather the near-infrared original spectrum of sample, set up the Quantitative Analysis Predictive Model of the Itanlian rye crude protein content based on near-infrared spectrum technique and chemometrics method, then, it is only necessary to by Itanlian rye sample to be measured by obtaining Itanlian rye sample powder to be measured after pretreatment；And gather its near-infrared primary light spectrogram, spectra collection process time is short, and detection is can be carried out after near infrared spectrum is gathered, with it is simple to operate, detection is rapid, detection efficiency is high, accuracy of detection is high the features such as.It is adapted to evaluate field popularization and application in Forage Nutrition Quality.
Description
Technical field
Field is evaluated the present invention relates to Forage Nutrition Quality, and in particular to a kind of measure of Itanlian rye crude protein content
Method.
Background technology
Itanlian rye (Lolium multiflorum Lam.) is that grass family Lolium is annual or more year life is herded
Grass, is suitable to be grown in one of warmer climate humid region, good forage of Shi Ju worlds cultivation meaning, saves the south China more
(city) has the cultivation of larger area.In recent years, with the adjustment of the National agricultural industrial structure, herbivorous stock raising is fast-developing,
Itanlian rye is because the advantages of its yield is high, the vigorous, strong adaptability of winter-spring season growth, nutritive value enrich, solving China south
The not enough problem of square winter-spring season domestic animal forage grass, has played extremely important effect, especially in the cereal-forage rotation of south China area
It is that the excellent Varieties of Lolium that Herbage harvest is high, nutritional quality is good is particularly important to Animal husbandry production.Educated in Itanlian rye
Plant in work, yield kind high is not only cultivated, while also to take into account the quality of herbage.
Crude protein (Crude Protein, CP) is the general name of nitrogen-containing compound in food, feed, not only including true albumen but also
Including non-protein nitrogen-containing compound, the latter potentially includes free amino acid, purine, pyridine, urea, nitrate and ammonia etc. again.Herd
The content of CP is the key factor for influenceing Forage Nutrition Quality in grass, and CP contents are high, show being of high nutritive value for herbage, therefore grind
The dynamic change for studying carefully CP contents in Itanlian rye has great importance for forage grass production, breeding.It is domestic at present right
Determine main based on conventional wet chemical method in herbage CP, there is larger complex operation, error, high cost, time-consuming, poisonous
The outstanding problems such as hazardous chemicals pollution environment, it is difficult to filter out CP from substantial amounts of Varieties of Lolium (being) or sample
Content kind high (being) or sample, therefore a kind of method that can quickly determine CP contents in Itanlian rye is found out, to many
Flower rye grass breeding and herbage quality control have great importance.
The content of the invention
The technical problems to be solved by the invention are to provide and a kind of can quickly determine Itanlian rye crude protein content
The assay method of Itanlian rye crude protein content.
The technical solution adopted for the present invention to solve the technical problems is：The measure side of the Itanlian rye crude protein content
Method, comprises the following steps：
A, set up Itanlian rye crude protein content near-infrared forecast model；The Itanlian rye crude protein content is closely red
Outer forecast model is adopted and set up with the following method, specifically includes following steps：
A, collection Itanlian rye sample, the Itanlian rye sample include different cultivars, different lines, different bearing
The fresh grass sample of phase, different planting and different parts, is respectively pre-processed the Itanlian rye sample of above-mentioned collection,
The method of the pretreatment is as described below：The Itanlian rye sample of collection is first finished 20min in 105 DEG C of environment, so
After being dried in 65 DEG C of environment afterwards, powder is ground into micropulverizer and 40 mesh sieves excessively obtain Itanlian rye sample powder
End；
B, the Itanlian rye sample powder for obtaining step a carry out respectively near infrared spectra collection obtain each spend more it is black
The near-infrared primary light spectrogram of wheat straw sample powder；
C, the near-infrared original spectrum of all Itanlian rye sample powders is analyzed using PCA algorithms, rejects tool
There is the Itanlian rye sample of similar spectral, remaining Itanlian rye sample is representative Itanlian rye sample；
D, the representative Itanlian rye sample obtained to step c using Kjeldahl's method are carried out crude protein content and entered one by one
Row measure obtains each representative Itanlian rye sample crude protein content value；
Representative Itanlian rye sample is divided into correction by the representative Itanlian rye sample crude protein content value of e, foundation
Collection and checking collection two parts, specific method are as follows：The representative Itanlian rye crude protein content value that will be obtained first from it is small to
It is ranked up greatly, 1 is then taken every 3 and is collected as checking, remaining adjusts representative Itanlian rye as calibration set
The minimum value and maximum of middle crude protein content, it is calibration set to be allowed to incorporate into；
F, by the atlas of near infrared spectra of calibration set sample and the importing OPUS/ of the crude protein content value of calibration set sample
In the commercial quantitative spectrochemical analysis softwares of QUENT 5.5, first, the near infrared spectrum to calibration set sample in full spectral limit is carried out
Pretreatment, then sets up prediction calibration model to calibration set sample using partial least-squares regression method combination validation-cross, according to
The parameter of near-infrared quantitative calibration models is evaluated prediction calibration model, the near-infrared evaluated prediction calibration model
Quantitative calibration models parameter includes coefficient of determination R2, validation-cross coefficient of determination R2Cv, validation-cross root-mean-square error RMSECV,
Its coefficient of determination R2It is 99.33%, validation-cross coefficient of determination R2 cvIt is 98.64%, validation-cross root-mean-square error RMSECV is
0.678, optimal spectrum pretreatment is determined for first derivative+MSC (multiplicative scatter correction), best modeled spectral regions are 6101.9~
4246.7cm-1, optimum factor number be 10, in evaluation procedure according to mahalanobis distance, THE PRINCIPAL FACTOR ANALYSIS figure, spectrum residual plot and
The Itanlian rye calibration set sample of chemical analysis value residual plot result rejecting abnormalities, so as to the Itanlian rye for obtaining optimal is thick
The optimal near-infrared prediction calibration model of protein content；Then, will verify that the near infrared spectrum of collection sample and checking collect the thick of sample
Checking is analyzed in the prediction calibration model that protein content importing is set up and obtains prediction checking model；Then, using near-infrared
The parameter of quantitative verification model is evaluated the prediction checking model of gained, the near-infrared evaluated prediction checking model
The parameter of quantitative verification model includes external certificate coefficient of determination R2Ev and checking root-mean-square error RMSEP, its external certificate is determined
Determine coefficients R2Ev is 98.75%, and checking root-mean-square error RMSEP is 0.572, according to mahalanobis distance, main cause in evaluation procedure
The Itanlian rye checking collection sample of plain analysis chart, spectrum residual plot and chemical analysis value residual plot result rejecting abnormalities, from
And obtain optimal Itanlian rye crude protein content near-infrared forecast model；
B, by Itanlian rye sample to be measured according to described in step a preprocess method process after obtain it is to be measured spend more it is black
Wheat straw sample powder；
C, the Itanlian rye sample powder to be measured that step B is obtained is carried out near infrared spectra collection obtain it is to be measured spend more it is black
The near-infrared primary light spectrogram of wheat straw sample powder；
D, the Itanlian rye that will be obtained in the near-infrared primary light spectrogram and step f of Itanlian rye sample powder to be measured
Crude protein content near-infrared forecast model is imported into the commercial quantitative spectrochemical analysis softwares of OPUS/QUENT 5.5, is transported by model
Point counting is analysed, you can obtain the content of crude protein in Itanlian rye sample to be measured.
It is further that breeding time of the Itanlian rye includes tillering stage, jointing stage, boot stage, heading stage, blooms
Phase, productive phase, maturity period.
Be further, the planting type of the Itanlian rye include broadcasting sowing planting type, culturing and transplanting seedlings planting type,
Applied nitrogen planting type.
It is further that the collection position of the Itanlian rye includes stem, leaf, complete stool.
It is further in stepb, Itanlian rye sample powder to be carried out closely respectively using method as described below
Infrared spectrum is gathered, specifically, taking appropriate Itanlian rye sample powder, is put into Bruker MPA type Fourier transformation NIRS instrument
In specimen cup, sample is shakeout naturally, set Instrument working parameter, it is closely red to gather sample under the conditions of being 25 ± 0.5 DEG C in temperature
External spectrum, obtains the first time near infrared light spectrum of the sample, then, specimen cup is placed into after the sample in specimen cup is taken out
In, sample is shakeout naturally, sample near infrared spectrum is gathered again, second near infrared light spectrum of the sample is obtained, then
First time near infrared light spectrum and second near infrared light spectrum are carried out averagely, obtaining the near-infrared of the Itanlian rye sample
Primary light spectrogram.
It is further that the Bruker MPA types Fourier transformation NIRS Instrument working parameters are set as：Spectral range
4000~12500cm-1, resolution ratio 8cm-1, scanning times 64 times.
It is further, using the commercial quantitative spectrochemical analysis softwares of OPUS/QUENT 5.5 to first time near infrared light spectrum
With the near-infrared primary light spectrogram that second near infrared light spectrum averagely obtain Itanlian rye sample.
It is further in step d, thick egg to be carried out using the representative Itanlian rye sample of Kjeldahl's method one by one
Bai Hanliang is measured and obtains each representative Itanlian rye sample crude protein content value；
It is further that in step f, the near infrared spectrum to calibration set sample in full spectral limit is led using single order
Number, second dervative, subtract straight line, first derivative+MSC (multiplicative scatter correction), first derivative+subtract straight line,
The normalization of order derivative+vector, without Pretreated spectra, min-max normalization, vector normalization, eliminate constant offset and
11 kinds of preprocessing procedures of multiplicative scatter correction.
The beneficial effects of the present invention are：The assay method of Itanlian rye crude protein content of the present invention is provided
The forecast model of crude protein real content in a kind of Itanlian rye based on near-infrared spectrum technique, it is true in known a large amount of samples
On the basis of real content, the near-infrared original spectrum of sample is gathered, set up and be based on near-infrared spectrum technique and Chemical Measurement side
The Quantitative Analysis Predictive Model of the Itanlian rye crude protein content of method, then, it is only necessary to by Itanlian rye sample to be measured
By obtaining Itanlian rye sample powder to be measured after pretreatment；And gather its near-infrared primary light spectrogram, spectra collection process
Time is short, and detection, in addition to early stage sets up forecast model, whole near infrared detection mistake are can be carried out after near infrared spectrum is gathered
Journey only needs short a few minutes, with it is simple to operate, detection is rapid, detection efficiency is high the characteristics of, and the method is
On the basis of knowing a large amount of sample real contents, gather the near-infrared original spectrum of sample, set up based on near-infrared spectrum technique and
The Quantitative Analysis Predictive Model of the Itanlian rye crude protein content of chemometrics method, its accuracy of detection is very high, additionally,
Detection method of the invention need not add any organic reagent, will not damage the health of testing staff, more will not be because of useization
The problems such as reagent causes environmental pollution, more safety and environmental protection, have for Itanlian rye production and breeding work and extremely weigh
The meaning wanted.
Brief description of the drawings
Fig. 1 is 404 parts of atlas of near infrared spectra of Itanlian rye sample described in embodiment；
Fig. 2 is 123 parts of atlas of near infrared spectra of representative Itanlian rye sample described in embodiment；
Fig. 3 is that the near infrared spectrum of calibration set sample in embodiment is (polynary in optimal pretreatment mode first derivative+MSC
Scatter correction) pre-processed after best modeled compose area atlas of near infrared spectra；
Fig. 4 is cross validation root-mean-square error RMSECV, validation-cross coefficient of determination R in embodiment2 cvAs main composition is tieed up
Several variation diagrams；
Fig. 5 is that the correlation between collection sample crude protein content chemical score and near infrared spectrum predicted value is verified in embodiment
Figure.
Specific embodiment
With reference to embodiment, the present invention is further illustrated.
The assay method of the Itanlian rye crude protein content, comprises the following steps：
A, set up Itanlian rye crude protein content near-infrared forecast model；The Itanlian rye crude protein content is closely red
Outer forecast model is adopted and set up with the following method, specifically includes following steps：
A, collection Itanlian rye sample, the Itanlian rye sample include different cultivars, different lines, different bearing
The fresh grass sample of phase, different planting and different parts, is respectively pre-processed the Itanlian rye sample of above-mentioned collection,
The method of the pretreatment is as described below：The Itanlian rye sample of collection is first finished 20min in 105 DEG C of environment, so
After being dried in 65 DEG C of environment afterwards, powder is ground into micropulverizer and 40 mesh sieves excessively obtain Itanlian rye sample powder
End；
B, the Itanlian rye sample powder for obtaining step a carry out respectively near infrared spectra collection obtain each spend more it is black
The near-infrared primary light spectrogram of wheat straw sample powder；
C, the near-infrared original spectrum of all Itanlian rye sample powders is analyzed using PCA algorithms, rejects tool
There is the Itanlian rye sample of similar spectral, remaining Itanlian rye sample is representative Itanlian rye sample；
D, the representative Itanlian rye sample obtained to step c using Kjeldahl's method are carried out crude protein content and entered one by one
Row measure obtains each representative Itanlian rye sample crude protein content value；
Representative Itanlian rye sample is divided into correction by the representative Itanlian rye sample crude protein content value of e, foundation
Collection and checking collection two parts, specific method are as follows：The representative Itanlian rye crude protein content value that will be obtained first from it is small to
It is ranked up greatly, 1 is then taken every 3 and is collected as checking, remaining adjusts representative Itanlian rye as calibration set
The minimum value and maximum of middle crude protein content, it is calibration set to be allowed to incorporate into；
F, by the atlas of near infrared spectra of calibration set sample and the importing OPUS/ of the crude protein content value of calibration set sample
In the commercial quantitative spectrochemical analysis softwares of QUENT 5.5, first, the near infrared spectrum to calibration set sample in full spectral limit is carried out
Pretreatment, then sets up prediction calibration model to calibration set sample using partial least-squares regression method combination validation-cross, according to
The parameter of near-infrared quantitative calibration models is evaluated prediction calibration model, the near-infrared evaluated prediction calibration model
Quantitative calibration models parameter includes coefficient of determination R2, validation-cross coefficient of determination R2Cv, validation-cross root-mean-square error RMSECV,
Its coefficient of determination R2It is 99.33%, validation-cross coefficient of determination R2 cvIt is 98.64%, validation-cross root-mean-square error RMSECV is
0.678, optimal spectrum pretreatment is determined for first derivative+MSC (multiplicative scatter correction), best modeled spectral regions are 6101.9~
4246.7cm-1, optimum factor number be 10, in evaluation procedure according to mahalanobis distance, THE PRINCIPAL FACTOR ANALYSIS figure, spectrum residual plot and
The Itanlian rye calibration set sample of chemical analysis value residual plot result rejecting abnormalities, so as to the Itanlian rye for obtaining optimal is thick
The optimal near-infrared prediction calibration model of protein content；Then, will verify that the near infrared spectrum of collection sample and checking collect the thick of sample
Checking is analyzed in the prediction calibration model that protein content importing is set up and obtains prediction checking model；Then, using near-infrared
The parameter of quantitative verification model is evaluated the prediction checking model of gained, the near-infrared evaluated prediction checking model
The parameter of quantitative verification model includes external certificate coefficient of determination R2Ev and checking root-mean-square error RMSEP, its external certificate is determined
Determine coefficients R2Ev is 98.75%, and checking root-mean-square error RMSEP is 0.572, according to mahalanobis distance, main cause in evaluation procedure
The Itanlian rye checking collection sample of plain analysis chart, spectrum residual plot and chemical analysis value residual plot result rejecting abnormalities, from
And obtain optimal Itanlian rye crude protein content near-infrared forecast model；
B, by Itanlian rye sample to be measured according to described in step a preprocess method process after obtain it is to be measured spend more it is black
Wheat straw sample powder；
C, the Itanlian rye sample powder to be measured that step B is obtained is carried out near infrared spectra collection obtain it is to be measured spend more it is black
The near-infrared primary light spectrogram of wheat straw sample powder；
D, the Itanlian rye that will be obtained in the near-infrared primary light spectrogram and step f of Itanlian rye sample powder to be measured
Crude protein content near-infrared forecast model is imported into the commercial quantitative spectrochemical analysis softwares of OPUS/QUENT 5.5, is transported by model
Point counting is analysed, you can obtain the content of crude protein in Itanlian rye sample to be measured.
The assay method of Itanlian rye crude protein content of the present invention provides a kind of based near infrared spectrum skill
The forecast model of crude protein real content in the Itanlian rye of art, on the basis of known a large amount of sample real contents, collection
The near-infrared original spectrum of sample, sets up the Itanlian rye crude protein based on near-infrared spectrum technique and chemometrics method
The Quantitative Analysis Predictive Model of content, then, it is only necessary to by Itanlian rye sample to be measured by obtaining to be measured after pretreatment
Itanlian rye sample powder；And its near-infrared primary light spectrogram is gathered, spectra collection process time is short, in collection near infrared light
Detection is can be carried out after spectrum, in addition to early stage sets up forecast model, whole near infrared detection process only needs short a few minutes, tool
There is the characteristics of simple to operate, detection is rapid, detection efficiency is high, and the method is in the base in known a large amount of sample real contents
On plinth, gather the near-infrared original spectrum of sample, set up based on near-infrared spectrum technique and chemometrics method spend more it is black
The Quantitative Analysis Predictive Model of wheat straw crude protein content, its accuracy of detection is very high, additionally, detection method of the invention need not
Any organic reagent is added, the health of testing staff will not be damaged, more will not be because causing environmental pollution etc. to be asked using chemical reagent
Topic, more safety and environmental protection, have particularly important meaning for Itanlian rye production and breeding work.
The accuracy of detection of forecast model has direct relation with the species of collection sample, in order to further increase forecast model
Accuracy of detection, need to gather the Itanlian rye sample of different growing, breeding time of the Itanlian rye include tillering stage,
Jointing stage, boot stage, heading stage, florescence, productive phase, maturity period.
It is further that accuracy of detection and the species of collection sample of forecast model have direct relation, in order to further
Increase the accuracy of detection of forecast model, the Itanlian rye sample of different planting, the cultivation of the Itanlian rye need to be gathered
Training mode includes broadcasting sowing planting type, culturing and transplanting seedlings planting type, applied nitrogen planting type.
It is further that accuracy of detection and the species of collection sample of forecast model have direct relation, in order to further
Increase the accuracy of detection of forecast model, the Itanlian rye sample of different parts, the collection portion of the Itanlian rye need to be gathered
Position includes stem, leaf, complete stool.
In order that the near-infrared primary light spectrogram of the Itanlian rye sample for obtaining is more accurate true, in stepb, adopt
Near infrared spectra collection is carried out respectively to Itanlian rye sample powder with method as described below, specifically, take spending more in right amount
Rye grass sample powder, is put into Bruker MPA type Fourier transformation NIRS instrument specimen cups, sample is shakeout naturally, sets instrument
Device running parameter, gathers sample near infrared spectrum, the first time near infrared light spectrum of the sample is obtained, then, by specimen cup
Sample take out after place into specimen cup, sample is shakeout naturally, gather sample near infrared spectrum again, obtain the sample
Second near infrared light spectrum, then to first time near infrared light spectrum and second near infrared light spectrum averagely, obtain
The near-infrared primary light spectrogram of the Itanlian rye sample.
It is further that the Bruker MPA types Fourier transformation NIRS Instrument working parameters are set as：Spectral range
4000~12500cm-1, resolution ratio 8cm-1, scanning times 64 times.
Operate for convenience, using the commercial quantitative spectrochemical analysis softwares of OPUS/QUENT 5.5 to first time near infrared spectrum
Value and second near infrared light spectrum averagely obtain the near-infrared primary light spectrogram of Itanlian rye sample.
It is further in step d, thick egg to be carried out using the representative Itanlian rye sample of Kjeldahl's method one by one
Bai Hanliang is measured and obtains each representative Itanlian rye sample crude protein content value；
It is further that in step f, the near infrared spectrum to calibration set sample in full spectral limit is led using single order
Number, second dervative, subtract straight line, first derivative+MSC (multiplicative scatter correction), first derivative+subtract straight line,
The normalization of order derivative+vector, without Pretreated spectra, min-max normalization, vector normalization, eliminate constant offset and
11 kinds of preprocessing procedures of multiplicative scatter correction.
Embodiment
A, set up Itanlian rye crude protein content near-infrared forecast model；The Itanlian rye crude protein content is closely red
Outer forecast model is adopted and set up with the following method, specifically includes following steps：
A, collection Itanlian rye sample, the Itanlian rye sample is the Itanlian rye of 2015-2016 collections
Sample, including 16 states examine kinds, 22 new lines, and collection breeding time includes tillering stage, jointing stage, boot stage, heading stage, opens
Florescence, productive phase, seven breeding times of maturity period, collection position include stem, leaf, complete stool, gather the planting type of Itanlian rye
Including broadcasting sowing planting type, culturing and transplanting seedlings planting type, applied nitrogen planting type, Itanlian rye sample has 403 parts altogether,
105 DEG C of de-enzyme 20min, after 65 DEG C of drying, powder are ground into micropulverizer and 40 mesh sieves are crossed, and obtain Itanlian rye sample
Product powder；
B, the Itanlian rye sample powder for obtaining step a carry out respectively near infrared spectra collection obtain each spend more it is black
The near-infrared primary light spectrogram of wheat straw sample powder；Specifically, taking appropriate Itanlian rye sample powder, Bruker companies are put into
In the MPA type Fourier transformation NIRS instrument specimen cups of production, sample is shakeout naturally, when loading sample, sample is kept as far as possible
Useful load, real close degree are consistent with surfacing, and sample loading volume is half of specimen cup capacity or so, setting instrument work ginseng
Number is 4000~12500cm of Spectral range-1, resolution ratio 8cm-1, scanning times 64 times are adopted using the built-in reference of instrument as correction
Collection sample spectra；Spectra collection is carried out under the conditions of 25 ± 0.5 DEG C of room temperature, the first time near infrared light spectrum of the sample is obtained,
Then, placed into after the sample in specimen cup is taken out in specimen cup, sample is shakeout naturally, sample near infrared light is gathered again
Spectrum, obtains second near infrared light spectrum of the sample, and collection is twice to down-sample the spectral drift for causing, then adopting
With the commercial quantitative spectrochemical analysis softwares of OPUS/QUENT 5.5 to first time near infrared light spectrum and second near infrared light spectrum
Carry out averagely, obtaining the near-infrared primary light spectrogram of Itanlian rye sample, sample primary light spectrogram is as shown in Figure 1；
C, the primary light spectrogram that will be obtained in step b import the commercial spectrum of OPUS/QUENT 5.5 of Bruker companies of Germany
In quantitative analysis software, the near-infrared original spectrum of all Itanlian rye sample powders is analyzed using PCA algorithms, picked
Except the Itanlian rye sample with similar spectral, remaining 123 parts of Itanlian rye samples are representative Itanlian rye sample,
Its sample primary light spectrogram is as shown in Figure 2；
D, the representative Itanlian rye sample obtained to step c using Kjeldahl's method are carried out crude protein content and entered one by one
Row measure obtains each representative Itanlian rye sample crude protein content value；
Described Kjeldahl's method (GB/T 6432-1994) is：The types of Kjeltec 8400 using FOSS companies are full-automatic
Kjeldahl apparatus carries out crude protein measure, and its step is as follows：Sample determination weighs 0.1~1g sample powders, is accurate to
0.0001g.FOSS Tecator digestings are opened, preheating is that temperature reaches 420 DEG C；The sample that will be weighed up is placed in digest tube
(it is careful not to stick on tube wall, in order to avoid digestion is incomplete), add 2 efficient kjeldahl determination catalyst plates and 12mL sulfuric acid
(H2SO4), digest tube is shaken gently for, sample is moistened by sulfuric acid, digest tube is placed in the FOSS having been warmed up to 420 DEG C
On Tecator digestings, while aspiration pump is opened into maximum, after 5min, aspiration pump is turned down to acid mist just full of waste discharge cover,
Condensation ring is formed in digest tube.Treatments of the sample takes out digest tube and is cooled to room temperature to transparent blue green liquid after about 90min.
Digest tube is put into the type full-automatic Kjeldahl determination devices of Foss Kjeltec 8400, according to kjeldahl apparatus Kjeltec's 8400
It is required that installing 40% NaOH (NaOH) solution, boric acid (H3BO3) (1% boric acid aqueous solution 1000mL adds 0.1% to absorbing liquid
Bromocresol green ethanol solution 10mL, 0.1% methyl red ethanol solution 7mL, 4% sodium hydrate aqueous solution 0.5mL), 0.1mol/L
Hydrochloric acid (HCL) titrand and cooling water, according to instrument, constant program is distilled and is titrated in itself, after end to be analyzed,
With the volume for recording consumed normal hydrochloric acid titrating solution.Blank determination carries out above-mentioned experiment with 0.5g sucrose instead of sample.Press
According to formula --- crude protein (%)=(V2-V1) × C × 0.0140 × K × 100 ÷ W calculate crude protein content；Wherein V2It is titration
The volume (mL) of hydrochloric acid standard solution is consumed during sample；V1The volume (mL) of consumption hydrochloric acid standard solution during for titration blank；C is
The hydrochloric acid standard solution concentration used during titration is 0.1mol/L；K is 6.25 for the mean coefficient that nitrogen is converted into protein；W
It is sample quality；
Representative Itanlian rye sample is divided into correction by the representative Itanlian rye sample crude protein content value of e, foundation
Collection and checking collection two parts, specific method are as follows：The representative Itanlian rye crude protein content value that will be obtained first from it is small to
It is ranked up greatly, 1 is then taken every 3 and is collected as checking, remaining is used as calibration set；I.e. representative 123 parts are spent more
In rye grass sample, there are 93 parts as calibration set, 30 parts collect as checking, and adjust crude protein content in Itanlian rye
Minimum value and maximum, it is calibration set to be allowed to incorporate into.
F, by the atlas of near infrared spectra of calibration set sample and the importing OPUS/ of the crude protein content value of calibration set sample
In the commercial quantitative spectrochemical analysis softwares of QUENT 5.5, first, the near infrared spectrum to calibration set sample in full spectral limit is carried out
Pretreatment, in full spectral limit to the near infrared spectrum of calibration set sample using first derivative, second dervative, subtract one it is straight
Line, first derivative+MSC (multiplicative scatter correction), first derivative+subtract straight line, first derivative+vector normalization, do not have
Pretreated spectra, min-max normalization, vector normalization, elimination constant offset and 11 kinds of spectrum of multiplicative scatter correction are pre-
Processing method, then sets up prediction calibration model, root to calibration set sample using partial least-squares regression method combination validation-cross
Prediction calibration model is evaluated according to the parameter of near-infrared quantitative calibration models, determines optimal spectrum preprocess method, it is main into
Part factor number and best modeled spectral regions, finally predicting the minimum value of the validation-cross root-mean-square error RMSECV of calibration model
Correspondence optimal spectrum preprocess method, best modeled spectral regions and optimal main Composition Factor number, Fig. 3 is the near red of calibration set sample
External spectrum best modeled after optimal pretreatment mode first derivative+MSC is pre-processed composes the atlas of near infrared spectra in area；Table 1
It is best modeled spectrum area and model parameter under different preprocessing procedures, as described in table 1, the final optimal spectrum for determining is located in advance
It is first derivative+MSC to manage, and best modeled spectral regions are 6101.9~4246.7cm-1, optimum factor number is 10；In evaluation procedure
It is middle according to many of the result rejecting abnormalities such as mahalanobis distance, THE PRINCIPAL FACTOR ANALYSIS figure, spectrum residual plot and chemical analysis value residual plot
Flower rye grass calibration set sample, so as to obtain the optimal near-infrared prediction calibration model of optimal Itanlian rye crude protein content,
Coefficient of determination R is included to the near-infrared quantitative calibration models parameter that prediction calibration model is evaluated2, the validation-cross coefficient of determination
R2Cv, validation-cross root-mean-square error RMSECV；Then, external certificate is carried out to prediction calibration model using checking collection sample,
The specific method of described external certificate is using calibration model is predicted to verifying that collecting spectrum is predicted, i.e., in German Bruker
Select to set up quantitative 2 methods in the commercial quantitative spectrochemical analysis softwares of OPUS/QUENT 5.5 of company, the near of collection sample will be verified
Checking is analyzed in the prediction calibration model that the crude protein content importing of infrared spectrum and checking collection sample is set up to be predicted
Checking model；Then, the prediction checking model of gained is evaluated using the parameter of near-infrared quantitative verification model, is being evaluated
During according to result rejecting abnormalities such as mahalanobis distance, THE PRINCIPAL FACTOR ANALYSIS figure, spectrum residual plot and chemical analysis value residual plots
Itanlian rye checking collection sample, so as to obtain optimal Itanlian rye crude protein content near-infrared forecast model；To prediction
The near-infrared quantitative verification model parameter that checking model is evaluated includes external certificate coefficient of determination R2Ev and checking root mean square
Error RMSEP.That is prediction calibration model has coefficient of determination R higher2, validation-cross coefficient of determination R2Cv and relatively low RMSECV,
Prediction checking model has external certificate coefficient of determination R higher2When ev and relatively low RMSEP values, the near-infrared forecast model
Suitable for the measure of Itanlian rye crude protein content；Fig. 4 is cross validation root-mean-square error RMSECV, validation-cross decision system
Number R2With the variation diagram of main composition dimension, Fig. 5 is that checking collection sample crude protein content chemical score is predicted near infrared spectrum to cv
Dependency graph between value；By optimizing evaluation, the forecast model of described optimal Itanlian rye crude protein content, it is determined
Determine coefficients R2It is 99.33%, validation-cross coefficient of determination R2 cvIt is 98.64%, external certificate coefficient of determination R2 evFor 98.75%,
RMSECV is that 0.678 and RMSEP is 0.572；It is 93 that the prediction calibration model does not have rejecting abnormalities sample, i.e. calibration set sample
It is individual；Described prediction checking model eliminates two abnormal samples, i.e. checking and concentrates for what is verified 28 samples；
Table 1
B, by Itanlian rye sample to be measured according to described in step a preprocess method process after obtain it is to be measured spend more it is black
Wheat straw sample powder；
C, the Itanlian rye sample powder to be measured that step B is obtained is carried out near infrared spectra collection obtain it is to be measured spend more it is black
The near-infrared primary light spectrogram of wheat straw sample powder；
D, the Itanlian rye that will be obtained in the near-infrared primary light spectrogram and step f of Itanlian rye sample powder to be measured
Crude protein content near-infrared forecast model is imported into the commercial quantitative spectrochemical analysis softwares of OPUS/QUENT 5.5, is transported by model
Point counting is analysed, you can obtain the content of crude protein in Itanlian rye sample to be measured.
Following table is the content value of the crude protein that 48 parts of Itanlian rye samples to be measured are measured using the above method；
As seen from the above table, using Itanlian rye crude protein content of the present invention assay method determine spend more it is black
With its actual value closely, its accuracy of detection is very high for the measured value of wheat straw crude protein content.
Embodiment described above is only that the preferred embodiment of the present invention is described, not to model of the invention
Enclose and be defined.Any those of ordinary skill in the art, are not departing from the situation of Spirit Essence of the invention and technical scheme
Under, may be by above-mentioned methods and techniques content and many possible variations and modification are made to technical solution of the present invention.Cause
This, every content without departing from technical solution of the present invention, according to technical spirit of the invention to variation made for any of the above embodiments
And modification, belong in the range of technical solution of the present invention protection.
Claims (9)
1. a kind of assay method of Itanlian rye crude protein content, it is characterised in that comprise the following steps：
A, set up Itanlian rye crude protein content near-infrared forecast model；The Itanlian rye crude protein content near-infrared is pre-
Survey model is adopted and set up with the following method, specifically includes following steps：
A, collection Itanlian rye sample, the Itanlian rye sample include different cultivars, different lines, different growing,
The fresh grass sample of different planting and different parts, is respectively pre-processed the Itanlian rye sample of above-mentioned collection, institute
The method for stating pretreatment is as described below：The Itanlian rye sample of collection is first finished 20min in 105 DEG C of environment, then
After being dried in 65 DEG C of environment, powder is ground into micropulverizer and 40 mesh sieves excessively obtain Itanlian rye sample powder
End；
B, the Itanlian rye sample powder for obtaining step a carry out near infrared spectra collection and obtain each Itanlian rye respectively
The near-infrared primary light spectrogram of sample powder；
C, the near-infrared original spectrum of all Itanlian rye sample powders is analyzed using PCA algorithms, rejecting has phase
Like the Itanlian rye sample of spectrum, remaining Itanlian rye sample is representative Itanlian rye sample；
D, the representative Itanlian rye sample obtained to step c using Kjeldahl's method are carried out crude protein content and surveyed one by one
Surely each representative Itanlian rye sample crude protein content value is obtained；
E, according to representative Itanlian rye sample crude protein content value by representative Itanlian rye sample be divided into calibration set and
Checking collection two parts, specific method is as follows：The representative Itanlian rye crude protein content value that will be obtained first is entered from small to large
Row sequence, 1 is then taken every 3 and is collected as checking, and remaining adjusts thick in representative Itanlian rye as calibration set
The minimum value and maximum of protein content, it is calibration set to be allowed to incorporate into；
F, by the atlas of near infrared spectra of calibration set sample and the importing OPUS/QUENT of the crude protein content value of calibration set sample
In 5.5 commercial quantitative spectrochemical analysis softwares, first, the near infrared spectrum to calibration set sample in full spectral limit carries out pre- place
Reason, then sets up prediction calibration model to calibration set sample using partial least-squares regression method combination validation-cross, according near red
The parameter of outer quantitative calibration models is evaluated prediction calibration model, and the near-infrared that prediction calibration model is evaluated is quantified
Calibration model parameter includes coefficient of determination R2, validation-cross coefficient of determination R2Cv, validation-cross root-mean-square error RMSECV, it is determined
Determine coefficients R2It is 99.33%, validation-cross coefficient of determination R2 cvIt is 98.64%, validation-cross root-mean-square error RMSECV is
0.678, optimal spectrum pretreatment is determined for first derivative+MSC (multiplicative scatter correction), best modeled spectral regions are 6101.9~
4246.7cm-1, optimum factor number be 10, in evaluation procedure according to mahalanobis distance, THE PRINCIPAL FACTOR ANALYSIS figure, spectrum residual plot with
And the Itanlian rye calibration set sample of chemical analysis value residual plot result rejecting abnormalities, so as to obtain optimal Itanlian rye
The optimal near-infrared prediction calibration model of crude protein content；Then, will verify that the near infrared spectrum of collection sample and checking collect sample
Checking is analyzed in the prediction calibration model that crude protein content importing is set up and obtains prediction checking model；Then, using near red
The parameter of outer quantitative verification model is evaluated the prediction checking model of gained, and what prediction checking model was evaluated is near red
The parameter of outer quantitative verification model includes external certificate coefficient of determination R2Ev and checking root-mean-square error RMSEP, its external certificate
Coefficient of determination R2Ev is 98.75%, and checking root-mean-square error RMSEP is 0.572, according to mahalanobis distance, master in evaluation procedure
The Itanlian rye checking collection sample of factor analysis figure, spectrum residual plot and chemical analysis value residual plot result rejecting abnormalities,
So as to obtain optimal Itanlian rye crude protein content near-infrared forecast model；
B, by Itanlian rye sample to be measured according to described in step a preprocess method process after obtain Itanlian rye to be measured
Sample powder；
C, the Itanlian rye sample powder to be measured that step B is obtained is carried out near infrared spectra collection obtain Itanlian rye to be measured
The near-infrared primary light spectrogram of sample powder；
D, the thick egg of Itanlian rye that will be obtained in the near-infrared primary light spectrogram and step f of Itanlian rye sample powder to be measured
Bai Hanliang near-infrared forecast models are imported into the commercial quantitative spectrochemical analysis softwares of OPUS/QUENT 5.5, by model calculation point
Analysis, you can obtain the content of crude protein in Itanlian rye sample to be measured.
2. the assay method of Itanlian rye crude protein content according to claim 1, it is characterised in that：It is described spend more it is black
The breeding time of wheat straw includes tillering stage, jointing stage, boot stage, heading stage, florescence, productive phase, maturity period.
3. the assay method of Itanlian rye crude protein content according to claim 1, it is characterised in that：It is described spend more it is black
The planting type of wheat straw includes broadcasting sowing planting type, culturing and transplanting seedlings planting type, applied nitrogen planting type.
4. the assay method of Itanlian rye crude protein content according to claim 1, it is characterised in that：It is described spend more it is black
The collection position of wheat straw includes stem, leaf, complete stool.
5. the assay method of Itanlian rye crude protein content according to claim 1, it is characterised in that：In stepb,
Near infrared spectra collection is carried out using method as described below respectively to Itanlian rye sample powder, specifically, taking appropriate many
Flower rye grass sample powder, is put into Bruker MPA type Fourier transformation NIRS instrument specimen cups, sample is shakeout naturally, sets
Instrument working parameter, sample near infrared spectrum is gathered under the conditions of being 25 ± 0.5 DEG C in temperature, and the first time for obtaining the sample is closely red
External spectrum value, then, is placed into specimen cup after the sample in specimen cup is taken out, and sample is shakeout naturally, and sample is gathered again
Product near infrared spectrum, obtains second near infrared light spectrum of the sample, then to first time near infrared light spectrum and second
Near infrared light spectrum averagely obtain the near-infrared primary light spectrogram of the Itanlian rye sample.
6. the assay method of Itanlian rye crude protein content according to claim 5, it is characterised in that：The Bruker
MPA type Fourier transformation NIRS Instrument working parameters are set as：4000~12500cm of Spectral range-1, resolution ratio 8cm-1, scanning
Number of times 64 times.
7. the assay method of Itanlian rye crude protein content according to claim 6, it is characterised in that：Using OPUS/
QUENT 5.5 is commercial, and quantitative spectrochemical analysis software is put down to first time near infrared light spectrum and second near infrared light spectrum
, the near-infrared primary light spectrogram of Itanlian rye sample is obtained.
8. the assay method of Itanlian rye crude protein content according to claim 1, it is characterised in that：In step d,
Crude protein content is carried out using the representative Itanlian rye sample of Kjeldahl's method one by one and is measured that to obtain each representative
Itanlian rye sample crude protein content value.
9. the assay method of Itanlian rye crude protein content according to claim 1, it is characterised in that：In step f,
In full spectral limit to the near infrared spectrum of calibration set sample using first derivative, second dervative, subtract straight line, single order and lead
Number+MSC (multiplicative scatter correction), first derivative+subtract straight line, first derivative+vector normalization, no spectrum are located in advance
Reason, min-max normalization, vector normalization, elimination 11 kinds of preprocessing procedures of constant offset and multiplicative scatter correction.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107655852A (en) * | 2017-09-29 | 2018-02-02 | 广东出入境检验检疫局检验检疫技术中心 | The near infrared spectrum quick determination method of essential nutrient in baby formula milk powder |
| CN109374548A (en) * | 2018-11-14 | 2019-02-22 | 深圳职业技术学院 | A method of quickly measuring nutritional ingredient in rice using near-infrared |
| CN110044841A (en) * | 2019-05-16 | 2019-07-23 | 四川省草原科学研究院 | Utilize the method for near infrared spectrum detection Phalaris grass crude protein content |
| CN112798555A (en) * | 2020-12-25 | 2021-05-14 | 江苏大学 | Modeling method for improving adaptability of coarse protein correction model of wheat flour |
| CN113189042A (en) * | 2021-05-13 | 2021-07-30 | 大连工业大学 | Method for rapidly detecting protein content of infant supplementary food nutrition bag |
| CN117054354A (en) * | 2023-10-12 | 2023-11-14 | 云南省林业和草原科学院 | Portable seed maturity spectrum detection system and device |
| CN117171566A (en) * | 2022-08-17 | 2023-12-05 | 无锡迅杰光远科技有限公司 | Sample content identification method, device and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104165886A (en) * | 2014-08-01 | 2014-11-26 | 湖北富邦科技股份有限公司 | Method for determining grain protein |
| CN104316492A (en) * | 2014-11-12 | 2015-01-28 | 东北农业大学 | Method for near-infrared spectrum measurement of protein content in potato tuber |
-
2017
- 2017-03-01 CN CN201710115574.7A patent/CN106908408A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104165886A (en) * | 2014-08-01 | 2014-11-26 | 湖北富邦科技股份有限公司 | Method for determining grain protein |
| CN104316492A (en) * | 2014-11-12 | 2015-01-28 | 东北农业大学 | Method for near-infrared spectrum measurement of protein content in potato tuber |
Non-Patent Citations (2)
| Title |
|---|
| 严衍禄 等: "《近红外光谱分析的原理、技术与应用》", 31 January 2013, 中国轻工业出版社 * |
| 赵环环 等: "近红外光谱分析技术在黑麦草粉粗蛋白测定中的应用", 《动物营养学报》 * |
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|---|---|---|---|---|
| CN107655852A (en) * | 2017-09-29 | 2018-02-02 | 广东出入境检验检疫局检验检疫技术中心 | The near infrared spectrum quick determination method of essential nutrient in baby formula milk powder |
| CN109374548A (en) * | 2018-11-14 | 2019-02-22 | 深圳职业技术学院 | A method of quickly measuring nutritional ingredient in rice using near-infrared |
| CN110044841A (en) * | 2019-05-16 | 2019-07-23 | 四川省草原科学研究院 | Utilize the method for near infrared spectrum detection Phalaris grass crude protein content |
| CN112798555A (en) * | 2020-12-25 | 2021-05-14 | 江苏大学 | Modeling method for improving adaptability of coarse protein correction model of wheat flour |
| CN113189042A (en) * | 2021-05-13 | 2021-07-30 | 大连工业大学 | Method for rapidly detecting protein content of infant supplementary food nutrition bag |
| CN117171566A (en) * | 2022-08-17 | 2023-12-05 | 无锡迅杰光远科技有限公司 | Sample content identification method, device and storage medium |
| CN117054354A (en) * | 2023-10-12 | 2023-11-14 | 云南省林业和草原科学院 | Portable seed maturity spectrum detection system and device |
| CN117054354B (en) * | 2023-10-12 | 2024-03-05 | 云南省林业和草原科学院 | Portable seed maturity spectrum detection system and device |
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