CN105445218A - Establishing method of self-adaptive model for detection of content of protein of rapeseeds on basis of mid-infrared spectrum - Google Patents
Establishing method of self-adaptive model for detection of content of protein of rapeseeds on basis of mid-infrared spectrum Download PDFInfo
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Abstract
An establishing method of a self-adaptive model for detection of content of protein of rapeseeds on the basis of a mid-infrared spectrum comprises steps as follows: I, mid-infrared photoacoustic spectrum information is sampled and acquired, continuous scanning is performed for multiple times, and an average spectrum is obtained; II, the content of the protein of the rapeseeds is chemically analyzed, and a chemical reference value is obtained; III, noise elimination, smoothing and standardized preprocessing are performed on the spectrum information; IV, spectrum data are calculated with an Euclidean distance method, and sequencing from small to large is performed; V, a prediction model based on the spectrum information is established; VI, a mid-infrared photoacoustic spectrum of to-be-tested samples is taken into the model, the content of the protein of the to-be-tested rapeseed samples is calculated and predicted, and a predicted value is obtained. The method is high in sensitivity, simple to operate and nondestructive to samples, the content of required samples is small, no chemical reagent is used, the method has the universality, the prediction result is accurate, invalid information interference of the samples can be effectively reduced, a sample modeling set can be optimized and simplified, and model calculation is quick and accurate.
Description
Technical field
The invention belongs to agriculture test method field, be specifically related to a kind of based on the method for building up of middle infrared spectrum to quick, accurate, the Non-Destructive Testing adaptive model of rapeseed protein content.
Background technology
Rape is one of large oil crops in the world four, and China is rape seed area 7,000,000 hectares throughout the year, and total product 1,200 ten thousand tons, accounts for other major oil vegetable seed producing countries of more than 60%, the Yuan Chao world of national edible vegetable oil total production.Rape-seed production occupies extremely important status in Chinese national economy, and the examination and controlling of rapeseed nutritional quality is that the important technology that china rape is produced supports.Nitrogen content is the important quality index of rapeseed, in dregs of rapeseed cake after oil expression, protein content reaches 35%-39%, compare corn, wheat exceeds 3-4 doubly, and Amino Acids in Proteins ratio of components is more reasonable, essential amino acids content is higher, is the important sources of feed protein.Thus, carry out quick, accurate and harmless mensuration to protein content in rapeseed, quality and the rape cake feedstuff quality of assessment rapeseed are significant
The detection method of traditional protein content has Kjeldahl's method, Thomas's combustion method etc., and these methods not only need to carry out pre-service to rapeseed sample, damage sample, and complicated operation, and cost is higher.Infrared spectrum technology is for the qualitative and quantitative analysis of agricultural product in recent years, but how to be undertaken by near-infrared spectral reflectance technology.When near-infrared spectrum technique characterizes rape variety, required sample size is generally 3-5g, can produce the small sample kind that selfing and hybridization etc. are important when breeding work, and these small sample seed amounts are low, can not meet sample size needs; Some rapeseed research needs special spectral device and system, comparatively complicated.Therefore, how detecting rapeseed content fast, improving the precision of prediction of infrared spectrum, is also a current important subject.
Middle infrared spectrum is that the fundamental frequency of material absorbs, and absorbance is large, and characteristic is strong.Optoacoustic spectroscopy is based on modern optoacoustic switch technology, a branch of infrared light incides optoacoustic annex, sample produces thermal effect after receiving Infrared irradiation, and by heat transfer to the gaseous state in sample cell, understand Swelling and contraction after gas is heated thus produce heat wave, heat wave is detected by the microphone of sensitivity, is optoacoustic spectroscopy, and optoacoustic spectroscopy can be exchanged into electric signal and obtains infrared photoacoustic spectra.Highly sensitive, the required sample size of optoacoustic spectroscopy is few, do not affect by sample shape, without the need to pre-treatment, to sample nondestructive, can realize in-site detecting, demonstrates good application potential in agricultural.
Mid-infrared spectral wavelength coverage is at 4000-400cm
-1, spectral information enriches, and peak overlap does not have near-infrared region serious, and detectability is more sensitive.But the demand of existing mid-infrared light spectral technology to test sample still there are certain requirements, the sample that Few sample of rapeseed seed amount is low can not be met, have some limitations, cannot be directly used in simply rapeseed protein content is carried out fast, accurately, harmless mensuration.
Summary of the invention
The object of this invention is to provide a kind of method for building up of the adaptive model quick to rapeseed protein content, accurate, harmless based on mid-infrared light acousto-optic spectrum spectrum.By detecting the infrared photoacoustic spectra information of rapeseed sample, utilize the spectroscopic data of the sample spectra information gathered and the rapeseed protein content measured, calculated by Euclidean distance, the training sample spectra the most similar to spectrum to be predicted is sorted from small to large by Euclidean distance, the spectroscopic data of new sort is built spectroscopic data model by partial least square method, further model is optimized by index of correlation value, can realizes carrying out fast the protein content of testing sample, accurately, Nondestructive Detection.
Technical scheme of the present invention is as follows:
A method for building up for middle infrared spectrum rapeseed protein content detection adaptive model, comprises following steps:
Step one: rapeseed samples every part of 100-200mg, is placed in FT-mid-IR fiber optics spectroscopy instrument-optoacoustic annex sample cell, and gather mid-infrared light acousto-optic spectrum information, continuous sweep repeatedly, is averaged spectrum;
Step 2: in step one light-metering spectrum rapeseed 5g, chemical analysis is carried out to its protein content, is multiplied by 6.25 in the result of nitrogen content, do the protein content of rapeseed, obtain chemical reference value;
Step 3: rapeseed spectral information step one gathered carries out de-noising, level and smooth, standardization pre-service;
Step 4: spectroscopic data step 3 handled well is calculated by Euclidean distance method; And the Euclidean distance calculated is sorted from small to large according to the distance the most close with spectrum to be predicted;
Step 5: the spectroscopic data of new sort, by partial least square method, sets up the rapeseed protein content prediction model based on spectral information.
The mid-infrared light acousto-optic bands of a spectrum of testing sample rapeseed are entered model by step 6: utilize the adaptive model set up in step 5, carry out calculating and predict, draw predicted value to the protein content of rapeseed sample to be measured;
Then step 2 chemical method gained chemistry reference value and adaptive model is utilized to predict that the predicted value of gained compares, the constructed mid-infrared light acousto-optic spectrum model chemical reference value that pre-and Kjeldahl's method detects to the predicted value of rapeseed protein content is basically identical, predicts the outcome reliably.
More optimize and more particularly, the method for operating of each step of the present invention is:
Step one: rapeseed samples every part of 100-200mg, be placed in FT-mid-IR fiber optics spectroscopy instrument (Nicolet8700, ThermoFisherScientific, USA)-optoacoustic annex (PA300, MTEC, USA), in sample cell, gather mid-infrared light acousto-optic spectrum information, collection wavelength coverage is 4000-800cm
-1, scanning resolution is 8cm
-1; Index glass speed is 0.4747cm
-1s, 64 continuous sweep is averaged spectrum.
Step 2: to its protein content, chemical analysis is carried out to the rapeseed 5g that in step one, light-metering has been composed, utilize full-automatic Kjeldahl determination device (Buchi339, CH), adopt Kjeldahl nitrogen determination, be multiplied by the result of nitrogen content the protein content that 6.25 do rapeseed, obtain chemical reference value.
Step 3: rapeseed spectral information step one gathered carries out de-noising, level and smooth, standardization pre-service (Du Changwen, " soil infrared photoacoustic spectra Principle and application ", Science Press, Beijing, 2012 editions).
Step 4: sample to be tested spectrum step 3 handled well and training sample spectroscopic data are calculated by Euclidean distance method.And the Euclidean distance calculated is sorted from small to large according to the distance the most close with spectrum to be predicted.
Step 5: the spectroscopic data of new sort, by partial least square method, sets up the rapeseed protein content prediction model based on spectral information.By index of correlation to model parameter as coefficient R
2, root-mean-square error RMSE and model prediction performance synthesis evaluation index RPD, makes the coefficient R of model
2close to 1, root-mean-square error RMSE is close to 0, and model prediction performance synthesis evaluation index RPD is greater than 2, can obtain the optimal sample number setting up forecast model.By to the comparison of model and optimization, finally obtain optimum adaptive model.Model is set up and is carried out (Mathwork, USA) with computation process by Matlab2013a software.
The mid-infrared light acousto-optic bands of a spectrum of testing sample rapeseed are entered model by step 6: utilize the adaptive model set up in step 5, carry out calculating and predict, draw predicted value to the protein content of rapeseed sample to be measured; Then step 7 chemical method gained chemistry reference value and adaptive model is utilized to predict that the predicted value of gained compares, the constructed mid-infrared light acousto-optic spectrum model chemical reference value that pre-and Kjeldahl's method detects to the predicted value of rapeseed protein content is basically identical, predicts the outcome reliably.
The advantages such as the method that the present invention utilizes Chemical Measurement to combine with infrared spectrum conveniently has fast in agricultural production, harmless, accurate, set up a kind of based on mid-infrared spectral adaptive model, can carry out fast rapeseed protein content, accurately, the mensuration that can't harm.Overcome rapeseed kind seed amount low, to implement in actual production comprehensive rapeseed quality control, maximum oil vegetable seed production economy effect, reduce testing cost have important practical significance.
Beneficial effect of the present invention is:
One, the present invention utilizes mid-infrared light acousto-optic to compose rapeseed protein content, and highly sensitive, required sample size is few; Simple to operate, to sample nondestructive, do not use chemical reagent.
Two, by detecting the infrared photoacoustic spectra information architecture adaptive model of rapeseed sample, be characterized in setting up to each sample spectra the adaptive model system meeting its spectral signature, this adaptive model has universality, model is sane, estimated performance is good, result accuracy is high, model prediction accuracy and background technology actual value close, predict the outcome accurately.
Three, by the structure of adaptive model, effectively can reduce the interference of sample invalid information, optimization, reduced sample modeling collection, model calculates quick, accurate.
Accompanying drawing explanation
Fig. 1 is rapeseed protein content prediction model scatter diagram.
Embodiment
Following examples for illustration of the present invention, but are not used for limiting the scope of the invention.
If do not specialize, the conventional means that technological means all in embodiment is well known to those skilled in the art.
Embodiment 1, the method for building up of quick to rapeseed protein content, accurate, the harmless adaptive model of spectrum is composed based on mid-infrared light acousto-optic:
For 180 parts, formation testing vegetable seed sample, sample is carried out random assortment, and wherein 70 percent (126 parts) are as training sample set, and 30 percent (54 parts) try sample set for waiting.
One, training sample set and the every increment product of sample to be tested collection are got 100-200mg, be placed in FT-mid-IR fiber optics spectroscopy instrument (Nicolet8700, ThermoFisherScientific, USA)-optoacoustic annex (PA300, MTEC, USA) in sample cell, sample is put into photoacoustic cell and is no more than 2/3, closes sample cell, open high-pure helium air valve after being placed by sample, purge with high-purity helium, remove steam and carbon dioxide in photoacoustic cell.Gather mid-infrared light acousto-optic spectrum information, collection wavelength coverage is 4000-800cm
-1, scanning resolution is 8cm
-1; Index glass speed is 0.4747cm
-1s, 64 continuous sweep is averaged spectrum.
Two, for sample rapeseed every part 5g originally, chemical analysis is carried out to its protein content by all, utilize full-automatic Kjeldahl determination device (Buchi339, CH), adopt Kjeldahl nitrogen determination.Concrete steps are as follows:
Every part of rapeseed 5g dries 6h at 100 DEG C, uses agate mortar grinds sample after drying after sample;
The rapeseed powder taking the levigate oven dry of 0.5g is placed in 50mL and disappears and boil pipe, instills a small amount of deionized water and soaks sample, add the 10mL concentrated sulphuric acid, shake up, hold over night.Disappearing after spending the night is boiled pipe and is placed in constant temperature digestion instrument (LabTechEHD36, USA) and disappears and boil.Disappear when boiling and prevent curved neck funnel at the bottleneck boiling pipe that disappears, first disappear with slow fire and boil, temperature is set to 150 DEG C, and decompose until the concentrated sulphuric acid raised temperature again of emerging in a large number after the supercilious look, temperature is set to 250 DEG C, takes off when solution is uniform brownish black.Add 10 hydrogen peroxide after slightly cold to continue to disappear and boil, so in triplicate, the hydrogen peroxide of interpolation be successively reduced to disappear boil liquid become colorless or limpid after, then heat about 8min, eliminate hydrogen peroxide, taking off disappears boils pipe cooling.With the curved neck funnel of a small amount of deionized water rinsing, washing fluid flows into and disappears and boil pipe, after will disappear and boil liquid and be settled in 100mL volumetric flask and shake up (Lu Rukun " soil agrochemistry chemical analysis method ", Chinese agriculture Science Press, Beijing, 2000 editions).
In Kjeldahl's method, reagent comprises 10molL
-1naOH, 2% boric acid, 0.02molL
-1dilution heat of sulfuric acid, boric acid the indicator (-bromcresol green that methylates of 0.099:0.066).The running parameter of azotometer is set to: disappear and boil liquid consumption 20mL, and sodium hydroxide concentration is 30mL, and boric acid consumption is 15mL, and the pH of titration end-point is 4.65.During mensuration, each sample arranges a blank assay, supposes a Quality control samples every 20 samples.
Adopt the result of the nitrogen content of Kjeldahl nitrogen determination to be multiplied by the protein content that 6.25 do rapeseed, obtain chemical reference value;
Three, sample spectra information unification is carried out de-noising, level and smooth, standardization pre-service (Du Changwen, " soil infrared photoacoustic spectra Principle and application ", Science Press, Beijing, 2012 editions), concrete grammar is as follows:
Denoising smooth method adopts wavelet filtering to carry out, and provides a lot of digital filtering function in Matlab software, and adopt filtfilt function to carry out, its syntactic structure is:
[b,a]＝butter(n,wn,’low’)
SpectrumF＝filtfilt(b,a,spectrum)
Wherein variable a, b have been footage application definition a n rank cutoff frequency is the butterworth filter of wn, and low represents that cutoff frequency is the low-pass filtering of wn, and after spectrum Spectrum filtering, rreturn value is SpectrumF.
Standardization adopts the normalization function provided in Matlab software:
[pn,ps]＝mapminmas(spectrum)
Wherein pn is the data after standard, and ps is the data containing former data average and standard deviation information.
Four, sample to be tested spectrum good for pre-service and training sample spectroscopic data are calculated by Euclidean distance method.Euclidean distance D computing formula between two samples is as follows:
Wherein X
isfor the spectroscopic data of training sample, X
imfor the spectroscopic data of sample to be tested; Often group spectroscopic data in training sample is taken out one by one, calculates with the spectroscopic data of sample to be tested, draw sample to be tested and its distance, and list with a matrix type.And by the D value of Euclidean distance according to resequencing from small to large, show that new spectrum that the distance the most close with spectrum to be predicted carries out sorting from small to large sorts training sample set.
Five, the spectroscopic data of new sort is by partial least square method, sets up the rapeseed protein content prediction model based on spectral information.Pass through coefficient R
2, root-mean-square error RMSE and model prediction performance synthesis evaluation index RPD calculates, and makes the coefficient R of model
2close to 1, root-mean-square error RMSE is close to 0, and model prediction performance synthesis evaluation index RPD is greater than 2, can draw the optimal sample number setting up forecast model.By to the comparison of model and optimization, finally obtain optimum adaptive model.Model is set up and is carried out (Mathwork, USA) with computation process by Matlab2013a software.
Wherein y and y' is chemical reference value and the infrared spectrum predicted value of a sample,
for the average of sample chemical reference value, n is sample capacity, and SD is the standard deviation of simple chemical reference value.Wherein R
2more less close to 1, RMSE, illustrate that the estimated performance of model is better.As RPD>2, think that model quality is excellent; As 1.5<PRD<2, think that model can accept; As RPD<1.5, then think model poor unacceptable (Du Changwen, " soil infrared photoacoustic spectra Principle and application ", Science Press, Beijing, 2012 editions).
The R of model is drawn by parameter optimization
2be 0.9205, RMSE be 0.594%, RPD value be 2.60, think that this model quality is excellent, quantitative effect is better.Fig. 1 mid point shape scatter diagram represents the scatter diagram of the pre-actual value of the training sample of this model and predicted value, fit line when figure bend is perfect forecast, and the training sample of rapeseed is roughly distributed in fit line both sides, does not have larger prediction deviation.
Six, the rapeseed optoacoustic spectroscopy data of testing sample are brought in the adaptive model that above-mentioned steps five sets up and the chemical score corresponding to the spectral value of sample to be tested is predicted, draw predicted value, then utilize chemical method gained chemistry reference value to compare.In Fig. 1, square scatter diagram represents the sample to be tested actual value of this model and the scatter diagram of predicted value, fit line when figure bend is perfect forecast, the R of sample to be tested
2be 0.9013, RMSE be 0.633%, RPD value be 2.51.The sample to be tested of rapeseed is roughly distributed in fit line both sides, does not have larger prediction deviation.
Visible, the chemical reference value that constructed mid-infrared light acousto-optic spectrum model detects the predicted value of rapeseed protein content and Kjeldahl's method is basically identical, predicts the outcome reliable.
The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the prerequisite not departing from the technology of the present invention principle; can also make some improvement and connect retouching, these improvements and modifications also should be considered as protection scope of the present invention.
Claims (6)
1. a method for building up for middle infrared spectrum rapeseed protein content detection adaptive model, comprises following steps:
Step one: rapeseed samples every part of 100-200mg, is placed in FT-mid-IR fiber optics spectroscopy instrument-optoacoustic annex sample cell, and gather mid-infrared light acousto-optic spectrum information, continuous sweep repeatedly, is averaged spectrum;
Step 2: in step one light-metering spectrum rapeseed 5g, chemical analysis is carried out to its protein content, is multiplied by 6.25 in the result of nitrogen content, do the protein content of rapeseed, obtain chemical reference value;
Step 3: rapeseed spectral information step one gathered carries out de-noising, level and smooth, standardization pre-service;
Step 4: spectroscopic data step 3 handled well is calculated by Euclidean distance method; And the Euclidean distance calculated is sorted from small to large according to the distance the most close with spectrum to be predicted;
Step 5: the spectroscopic data of new sort, by partial least square method, sets up the rapeseed protein content prediction model based on spectral information;
The mid-infrared light acousto-optic bands of a spectrum of testing sample rapeseed are entered model by step 6: utilize the adaptive model set up in step 5, carry out calculating and predict, draw predicted value to the protein content of rapeseed sample to be measured.
2. the method for building up of middle infrared spectrum rapeseed protein content detection adaptive model according to claim 1, is characterized in that, in step one, gathering mid-infrared light acousto-optic spectrum information is that collection wavelength coverage is 4000-800cm
-1, scanning resolution is 8cm
-1; Index glass speed is 0.4747cm
-1s, 64 continuous sweep is averaged spectrum.
3. the method for building up of middle infrared spectrum rapeseed protein content detection adaptive model according to claim 1, it is characterized in that, in step 4, sample to be tested spectrum good for pre-service and training sample spectroscopic data are calculated by Euclidean distance method, the Euclidean distance D computing formula between two samples is as follows:
Wherein X
isfor the spectroscopic data of training sample, X
imfor the spectroscopic data of sample to be tested; Often group spectroscopic data in training sample is taken out one by one, calculates with the spectroscopic data of sample to be tested, draw sample to be tested and its distance, and list with a matrix type; And by the D value of Euclidean distance according to resequencing from small to large, show that new spectrum that the distance the most close with spectrum to be predicted carries out sorting from small to large sorts training sample set.
4. according to the method for building up of the middle infrared spectrum rapeseed protein content detection adaptive model one of claim 1-3 Suo Shu, it is characterized in that, the operation of step 5 is: the spectroscopic data of new sort, by partial least square method, sets up the rapeseed protein content prediction model based on spectral information; By index of correlation to model parameter as coefficient R
2, root-mean-square error RMSE and model prediction performance synthesis evaluation index RPD, makes the coefficient R of model
2close to 1, root-mean-square error RMSE is close to 0, and model prediction performance synthesis evaluation index RPD is greater than 2, obtains the optimal sample number setting up forecast model; By to the comparison of model and optimization, finally obtain optimum adaptive model.
5. the method for building up of middle infrared spectrum rapeseed protein content detection adaptive model according to claim 4, is characterized in that, the model in step 5 is set up and computation process, is undertaken by Matlab2013a software.
6. the method for building up of middle infrared spectrum rapeseed protein content detection adaptive model according to claim 5, is characterized in that, the model in step 5 is set up and computation process, is pass through coefficient R
2, root-mean-square error RMSE and model prediction performance synthesis evaluation index RPD calculates, and makes the coefficient R of model
2close to 1, root-mean-square error RMSE is close to 0, and model prediction performance synthesis evaluation index RPD is greater than 2, can draw the optimal sample number setting up forecast model; By to the comparison of model and optimization, finally obtain optimum adaptive model; Model is set up and with the formula of computation process is:
Wherein y and y' is chemical reference value and the infrared spectrum predicted value of a sample,
for the average of sample chemical reference value, n is sample capacity, and SD is the standard deviation of simple chemical reference value; Wherein R
2more less close to 1, RMSE, illustrate that the estimated performance of model is better; As RPD>2, think that model quality is excellent; As 1.5<PRD<2, think that model can accept; As RPD<1.5, then think that model is poor unacceptable.
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