CN106018335A - Method for nondestructively determining content of phytic acid in whole cottonseed based on near infrared spectroscopy - Google Patents
Method for nondestructively determining content of phytic acid in whole cottonseed based on near infrared spectroscopy Download PDFInfo
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- IMQLKJBTEOYOSI-UHFFFAOYSA-N Phytic acid Natural products OP(O)(=O)OC1C(OP(O)(O)=O)C(OP(O)(O)=O)C(OP(O)(O)=O)C(OP(O)(O)=O)C1OP(O)(O)=O IMQLKJBTEOYOSI-UHFFFAOYSA-N 0.000 title claims abstract description 64
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
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Abstract
The invention discloses a method for nondestructively determining the content of phytic acid in a whole cottonseed based on near infrared spectroscopy. The method comprises the following steps: preparing different varieties and multiple years of whole cottonseed samples planted in different regions, and acquiring the full spectrum data of every whole cottonseed sample; and preprocessing the full spectrum data by adopting various preprocessing technologies, accurately determining the content of phytic acid in every sample by using high performance ion chromatography, establishing a plurality of correction models in a full spectrum range by adopting a full cross validation technology combined multivariate calibration regression technology, determining an optimal near infrared spectroscopy correction model, and detecting a whole cottonseed sample to be determined by using the correction model to obtain the phytic acid content of the whole cottonseed sample to be determined. The method for acquiring the spectrogram of the whole cottonseed has the advantages of fast determination speed, high accuracy, and no need of chemical reagents, is a method for nondestructively analyzing the content of phytic acid in a whole cottonseed, and is important for cultivating low-phytic acid cotton varieties and promoting the processing utilization of cotton byproducts.
Description
Technical field
The invention discloses the assay method of a kind of agricultural byproducts content.Particularly relate to a kind of based on the reddest
The non-destructive determination method of phytic acid content in the whole cottonseed of external spectrum, uses near-infrared spectrum technique and chemistry meter
Amount method carries out nondestructive analysis to phytic acid content in whole cottonseed.
Background technology
Semen Gossypii is the principal by product of Cotton Gossypii, and whole nation annual output reaches more than 10,000,000 tons, produces cottonseed cake per year and reaches
More than 6000000 tons, widely distributed, the stock number whole world first.Rich in substantial amounts of protein in Semen Gossypii
(27.83～45.60%) and fat (28.24～44.05%), obtain Oleum Gossypii semen and cottonseed cake through squeezing after shelling, cotton
Seed oil edible, cottonseed cake can be as poultry and livestock feedstuff.Protein content in cottonseed cake is only second to bean
The dregs of rice, compare with Semen Tritici aestivi with rice, and protein content exceeds 5～8 times.17 kinds can be obtained after cottonseed cake hydrolysis
Aminoacid, from the point of view of necessary aminoacid, cottonseed protein is close with soybean protein；From vitamin and mineral side
Face is seen, cottonseed cake contains abundant B and E vitamin, and phosphorus content is up to 0.83～1.04%.Therefore Semen Gossypii
Cake not only can alleviate showing of China's protein resource shortage as the forage protein source of poultry and aquatic animal
Shape, but also feed cost can be reduced, increase economic efficiency.But, owing in Semen Gossypii, antinutritional factor is planted
The existence of acid, Semen Gossypii nutrient substance fails to be fully utilized, and particularly have impact on cottonseed cake as animal feed
Nutritive value.Therefore, the phytic acid content in Accurate Determining Semen Gossypii is for cultivating low phytic acid cotton variety and rush
The processing and utilization entering cotton side-product is significant.
Measure at present in Semen Gossypii phytic acid content based on conventional chemical method, as the sedimentation method, spectrophotography,
Titrimetry, ion exchange, high performance liquid chromatography, high-efficient ion chromatogram method, high performance capillary electrophoresis and
Nuclear magnetic resonance method etc..But these traditional methods exist, and preparation of samples is loaded down with trivial details, reagent toxicity is relatively big, analysis time
The problems such as length, sensitivity is low, testing cost is high.Near-infrared spectrum technique (Near Infrared Spectroscopy,
NIRS) wavelength C-H, N-H, O-H and S-H etc. in organic compound in the range of 780～2526nm are referred to
The frequency multiplication of group and the produced absorption spectrum of sum of fundamental frequencies vibration.Since the nineties in 20th century, along with near infrared light
Spectral technology and the fast development of Chemical Measurement, near-infrared spectrum technique be successfully applied to food, medicine,
The analysis of many industry products such as Nicotiana tabacum L., feedstuff and petrochemical industry measures.Particularly at the product of agricultural byproducts
On matter is analyzed, because it is quick, without pre-treatment, non-destructive and multicomponent Simultaneous Quantitative Analysis test etc.
Advantage and be more widely applied.
In Semen Gossypii, phytic acid content is the important indicator affecting Semen Gossypii comprehensive utilization, according to conventional chemical processes
Measuring phytic acid content long for analysis time, testing cost is high, and consumes the most poisonous chemical reagent, pollutes ring
Border, safety is low, adds difficulty to the overall merit of Semen Gossypii Middle nutrition material.The more important thing is by passing
Phytic acid content in system chemical analysis methods Semen Gossypii, need to peel off to Semen Gossypii, pulverizing, not only can consume examination
Test sample, make test sample cannot return utilization, and take considerable time, also can affect phytic acid content and measure
Accuracy, hinder its comprehensive utilization in Semen Gossypii.
Summary of the invention
It is an object of the invention to for not enough present in existing chemical analysis technology, it is provided that a kind of based on closely
The non-destructive determination method of phytic acid content in the whole cottonseed of infrared spectrum.The method uses near-infrared spectrum technique
With chemometrics method, phytic acid content in whole cottonseed is carried out non-destructive determination, efficiently solve above-mentioned asking
Topic, had both overcome the drawback of traditional chemical routes, and the Semen Gossypii material of preciousness is not the most lost in breeding process, for
In whole cottonseed, the detection of phytic acid content provides one and analyzes method fast and efficiently, has lossless, green
Color, the advantage such as accurately.
The technical solution used in the present invention is:
1) preparation is at the whole cottonseed sample of many times of the different cultivars of different regions plantation；
2) near infrared spectrometer is utilized to gather the spectroscopic data of whole cottonseed sample；
3) according to step 2) in the spectroscopic data of whole cottonseed sample that gathers, use 15 kinds of preprocess methods pair
Spectroscopic data carries out pretreatment respectively, obtains pretreated spectroscopic data；
4) phytic acid content of whole cottonseed sample, integrating step 3 are recorded by high-efficient ion chromatogram method (HPIC))
In the pretreated spectroscopic data that obtains of 15 kinds of preprocess methods, use full cross-validation method and Multivariate Correction
Homing method sets up multiple near infrared correction of whole cottonseed phytic acid content in full spectral region；
5) prediction related coefficient (R is therefrom selected2) value and remaining predicted deviation (RPD) value are maximum and predict mean square
The model of root error (RMSEP) value and cross validation root-mean-square error (RMSECV) value minimum is as optimum
Whole cottonseed phytic acid content near infrared correction；
6) use step 1) and 2) described same procedure collection whole cottonseed sample to be measured spectroscopic data, use
State step 5) constructed by optimum whole cottonseed phytic acid content near infrared correction detect whole cottonseed to be measured
Sample, obtains its phytic acid content.
Described step 2) utilize the spectroscopic data of near infrared spectrometer collection whole cottonseed sample to concretely comprise the following steps:
Obtain spectroscopic data after every part of sample is divided 6 dress sample scanning, calculate 6 spectroscopic datas of every part of sample
Average light spectrum, and reflex strength (R) is converted into log (1/R), the near-infrared obtaining whole cottonseed sample is inhaled
Receive spectrum；The collection wave-length coverage of near infrared spectrometer is 4000-10000cm-1, every 4cm-1Gather reflection
Intensity (R), altogether 1501 spectrum points, average after multiple scanning 64 times；The scanning of dress sample is upper every time
Sample amount is about 2.5g, and sample cell is the cylinder of diameter 1cm, highly 5cm, every time the scanning of dress sample be all
Carry out under 25 ± 0.5 DEG C of temperature conditionss.
Described step 3) in 15 kinds of preprocess methods be respectively Savitzky-Golay smoothing techniques, first differential
Method, second-order differential method, standard normal variable method, multiplicative scatter correction method, normalization method, spectrum transformation approach,
Conversion base-line method, Savitzky-Golay be smooth+and first differential method, Savitzky-Golay be smooth+standard normal
Quantity method, Savitzky-Golay be smooth+multiplicative scatter correction method, first differential+standard normal variable method, one
Rank differential+multiplicative scatter correction method, Savitzky-Golay be smooth+standard normal variable method+first differential method,
Savitzky-Golay smooths+multiplicative scatter correction+first differential method.
Described step 4) in Multivariate Correction homing method specifically include linear offset minimum binary (PLS) method, non-thread
Property least square method supporting vector machine (LS-SVM) method, Nonlinear weighting least square support vector machine
(WLS-SVM) method and nonlinear iteration Weighted Least Squares Support Vector Machines (RWLS-SVM) method.
Preferably, described preprocess method use Savitzky-Golay smooth+standard normal variable method+single order is micro-
Divide preprocess method.
Preferably, described Multivariate Correction homing method uses Nonlinear weighting least square support vector machine
(WLS-SVM) method.
Described step 5) in optimum whole cottonseed phytic acid content near infrared correction use and pass through
Savitzky-Golay is smooth+nonlinear weight that obtains of standard normal variable method+first differential preprocess method
Least square method supporting vector machine (WLS-SVM) model；Savitzky-Golay is smooth+and standard normal variable method+
First differential preprocess method specifically first passes through Savitzky-Golay smoothing techniques and eliminates high frequency noise to spectrum
Impact, recycling standard normal variable method reduces that granular size is uneven and the non-specific scattering of particle surface
Impact on spectrum, finally uses first differential method to eliminate spectrum baseline and ambient interferences, improves dividing of spectrum
Resolution and sensitivity.
Compared with prior art, the invention has the beneficial effects as follows:
1. the present invention utilizes B ü chi NIR Flex-N500 ft-nir spectrometer (Switzerland's step fine jade public affairs
Department) gather whole cottonseed sample spectroscopic data, have studied modeling and the application of phytic acid content in whole cottonseed
Method.Its resolution (4cm compared with existing near infrared spectrometer-1) higher, the spectrum of collection counts (1501)
More, can preferably obtain the whole cottonseed sample spectral signature near infrared spectrum region, its spectroscopic data
More accurate.
2. the present invention utilizes whole cottonseed to be corrected the structure of model as test sample.Existing phytic acid content
Assay method the most directly uses whole cottonseed to carry out spectrum data gathering, and it is because at scanning whole cottonseed
During near infrared spectrum, the uncertain factor such as the size of whole cottonseed, shape and Maturity is to spectroscopic data
Introduce substantial amounts of noise and background information；And sample cell exists gap, also to spectrum number between whole cottonseed
According to bringing a lot of irrelevant information.Factors above all reduces spectral signal-noise ratio, strengthens near-infrared straightening die
The difficulty that type builds.The calibration model that the present invention builds is applied to whole cottonseed test sample, solves above-mentioned
The technical problem that whole cottonseed mensuration processes, and need not peel off, physical work that pulverizing etc. is wasted time and energy,
It is possible not only to the integrity of protection test sample, makes test sample normally return utilization, and finding speed is fast,
Accuracy is high, pollution-free, is a kind of assay method lossless, green, efficient, cotton for cultivating low phytic acid
The processing and utilization of flower variety and the cotton side-product of promotion is significant and is worth.
Accompanying drawing explanation
Fig. 1 is whole cottonseed sample phytic acid content scattergram in the embodiment of the present invention.
Fig. 2 is whole cottonseed sample near-infrared primary light spectrogram in the embodiment of the present invention.
Fig. 3 is near infrared light spectrogram after the optimum pretreatment of whole cottonseed sample in the embodiment of the present invention.
Fig. 4 is the optimal latent variable selection figure of whole cottonseed sample correction model in the embodiment of the present invention.
Fig. 5 is the parameter optimization of optimum whole cottonseed phytic acid content near infrared correction in the embodiment of the present invention
Procedure chart.
Fig. 6 is whole cottonseed sample phytic acid chemical measurements and near infrared spectrum predictive value in the embodiment of the present invention
Between dependency graph.
Detailed description of the invention
The present invention will be further described with embodiment below in conjunction with the accompanying drawings.
The specific embodiment of the present invention is as follows:
1) the choosing of sample
Sample is that the granulate of the different cultivars taking from 11 the planted in different ecological areas plantations in the whole nation in 2014 and 2015 is cotton
Seed, including Hunan Wulin tomb, Lixian County, Hunan, Jiangshan of Zhejiang Province, Huanggang, Hefei ,Anhui, Yancheng, Jiangsu Province,
The different ecological growing areas such as yueyang, hunan, Wuhu, Jiujiang, Nanjing, Jinhua, Zhejiang, altogether
456 whole cottonseed samples.
2) sample spectra acquisition
Obtain spectroscopic data after every part of sample is divided 6 dress sample scanning, calculate 6 spectrum numbers of every part of sample
According to average light spectrum, and reflex strength (R) is converted into log (1/R), obtains the reddest of whole cottonseed sample
Outer absorption spectrum.Whole cottonseed sample near-infrared original spectrum as in figure 2 it is shown, in whole spectral region,
The number at spectral absorption peak and position consistency, the curve of spectrum more uniform smooth, but the most permissible in spectrum
Find out certain baseline drift and skew.
Near infrared spectra collection condition: utilize B ü chi NIR Flex-N500 ft-nir spectrometer
(Bu Qi company of Switzerland) gathers the spectrogram of whole cottonseed, and the collection wave-length coverage of near infrared spectrometer is
4000-10000cm-1, every 4cm-1Gather reflex strength (R), 1501 spectrum points, multiple scanning altogether
Average after 64 times；The applied sample amount of dress sample scanning is about 2.5g every time, and sample cell is a diameter of 1cm's
Cylinder, cylinder height is 5cm；The scanning of dress sample is all to carry out under 25 ± 0.5 DEG C of temperature conditionss every time, uses
Spectroscopic data is analyzed by Unscrambler V9.7 and matlab R2011a software.
3) Pretreated spectra
Utilize Savitzky-Golay smoothing techniques, first differential method, second-order differential method, standard normal variable method,
Multiplicative scatter correction method, normalization method, spectrum transformation approach, conversion base-line method, Savitzky-Golay be smooth+
First differential method, Savitzky-Golay be smooth+and standard normal variable method, Savitzky-Golay be smooth+polynary
Scatter correction method, first differential+standard normal variable method, first differential+multiplicative scatter correction method,
Savitzky-Golay is smooth+and standard normal variable method+first differential method, Savitzky-Golay is smooth+polynary dissipates
Penetrate 15 kinds of processing methods such as correction+first differential method and respectively original spectrum is carried out pretreatment.
4) phytic acid content during high-efficient ion chromatogram method (HPIC) measures whole cottonseed
Whole cottonseed through lint, dry, peel off and again dry after, with sample grinding machine, Cottonseed is clayed into power, mistake
60 mesh sieves, obtain Cottonseed powder sample.
First with dehydrated alcohol Cottonseed powder sample carried out water-bath ungrease treatment, then with hydrochloric acid through water-bath, cooling and
The centrifugal phytic acid extracted in Cottonseed powder sample, then passes sequentially through two Cleanert IC chromatography of ions pre-treatments
Post and water system filter membrane purification, carry out HPIC and detect its content；Chromatographic condition is: use DIONEX ICS-3000
Ion chromatograph, AG16-HC Guaed (4 × 50mm) protect and AS16-HC Analytical (4 × 250mm)
The condition inspection that detached dowel, leacheate are KOH, flow rate of mobile phase is 1.0ml/min, sample size is 100 μ L
Survey.The phytic acid content percentage composition measured represents.
The HPIC analysis result of phytic acid percentage composition in 456 parts of whole cottonseed samples that the present embodiment mainly provides
See Fig. 1；Because sample comes from different year, different regions and different cultivars, the content of phytic acid has larger difference,
Being shown in Table 1, wherein sample material phytic acid content is big (0.2260～3.2880%) across width, has good representativeness,
Condition is provided for setting up near infrared correction.
Phytic acid content distributional difference in table 1 whole cottonseed
| Composition | Minima | Maximum | Meansigma methods | Standard deviation |
| Phytic acid | 0.2260 | 3.2880 | 1.4086 | 0.5221 |
5) the choosing of calibration set and forecast set sample
Utilize near infrared spectrometer to gather the spectroscopic data of above-mentioned sample, use Kennard-Stone algorithm by whole
Grain Semen Gossypii sample is divided into calibration set sample and forecast set sample according to the ratio of 3:1, i.e. carries out 456 parts of samples
Diversity, obtains 342 parts of calibration set sample, it was predicted that 114 parts of sample of collection, wherein calibration set is the reddest for setting up
External model, it was predicted that collection is used for carrying out model evaluation.Set up described near-infrared model, calibration set and forecast set sample
This distribution such as table 2.
Phytic acid content distribution in table 2 calibration set and forecast set sample
| Sample sets | Sample number | Minima | Maximum | Meansigma methods | Standard deviation |
| Calibration set | 342 | 0.2260 | 3.2880 | 1.4123 | 0.5383 |
| Forecast set | 114 | 0.4527 | 2.7188 | 1.3976 | 0.4725 |
From table 2 it can be seen that calibration set sample phytic acid content scope (0.2260～3.2880%) is wide, comprise prediction
Collection sample phytic acid content scope (0.4527～2.7188%), shows that both of which can represent the data of original sample and divide
Cloth situation, is suitable for the structure of near infrared correction.
6) the selecting and the structure of PLS model of preprocess method
For the calibration set sample of 342 parts, full cross validation is used to set up PLS model in full spectral region,
Investigating the impact on PLS model of 15 kinds of different preprocessing procedures respectively, 15 kinds of preprocess methods are respectively
For Savitzky-Golay smoothing techniques, first differential method, second-order differential method, standard normal variable method, polynary dissipate
Penetrate correction method, normalization method, spectrum transformation approach, conversion base-line method, Savitzky-Golay smooth+single order is micro-
Point-score, Savitzky-Golay be smooth+and standard normal variable method, Savitzky-Golay be smooth+polynary scattering school
Execute, first differential+standard normal variable method, first differential+multiplicative scatter correction method, Savitzky-Golay
Smooth+standard normal variable method+first differential method, Savitzky-Golay be smooth+and multiplicative scatter correction+single order is micro-
Point-score.
The most all with prediction related coefficient (R2) value and remaining predicted deviation (RPD) value be maximum and prediction root-mean-square by mistake
Difference (RMSEP) value and cross validation root-mean-square error (RMSECV) value minimum choose the pretreatment side of optimum
Method is as the preprocess method of modeling, and in the present invention, optimum preprocess method is that Savitzky-Golay smooths+mark
Quasi-normal variate method+first differential method.Fig. 3 is original spectrum spectrum after optimum preprocess method processes
Figure, after, standard normal variable method smooth through Savitzky-Golay and first differential method process, the big portion of spectrum
Point absorption value all close to 0, essentially eliminate baseline, fused peaks, noise, surface scattering, change in optical path length and
The impact on spectrum of the solid particle size, significantly enhances the absorption characteristic of spectrum.15 kinds of preprocess methods are built
Vertical PLS model reference metrics evaluation is shown in Table 3.
The PLS model parameter evaluation index that 3 15 kinds of preprocess methods of table are set up
In table 3: Control indicates without pretreatment；SG represents that Savitzky-Golay smooths；1D represents one
Rank differential；SNV represents standard normal variable；MSC represents multiplicative scatter correction；N represents normalization method；
ST represents spectrum transformation approach；BL represents conversion base-line method；RMSECV represents cross validation root-mean-square error
(the least effect of numerical value is the best)；RMSEP represents predicted root mean square error (the least effect of numerical value is the best)；
R2Represent prediction related coefficient (R2> 0.9 represent can substitute completely tradition assay method)；RPD represents residue
Prediction deviation (RPD > 2.5 represents that the robustness of model is good).
7) foundation of near infrared correction and optimization
Pretreated spectroscopic data is imported in matlab software, first determines according to the change of press value
Good latent variable, such as Fig. 4, along with the increase of latent variable number, its press value declines therewith, works as latent variable
Number is to drop to minimum when 12, and this trend keeps being basically unchanged the most gently, determines optimal latent variable
Number is 12.
Then utilizing chemometrics method and Multivariate Correction homing method to set up model, wherein Multivariate Correction returns
Method is returned to specifically include linear offset minimum binary (PLS) method, non-linear least square support vector machine (LS-SVM)
Method, Nonlinear weighting least square support vector machine (WLS-SVM) method and nonlinear iteration weighted least-squares
Support vector machine (RWLS-SVM) method.
The whole cottonseed phytic acid content near infrared correction of present invention optimum uses passes through Savitzky-Golay
The Nonlinear weighting least square support that smooth+standard normal variable method+first differential preprocess method obtains to
Amount machine (WLS-SVM) model, this model R2=0.9768 value and RPD=6.5902 value the highest and
RMSECV=0.0851 value and RMSEP=0.0717 value are minimum, have preferable prediction effect and higher survey
Determine accuracy.Model evaluation parameter is shown in Table 4.
4 four kinds of phytic acid content near-infrared model parameter evaluation indexs of table
In table 4: PLS represents partial least square method；LS-SVM represents least square method supporting vector machine；
WLS-SVM represents Weighted Least Squares Support Vector Machines；RWLS-SVM represents iteration weighted least-squares
Support vector machine；RMSECV represents cross validation root-mean-square error (the least effect of numerical value is the best)；RMSEP
Represent predicted root mean square error (the least effect of numerical value is the best)；R2Represent prediction related coefficient (R2> 0.9 table
Show and can substitute tradition assay method completely)；RPD represents that (RPD > 2.5 represents model to remaining predicted deviation
Robustness is good).
When setting up nonlinear model, need to find optimal model parameter, i.e. punish parameter (γ) and kernel function ginseng
Number (σ2), parameter optimisation procedure such as Fig. 5 of optimum whole cottonseed phytic acid content near infrared correction, passes through
After 20 generations, its optimal adaptation degree and average fitness all tend towards stability, and 20 to 50 generations it
Between keep floor level.
As can be seen here, the inventive method, wherein sample material phytic acid content is big (0.2260～3.2880%) across width,
There is good representativeness, be suitable near infrared spectrum modeling；By comparing different pretreatments method, obtain
Excellent preprocess method is that Savitzky-Golay smooths+standard normal variable+first differential method；Use this pre-place
Reason method sets up different phytic acid calibration models, determines the whole cottonseed sample phytic acid content near-infrared school of optimum
Positive model is Weighted Least Squares Support Vector Machines (WLS-SVM) model, this model R2Value and RPD value are
High and RMSECV value and RMSEP value are minimum, respectively 0.9768,6.5902,0.0851 and 0.0717,
The phytic acid content in whole cottonseed can be measured accurately.Its phytic acid chemical measurements is predicted with near infrared spectrum
Dependency graph between value, as shown in Figure 6, wherein diagonal represent and optimal predict the outcome (predictive value=
Chemical score), sample point, closer to diagonal, illustrates that the effect of model is the best, and vice versa.
8) prepare whole cottonseed sample to be measured, gather the near-infrared of whole cottonseed sample to be measured under the same conditions
Spectroscopic data, detects whole cottonseed sample to be measured with the optimum near infrared spectrum calibration model constructed by above-mentioned steps
This, obtain its phytic acid content.
The innovation of the present invention is:
1. the present invention utilizes B ü chi NIR Flex-N500 ft-nir spectrometer (Switzerland's step fine jade public affairs
Department) gather whole cottonseed sample spectroscopic data, have studied modeling and the application of phytic acid content in whole cottonseed
Method.Its resolution (4cm compared with existing near infrared spectrometer-1) higher, the spectrum of collection counts (1501)
More, can preferably obtain the whole cottonseed sample spectral signature near infrared spectrum region, its spectroscopic data
More accurate.
2. the present invention utilizes whole cottonseed to be corrected the structure of model as test sample.Existing phytic acid content
Assay method the most directly uses whole cottonseed to carry out spectrum data gathering, and it is because at scanning whole cottonseed
During near infrared spectrum, the uncertain factor such as the size of whole cottonseed, shape and Maturity is to spectroscopic data
Introduce substantial amounts of noise and background information；And sample cell exists gap, also to spectrum number between whole cottonseed
According to bringing a lot of irrelevant information.Factors above all reduces spectral signal-noise ratio, strengthens near-infrared straightening die
The difficulty that type builds.The calibration model that the present invention builds is applied to whole cottonseed test sample, solves above-mentioned
The technical problem that whole cottonseed mensuration processes, as long as gathering the spectroscopic data of whole cottonseed, according to optimum pre-
Disposal methods spectroscopic data, utilizes above-mentioned optimum calibration model, just quickly can measure in whole cottonseed and plant
The content of acid, and need not peel off, physical work that pulverizing etc. is wasted time and energy, be possible not only to protection test sample
This integrity, makes test sample normally return utilization, and finding speed is fast, and accuracy is high, pollution-free,
It is a kind of assay method lossless, green, efficient, for cultivating low phytic acid cotton variety and promoting cotton by-product
The processing and utilization of product is significant and is worth.
Claims (6)
1. a non-destructive determination method for phytic acid content in whole cottonseed based near infrared spectrum, its feature exists
In comprising the steps:
1) preparation is at the whole cottonseed sample of many times of the different cultivars of different regions plantation；
2) near infrared spectrometer is utilized to gather the spectroscopic data of whole cottonseed sample；
3) according to step 2) in the spectroscopic data of whole cottonseed sample that gathers, use preprocess method to spectrum
Data carry out pretreatment respectively, obtain pretreated spectroscopic data；
4) phytic acid content of whole cottonseed sample, integrating step 3 are recorded by high-efficient ion chromatogram method (HPIC))
In the pretreated spectroscopic data that obtains of 15 kinds of preprocess methods, use full cross-validation method and Multivariate Correction
Homing method sets up multiple near infrared correction of whole cottonseed phytic acid content in full spectral region；
5) prediction related coefficient (R is therefrom selected2) value and remaining predicted deviation (RPD) value are maximum and predict mean square
The model of root error (RMSEP) value and cross validation root-mean-square error (RMSECV) value minimum is as optimum
Whole cottonseed phytic acid content near infrared correction；
6) use step 1) and 2) described same procedure collection whole cottonseed sample to be measured spectroscopic data, use
State step 5) constructed by optimum whole cottonseed phytic acid content near infrared correction detect whole cottonseed to be measured
Sample, obtains its phytic acid content.
The nothing of phytic acid content in a kind of whole cottonseed based near infrared spectrum the most according to claim 1
Damage assay method, it is characterised in that:
Described step 2) utilize the spectroscopic data of near infrared spectrometer collection whole cottonseed sample to concretely comprise the following steps:
Obtain spectroscopic data after every part of sample is divided 6 dress sample scanning, calculate 6 spectroscopic datas of every part of sample
Average light spectrum, and reflex strength (R) is converted into log (1/R), the near-infrared obtaining whole cottonseed sample is inhaled
Receive spectrum；The collection wave-length coverage of near infrared spectrometer is 4000-10000cm-1, every 4cm-1Gather reflection
Intensity (R), altogether 1501 spectrum points, average after multiple scanning 64 times；The scanning of dress sample is upper every time
Sample amount is about 2.5g, and sample cell is the cylinder of diameter 1cm, highly 5cm, every time the scanning of dress sample be all
Carry out under 25 ± 0.5 DEG C of temperature conditionss.
The nothing of phytic acid content in a kind of whole cottonseed based near infrared spectrum the most according to claim 1
Damage assay method, it is characterised in that: described step 3) in 15 kinds of preprocess methods be respectively
Savitzky-Golay smoothing techniques, first differential method, second-order differential method, standard normal variable method, polynary scattering
Correction method, normalization method, spectrum transformation approach, conversion base-line method, Savitzky-Golay smooth+first differential
Method, Savitzky-Golay be smooth+and standard normal variable method, Savitzky-Golay be smooth+multiplicative scatter correction
Method, first differential+standard normal variable method, first differential+multiplicative scatter correction method, Savitzky-Golay are flat
Cunning+standard normal variable method+first differential method, Savitzky-Golay smooth+multiplicative scatter correction+first differential
Method.
The nothing of phytic acid content in a kind of whole cottonseed based near infrared spectrum the most according to claim 1
Damage assay method, it is characterised in that: described step 4) in Multivariate Correction homing method specifically include linear partially
Least square (PLS) method, non-linear least square support vector machine (LS-SVM) method, a nonlinear weight young waiter in a wineshop or an inn
Take advantage of support vector machine (WLS-SVM) method and nonlinear iteration Weighted Least Squares Support Vector Machines
(RWLS-SVM) method.
The nothing of phytic acid content in a kind of whole cottonseed based near infrared spectrum the most according to claim 3
Damage assay method, it is characterised in that: described preprocess method uses Savitzky-Golay to smooth+standard normal
Quantity method+first differential preprocess method.
The nothing of phytic acid content in a kind of whole cottonseed based near infrared spectrum the most according to claim 4
Damage assay method, it is characterised in that: described Multivariate Correction homing method uses Nonlinear weighting least square to prop up
Hold vector machine method.
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| CN106770006A (en) * | 2016-11-29 | 2017-05-31 | 安徽财经大学 | A kind of unginned cotton method for detecting impurities based near infrared spectrum |
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| CN112326848A (en) * | 2020-10-23 | 2021-02-05 | 杭州师范大学 | Methyldiazomethane methyl esterification phytic acid analysis method based on trimethylsilyl |
| CN112326848B (en) * | 2020-10-23 | 2022-11-29 | 杭州师范大学 | Methyldiazomethane methyl esterification phytic acid analysis method based on trimethylsilyl |
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| CN117147468A (en) * | 2023-11-01 | 2023-12-01 | 广东省农业科学院动物科学研究所 | Method and system for detecting anti-nutritional factors of plant source agricultural wastes |
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