CN110044842A - A kind of method of the odd sub- seed moisture content of quick measurement - Google Patents
A kind of method of the odd sub- seed moisture content of quick measurement Download PDFInfo
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- 238000004497 NIR spectroscopy Methods 0.000 description 5
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- 238000012360 testing method Methods 0.000 description 4
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- MXXWOMGUGJBKIW-YPCIICBESA-N piperine Chemical compound C=1C=C2OCOC2=CC=1/C=C/C=C/C(=O)N1CCCCC1 MXXWOMGUGJBKIW-YPCIICBESA-N 0.000 description 1
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- 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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Abstract
The invention discloses a kind of methods of the odd sub- seed moisture content of quickly measurement, belong to analysis detection field.The method of the present invention obtains reference value with national standard measurement sample moisture content, sample is scanned in fixed spectra collection method simultaneously, determines number of principal components, selects preprocessing procedures, based on Partial Least Squares, the calibration model between spectral information and moisture content reference value is constructed.The content information of each ingredient can be quickly obtained using established calibration model, and established model prediction accuracy with higher is verified by cross-validation method.The quantitative analysis of the method for the present invention moisture suitable for odd sub- seed, method is accurate, time-saving and efficiency.
Description
Technical field
The present invention relates to a kind of methods of the odd sub- seed moisture content of quickly measurement, belong to analysis detection field.
Background technique
Odd Asia seed (Chia Seed) is the seed of chia (Salvia Hispanica L.), small in size, is thin
The close relative of lotus plant families.It is odd sub- cold-resistant, it is grown in the sandy or Rocks, Soils of hot Arid Area, its initial growth is in ink
The High aititude desert area of western brother.As a " star's food ", " super food ", odd Asia seed be most initially American-European popular,
Gradually incoming domestic afterwards, national health State Family Planning Commission is new raw-food material in the odd sub- seed of approval in 2014, and in addition to directly eating, surprise is sub-
Seed as raw material or auxiliary material be also widely used for cereal meal replacement powder, cereal bars, biscuit, bread, Yoghourt, corn-dodger and jam it
In.But odd Asia seed does not have plantation at home, and the sub- seed of the surprise on domestic market all relies on import, and sample collection is not easy.
The moisture content of odd Asia seed is to influence the Fundamentals of odd sub- seed quality comparison, is odd sub- seed processing, storage, receives
The important indicator that must be detected in purchase, transit link, it is closely related with the accounting of odd sub- seed weight, directly influence the benefit sold
Profit.In conjunction with the reason of sample collection aspect, the measurement of odd Asia seed moisture content generallys use 105 DEG C of oven drying methods of national standard.This side
Although method chemical analysis results are more accurate, operation is not only time-consuming but also laborious, and detection cycle is long, and sample must be destroyed
The processing of property, it is inefficient.So seeking measurement of quick, effective, the lossless detection method of one kind to odd sub- seed moisture content
It has important practical significance.
Near infrared spectrum (Near Infrared Spectroscopy, NIRS) be based on visible light and middle infrared spectrum it
Between a Duan Guangpu, it is hydric group (C-H, N-H, O-H) that wave-length coverage 780nm-2526nm, which belongs to molecular vibration spectrum,
The frequency multiplication and sum of fundamental frequencies of vibration absorb, and are a kind of effective carriers for obtaining hydric group characteristic information.With adding for Chemical Measurement
Enter, near-infrared spectrum technique has more application in the food inspections such as agricultural product, and its feature is: testing cost is low, fastly
Speed, harmless sample to be tested are a kind of food quality analytical technologies of maturation, it can be achieved that on-line checking.This is by the technology
Analyzing and monitor in real time for odd sub- seed moisture content becomes a kind of possibility.
Has the report using near infrared spectrum detection moisture content at present, for example the Li Xiaoli of Zhejiang University (is based on unrestrained
The first green tea moisture content lossless detection method processed of reflectance spectrum, Journal of Agricultural Engineering) it is explored by many experiments, discovery is detecting
In green tea when moisture content, using the spectroscopic data of Short-wave near-infrared spectroscopy 888-1007 range, converted by wavelet function,
To 19 wavelet character coefficients, then basis, which is specifically calculated with the associated moisture content formula of 19 wavelet character functions, contains
Water rate；Although this method can accurately measure the moisture content in green tea, due to physical environment difference, moisture absorption
Wave band differs greatly, and can not establish accurate linearity correction model using the wave band data in this method.Xiong Lihua (near infrared light
Spectrometry quickly detects the research of crude fibre in tealeaves, moisture and ash content, East China University of Science) tea is established using near infrared spectroscopy
Moisture content model in leaf, selects scanning range for 4150~6200cm-1, 6800~8000cm-1Region it is quantitative as establishing
The SPECTRAL REGION of model；This method is not directed to the selection of characteristic wave bands, it is difficult to guarantee that the region is best modeled wave band.In addition,
The Lv Daizhu (CN103278473) of Analysis and Measurements Center, Chinese Academy of Tropical Agriculture Sciences passes through in terms of composition measurement in white pepper
Many experiments exploration shows: white pepper can acquire spectral information in 950-1650 Spectral range, then use stoichiometry side
Method establishes data model, and then measures piperine and moisture content in white pepper；However, this method and not yet explicitly spectroscopic data are such as
What building calibration model, and the wave band in this method equally also can not effectively, accurately predict moisture content in odd sub- seed.Cause
This, it is highly important for developing a kind of quick, effective, lossless and accurate odd sub- seed moisture content detection method.
Summary of the invention
The purpose of the invention is to overcome moisture content in existing odd sub- seed time-consuming and laborious in the analysis process, detection week
Phase is long, sample broke test, ineffective disadvantage, and it is quasi- to provide moisture content in a kind of sub- seed of surprise based near infrared spectrum
True modeling method and simple and rapid detection method, to evaluate the quality of odd sub- seed, for odd sub- seed transport and trade quality
Identification.
Since moisture contains O-H group in odd sub- seed, have in the level-one frequency multiplication of near infrared region and second level frequency multiplication area relatively strong
Absorption, the molecular structure information for including near infrared spectrum can be very good characterization target quality concentration feature, after pretreatment
Spectrum it is associated with actually measured moisture content reference value, calibration model is established using Partial Least Squares, thus may be used
By the atlas of near infrared spectra of the odd sub- seed of scanning, identical pretreated spectrum is called in calibration model, obtain in odd sub- seed
Accurate moisture content percentage value.
The first purpose of the invention is to provide a kind of methods of the odd sub- seed moisture content of measurement, and the method includes as follows
Step:
(1) in 4000-10000cm-1The odd sub- seed sample of diffusing reflection scanning, obtains near infrared spectrum in full spectrum Spectral range
Figure；
(2) in gained atlas of near infrared spectra choose specific band range, to the spectral information within the scope of specific band into
Row pretreatment, obtains peak intensity angle value；The pretreated mode includes multiplicative scatter correction (MSC), standard normal variation
(SNV), first derivative (1st), second dervative (2nd), one or more of SG is smooth and Norris is smooth；It is described specific
Wavelength band includes 4000-10000cm-1、4200-7400cm-1、4800-4900cm-1、5300-5400cm-1、6500-
6800cm-1One of or it is a variety of.
(3) by moisture content in the odd sub- seed sample of national standard method measurement as reference value, and Partial Least Squares is utilized, with
The peak intensity angle value that step (2) obtains establishes calibration model；
(4) sample to be tested obtains peak intensity angle value through step (1), (2), according to the calibration model in step (3), is calculated
Moisture content in sample to be tested sample.
In one embodiment of the invention, the preferred 4200-7400cm of specific band range in the step (2)-1、
4800-4900cm-1、5300-5400cm-1、6500-6800cm-1One of or it is a variety of.
In one embodiment of the invention, the further preferred 4200- of specific band range in the step (2)
7400cm-1Or 4800-4900cm-1、5300-5400cm-1And 6500-6800cm-1Combination.
In one embodiment of the invention, the further preferred 4200- of specific band range in the step (2)
7400cm-1。
In one embodiment of the invention, the step (1) is that odd sub- seed sample is placed in specimen cup, in spectrum area
Diffusing reflection scans in range, resolution ratio 4-16cm-1, scanning times 16-64 times 4-8 times of gain, obtain near infrared spectrum.
In one embodiment of the invention, the step (1) is that odd sub- seed sample is placed in specimen cup, in spectrum area
Diffusing reflection scans in range, resolution ratio 8cm-1, scanning times 32 times, 8 times of gain, obtain near infrared spectrum.
In one embodiment of the invention, the preferred multiplicative scatter correction of pretreated mode, two in the step (2)
Order derivative and the smooth combination of Norris perhaps standard normal variation, first derivative and the smooth combination or standard of Norris
The combination that normal state changes, second dervative and Norris are smooth.
In one embodiment of the invention, the further preferably polynary scattering of pretreated mode in the step (2)
It corrects, the combination that second dervative and Norris are smooth.
In one embodiment of the invention, using sample in MSC removal near-infrared diffusing reflection spectrum in the pretreatment
Noise caused by the mirror-reflection and inhomogeneities of product and spectrum it is not repeated；Disappeared using first derivative and/or second dervative
Except baseline and improve resolution ratio, reduction noise jamming；Using SG is smooth and/or Norris smoothly improves the noise of effective information
Than.
In one embodiment of the invention, calibration model is established with Partial Least Squares in the step (3), in conjunction with
Principal component analysis carries out dimensionality reduction compression to spectral information.
Second object of the present invention is that above-mentioned detection method is applied to moisture content change in the odd sub- seed of real-time detection
In.
Third object of the present invention is applied to above-mentioned detection method in odd sub- seed storage quality monitoring field.
The beneficial effects of the present invention are:
Near infrared spectrum combination chemometrics method is introduced the non-destructive testing of odd sub- seed moisture content by the present invention for the first time,
For the quantitative analysis of moisture in odd sub- seed, method is accurate, time-saving and efficiency.
For the present invention compared with traditional chemical analysis method, detection speed is fast, does not damage sample, and whole continuous mode is not necessarily to one
Minute, it is a kind of convenient convenience, environmentally protective detection method.
Near-infrared spectrum technique is introduced into odd sub- building for seed database model by the method for the present invention may be implemented online reality
When the odd sub- seed moisture content in storage of detection variation, be very intentionally to the stability for ensuring odd sub- seed storage quality
Justice.
Detailed description of the invention
Fig. 1 is the flow chart that near-infrared spectrum technique establishes moisture content model in odd sub- seed；
Fig. 2 is the original atlas of near infrared spectra of odd sub- seed；
Fig. 3 is variation diagram of the RMSECV with number of principal components；
Fig. 4 is the predicted value of calibration set sample figure related to reference value；
Fig. 5 is the predicted value figure related to reference value of verifying collection sample；
Fig. 6 is the result figure of sample interior cross validation.
Specific embodiment
Below by way of examples to near-infrared spectroscopy of the present invention establish and application process furtherly
Bright, which should not be construed as limitation of the present invention.
Near-infrared spectroscopy of the present invention is established and application process such as Fig. 1, specific as follows:
1. the collection and classification of representative sample:
According to the growing environment and growth cycle feature of odd sub- seed, the sample on each odd sub- seed main product ground, sample are collected respectively
Product amount reaches 103 parts, including the ground such as Mexico, Australia, Argentina, Bolivia, Ecuador, Nicaragua, Peru
Area, collecting the period is greater than 2 years (odd sub- be pennyroyal annual plant), multiple batches of acquisition, collect type include Hei Qiya seed and
Bai Qiya seed two types.Sample is divided into Calibration and verification sample collection, every collection covers each area, batch and color
The sub- seed of the surprise of type, effectively expands the range of sample data.Sample carries out pressing national standard method survey while spectra collection immediately
Moisture content in Ding Qiya seed establishes odd sub- seed sample moisture content data library.
2. the acquisition of instrument condition and sample spectra
Instrument: near infrared spectrum is closely red by the Antaris II purchased from scientific and technological (China) Co., Ltd of Thermo Fisher
The scanning of outer analysis instrument is collected, which is RESULT-Integration equipped with spectra collection software；Modeling software is TQ
Analyst is scientific and technological (China) the Co., Ltd exploitation of Thermo Fisher.Meanwhile being furnished with InGaAs detector.
The acquisition of sample spectra: near infrared spectrum spectrogram is carried out to odd sub- seed sample to be measured under conditions of 25 DEG C ± 2 DEG C
Acquisition, weigh 25g seed in standard sample cup, scan odd sub- seed sample with irreflexive mode in the Spectral range of selection
The near infrared spectrum of product, resolution ratio 8cm-1, scanning times 32 times, gain 8 ×, same sample pours out specimen cup, fills cup again, such as
This scanning three times or more, takes average spectrum as the standard spectrum of the sample.
3. the measurement of basic data:
Contain by the moisture that GB 5009.3-2016 " measurement of moisture in national food safety standard food " measures odd sub- seed
Reference value is measured, each sample detection three times, is averaged.
4. sample sets divide:
103 samples are divided into two groups, one group is calibration set, for establishing quantitative model；Another group, as verifying collection, is used
In the Stability and veracity of testing model.In order to avoid due to sample grouping it is unreasonable caused by deviation, subset select such as
Lower progress: for every 10 samples, random selection 8 are used as calibration set, and remaining sample is used as forecast set.Therefore, this experiment
It is used as calibration set using 81, in addition 22 composition verifying collection.As shown in Table 1, the content range of calibration set sample, which covers, tests
The content range of card collection sample, illustrates that the group result is preferable.
The sample number and content of 1 calibration set of table and verifying collection
| Sample sets | Content unit | Sample number | Content range | Average content | Standard deviation |
| Calibration set | g/g | 81 | 2.45~8.65 | 5.76 | 1.45 |
| Verifying collection | g/g | 22 | 2.56~7.95 | 5.96 | 1.38 |
5. establishing calibration model
Spectrum is pre-processed using modeling software, extracts the characteristic spectrum letter of the odd sub- seed moisture content of concurrent big expression
Breath.Preprocessing procedures include: for caused by the mirror-reflection of sample in removal near-infrared diffusing reflection spectrum and inhomogeneities
Noise and the not repeated of spectrum use MSC；First derivative and second dervative are used to eliminate baseline and improving resolution ratio, is
Reduce noise jamming；The signal-to-noise ratio for improving effective information uses SG smoothly and Norris is smooth.In combination with principal component analysis pair
Spectral information carries out dimensionality reduction compression, establishes calibration model with Partial Least Squares.
6. cross-validation
Regulation all samples are calibration set sample, carry out cross-validation to model using leaving-one method, that is, leave portion
Sample divides content as sample to be predicted, this sample water of remaining sample participation modeling and forecasting, and so circulation measures 103 repeatedly
The relational graph of part predicted value and moisture content reference value, with coefficient RCVWith cross validation root-mean-square error (Root Mean
Square Error of Cross Validation, RMSECV) assessment models.
7. carrying out sample prediction
Under stable environmental condition, the halogen tungsten lamp light source in near-infrared analyzer issues light radiation, is radiated at odd sub- seed
On sample, the light that diffusing reflection comes out is integrated ball collection, converts digital data transmission near infrared spectrum by detector and arrives
Computer, then digital signal is analyzed with the calibration model for having been established and verifying, to obtain moisture content in odd sub- seed
Data.
Embodiment 1: the building of odd Asia seed moisture content calibration model
(1) near-infrared is carried out to odd sub- seed sample (be divided into calibration set and verifying collects) to be measured under conditions of 25 DEG C ± 2 DEG C
The acquisition of spectrum spectrogram weighs 25g seed in standard sample cup, in 4000-10000cm-1With irreflexive in Spectral range
Mode scans the near infrared spectrum of odd sub- seed sample, resolution ratio 8cm-1, scanning times 32 times, gain 8 ×, same sample pours out sample
Product cup, fills cup again, and so scanning three times or more, takes average spectrum as the standard spectrum of the sample.
(2) it chooses to 4200-7400cm in standard spectrum-1Spectral information in Spectral range is pre-processed, described pre-
Processing mode is MSC+2nd+ Norris is smooth；
(3) odd sub- seed sample obtains sample moisture content reference value by the moisture content in the odd sub- seed of national standard method measurement；
Extract 4200-7400cm-1All-wave section establishes Partial Least Squares and establishes calibration model, obtains predicted value and moisture content refers to
The linear model of value；It is respectively 0.317,0.276, RPD 5.00 that R, which is 0.9807, RMSEC and RMSEP, in PLS modeling, pre- to locate
The preferable model of reason method prediction accuracy with higher, can be used for the quantitative determination of actual sample.Figure 4 and 5 are correction respectively
The predicted value figure related to moisture content reference value of collection and verifying collection sample, wherein the related coefficient of calibration set and verifying collection
Respectively 0.9905 and 0.9829, root-mean-square error is respectively 0.199 and 0.256.
Embodiment 2: the verifying of odd Asia seed moisture content calibration model
If all samples are calibration set sample, cross-validation is carried out to model using leaving-one method, that is, leaves a sample
Product divide content as sample to be predicted, this sample water of remaining sample participation modeling and forecasting, and so circulation measures 103 parts repeatedly
Predicted value, with coefficient RCVWith RMSECV assessment models.
Fig. 6 is with the calibration set reference value (national standard measures sample moisture content) and NIR predicted value after above-mentioned cross validation
Correlation figure, can intuitively find out very much from figure, and there is no the larger point for deviateing fitting a straight line, linear fit is good.Wherein, RCV
For 0.9821, RMSECV 0.272.RMSECV is smaller, RCVGreater than 0.9, show partially minimum using near-infrared spectrum technique combination
Square law can carry out quantitative analysis to moisture content in odd sub- seed.
Embodiment 3: the influence that Pretreated spectra mode models PLS
Pretreatment mode in step (2) is replaced with pretreatment mode as shown in Table 2 by reference implementation example 1, other
Part is constant, carries out PLS modeling.
Table 2 selects the sub- seed moisture content PLS modeling result of the surprise of different pretreatments method
Wherein: 1st: first derivative；2nd: second dervative；MSC: multiplicative scatter correction；SNV: standard normal variation；
Norris is smooth: Norris derivative fiter；SG is smooth: Savitzky-Golay filter；Main Composition Factor number
It is matched optimized parameter condition under each pretreatment mode.
Spectrogram is optimized by various preprocessing procedures, analysis software automatically selects wave-number range and principal component
Number, as a result by coefficient R and root-mean-square error (RMSEC and RMSEP) come the superiority and inferiority of evaluation model, R (RpGreater than threshold value 0.7)
Bigger, RMSEC and RMSEP are smaller, and relation analysis error (RPD) is bigger, then the preprocess method is preferable.Concrete outcome such as table 2
Shown, best preprocess method is MSC+2nd+ Norris is smooth, and R is that 0.9807, RMSEC and RMSEP is respectively in PLS modeling
0.317,5.00 0.276, RPD, RPD are greater than 3, illustrate model prediction accuracy with higher, can be used for actual sample
Quantitative determination.
Embodiment 4: different pretreatments wave band, which models surprise Asia seed moisture content PLS, to be influenced
Reference implementation example 1 selects best pretreatment mode MSC+2nd+ Norris is smooth, and the wave band in step (2) is replaced
For wave-number range as shown in table 3, other conditions are constant, carry out PLS modeling.
Table 3 selects odd sub- seed moisture content PLS modeling result under different-waveband range
Select 4000-10000cm-1All-wave number interval establishes Partial Least Squares and establishes calibration model, obtain predicted value with
The linear model of reference value；R is 0.9414, RPD less than 3 in PLS modeling, shows all-wave number drag poor accuracy, but still
It can be used for the bigness scale of moisture content.Comprehensively consider table 2 and table 3, specific wave number 4200-7400cm-1Under, R 0.9829,
RMSEC and RMSEP is respectively 0.199,0.256, RPD 5.39, and RPD is greater than 3, and has more in the preferable model of preprocess method
High prediction accuracy is more conducive to the accurate quantitative analysis measurement of actual sample.
In addition, number of principal components is also one of evaluation parameter of calibration model, works as root-mean-square error when being modeled using PLS
(RMSECV) it is reduced with the increase of number of principal components when almost stable, obtaining best number of principal components is 5 (see Fig. 3), this
When contribution rate 99%.
Claims (10)
1. a kind of method of moisture content in odd sub- seed of detection, which is characterized in that described method includes following steps:
(1) in 4000-10000cm-1The odd sub- seed sample of diffusing reflection scanning, obtains atlas of near infrared spectra in full spectrum Spectral range；
(2) specific band range is chosen in gained atlas of near infrared spectra, the spectral information within the scope of specific band is carried out pre-
Processing, obtains peak intensity angle value；The pretreated mode includes multiplicative scatter correction, standard normal variation, first derivative, second order
One or more of derivative, SG are smooth and Norris is smooth；The specific band range includes 4000-10000cm-1、
4200-7400cm-1、4800-4900cm-1、5300-5400cm-1、6500-6800cm-1One of or it is a variety of；
(3) by moisture content in the odd sub- seed sample of national standard method measurement as reference value, and it is based on Partial Least Squares, with step
(2) the peak intensity angle value obtained establishes calibration model；
(4) odd sub- seed sample to be measured obtains peak intensity angle value through step (1), (2), according to the calibration model in step (3), calculates
To the moisture content in sample to be tested sample.
2. the method according to claim 1, wherein specific band range is 4200- in the step (2)
7400cm-1、4800-4900cm-1、5300-5400cm-1、6500-6800cm-1One of or it is a variety of.
3. method according to claim 1 or 2, which is characterized in that specific band range is 4200- in the step (2)
7400cm-1, or be 4800-4900cm-1、5300-5400cm-1And 6500-6800cm-1Combination.
4. method according to claim 1 to 3, which is characterized in that pretreated mode is more in the step (2)
First scatter correction, second dervative and the smooth combination of Norris or standard normal variation, first derivative and Norris are smooth
Combination or the combination that standard normal changes, second dervative and Norris are smooth.
5. method according to claim 1 to 4, which is characterized in that pretreated mode is more in the step (2)
First scatter correction, second dervative and the smooth combination of Norris.
6. -5 any method according to claim 1, which is characterized in that the step (1) is to be placed in odd sub- seed sample
In specimen cup, diffusing reflection is scanned in full spectrum Spectral range, resolution ratio 4-16cm-1, scanning times 16-64 times, gain 4-8
Times, obtain near infrared spectrum.
7. -6 any method according to claim 1, which is characterized in that the step (1) is to be placed in odd sub- seed sample
In specimen cup, diffusing reflection is scanned in full spectrum Spectral range, resolution ratio 8cm-1, scanning times 32 times, 8 times of gain, obtain close
Infrared spectroscopy.
8. -7 any method according to claim 1, which is characterized in that using the stability of leaving-one method verifying calibration model
With reliability.
9. application of any detection method of claim 1-8 in the odd sub- seed of real-time detection in terms of moisture content change.
10. application of any detection method of claim 1-8 in odd sub- seed storage quality monitoring field.
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