CN107831133A - A kind of large-scale melon and fruit inside quality near infrared spectrum on-line detecting system and implementation method - Google Patents
A kind of large-scale melon and fruit inside quality near infrared spectrum on-line detecting system and implementation method Download PDFInfo
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- CN107831133A CN107831133A CN201710086729.9A CN201710086729A CN107831133A CN 107831133 A CN107831133 A CN 107831133A CN 201710086729 A CN201710086729 A CN 201710086729A CN 107831133 A CN107831133 A CN 107831133A
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- 235000013399 edible fruits Nutrition 0.000 title claims abstract description 42
- 241000219112 Cucumis Species 0.000 title claims abstract description 41
- 235000015510 Cucumis melo subsp melo Nutrition 0.000 title claims abstract description 41
- FJJCIZWZNKZHII-UHFFFAOYSA-N [4,6-bis(cyanoamino)-1,3,5-triazin-2-yl]cyanamide Chemical compound N#CNC1=NC(NC#N)=NC(NC#N)=N1 FJJCIZWZNKZHII-UHFFFAOYSA-N 0.000 title claims abstract description 41
- 238000002329 infrared spectrum Methods 0.000 title claims abstract description 20
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000001228 spectrum Methods 0.000 claims abstract description 30
- 230000003595 spectral effect Effects 0.000 claims abstract description 14
- 239000013307 optical fiber Substances 0.000 claims abstract description 13
- 229910052736 halogen Inorganic materials 0.000 claims abstract description 8
- 150000002367 halogens Chemical class 0.000 claims abstract description 7
- 230000005540 biological transmission Effects 0.000 claims abstract description 5
- 238000001514 detection method Methods 0.000 claims description 13
- 230000003068 static effect Effects 0.000 claims description 7
- 244000241235 Citrullus lanatus Species 0.000 claims description 4
- 235000012828 Citrullus lanatus var citroides Nutrition 0.000 claims description 4
- 238000004611 spectroscopical analysis Methods 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 4
- 239000000284 extract Substances 0.000 claims description 3
- 230000010354 integration Effects 0.000 claims description 3
- 239000000835 fiber Substances 0.000 claims 1
- 239000000523 sample Substances 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 244000141359 Malus pumila Species 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 244000298715 Actinidia chinensis Species 0.000 description 1
- 235000009434 Actinidia chinensis Nutrition 0.000 description 1
- 235000009436 Actinidia deliciosa Nutrition 0.000 description 1
- 235000015001 Cucumis melo var inodorus Nutrition 0.000 description 1
- 240000002495 Cucumis melo var. inodorus Species 0.000 description 1
- 244000179970 Monarda didyma Species 0.000 description 1
- 235000010672 Monarda didyma Nutrition 0.000 description 1
- 235000014443 Pyrus communis Nutrition 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 235000021016 apples Nutrition 0.000 description 1
- 235000021028 berry Nutrition 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 238000009659 non-destructive testing Methods 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
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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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- Biochemistry (AREA)
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Abstract
The present invention relates to a kind of near infrared spectrum on-line detecting system and implementation method, more particularly to a kind of large-scale melon and fruit inside quality near infrared spectrum on-line detecting system and implementation method, including frame, helical feed rod, spectra collection room, light source fixing frame, halogen light source, optically focused collimating mirror, motor, optical fiber, spectrometer, computer；The present invention devises adjustable angle light source fixing frame, by angle adjustment, light source route can be easily adjusted, makes light source diffusing transmission after melon and fruit, light source refracts to optically focused collimating mirror, infrared-ray is sent to spectrometer through optical fiber, and the spectral manipulation collected is analyzed by computer, can realize zero damage check melon and fruit inside quality, simultaneously, with reference to helix transporting device, the achievable melon and fruit inside quality on-line checking of the present apparatus, detected suitable for the large-scale melon and fruit grade such as field "Hami" melon.
Description
Technical field
The present invention relates to a kind of near infrared spectrum on-line detecting system and implementation method, more particularly to a kind of large-scale melon and fruit
Inside quality near infrared spectrum on-line detecting system and implementation method, belong to Intelligent agricultural product testing equipment field.
Background technology
China is the big country of a Production of fruit and consumption, with the improvement of people's living standards, the quality to fruit
Higher requirement is proposed, a kind of simple effective method is needed in the Non-Destructive Testing of fruit badly.At present, has related scholar both at home and abroad
Correlative study has been done to the multi-step detection of moving of large-scale melon and fruit.
Lammertyn etc. (2000) compared for three kinds of different probes and Jonadold apples soluble solid carried out closely
The testing research of reflection infrared spectrum characteristic, is as a result shown in the range of 880-1650nm, optical fiber combined crosswise probe detection effect
Fruit is relatively preferable, coefficient R=0.91, RMSEP=0.57%.
Soluble solid content SSCs and TA of the Liu etc. (2010) using CCD type near infrared spectrometer to Nanfeng orange
Detected, establish interval partial least square model using effective wave band in 600-980nm wavelength bands, as a result obtain, SSC
Coefficient R=0.64, RMSEP=0.09% of coefficient R=0.92, RMSEP=0.65%, TA forecast model of forecast model.
Moghimi etc. (2010) is predicted in the range of wavelength 400-1000nm to the SSC and pH of Kiwi berry, is used
Different preprocess methods, the results showed that, converting (SNV) using standard normal variable can obtain with reference to medium filtering and first differential
Obtain best prediction result (SSC：R=0.93, RMSEP=0.259%；pH：R=0.943, RMSEP=0.076).
Zhang Dehu etc.（2015）It has studied stepwise multiple linear regression（SMLR）, interval partial least square（iPLS）, it is anti-
To section PLS（biPLS）And joint section PLS（siPLS））To honeydew melon instance model precision and
The influence of prediction result.Found by contrasting, biPLS algorithms（When rejecting 8 sections）The pol characteristic wavelength of extraction, which becomes, to be measured
The prediction effect arrived is best（RMSE=1.18%）.
As fully visible, at present both at home and abroad, fruit quality is detected using near infrared technology, is all by spectroscopic data mostly
Spectral information and the correlation of sample quality information are established in analysis, are concentrated mainly on to melon and fruit（Apple, bergamot pear, watermelon etc.）It is quiet
State detection research, it is less for the report of large-scale melon and fruit on-line checking research.
The present invention provides a kind of large-scale melon and fruit detecting system and implementation method based on infrared spectrum, is coordinated using spectrometer
Helicoidal gear online acquisition passes through the infrared spectrum of melon and fruit, coordinates software systems, to reach in the large-scale melon and fruit of on-line checking
The purpose of component matter.
The content of the invention
It is an object of the invention to provide a kind of simple in construction, safe operation, fast and accurately large-scale melon and fruit inside quality exists
Line detecting system and its implementation.
The purpose of the present invention is achieved through the following technical solutions：
Present invention be characterized in that：Including frame, helical feed roller, spectra collection room, c-type light source fixing frame, halogen light source,
Optically focused collimating mirror, motor, optical fiber, spectrometer, computer etc..The halogen light source is arranged on c-type light source fixing frame；It is described
C-type light source fixing frame is arranged on the framework of spectra collection room by adjustable connecting plate and bolt and nut；The helical feed roller leads to
Bearing is crossed to be fixed in frame；The motor provides power by sprocket wheel chain for helical conveyer system；The optically focused collimating mirror
On collimating mirror supporting guide, immediately below position adjustment to spectra collection room center；The optical fiber connects optically focused collimating mirror
And spectrometer；The USB data line connection spectrometer and computer.During system job, according to melon and fruit shape adjustment c-type light source incidence
Angle passes through large-scale melon and fruit to making light through diffusing transmission（Such as "Hami" melon, watermelon）Afterwards, the optically focused that underface is refracted to through melon and fruit is accurate
The infrared spectrum being collected into is reached spectrometer by straight mirror, optical fiber, and spectrometer is connected with computer, coordinates software program, Bian Keshi
Existing static, dynamic acquisition infrared spectrum.After spectrometer initialization, spectrometer is opened, carries out parameter setting, when integration is set respectively
Between, discrete spectrum adds up times of collection, smooth points, then obtains the curve of spectrum, extracts single wave band and spectral value, judgement is
The no threshold value for being less than setting（Because melon and fruit is not delivered to directly over optically focused collimating mirror, near infrared light is directly beaten to be collimated in optically focused
On mirror, now threshold value is maximum）, single wave band and spectral value are otherwise extracted again, if carrying out data acquisition, extraction is single again
One wave band and spectral value, judge whether, more than the threshold value set, otherwise to extract single wave band and spectral value again, be to preserve number
According to, progress average computation, preservation current light spectrum data.Into software systems, inside quality is detected into required spectroscopic data and led
Enter existing detection model, differentiate inside quality, export prediction result, all samples detection finishes, and exits software systems, closes
Hardware platform, otherwise return to helix transporting device and continue to detect.
Compared with prior art, the present invention devises adjustable angle light source fixing frame, by angle adjustment, can easily adjust
Whole light source route, making light source diffusing transmission, light source refracts to optically focused collimating mirror after melon and fruit, and infrared-ray is sent to light through optical fiber
Spectrometer, the spectral manipulation collected is analyzed by software systems, zero damage check melon and fruit inside quality can be realized.Together
When, with reference to helix transporting device, the achievable melon and fruit inside quality on-line checking of the present apparatus, suitable for field "Hami" melon etc.
Large-scale melon and fruit Quality Detection.
Brief description of the drawings
Fig. 1 is a kind of large-scale melon and fruit inside quality near infrared spectrum on-line detecting system apparatus structure schematic diagram
Fig. 2 is helix transporting device structure chart
Fig. 3 is light-source angle fixed installation diagram
Fig. 4 is optically focused collimating mirror scheme of installation
Fig. 5 is near infrared spectrum calibration model Establishing process figure
Fig. 6 is working-flow figure
In diagram：1-USB data line, 2-spectrometer, 3-computer, 4-optical fiber, 5-collimating mirror supporting guide, 6-optically focused
Collimating mirror, 7-melon and fruit sample, 8-spectra collection room, 9-light source fixing frame, 10-halogen light source, 11-helical feed roller,
12-driving-chain, 13-motor, 14-frame, 15-adjustable connecting plate, 16-optically focused collimating mirror bracket, 17-sprocket wheel, 18-
Bearing.
Embodiment
Embodiment 1：Referring to the drawings 1,2,3,4, the present embodiment：Including frame（14）, helical feed roller（11）, spectra collection
Room（8）, light source fixing frame（9）, halogen light source（10）, optically focused collimating mirror（6）, motor（6）, optical fiber（4）, spectrometer（2）, meter
Calculation machine（3）Deng.The halogen light source（10）Installed in c-type light source fixing frame（9）On；The c-type light source fixing frame（9）Pass through
Adjustable connecting plate（15）And bolt and nut is arranged on spectra collection room（8）On framework；The helical feed roller（11）Pass through bearing
（18）And its support is fixed in frame；The motor（13）It is connected with helix transporting device, passes through sprocket wheel（17）And chain passes
It is dynamic（12）Power is provided for helical conveyer system；The optically focused collimating mirror（6）Installed in collimating mirror supporting guide（5）On, position
Adjust to spectra collection room（8）Immediately below center；The optical fiber（4）Connect optically focused collimating mirror（6）And spectrometer（2）；The USB
Data wire（1）Connect spectrometer（2）And computer（3）.During system job, according to melon and fruit shape adjustment c-type light source fixing frame
（10）Incident angle passes through melon and fruit sample to making light through diffusing transmission（7）（Such as "Hami" melon, watermelon）Afterwards, underface is refracted to through melon and fruit
Optically focused collimating mirror（6）, optical fiber（4）The infrared spectrum being collected into is reached into spectrometer（2）, spectrometer is connected with computer, matches somebody with somebody
Software program is closed, static, dynamic acquisition ir data can be realized.
Embodiment 2：System on-line checking process：After spectrometer initialization, spectrometer is opened, carries out parameter setting, respectively
The time of integration is set, and discrete spectrum adds up times of collection, smooth points, then obtains the curve of spectrum, extracts single wave band and light
Spectrum, judge whether the threshold value less than setting（Because melon and fruit is not delivered to directly over optically focused collimating mirror, near infrared light is directly beaten
On optically focused collimating mirror, now threshold value is maximum）, single wave band and spectral value are otherwise extracted again, if carrying out data acquisition,
Single wave band and spectral value are extracted again, judge whether, more than the threshold value set, otherwise to extract single wave band and spectral value again,
It is to preserve data, carries out average computation, preserves current light spectrum data.Into software systems, inside quality detection is required
Spectroscopic data imports existing detection model, differentiates inside quality, exports prediction result, and all samples detection finishes, and exits software
System, hardware platform is closed, otherwise return to helix transporting device and continue to detect.
Embodiment 3：The detection model method for building up：By test obtain pol physics and chemistry true value and original static spectrum with
Dynamic spectrum, original static spectrum is pre-processed with dynamic spectrum with a variety of methods, and by pretreated spectrum with
Machine is divided into calibration set and forecast set, and sugar degree of fruit and melon visible and near infrared spectrum model is established using calibration set, should by forecast set input
Model draws prediction result, and prediction result is to characterize the stability of the model and accuracy by R and RMSEP indexs.
Described above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, without departing from the technical principles of the invention, some improvement and modification can also be made, these are improved also special
In sharp protection domain.
Claims (2)
- To exist 1. the present invention relates to a kind of large-scale melon and fruit inside quality near infrared spectrum on-line detecting system and implementation method, its feature In：Including frame, helical feed roller, spectra collection room, c-type light source fixing frame, halogen light source, optically focused collimating mirror, motor, light Fibre, spectrometer, computer etc.；The halogen light source is arranged on c-type light source fixing frame；The c-type light source fixing frame passes through Adjustable connecting plate and bolt and nut are arranged on the framework of spectra collection room；The helical feed roller is fixed on frame by bearing On；The motor provides power by sprocket wheel chain for helical conveyer system；The optically focused collimating mirror supports installed in collimating mirror On guide rail, immediately below position adjustment to spectra collection room center；The optical fiber connection optically focused collimating mirror and spectrometer；The USB Data wire connects spectrometer and computer；During system job, according to melon and fruit shape adjustment light source incidence angle to making light through diffusing transmission Through large-scale melon and fruit（Such as "Hami" melon, watermelon etc.）Afterwards, light refracts to the optically focused collimating mirror of underface through melon and fruit, and optical fiber will be collected To infrared spectrum reach spectrometer, spectrometer is connected with computer, coordinates software program, can realize static, dynamic acquisition Infrared spectrum.
- 2. in a kind of large-scale melon and fruit inside quality on-line detecting system of according to claims 1 based on infrared spectrum and Implementation method, it is characterised in that：（1）The detection model method for building up：Pol physics and chemistry true value and original static spectrum and dynamic spectrum are obtained by testing, Original static spectrum is pre-processed with dynamic spectrum with a variety of methods, and pretreated spectrum is randomly divided into correction Collection and forecast set, establish sugar degree of fruit and melon visible and near infrared spectrum model using calibration set, by forecast set input the model draw it is pre- Survey result, prediction result be by prediction related coefficient R and prediction root-mean-square-deviation RMSEP come characterize the stability of the model and Accuracy；（2）System on-line checking process：After spectrometer initialization, spectrometer is opened, carries out parameter setting, when integration is set respectively Between, discrete spectrum adds up times of collection, smooth points, then obtains the curve of spectrum, extracts single wave band and spectral value, judgement is The no threshold value for being less than setting（Because melon and fruit is not delivered to directly over optically focused collimating mirror, near infrared light is directly beaten to be collimated in optically focused On mirror, now threshold value is maximum）, single wave band and spectral value are otherwise extracted again, are if it is carried out data acquisition, are extracted again Single wave band and spectral value, judge whether, more than the threshold value set, otherwise to extract single wave band and spectral value again, be to keep Data, average computation is carried out, preserve data, into software systems, it is existing that inside quality is detected into required spectroscopic data importing Detection model, differentiate inside quality, export prediction result, all samples detection finishes, and exits software systems, closes hardware and puts down Platform, otherwise return to helix transporting device and continue to detect.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108801976A (en) * | 2018-08-28 | 2018-11-13 | 西北农林科技大学 | A kind of detecting system for the near infrared light source apparatus of simple grain grain quality detection and based on the device |
| CN109765191A (en) * | 2019-01-18 | 2019-05-17 | 中国矿业大学 | A kind of movement coal petrography parallel-moving type tracking EO-1 hyperion identification device |
| CN109856072A (en) * | 2019-03-13 | 2019-06-07 | 西北农林科技大学 | Kiwi berry based on Vis/NIR expands fruit detection method and device |
| CN110208212A (en) * | 2019-07-04 | 2019-09-06 | 中南林业科技大学 | A kind of comprehensive non-destructive testing device of near infrared spectrum and control method |
| CN110320176A (en) * | 2019-07-04 | 2019-10-11 | 中南林业科技大学 | A kind of tunable light source device and control method near infrared spectrum detection |
| CN111220568A (en) * | 2020-03-12 | 2020-06-02 | 中国科学院合肥物质科学研究院 | Apple sugar determination device and method based on near infrared spectrum analysis technology |
| CN112775022A (en) * | 2020-12-04 | 2021-05-11 | 江苏大学 | Small-size fruit inside quality intelligence classification equipment |
| CN113396969A (en) * | 2021-05-26 | 2021-09-17 | 江苏大学 | Flexible electrostatic spraying equipment and method based on fruit electrical characteristics |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104251837A (en) * | 2014-10-17 | 2014-12-31 | 北京农业智能装备技术研究中心 | Near-infrared transmittance spectroscopy on-line detecting system and method for fruit internal quality |
-
2017
- 2017-02-17 CN CN201710086729.9A patent/CN107831133A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104251837A (en) * | 2014-10-17 | 2014-12-31 | 北京农业智能装备技术研究中心 | Near-infrared transmittance spectroscopy on-line detecting system and method for fruit internal quality |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108801976A (en) * | 2018-08-28 | 2018-11-13 | 西北农林科技大学 | A kind of detecting system for the near infrared light source apparatus of simple grain grain quality detection and based on the device |
| CN109765191B (en) * | 2019-01-18 | 2023-11-10 | 中国矿业大学 | Motion coal rock translation type tracking hyperspectral identification device |
| CN109765191A (en) * | 2019-01-18 | 2019-05-17 | 中国矿业大学 | A kind of movement coal petrography parallel-moving type tracking EO-1 hyperion identification device |
| CN109856072A (en) * | 2019-03-13 | 2019-06-07 | 西北农林科技大学 | Kiwi berry based on Vis/NIR expands fruit detection method and device |
| CN110208212A (en) * | 2019-07-04 | 2019-09-06 | 中南林业科技大学 | A kind of comprehensive non-destructive testing device of near infrared spectrum and control method |
| CN110320176A (en) * | 2019-07-04 | 2019-10-11 | 中南林业科技大学 | A kind of tunable light source device and control method near infrared spectrum detection |
| CN110208212B (en) * | 2019-07-04 | 2021-06-18 | 中南林业科技大学 | Near infrared spectrum omnibearing nondestructive detection device and control method |
| CN110320176B (en) * | 2019-07-04 | 2021-07-13 | 中南林业科技大学 | Adjustable light source device for near infrared spectrum detection and control method |
| CN111220568A (en) * | 2020-03-12 | 2020-06-02 | 中国科学院合肥物质科学研究院 | Apple sugar determination device and method based on near infrared spectrum analysis technology |
| CN111220568B (en) * | 2020-03-12 | 2024-05-03 | 中国科学院合肥物质科学研究院 | Apple sugar determination device and method based on near infrared spectrum analysis technology |
| CN112775022A (en) * | 2020-12-04 | 2021-05-11 | 江苏大学 | Small-size fruit inside quality intelligence classification equipment |
| CN113396969B (en) * | 2021-05-26 | 2022-09-16 | 江苏大学 | Flexible electrostatic spraying equipment and method based on fruit electrical characteristics |
| CN113396969A (en) * | 2021-05-26 | 2021-09-17 | 江苏大学 | Flexible electrostatic spraying equipment and method based on fruit electrical characteristics |
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