AU774890B2 - Optical analysis of grain stream - Google Patents
Optical analysis of grain stream Download PDFInfo
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- AU774890B2 AU774890B2 AU17578/01A AU1757801A AU774890B2 AU 774890 B2 AU774890 B2 AU 774890B2 AU 17578/01 A AU17578/01 A AU 17578/01A AU 1757801 A AU1757801 A AU 1757801A AU 774890 B2 AU774890 B2 AU 774890B2
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- 230000003287 optical effect Effects 0.000 title claims description 20
- 230000005855 radiation Effects 0.000 claims description 41
- 239000000835 fiber Substances 0.000 claims description 25
- 239000000470 constituent Substances 0.000 claims description 24
- 239000000523 sample Substances 0.000 claims description 12
- 230000003595 spectral effect Effects 0.000 claims description 9
- 230000001678 irradiating effect Effects 0.000 claims description 4
- 229910052736 halogen Inorganic materials 0.000 claims description 2
- 235000013339 cereals Nutrition 0.000 description 19
- 238000000034 method Methods 0.000 description 10
- 238000012360 testing method Methods 0.000 description 6
- 238000013528 artificial neural network Methods 0.000 description 5
- 238000001228 spectrum Methods 0.000 description 5
- 238000012549 training Methods 0.000 description 5
- 238000005286 illumination Methods 0.000 description 4
- 108090000623 proteins and genes Proteins 0.000 description 4
- 102000004169 proteins and genes Human genes 0.000 description 4
- 241000209140 Triticum Species 0.000 description 3
- 235000021307 Triticum Nutrition 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- 230000001537 neural effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000010521 absorption reaction Methods 0.000 description 2
- 239000000428 dust Substances 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000003062 neural network model Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 239000013074 reference sample Substances 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 101150110330 CRAT gene Proteins 0.000 description 1
- 101150087426 Gnal gene Proteins 0.000 description 1
- 125000000174 L-prolyl group Chemical class [H]N1C([H])([H])C([H])([H])C([H])([H])[C@@]1([H])C(*)=O 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
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- 238000012986 modification Methods 0.000 description 1
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- 230000004044 response Effects 0.000 description 1
- 238000013179 statistical model Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/02—Details
- G01J3/0291—Housings; Spectrometer accessories; Spatial arrangement of elements, e.g. folded path arrangements
-
- 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
-
- 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
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/85—Investigating moving fluids or granular solids
-
- 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
- G01N21/84—Systems specially adapted for particular applications
- G01N21/85—Investigating moving fluids or granular solids
- G01N2021/8592—Grain or other flowing solid samples
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/02—Food
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- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- Chemical & Material Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Health & Medical Sciences (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Description
1 OPTICAL ANALYSIS OF GRAIN STREAM This application claims priority of U.S. provisional patent application No.
60/164,161 filed November 8, 1999.
FIELD OF THE INVENTION The present invention relates to a method and apparatus for optically analysing a stream of an agricultural product in order to determine constituents of the product.
BACKGROUND OF THE INVENTION Systems are known in the art for the optical analysis of a stream of grain.
As the grain is harvested in the field, a light source passes light through the grain stream. The transmitted light is detected by a receiver and processed by a computer under software control. By comparing the spectral absorption with values representing known absorption, the grain can be analyzed to determine its constituents. A need exists for improvements in the optical analysis of agricultural products.
SUMMARY OF THE INVENTION An apparatus consistent with the present invention measures constituents of an agricultural product. In the apparatus, a device forms a stream of the agricultural product. An optical sensing window in the device passes the stream of agricultural product, and a radiation source contained within the housing irradiates the stream of agricultural product as it passes through the optical sensing window. A receiver receives radiation transmitted through the stream of agricultural product and converts the received radiation into a corresponding electronic signal. A processor, coupled to the receiver, receives the electronic signal and analyzes it under software control to determine the constituents of the agricultural product.
ooo i In a first aspect, the present invention provides an apparatus for measuring constituents of an agricultural product, including: a device for forming a stream of the agricultural product; 30 an optical sensing window in the device allowing passage of radiation from "a radiation source to pass through the stream of agricultural product to a receiver; .o e* *o a radiation source for irradiating the stream of agricultural product as the stream of agricultural product passes the optical sensing window; a receiver for receiving radiation transmitted from the radiation source through the stream of agricultural product and the optical sensing window and for converting the received radiation into a corresponding electronic signal; and a processor, coupled to the receiver, for receiving the electronic signal and for analyzing the electronic signal to determine the constituents of the agricultural product using a calibration based at least in part upon the agricultural product.
In a second aspect, the present invention provides an apparatus for measuring constituents of an agricultural product, including: a device for forming a stream of the agricultural product; a radiation source for irradiating the stream of agricultural product as the stream of agricultural product passes the device; a fiber optic cable; a sensing head for receiving the radiation transmitted from the radiation source through the stream of agricultural product and the device for focusing the received radiation onto the fiber optic cable; a spectrometer, coupled to the fiber optic cable, for converting the received radiation into a corresponding electronic signal; and a processor, coupled to the spectrometer, for receiving the electronic signal and for analyzing the electronic signal to determine the constituents of the agricultural product using a calibration based at least in part upon the agricultural product.
BRIEF DESCRIPTION OF THE DRAWINGS 25 FIG. 1 is a block diagram of a system for optically analyzing a stream of an S o agricultural product.
oFIG. 2 is a diagram of a side cover in the system of FIG. 1.
FIG. 3 is a perspective diagram of a detector box in the system of FIG. 1.
FIG. 4 is a perspective view of a sensing window in the system of FIG. 1.
30 FIG. 5 is a top view of the sensing window.
FIG. 6 is a side view of the sensing window.
o *o WO 01/35076 PCT/US00/30627 2 FIG. 7 is a front view of the sensing window.
DETAILED DESCRIPTION Optical Analysis System A system to predict the protein/constituents of agricultural products is described below with reference to FIGS. 1-7. As shown in FIG. 1. an inlet I of the material handling system includes specially designed pipes and accessories. It can be attached to an auger, a clean grain elevator or any outlet of a storage bin. The grain or product entering through inlet 1 moves through grain passage 3. bounded by inner transparent wall 4 and metallic outer wall 5. The grain entering through inlet I passes through a sensing window 6. which has a definite thickness. A position switch 2 is connected to a control unit 7. which is also connected to an electric motor 8. operated by Direct Current (DC) power source 9. Electric motor 8 is mounted within an enclosure box of an auger 10 containing discharger auger 11.
Auger 1II is driven by motor 8. Auger 1 I through an outlet 12 can discharge the grain out from the system back to the original stream of grain or any user-defined location.
An illumination chamber 13 is bounded by transparent wall 4 and vertical opaque wall 17. A base 14 is mounted on a wall 17. A lamp (illumination source) 16 is attached by a lamp holder 15 and is connected to the power source and control box 19 through a cable 17- A. Sensor body 21 includes air inlet passages 43. Lamp 16 may be implemented with, for example, a tungsten-halogen lamp.
Sensor body 21 is attached with a DC fan 20. A side cover 22 of sensor body 21 (shown in FIG. 2) has a small fan 23 mounted on the cover and is operated by DC power source 24. A sensor head 32 is composed of optical passage 25, optically isolated from outer environment by metallic covers 33 and a detector box 26. Sensor head 32 is attached to sensor body 21 by a mount 31. The tip of fiber optic probe 27 is mounted on detector wall 34 (FIG. 3) of detector box 26. Detector box 26 is composed of a front lens wall 35. a detector wall 34, a base plate 37. and a top cover 36 (FIG. Front lens wall 35 contains two lenses.
41 and 42 (in series) arranged between three retainers 38, 39. and Fiber optic cable 28 is connected to a portable spectrometer 29 including a diffraction grating and an array of charged coupled device (CCD) detectors. Spectrometer 29 is coupled to with a computer Operation The grain or agriculture product enters through inlet 1, and it fills up grain passage 3-
EM"'
WO 01/35076 PCT/US0/30627 3 A and 3 and the empty space in the augcr. When the level of grain reaches the level at which position or proximity sensor 2 is located, position sensor 2 triggers the auger to run auger 1 I.
The running of the auger allows the grain to move through auger 11 and out from the system through outlet 12. The location of position sensor 2 along with features of wall 4, sensing window 6, grain passage 3 and 3-A, and auger 11 allow the grain to move at a constant rate.
This feature also helps to eliminate dust build-up on the inner wall of sensing window 6.
Dust build-up can adversely affect performance of the sensor. The near infrared (NIR) beam contained in the emitted illumination by light 16 transmits through the flowing grain in the sensing window 6. The transmitted light passes through optical passage 25 and subsequently passes through detector box 26. The front wall of optical system 35 of detector box 26 converges the transmitted light or radiation to fall on the tip of fiber optic probe 27.
The transmitted light/radiation is conveyed through fiber optic cable 28 to portable spectrometer 29. Spectrometer 29 with the use of the computer 30. under software control.
records the spectral signature of the transmitted light or radiation between 700-1100 nanometers (nm).
Sensing Window FIG. 4 is a perspective view providing more detail of sensing window 6 in the system of FIG. 1. FIGS. 5-7 are, respectively, top, side, and front views also providing more detail of sensing window 6. As shown in FIGS. 4-7, sensing window 6 is formed by inner transparent wall 4. and outer sensing wall 6-B. located behind metallic outer wall 5. The two side walls 6-B of the sensing windows are composed of opaque materials, and they connect the inner and outer walls. Grain passage 3 is empty space formed by the inner transparent wall 4, outer sensing wall 6-B. and two side walls 6-A. A circular area 6-C on the metallic outer wall 5 defines the effective sensing region through which the transmitted beam passes to the sensing head.
Software Processing Computer 30 may use a number of software-implemented techniques and algorithms to process the signal output by spectrometer 29 and determine constituents of the agricultural product. Examples of those techniques and algorithms are explained in Appendix A.
While the present invention has been described in connection with an exemplary embodiment, it will be understood that many modifications will be readily apparent to those skilled in the art, and this application is intended to cover any adaptations or variations thereof. For example, different types of materials for the device, and various types of WO 01/35076 PCT/US00/30627 4 software algorithms for processing the signal resulting from irradiation of the agricultural product, may be used without departing from the scope of the invention. This invention should be limited only by the claims and equivalents thereof.
WO 01/35076 PCT/USOO/30627 The vidwantagrcs of these silgorithmz: At present, the conventional technique in mneasuring/predicting the concentarion of desired cotituent protein, or oil content) using NIR technique involves the tranzinission/ reflectance of a reference sample. To trnslate this proes for on-the-go sensor could crat problem. It will be difficult to use a searate referene sample (other than the product) to obtain reference signal to be used for predicting the constituent's contribution in real-tune/on-the-go, basis. Thus we have proposed algorithms/techniques that could eliminate the need for having a separate reference sample (othier than the product) and thus could be used with on-the-go sensor, and could make the design development and operational process of the sensor more cffciezit.
(Continued..) SUBSTITUTE SHEET (RULE 26) WO 01/35076 PT10102 PCTfUSOO/30627 6 Algorithm Nomenclature: Raw transmission or reflection sigenal (signal-lark) A 0 wavelength Figure I Xi. wavelengths ciical for predicting the constitu -ct of product.
wavelengths w.ith highest or higher correlation with the conentration of constituent reference wavelength, that does not contribute to the concentration of the desired constituent or does not hawe any correlations with the concentration of the desired constituent.
Alrorithm 1I X*i. X2. X3 or could be obtained from prior expeniments. literature or be determined for a given equipment aid/or for a given agricultur-al product with specific to the desired constituent. They can also be determiined by conducting experiments and using stuitistical. or other data ruinnirig techniques such as neural networkigectic algorithms.
(Continued..) SUBSTITUTE SHEET (RULE 26) WO 01/35076 PCTIUSOO/30627 7 1. Obtain the raw spectra of a sample 2. Subtract the dark signal from the raw spectra to obtain [S-A (spect-a dark),., L l 3. Normalize the (spectra dark) signal, Sui.. by Id, using the following relationship.
[sns"i C [Sul
SMW
where, Lnl=normalized signal from X k to I~ L Aj-normalizing wavelength S spectral signal at normalizing wavelength Ad Xdcan b X1, or Xz,or 3 X.o c an also be P wheat. P X2. 4. Normalized spectra. Sn 4 or its first or second or any other higher order derivative: along with suitable statistical or neural network based prediction technique can be used to predict the concentrabou of the desired constituent.
Corollary 1: .At step 3. in addition to normalizing, SuA, additional linear or non-Linear processing of spectra. could be posibke.
At step 3. before normalizing, the (spectra-dark) signal, Su~A. can be processed in any linearinon-linear way.
a At step 3. in equation can be replaced by S." A-q Signal at a given wavelength. X (3) or S= P-where, (Continued....) SUBSTITUTE SHEET (RULE 26) WO 01/35076 PCTIUSOO/30627 8 Signal X-t 0A wavelength Band of wavclength ccntcrcd around x Figure2 (Continur-d..) SUBSTITUTE SHEET (RULE 26) WO 01/35076 WO 0135076PCTIUSOO/30627 9 Flow Chart M-0 (spcural dark) signal, &qj Protein content or other cnstituent (Continued... SUBSTITUTE SHEET (RULE 26) WO 01/35076 PCTIUSOO/30627 Corollary II: Aniother corollary (Corollary 11) is described below-.
Xs. No wavelengths critical for predicting the constituent of product (figure 1) 1Q2 ~nintted radiation at )a trn=itted radiation at MJ incident radiation at Aj incident radiation at Xj Thickness of sample, 1. of the product, whose constituent is being measured Sensing window Figure: 3 Algorithm 2: 1. Obtain dark signal of the sctup~ (with a given tight source, fiber optics. spectrometer).
2. Obtain These can be obtained without using any smple in thesesn window.
3. Obtain and (The sample needs to be there) in the sensing window.
4. Detemine signet Se can be used to predict the constituent of the given product, using a suitable neural network or statistical prediction model.
(Continued...
SUBSTITUTE SHEET (RULE 26) WO 01/35076 PCT/USOO/30627 Afrorithv 3.: This algorithm could eliminate the need for taklinst separate reference si gnal for the on-the-go San=o.
Sensor head SpeUme T-iber optics 'IllrninfionSensing window Source 1 for the given setup of illumination. sensing window, sensor head, fiber optic and its associated setring, find dark signal 2. Using the available gating mechanism (which can be automatically controlled), the intensity of light is reduced and with no sample of the product in the s=enn window, find the spectral response from wavelength, k to L. Let that be denoted by reference signsal. 3. Under running condition, the sample of the product will move through the sensing window. The gatig mechanism will be adjusted back for the light to opera=e in, the desired intensity. Obtain the transmitted Signal, [Tt.
4. Subtract da"- signal from both PRcferenace signal. and transmnitted signal (Tt.
Obtain the normalized signal, [s I T~-darksuiga----- (R dark signal 6. Process the normalized signal. [Sn1t4 for reducing diincusionlities by averaging.
7. Find the second derivative of the normnalized signal and further use the second derivatives to predict the caricenirafion of the constituent using suitable neural network or statistical model.
SUBSTITUTE SHEET (RULE 26) WO 01/35076 PCTIUS00130627 12 Algorithm 1, Corollary 1, was tested on wheat data collected for both static and dynamizconditions.
'MTe raw spectral signal was obtained using PC- 1000 aad .1-200±iberoptics based spectrometer, (Ocean Optics Company. FL). The original data ranged from 682.67 run 1212.37 =m (1100 data points). This signal wasilready subtracted from dark signal.
Kept the data points between 699.67 inn and 1050.3 em (including both ends) thus keeping 698 data points. (used Mvicrosoft Excel) Reduced (preprocess) the data a factor of 4 I using commercial software, GRAMSI32.
(Galactic Industries Corporation NE).
Cboosing reference wavelength. k as 830 nm.
(This was done by Microsoft Excel) )-The normalized signal, Sh 1 was obtained by dividing the processed signal Sj..
SThe second derivatives of Sni was obtained using cormmercial software. GRAMS/32, (Galactic 1ndustrics Corporation, NW).
The second derivatives of were used as the input to the Back Propagation Neural Network. Protein content used as the output of the neural netwozr. Two data sets were created. One set was the -training aet" and the other was the "testing set". The inputs of the training and test set were normalized (with a mean of and standard deviation of Cmri software Professional 11/Plus. (Neural ware, Pittsburgh. was used to develop neural network. A neural network model (with momesdtwn of 0.6 and leIngcoefficient of 0.3) was developed as the prediction model. The neural network was trined on trnining data set and tested on test data set The performance of the prediction model in predi cting protein content was evaluated by comparing the predicted protein content vs.
actual protein content of the wheat samples.
A stand-alone C" program -aas written to calculate thec overall of accuracy. average absolute error, minimumn absolute error and maximum absolute error.
Absolute earor Absolutel(Axtual protein content Predicted protein conteni)I Maximuml absolute ezyor =maximum value among all the absolute errors for the samples in the data se Minimum absolute enor minimum value amnong all the absolute effrm for the samples in the data set SUBSTITUTE SHEET (RULE 26) WO 0 1 /35076 PCTIUSOO/30627 13 For the static conition. the described algorithm showcd an accuracy of 96.17% and 93.80%Y (for training and testing data set respectively) with an avera~ge absolute error of 0.54 point of protein content (for training) and 0.84 point of protcin coutent (for tcitiva).
For dynamic condition, the above algorithim showed an arccwcy of 97.88% (for tralning) and 95.98% (for testing). The average absohrtc error was found to be 0.31 point of protein rcontent (for training) and 0.59 point of protein content (for test data).
SUBSTITUTE SHEET (RULE 26)
Claims (13)
1. An apparatus for measuring constituents of an agricultural product, including: a device for forming a stream of the agricultural product; an optical sensing window in the device allowing passage of radiation from a radiation source to pass through the stream of agricultural product to a receiver; a radiation source for irradiating the stream of agricultural product as the stream of agricultural product passes the optical sensing window; a receiver for receiving radiation transmitted from the radiation source through the stream of agricultural product and the optical sensing window and for converting the received radiation into a corresponding electronic signal; and a processor, coupled to the receiver, for receiving the electronic signal and for analyzing the electronic signal to determine the constituents of the agricultural product using a calibration based at least in part upon the agricultural product.
2. The apparatus of claim 1 wherein the receiver includes: a fiber optic cable; a sensing head for receiving the radiation transmitted through the stream of agricultural product and for focusing the received radiation onto the fiber optic cable; and a spectrometer, coupled to the fiber optic cable, for converting the received radiation into a corresponding electronic signal. s ee
3. The apparatus of claim 2 wherein the fiber optic cable includes a single fiber optic cable.
4. The apparatus of claim 2 wherein the spectrometer includes: 25 a diffraction grating for dividing the receiving radiation into spectral components; and an array of charge coupled devices oriented to receive the spectral S components.
5. The apparatus of claim 2 wherein the sensing head includes: a fiber optic probe coupled to the fiber optic cable; and a plurality of optical lenses positioned between the optical sensing window and the fiber optic cable for focusing the received radiation on the fiber optic probe.
6. The apparatus of claim 1, further including a housing for containing the device, the radiation source, the optical sensing window, and the receiver.
7. The apparatus of claim 6, further including a fan mounted within the housing.
8. The apparatus of claim 1, further including an inlet, coupled to the device, for attachment to a source providing the agricultural product.
9. The apparatus of claim 6, further including a mounting location for accessories. An apparatus for measuring constituents of an agricultural product, including: a device for forming a stream of the agricultural product; a radiation source for irradiating the stream of agricultural product as the stream of agricultural product passes the device; S:a fiber optic cable; o a sensing head for receiving the radiation transmitted from the radiation 20 source through the stream of agricultural product and the device for focusing the received radiation onto the fiber optic cable; "i a spectrometer, coupled to the fiber optic cable, for converting the received radiation into a corresponding electronic signal; and a processor, coupled to the spectrometer, for receiving the electronic 25 signal and for analyzing the electronic signal to determine the constituents of the agricultural product using a calibration based at least in part upon the agricultural oooo product.
S
11. The apparatus of claim 10 wherein the spectrometer includes: 16 a diffraction grating for dividing the receiving radiation into spectral components; and an array of charge coupled devices oriented to receive the spectral components.
12. The apparatus of claim 10 wherein the sensing head includes: a fiber optic probe coupled to the fiber optic cable; and a plurality of optical lenses positioned between the device and the fiber optic cable for focusing the received radiation on the fiber optic probe.
13. The apparatus of claim 10, further including a tungsten-halogen lamp for providing the radiation transmitted through the stream of agricultural product. DATED this 2 0 th day of May 2004 NDSU RESEARCH FOUNDATION WATERMARK PATENT TRADE MARK ATTORNEYS LEVEL 21 77 ST GEORGES TERRACE PERTH WA 6000 AUSTRALIA P20064AU00 *o* *oeoo *g* *ooo*
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US16416199P | 1999-11-08 | 1999-11-08 | |
| US60/164161 | 1999-11-08 | ||
| PCT/US2000/030627 WO2001035076A1 (en) | 1999-11-08 | 2000-11-08 | Optical analysis of grain stream |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| AU1757801A AU1757801A (en) | 2001-06-06 |
| AU774890B2 true AU774890B2 (en) | 2004-07-08 |
Family
ID=22593253
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| AU17578/01A Ceased AU774890B2 (en) | 1999-11-08 | 2000-11-08 | Optical analysis of grain stream |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP1147395A1 (en) |
| AU (1) | AU774890B2 (en) |
| WO (1) | WO2001035076A1 (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102004038408A1 (en) * | 2004-08-07 | 2006-02-23 | Deere & Company, Moline | measuring device |
| AU2006200712B1 (en) * | 2006-02-21 | 2006-09-28 | Rosewood Research Pty Ltd | Spectographic sample monitoring |
| AU2008322904A1 (en) * | 2007-11-13 | 2009-05-22 | Minch Malt Limited | A process and apparatus for analysing and separating grain |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5751421A (en) * | 1997-02-27 | 1998-05-12 | Pioneer Hi-Bred International, Inc. | Near infrared spectrometer used in combination with a combine for real time grain analysis |
| WO1999040419A1 (en) * | 1998-02-06 | 1999-08-12 | Dsquared Development, Inc. | Grain quality monitor |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4146332A (en) * | 1977-04-19 | 1979-03-27 | The United States Of America As Represented By The Secretary Of The Navy | Spectrometer with electronic readout |
| GB8906020D0 (en) * | 1989-03-16 | 1989-04-26 | Shields Instr Ltd | Infrared spectrometer |
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2000
- 2000-11-08 WO PCT/US2000/030627 patent/WO2001035076A1/en not_active Application Discontinuation
- 2000-11-08 AU AU17578/01A patent/AU774890B2/en not_active Ceased
- 2000-11-08 EP EP00980297A patent/EP1147395A1/en not_active Withdrawn
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5751421A (en) * | 1997-02-27 | 1998-05-12 | Pioneer Hi-Bred International, Inc. | Near infrared spectrometer used in combination with a combine for real time grain analysis |
| WO1999040419A1 (en) * | 1998-02-06 | 1999-08-12 | Dsquared Development, Inc. | Grain quality monitor |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2001035076B1 (en) | 2001-09-07 |
| AU1757801A (en) | 2001-06-06 |
| WO2001035076A1 (en) | 2001-05-17 |
| EP1147395A1 (en) | 2001-10-24 |
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| Date | Code | Title | Description |
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| FGA | Letters patent sealed or granted (standard patent) |