CN102384767A - Nondestructive detection device and method for facility crop growth information - Google Patents
Nondestructive detection device and method for facility crop growth information Download PDFInfo
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- CN102384767A CN102384767A CN2011103637643A CN201110363764A CN102384767A CN 102384767 A CN102384767 A CN 102384767A CN 2011103637643 A CN2011103637643 A CN 2011103637643A CN 201110363764 A CN201110363764 A CN 201110363764A CN 102384767 A CN102384767 A CN 102384767A
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Abstract
The invention discloses a nondestructive detection device and a nondestructive detection method for facility crop growth information, and belongs to the technical field of monitoring of facility crops. The device comprises a growth information sensing system, an electric control mechanical rocker arm and a control computer; the control computer drives the electric control mechanical rocker arm to be positioned at a detection position, and controls the growth information sensing system; reflection spectrums of nitrogen, phosphorus, potassium and moisture of crops, multispectral images, canopy temperature characteristic, multispectral morphological characteristics of canopies, stalks, plants and fruits, fruit quality information, and information of environmental illumination, temperature and humidity are acquired by using a multispectral imager and sensors of infrared temperature, irradiance, environmental temperature and humidity and load; nutrient and moisture characteristic spaces are acquired by optimizing and compensating the nutrient and moisture characteristics of the crops; and growth vigor information of canopy area, stalk thickness, fruit quality, plant height and the like is acquired by extracting the multispectral morphological characteristics of the crops, and comprehensive acquisition and nondestructive detection of the growth information of the crops are realized by combining nutrient, moisture and growth vigor characteristics.
Description
Technical field
The present invention relates to a kind of protected crop growth information the cannot-harm-detection device and method, belong to the protected crop monitoring technical field.Refer in particular to the visible light-near-infrared reflection spectrum, multispectral image, canopy surface temperature, canopy illumination, ambient temperature and humidity and the load sensor that utilize protected crop and carry out the Non-Destructive Testing of plant growth information; Can be through technological the organically blending of multiple lossless detection such as spectrum, visual pattern, infrared temperature detection; Illumination and humiture environmental monitoring in conjunction with plant growth; The integrated information of plant growths such as comprehensive nitrogen, phosphorus, potassium, moisture and the canopy area that obtains protected crop synchronously, stem are thick, plant height, fruit quality; The information that provides through this device; Can carry out the regulation and control of water and fertilizer management and facilities environment according to the growth conditions and the dynamic need of protected crop.
Background technology
The protected crop growth information is meant the integrated information of the main nutrient elements level that comprises crop, moisture, stem fruit leaf growing way etc.
On behalf of the ratio of the large-scale attached-greenhouse area of facilities horticulture modernization level, China's facilities horticulture total area the first in the world wherein increase year by year.But need fertile water information and the growth information detection system of needing owing to lack advanced and applicable protected crop; Can't nutrition moisture content, the growth information of crop be carried out comprehensively, detects accurately and resolve; Can't perception regulate and control requirement really, cause the crop yield potentiality not by abundant excavation with the reflection plant growth.And to obtain the product of high yield and high quality and the repayment of high economic benefit, and just must be according to the actual demand of crop, through obtaining a series of plant growth information, and growth information is carried out comprehensive evaluation, carry out water and fertilizer management and environment conditioning according to evaluation result.Therefore, press for application more comprehensively, the plant growth information detector of system, science, instruct the production run of modern installations, to improve output, reduce the regulation and control cost, reduce waste and pollution of area source that excessive fertilization causes, increase economic efficiency.
Growing way information such as the Non-Destructive Testing of protected crop growth information comprises mainly that nutrients such as crop n p k nutrition, moisture detect and canopy area, stem are thick, plant height, plant strain growth speed, fruit quality and growth rate detect two aspects.Because crop alimentary and moisture lack when superfluous, can cause crop leaf surface and the change of interior tissue physiological property, thereby cause that crop leaf and canopy change to the reflection characteristic and the characteristics of image of spectrum.Simultaneously, the water stress state of crop and its canopy surface temperature significant correlation through different saturation vapours being depressed the analysis of hat-temperature poor (canopy surface temperature and environment temperature poor) Changing Pattern, can carry out Non-Destructive Testing to the moisture information of plant.And growing way information such as the canopy area of crop, stem are thick, plant height, fruit appearance also can be obtained through image method.
At present, crop alimentary, the more existing correlative studys in water content detection aspect.Crop alimentary lacks and the superfluous change that can cause the crop spectral reflection characteristic.Based on this principle; Aspect spectral detection; Application number is 200510088935.0 application for a patent for invention; Disclose the lossless detection method and the surveying instrument of a kind of portable plant nitrogen and moisture, carried out the nutrient diagnosis of plant at the spectral reflectance strength information of four characteristic wave strong points, utilized nitrogen and the water percentage information of the inverting of four wavelength vegetation indexs being obtained plant through detecting plant leaf.Application number is 200820078489.4 utility application, discloses a kind of nitrogen reflection index detector, utilize crop leaf in the spectral reflectance information of two certain wave strong points as the nitrogen reflection index, and then infer the yield and quality of crop.Application number is 200510088935.0 application for a patent for invention, discloses a kind of lossless detection method of plant leaf blade physical signs, and the spectral reflectance information that can utilize 380～1100nm is to chlorophyll, xenthophylls, and nitrogen and moisture etc. detects.It at application number 200410048127.7 application for a patent for invention; A kind of cucumber leaves nitrogen content Forecasting Methodology based on the natural lighting reflectance spectrum is disclosed; Can draw the reflection vegetation index of blade through the spectral reflectance intensity of cucumber leaves, and then judge its nitrogen level at the specified wavelength place.At present; The related research method of patent of nutrient such as crop alimentary and moisture information spectroscopic diagnostics; Mainly be to utilize plant leaf blade to detect, that is to say, through spectral reflectivity analysis to individual blade in the nutrition of the spectral reflectivity of some certain wave strong point and combined information thereof to crop; And then infer the nutrition condition of single plant, and colony's trophic level of analyzed area implants in view of the above.And only utilize the blade information of plant, and can't fully characterize the nutritional status of whole strain plant, therefore, the trophic level of knowing crop through individual blade by inference then can cause very big error.Therefore, could really satisfy the demand based on the nutrient diagnosis method of canopy level.In addition, be the point source sample mode because the spectral information collection adopts, sampled point is had relatively high expectations, and be subject to the influence of background and context factor, therefore, only utilize the reflectance spectrum information of crop to carry out nutrition and the water content detection error is bigger.
It is to lack caused change in physical properties according to crop alimentary that the visual pattern of crop alimentary detects, and utilizes imageing sensor to obtain characteristics such as the crop color (gray scale) relevant with trophic level, texture.In the visual pattern context of detection, application number is 200710069116.0 patent of invention, discloses a kind of method of quickly non-destructive measurement for nitrogen content of tea using multiple spectrum imaging technology.Application number is that application for a patent for invention and the application number of 200510062298.X is 200520134360.7 utility application, has announced a kind of multiple spactrum image diagnosis mothod of rape nitrogen nutrition and diagnostic system.Said system all adopts the multispectral camera system of 3CCD as the vision collecting device, under computer control, gathers influences of plant crown multispectral image information through the multispectral camera system of 3CCD, can the nondestructive nitrogen nutritional status of diagnosing plant.Though this type systematic can pass through the color of influences of plant crown multispectral image and the analysis of textural characteristics; Come the nitrogen nutrition situation of diagnosis of plant; But, especially have significantly positive reciprocation between nitrogen and the moisture, and this type systematic can't detect to the water stress information of plant because plant nutrition exists reciprocation each other; Therefore under the situation that can't know moisture information, the detection of nitrogen also can receive certain influence.And the multispectral camera system of 3CCD only can be obtained the multispectral image information of specific wavelength; Be difficult to the crop alimentary characteristic is extracted accurately and effectively and screened; Therefore; Have only the multispectral or ultra-optical spectrum imaging system that adopts the higher variable wavelength of spectral resolution could accurately obtain the nutrient information of crop, improve the nutrition accuracy of detection.
Utilizing canopy surface temperature to carry out the crop water context of detection.Application number is that 200710178192.5 application for a patent for invention and application number are 200720190401.3 utility application; A kind of online crop water stress irrigation decision monitoring system is disclosed; Through the monitoring devices such as environment temperature sensor that are provided with on inner infrared canopy surface temperature sensor of installing of one group of high speed The Cloud Terrace and the rack rod, can realize monitoring to the canopy surface temperature of crop in the sub-district.But owing to the trend that can only show water stress based on the water stress index index of canopy-air temperature difference; Can't carry out quantitative evaluation to the water percentage of plant; And water stress index receives the influence of ambient temperature and humidity bigger, must utilize the environmental information of synchronous acquisition to revise in real time.Therefore, only adopt single canopy-air temperature difference information to carry out the moisture monitoring of plant, can only carry out trend and judge; Therefore; Must introduce, and envirment factor is revised in real time, could improve the precision of plant water content detection like various features such as near-infrared reflection spectrum and image informations.
Growing way context of detection crop; Application number is the application for a patent for invention of 200610097576.X; A kind of embedded agricultural plant growth state monitor and method of work thereof are disclosed, can be thick, plant height, consistency of soil and potential of hydrogen survey to the ambient temperature and humidity of plant growth, stem, this system is only thick through stem, plant height is judged crop growing state; And lack dynamic plant growth evaluation model, therefore be difficult to crop growing state is made comprehensive science appraisal.Application number is that 200410014648.0 application for a patent for invention discloses a kind of crop growth monitoring and nutrient fertilization prescription generating apparatus and method of being used for; This invention adopt video camera obtain the stem, leaf, flower of crop, really, the skin image information; Utilize the nutritional labeling detector to obtain crops and soil nutrient information detects; Because video camera only can obtain the visible light composograph; Be difficult to n p k nutrition and the water characteristic of crop are carried out Accurate Analysis, though the nutritional labeling detector can obtain the nutritional information of crop, its sample circuit detection mode can cause damage to crop.
The Non-Destructive Testing of the growth information of crop is mainly based on spectrum and image technique at present.Spectral technique can more convenient acquisition nitrogen content, water percentage and spectral reflectivity or its are drilled the relation of the amount of giving birth to; Visible light or near-infrared vision color of image (gray scale), texture, morphological feature also can characterize information such as crop alimentary level, water stress, leaf area, stem fruit leaf to a certain extent, and the hat of crop-temperature difference and water stress be significant correlation also.But the single detection method of spectrum, image and canopy surface temperature is only obtained nutrition or moisture or leaf area index, stem, fruit is heavily waited isolated information, be difficult to crop growthing state make comprehensively, the judgement of system, science.And between the nutrition, have reciprocation between nutrition and the moisture; Testing process receives the influence of envirment factors such as crop canopies structure, Soil Background spectrum and atmospheric window, humiture bigger; Therefore; Only use spectral technique, or the single detective technical deficiencies such as canopy-air temperature difference of photopic vision image or near-infrared vision image or plant are to reflect growth information such as crop alimentary, moisture and growing way accurately, comprehensively.
In sum, urgent need is a kind of in the facility production can merge multiple Dynamic Non-Destruction Measurement, and the multiple information of integrated use is carried out rapid extraction to growth information such as crop alimentary, moisture and growing ways; The protected crop growth information pick-up unit of accurate analysis and scientific evaluation; Regulation and control of scientific guidance facilities environment and water and fertilizer management, the quality and yield of raising agricultural product reduces the cost that facilities environment is regulated and control; To increase economic efficiency, realize the great-leap-forward development of China's facilities horticulture.
Summary of the invention
The purpose of this invention is to provide a kind of based on many senses information mix together technology; Can make full use of the multiple effective information such as visible light-near-infrared reflection spectrum, multispectral image, canopy surface temperature, canopy illumination, ambient temperature and humidity of protected crop; Nutrition, moisture level and the growth information of crop are comprehensively judged and the protected crop growth information quick nondestructive detection system of scientific evaluation, for modern installations environment conditioning and water and fertilizer management provide scientific basis.
For realizing above-mentioned purpose, the present invention's a kind of protected crop growth information the cannot-harm-detection device and method adopt following technical scheme:
A kind of protected crop growth information the cannot-harm-detection device comprises electric-controlled mechanical rocking arm, growth information sensor-based system and three parts of control computer, and wherein growth information sensor-based system and control computer are installed on the electric-controlled mechanical rocking arm;
Wherein the electric-controlled mechanical rocking arm comprise tripod, VTOL (vertical take off and landing) bar, move horizontally bar, automatically controlled The Cloud Terrace A and automatically controlled The Cloud Terrace B; Wherein tripod is installed in the bottom of electric-controlled mechanical rocking arm, and its bottom is equipped with three universal wheels, and there is fixedly internal thread hole at center, tripod upper end, and there is axle sleeve at the center, lower end, and the VTOL (vertical take off and landing) bar is installed in socket; The VTOL (vertical take off and landing) bar is a screw structure, and its top moves horizontally bar through the connection of cross web member; Moving horizontally bar is screw structure, is positioned at the top of VTOL (vertical take off and landing) bar and the top of electric-controlled mechanical rocking arm; Said automatically controlled The Cloud Terrace A is installed in through the internal thread slide block on the leading screw that moves horizontally bar, and automatically controlled The Cloud Terrace B is installed on the screw mandrel of VTOL (vertical take off and landing) bar through the internal thread slide block.
Wherein the growth information sensor-based system comprises multisensor unit, data collecting card and light source, and the multisensor unit is installed on the automatically controlled The Cloud Terrace A and automatically controlled The Cloud Terrace B of electric-controlled mechanical rocking arm; Light source is installed on the automatically controlled The Cloud Terrace A, be positioned at the multisensor unit under; Data collecting card is connected with the multisensor unit, and the tripod top of said electric-controlled mechanical rocking arm is installed.
Wherein control computer is installed in the tripod top of electric-controlled mechanical rocking arm, links to each other through usb bus with data collecting card, motion control card and multi-spectral imager A, multi-spectral imager B.
The unit of multisensor described in the present invention comprises by multi-spectral imager A, multi-spectral imager B, infrared temperature detector A, infrared temperature detector B, infrared temperature detector C, irradiance sensor, Temperature Humidity Sensor, load sensor, light shield and scale; Wherein multi-spectral imager A, infrared temperature detector A, infrared temperature detector B, irradiance sensor, Temperature Humidity Sensor, light shield are installed on the automatically controlled The Cloud Terrace A of said electric-controlled mechanical rocking arm, are fixed on the below of automatically controlled The Cloud Terrace A, are in head-down position; Said multi-spectral imager B, infrared temperature detector C are installed on the automatically controlled The Cloud Terrace B of electric-controlled mechanical rocking arm, are fixed on the left side of automatically controlled The Cloud Terrace B, are in the side-looking position; Said load sensor is positioned at the below of detecting the sample fruit, is vertically fixed in the greenhouse soil box through support bar; Said scale is fixed on and detects the other vertical and ground of sample, and sample is parallel with detecting.
A kind of protected crop growth information of the present invention lossless detection method, carry out according to following step:
(1) utilizes multi-spectral imager A and multi-spectral imager B; The acquisition testing sample overlook visible light-near-infrared reflection spectrum and the multispectral image with the side-looking visual field; And upload control computer through usb bus, can judge nitrogen, phosphorus, potassium nutrition level and the canopy area, the fruit morphology information that detect sample in view of the above;
(2) utilize the canopy surface temperature information of infrared temperature detector A, infrared temperature detector B, infrared temperature detector C acquisition testing sample; Utilize load sensor, the fruit quality information of acquisition testing sample; Utilize irradiance sensor and Temperature Humidity Sensor, the illumination of acquisition testing sample growing environment and humiture information; After above-mentioned information input data capture card carried out digitizing conversion, upload control computer through usb bus;
(4) visible light-near-infrared reflection spectrum and the multispectral image of gathering carried out analyzing and processing; Control computer is extracted nitrogen, phosphorus, the spectral signature wavelength of potassium and color, texture, gray average and the fusion feature of multispectral image that detects sample; Utilize the intensity signal that obtains synchronously to carry out feature compensation; And then the spectral signature wavelength of the nitrogen phosphorus potassium that extracts, color, texture, gray average and the fusion feature of multispectral image be optimized, make up nitrogen phosphorus potassium spectrum and make up feature space with image;
(5) utilize the visible light-near-infrared reflection spectrum gathered and the canopy surface temperature information that detects sample, control computer is extracted spectral signature and the canopy surface temperature characteristic that detects sample moisture, and combining environmental humiture information is obtained hat-temperature difference and saturation vapour pressure; Utilize the ambient lighting information of obtaining synchronously to carry out feature compensation, make up the spectrum and the canopy surface temperature assemblage characteristic space of moisture through characteristic optimization;
Multispectral image and the fruit quality information of (6) utilize gathering combine with reference to scale, the canopy area, stem that control computer is extracted the detection sample slightly, plant height, fruit morphology and qualitative data; And, try to achieve canopy area spreading rate, plant strain growth speed and fruit growth speed according to the Continuous Observation data;
(7) utilize crop nitrogen, phosphorus, potassium nutrition, moisture and the growth information that obtains, utilize control computer to carry out the continuous monitoring record, as the detection data of the growth information that detects sample.
Wherein the analysis and processing method of the reflectance spectrum of the employing described in the step (4) comprises: at first carry out filtering, progressively return afterwards and principal component analysis (PCA); The analysis and processing method of multispectral image comprises: at first strengthen multispectral image and carry out pixel-level image and merge; Cut apart background through ultra green characteristic and two-dimensional histogram afterwards, carry out color (gray scale) mean value computation, texture analysis and fusion feature analysis at last.
Effect of the present invention is that visible light-near-infrared reflection spectrum and multispectral image, canopy surface temperature, canopy illumination, ambient temperature and humidity and the load sensor that (1) the present invention adopts crop simultaneously carries out the Non-Destructive Testing of plant growth information; Can be through technological the organically blending of multiple lossless detection such as spectrum, image, infrared temperature, radiation intensity; Environment and humiture monitoring in conjunction with plant growth; The comprehensive integrated information of obtaining plant growth synchronously, not only the information amount of obtaining is bigger, and is abundanter; And can hold the growth conditions of crop more comprehensively, exactly, this does not all relate in file in the past; (2) traditional nutrition detection method only detects to nitrogen nutrition and moisture usually; Growth information also only through leaf area, stem information such as thick and plant height carry out experience and judge; Owing to have mutual and antagonism between the crop alimentary, also have alternately between the nutrient water, and crop growing state and the origin cause of formation thereof have uncertainty; Therefore, only according to the growth conditions that the thick detection of information of nitrogen, moisture or plant height, stem of crop is not enough to reflect all sidedly crop.Compare with detected object with traditional single detection means; Growing way information such as nutrient information such as the nitrogen phosphorus potassium of the present invention through obtaining crop, moisture and canopy area, stem are thick, plant height, fruit quality, plant and fruit growth speed; The combining environmental information detection; Can carry out continuous comprehensive comprehensive monitoring to the protected crop growth conditions, this does not all relate in file in the past; (3) the present invention comes the comprehensive n p k nutrition level of judging crop through the visible light-near-infrared reflection spectrum of crop and the fusion of multispectral image information; Judge the water stress state of crop through the information fusion of near infrared spectrum and canopy infrared temperature; Visual pattern through crop; Extract the growing way of morphological feature and then judgement crop; And through ambient lighting and humiture information measuring error is compensated, to obtain the growth information of crop all-sidedly and accurately, this does not all relate in file in the past; (4) the present invention organically blends multiple lossless detection technology, and the comprehensive comprehensive growth information of obtaining crop has synchronously improved efficient, lower labour intensity.
Description of drawings
Fig. 1 is a kind of protected crop growth information of the present invention the cannot-harm-detection device structural representation;
1-scale 2-light shield 3-halogen light source A
4-irradiance sensor 5-Temperature Humidity Sensor 6-infrared temperature detector A
7-multi-spectral imager A 8-infrared temperature detector B 9-halogen light source B
The multispectral video camera B of the automatically controlled The Cloud Terrace A of 10-11-12-infrared temperature detector C
13-load sensor 14-detects sample 15-and moves horizontally bar
The automatically controlled The Cloud Terrace B of 16-VTOL (vertical take off and landing) bar 17-18-electric-controlled mechanical rocking arm
19-tripod 20-data collecting card 21-motion control card
22-control computer 23-greenhouse soil box.
Embodiment
Below in conjunction with accompanying drawing the present invention is carried out detailed description.
With reference to accompanying drawing 1, a kind of protected crop growth information of the present invention the cannot-harm-detection device comprises electric-controlled mechanical rocking arm 18, growth information sensor-based system and 22 3 parts of control computer.Said growth information sensor-based system and control computer 22 are installed on the electric-controlled mechanical rocking arm 18, carry out the adjustment of all around, upper-lower position through controlling mechanical rocking arm 18, make the growth information sensor-based system arrive the detection position.
Said electric-controlled mechanical rocking arm 18 comprises tripod 19, VTOL (vertical take off and landing) bar 16, moves horizontally bar 15, automatically controlled The Cloud Terrace A10 and automatically controlled The Cloud Terrace B17.Said tripod 19 is installed in the bottom of electric-controlled mechanical rocking arm 18, and its bottom is equipped with three universal wheels, and effect is to stablize electric-controlled mechanical rocking arm 18, and can make electric-controlled mechanical rocking arm 18 in operator's move left and right forwards, backwards; There is fixedly internal thread hole at center, tripod upper end, and there is axle sleeve at the center, lower end, and VTOL (vertical take off and landing) bar 16 is installed in socket; VTOL (vertical take off and landing) bar 16 is a screw structure, and its top moves horizontally bar 15 through the connection of cross web member; Move horizontally bar 15 and be screw structure, be positioned at the top of VTOL (vertical take off and landing) bar 16, in the top of electric-controlled mechanical rocking arm 18; Automatically controlled The Cloud Terrace A10 is installed in through the internal thread slide block on the leading screw that moves horizontally bar 15, and automatically controlled The Cloud Terrace B17 is installed on the screw mandrel of VTOL (vertical take off and landing) bar 16 through the internal thread slide block.Said electric-controlled mechanical rocking arm 18 can drive the internal thread slide block and drive automatically controlled The Cloud Terrace B17 carries out vertical direction in 500～3000mm altitude range position adjustment through the leading screw rotation of VTOL (vertical take off and landing) bar 16; Electric-controlled mechanical rocking arm 18 can drive automatically controlled The Cloud Terrace A10 through the leading screw rotation driving internal thread slide block that moves horizontally bar 15 and in 200～2000mm scope, carry out horizontal position adjustment.Through all around displacement movement of electric-controlled mechanical rocking arm 18, adjust in conjunction with the level of automatically controlled The Cloud Terrace A10 and automatically controlled The Cloud Terrace B17 and the position of vertical direction, can drive the growth information sensor-based system that is installed in electric-controlled mechanical rocking arm 18 and arrive required detection position.
Said growth information sensor-based system comprises multisensor unit, data collecting card 20 and light source.Said multisensor unit is installed on the automatically controlled The Cloud Terrace A10 and automatically controlled The Cloud Terrace B17 of electric-controlled mechanical rocking arm 18, and light source is installed on the automatically controlled The Cloud Terrace A10, be positioned at multisensor cell mesh that the automatically controlled The Cloud Terrace A10 of electric-controlled mechanical rocking arm 18 go up to install under; Data collecting card 20 is connected with the multisensor unit, is installed in tripod 19 tops of electric-controlled mechanical rocking arm 18.Said multisensor unit comprises multi-spectral imager A7, multi-spectral imager B11, infrared temperature detector A6, infrared temperature detector B8, infrared temperature detector C 12, irradiance sensor 4, Temperature Humidity Sensor 5, load sensor 13, light shield 2 and scale 1.Wherein multi-spectral imager A7, infrared temperature detector A6, infrared temperature detector B8, light shield 2 are installed on the automatically controlled The Cloud Terrace A10 of said electric-controlled mechanical rocking arm; Be fixed on the below of automatically controlled The Cloud Terrace A10; Be in head-down position; Wherein multi-spectral imager A7 is installed in center, automatically controlled The Cloud Terrace A below; Infrared temperature detector A6, infrared temperature detector B8 are installed in the symmetric position at 1/4th places at the rectangular centre line two ends below the automatically controlled The Cloud Terrace A10, lay respectively at left side and the right side of multi-spectral imager A7; Irradiance sensor 4, Temperature Humidity Sensor 5 are fixed on the symmetric position at 1/3rd places at the rectangular centre line two ends, top of automatically controlled The Cloud Terrace A10.Multi-spectral imager B11, infrared temperature detector C 12 are installed on the automatically controlled The Cloud Terrace B17 of electric-controlled mechanical rocking arm; Be fixed on the symmetric position at 1/3rd places at the rectangular centre line two ends, left side of automatically controlled The Cloud Terrace B17; Be in the side-looking position, multi-spectral imager B11 is positioned at the top of infrared temperature detector C 12.Said load sensor is positioned at the fruit below of detecting sample 14, is installed on the support bar, and support bar is fixed on the greenhouse soil box 23, perpendicular to greenhouse soil box 23; Said scale 1 is fixed on and detects 20cm place, sample 14 left side, vertical and greenhouse soil box 23, and sample 14 is parallel with detecting.In the above-mentioned said sensor; The power input of infrared temperature detector A6, infrared temperature detector B8, infrared temperature detector C 12, irradiance sensor 4, Temperature Humidity Sensor 5, load sensor 13 adopts parallel way to connect; All adopt the power supply of DC24V power supply; Its output is～the 5V signal, and signal output part all links to each other with the signal input part of data collecting card 20, carries out digitizing conversion back and uploads control computer 22 through the usb bus of data collecting card 20; Multi-spectral imager A7, multi-spectral imager B11 link to each other with control computer 22 through usb bus; Adopt the usb bus power supply and the data transmission of control computer, with the visible light-near-infrared reflection spectrum and the multispectral image information uploading control computer 22 of gathering.
The said multi-spectral imager A7 that is in head-down position; Visible light-near-infrared reflection the spectrum and the multispectral image information of detection sample 14 of 5 different characteristic wavelength of 300 ~ 1100nm wavelength coverage can be obtained simultaneously, nitrogen, phosphorus, potassium nutrition level and canopy area, the fruit morphology information of crop can be judged in view of the above.The multi-spectral imager B11 that is in the side-looking position is identical with multi-spectral imager A7 model; In conjunction with scale 1; Can obtain the visible light-near-infrared reflection spectrum and the multispectral image information of detection sample of stem stalk, plant and the different field of view angle of crop, the stem that can obtain crop in view of the above is thick, plant height information and n p k nutrition information.Infrared temperature detector A6, infrared temperature detector B8, infrared temperature detector C 12 are same model; Measurement range is-40～80 ° of C; Its major function is to obtain the canopy surface temperature information of crop diverse location; Environment temperature, the moisturt register information obtained in conjunction with Temperature Humidity Sensor 5 can obtain hat-temperature difference and saturation vapour pressure; Judge the water stress state that detects sample in view of the above, wherein the measurement range of temperature sensor 5 is-40～80 ° of C, and the measurement range of humidity sensor 5 is 0～100%RH; Irradiance sensor 4 is used for obtaining real-time lighting intensity, can the influence that environmental light intensity changes measuring accuracy be compensated in view of the above, and its measurement range is 0～100Klux; The measurement range of load sensor 13 is 0～1000g,, measures its quality through the fruit of lifting crop sample 14, and then obtains fruit growth speed according to the continuous coverage data computation fixedly in the greenhouse soil box through support bar.
Said data collecting card 20 is 16 usb data capture cards; Be installed in tripod 19 tops of electric-controlled mechanical rocking arm 18; Its signal input part links to each other with infrared temperature detector A6, infrared temperature detector B8, infrared temperature detector C 12, irradiance sensor 4, Temperature Humidity Sensor 5, load sensor 13 signal output parts; Input signal is carried out the A/D conversion; Its output terminal links to each other with control computer 22 through the usb bus of data collecting card 20, digital signal is uploaded to control computer 22 analyzes and handle.
Said light-source system comprises light source and light shield 2, is used for providing for multi-spectral imager A7 and multi-spectral imager B11 the visible light-near-infrared light source of 250～3000nm spectral coverage, to obtain multispectral image and stable reflected spectrum data clearly.Wherein light source is made up of halogen light source A3 and halogen light source B9, and it is inboard with the rectangular centre line right ends that moves horizontally the slide block that bar 15 is connected to be installed in automatically controlled The Cloud Terrace A10 respectively; Light shield 2 is installed in the outside, rectangular centre line two ends of the slide block that moves horizontally bar 15 connections; Its effect is that external light source is shielded; And strengthen the radiation intensity and the uniformity coefficient of light source through irreflexive arc reflective surface; With the shielding external disturbance, improve the precision and the stability of reflectance spectrum and high spectrum image data.
The major function of said control computer 22 is to realize signals collecting control, the motion control of electric-controlled mechanical rocking arm and data analysis.Control computer 22 is installed in the top of the tripod 19 of electric-controlled mechanical rocking arm 18; Link to each other with data collecting card 20, motion control card 21, multi-spectral imager A7 and multi-spectral imager B11 through the usb data line, through the visible light-near-infrared reflection spectrum and the multispectral image information of control multi-spectral imager A7 and multi-spectral imager B11 acquisition testing sample; Gather infrared temperature detector A6, infrared temperature detector B8, infrared temperature detector C 12, irradiance sensor 4, Temperature Humidity Sensor 5, load sensor 13 signals through control data capture card 20; Motion through motion control card 21 control electric-controlled mechanical rocking arms 18.And the plant growth information data of obtaining shown, analyzes and handle.
Implement a kind of step of protected crop growth information lossless detection method:
(1) control computer 22 control electric-controlled mechanical rocking arms 18 carry out the front and back position adjustment on the operation path in the ranks between the protected crop; After arriving the detection sample position; Drive the leading screw rotation of VTOL (vertical take off and landing) bar 16; Drive internal thread slide block and automatically controlled The Cloud Terrace B17 and make sensor mounted thereto go up and down to carry out the high and low position adjustment, and then carry out the sensor horizontal position adjustment and arrive detection position directly over the crop through controlling the automatically controlled The Cloud Terrace A10 that moves horizontally on the bar 15;
(2) start halogen light source 3 and 9; And start to lay respectively at and detect directly over the sample 14 in the middle part of the multi-spectral imager A7 on the automatically controlled The Cloud Terrace A10 and crop on the automatically controlled The Cloud Terrace B17; The multi-spectral imager B11 of side direction horizontal level; Acquisition testing sample 14 overlook visible light-near-infrared reflection spectrum and the multispectral image with the side-looking visual field, and upload control computer 22 through usb bus;
(3) start and to be positioned at the infrared temperature detector C 12 that the automatically controlled The Cloud Terrace B17 that detects infrared temperature detector A6, the infrared temperature detector B8 on the automatically controlled The Cloud Terrace A10 directly over the sample 14 and detect sample 14 middle parts goes up the side direction horizontal level, obtain the canopy surface temperature information of crop; Start the load sensor 13 that is positioned at detection sample 14 fruits below, obtain fruit weight information; Startup synchronously is positioned at the irradiance sensor 4 and Temperature Humidity Sensor 5 directly over the detection sample 14; The real-time lighting of acquisition testing sample 14 growing environments and ambient temperature and humidity information, and the voltage signal difference of the sensor is imported data collecting card 20 carry out uploading control computer 22 through usb bus after the A/D conversion;
(4) utilize visible light-near-infrared reflection spectrum and the multispectral image gathered to handle, the analysis and processing method of the reflectance spectrum that is adopted comprises: at first carry out filtering, progressively return afterwards and principal component analysis (PCA); The analysis and processing method of multispectral image comprises: at first strengthen multispectral image and carry out pixel-level image and merge; Cut apart background through ultra green characteristic and two-dimensional histogram afterwards, carry out color (gray scale) mean value computation, texture analysis and fusion feature analysis at last.Control computer is extracted the spectral signature wavelength of the nitrogen phosphorus potassium that detects sample 14 and color, texture, gray average and the fusion feature of multispectral image; Utilize the intensity signal that obtains synchronously to carry out feature compensation; And then the nitrogen that extracts, phosphorus, the spectral signature wavelength of potassium, color, texture, gray average and the fusion feature of multispectral image be optimized, make up nitrogen phosphorus potassium spectrum and make up feature space with image;
(5) utilize the visible light-near-infrared reflection spectrum and the canopy surface temperature information of gathering, control computer 22 is extracted the reflection spectrum characteristic and the canopy surface temperature characteristic of the moisture that detects sample 14, and combining environmental humiture information is obtained hat-temperature difference and saturation vapour pressure; Utilize the ambient lighting information of obtaining synchronously to carry out feature compensation, make up the spectrum and the canopy surface temperature assemblage characteristic space of moisture through characteristic optimization;
Multispectral image and the fruit quality information of (6) utilize gathering combine with reference to scale 1 reference target, the canopy area, stem that control computer 22 is extracted detection samples 14 slightly, plant height, fruit morphology and qualitative data; And, try to achieve canopy area spreading rate, plant strain growth speed and fruit growth speed according to the Continuous Observation data;
(7) utilize n p k nutrition, moisture and the growth information of the detection sample 14 obtain, utilize control computer 22 to carry out the continuous monitoring record, as the detection data of the growth information that detects sample 14.
Claims (4)
1. protected crop growth information the cannot-harm-detection device is characterized in that comprising electric-controlled mechanical rocking arm, growth information sensor-based system and three parts of control computer, and wherein growth information sensor-based system and control computer are installed on the electric-controlled mechanical rocking arm;
Wherein the electric-controlled mechanical rocking arm comprise tripod, VTOL (vertical take off and landing) bar, move horizontally bar, automatically controlled The Cloud Terrace A and automatically controlled The Cloud Terrace B; Wherein tripod is installed in the bottom of electric-controlled mechanical rocking arm, and its bottom is equipped with three universal wheels, and there is fixedly internal thread hole at center, tripod upper end, and there is axle sleeve at the center, lower end, and the VTOL (vertical take off and landing) bar is installed in socket; The VTOL (vertical take off and landing) bar is a screw structure, and its top moves horizontally bar through the connection of cross web member; Moving horizontally bar is screw structure, is positioned at the top of VTOL (vertical take off and landing) bar and the top of electric-controlled mechanical rocking arm; Said automatically controlled The Cloud Terrace A is installed in through the internal thread slide block on the leading screw that moves horizontally bar, and automatically controlled The Cloud Terrace B is installed on the screw mandrel of VTOL (vertical take off and landing) bar through the internal thread slide block;
Wherein the growth information sensor-based system comprises multisensor unit, data collecting card and light source, and the multisensor unit is installed on the automatically controlled The Cloud Terrace A and automatically controlled The Cloud Terrace B of electric-controlled mechanical rocking arm; Light source is installed on the automatically controlled The Cloud Terrace A, be positioned at the multisensor unit under; Data collecting card is connected with the multisensor unit, and the tripod top of said electric-controlled mechanical rocking arm is installed;
Wherein control computer is installed in the tripod top of electric-controlled mechanical rocking arm, links to each other through usb bus with data collecting card, motion control card and multi-spectral imager A, multi-spectral imager B.
2. a kind of protected crop growth information the cannot-harm-detection device according to claim 1 is characterized in that said multisensor unit comprises by multi-spectral imager A, multi-spectral imager B, infrared temperature detector A, infrared temperature detector B, infrared temperature detector C, irradiance sensor, Temperature Humidity Sensor, load sensor, light shield and scale; Wherein multi-spectral imager A, infrared temperature detector A, infrared temperature detector B, irradiance sensor, Temperature Humidity Sensor, light shield are installed on the automatically controlled The Cloud Terrace A of said electric-controlled mechanical rocking arm, are fixed on the below of automatically controlled The Cloud Terrace A, are in head-down position; Said multi-spectral imager B, infrared temperature detector C are installed on the automatically controlled The Cloud Terrace B of electric-controlled mechanical rocking arm, are fixed on the left side of automatically controlled The Cloud Terrace B, are in the side-looking position; Said load sensor is positioned at the below of detecting the sample fruit, is vertically fixed in the greenhouse soil box through support bar; Said scale is fixed on and detects the other vertical and ground of sample, and sample is parallel with detecting.
3. protected crop growth information lossless detection method is characterized in that carrying out according to following step:
(1) utilizes multi-spectral imager A and multi-spectral imager B; The acquisition testing sample overlook visible light-near-infrared reflection spectrum and the multispectral image with the side-looking visual field; And upload control computer through usb bus, can judge nitrogen, phosphorus, potassium nutrition level and the canopy area, the fruit morphology information that detect sample in view of the above;
(2) utilize the canopy surface temperature information of infrared temperature detector A, infrared temperature detector B, infrared temperature detector C acquisition testing sample; Utilize load sensor, the fruit quality information of acquisition testing sample; Utilize irradiance sensor and Temperature Humidity Sensor, the illumination of acquisition testing sample growing environment and humiture information; After above-mentioned information input data capture card carried out digitizing conversion, upload control computer through usb bus;
(4) visible light-near-infrared reflection spectrum and the multispectral image of gathering carried out analyzing and processing; Control computer is extracted nitrogen, phosphorus, the spectral signature wavelength of potassium and color, texture, gray average and the fusion feature of multispectral image that detects sample; Utilize the intensity signal that obtains synchronously to carry out feature compensation; And then the spectral signature wavelength of the nitrogen phosphorus potassium that extracts, color, texture, gray average and the fusion feature of multispectral image be optimized, make up nitrogen phosphorus potassium spectrum and make up feature space with image;
(5) utilize the visible light-near-infrared reflection spectrum gathered and the canopy surface temperature information that detects sample, control computer is extracted spectral signature and the canopy surface temperature characteristic that detects sample moisture, and combining environmental humiture information is obtained hat-temperature difference and saturation vapour pressure; Utilize the ambient lighting information of obtaining synchronously to carry out feature compensation, make up the spectrum and the canopy surface temperature assemblage characteristic space of moisture through characteristic optimization;
Multispectral image and the fruit quality information of (6) utilize gathering combine with reference to scale, the canopy area, stem that control computer is extracted the detection sample slightly, plant height, fruit morphology and qualitative data; And, try to achieve canopy area spreading rate, plant strain growth speed and fruit growth speed according to the Continuous Observation data;
(7) utilize crop nitrogen, phosphorus, potassium nutrition, moisture and the growth information that obtains, utilize control computer to carry out the continuous monitoring record, as the detection data of the growth information that detects sample.
4. a kind of protected crop growth information lossless detection method according to claim 3; It is characterized in that wherein the analysis and processing method of the reflectance spectrum of the employing described in the step (4) comprises: at first carry out filtering, progressively return afterwards and principal component analysis (PCA); The analysis and processing method of multispectral image comprises: at first strengthen multispectral image and carry out pixel-level image and merge; Cut apart background through ultra green characteristic and two-dimensional histogram afterwards, carry out color (gray scale) mean value computation, texture analysis and fusion feature analysis at last.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1514443A (en) * | 2002-12-31 | 2004-07-21 | 中国科学院地理科学与资源研究所 | Omnibearing multi angle measuring platform |
| CN1581457A (en) * | 2004-05-20 | 2005-02-16 | 上海交通大学 | Ball-grating array semiconductor device quality detecting system based on dual-eye machine vision |
| JP2005087042A (en) * | 2003-09-16 | 2005-04-07 | Hitachi Ltd | Plant growth analyzer |
| CN101936882A (en) * | 2010-08-10 | 2011-01-05 | 江苏大学 | Nondestructive testing method and device for nitrogen and water of crops |
| CN102081039A (en) * | 2010-08-17 | 2011-06-01 | 江苏大学 | Environment-controllable hyperspectral image detecting device for crop nutrition and moisture |
| CN202382768U (en) * | 2011-11-17 | 2012-08-15 | 江苏大学 | Facility crop growth information nondestructive test apparatus |
-
2011
- 2011-11-17 CN CN201110363764.3A patent/CN102384767B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1514443A (en) * | 2002-12-31 | 2004-07-21 | 中国科学院地理科学与资源研究所 | Omnibearing multi angle measuring platform |
| JP2005087042A (en) * | 2003-09-16 | 2005-04-07 | Hitachi Ltd | Plant growth analyzer |
| CN1581457A (en) * | 2004-05-20 | 2005-02-16 | 上海交通大学 | Ball-grating array semiconductor device quality detecting system based on dual-eye machine vision |
| CN101936882A (en) * | 2010-08-10 | 2011-01-05 | 江苏大学 | Nondestructive testing method and device for nitrogen and water of crops |
| CN102081039A (en) * | 2010-08-17 | 2011-06-01 | 江苏大学 | Environment-controllable hyperspectral image detecting device for crop nutrition and moisture |
| CN202382768U (en) * | 2011-11-17 | 2012-08-15 | 江苏大学 | Facility crop growth information nondestructive test apparatus |
Cited By (85)
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