EP2094074A2 - Procédé, appareil et système permettant de détecter un besoin en substances de croissance pour promouvoir la croissance de végétaux - Google Patents

Procédé, appareil et système permettant de détecter un besoin en substances de croissance pour promouvoir la croissance de végétaux

Info

Publication number
EP2094074A2
EP2094074A2 EP07858323A EP07858323A EP2094074A2 EP 2094074 A2 EP2094074 A2 EP 2094074A2 EP 07858323 A EP07858323 A EP 07858323A EP 07858323 A EP07858323 A EP 07858323A EP 2094074 A2 EP2094074 A2 EP 2094074A2
Authority
EP
European Patent Office
Prior art keywords
image
vegetation
message
indices
status information
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP07858323A
Other languages
German (de)
English (en)
Inventor
Jouko Kleemola
Jari Peltonen
Iikka Saarelainen
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yara International ASA
Original Assignee
Yara International ASA
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Yara International ASA filed Critical Yara International ASA
Publication of EP2094074A2 publication Critical patent/EP2094074A2/fr
Withdrawn legal-status Critical Current

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Classifications

    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01C—PLANTING; SOWING; FERTILISING
    • A01C21/00—Methods of fertilising, sowing or planting
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01C—PLANTING; SOWING; FERTILISING
    • A01C21/00—Methods of fertilising, sowing or planting
    • A01C21/007—Determining fertilization requirements
    • 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

Definitions

  • the present invention relates to a method, an apparatus and a system for determining a need for growth aids to promote vegetation growth according to the preambles of the following claims.
  • the invention relates also to a wireless radio frequency terminal as well as to a computer program.
  • the object of the present invention is to minimise or even to totally eliminate the above-mentioned problems.
  • An object of the present invention is thus to provide an easy and fast method for determining the need of growth aids.
  • Another object of the present invention is a program for fast and reliable determination of the need of growth aids based on analysis of received images.
  • a typical method according to the present invention determining a need for growth aids to promote vegetation growth comprises following steps
  • a typical apparatus for determining a need for growth aids to promote vegetation growth, comprises - a communication module arranged to receive information in image format, an identification code, and optionally an image attribute, and to send a selected predetermined message and/or vegetation status information to a recipient identified by the identification code,
  • an image analysis module arranged to analyse image and comprising
  • a database module for storing the obtained vegetation index or indices, together with the identification code, and optionally the image attribute,
  • a vegetation index calculation module for comparing the obtained vegetation index or indices with reference values in order to obtain a vegetation status information for the vegetation to be analysed
  • - message selection module for choosing a message from the group of predetermined messages on basis of the image attribute and/or the vegetation status information.
  • a typical system according to the present invention comprises
  • remote end stations arranged to send information in image format, an identification code, and optionally an image attribute to the central unit for determination and storage of vegetation index or indices, the remote end stations being suitable for receiving a selected pre-determined message and/or vegetation status information from the central unit.
  • a typical computer program according to the present invention and comprising computer program code means arranged to determine a need for growth aids to promote vegetation growth comprises: - code means arranged to receive information in image format, an identification code, and optionally an image attribute, and to send a selected pre-determined message and/or vegetation status information to a recipient identified by the identification code,
  • - code means arranged to analyse image and comprising
  • code means for dividing the image into sub-areas comprising a number of image units, such as pixels,
  • - code means for storing the obtained vegetation index or indices, together with the identification code, and optionally the image attribute,
  • - code means for choosing a message from the group of pre-determined messages on basis of the image attribute and/or the vegetation status information.
  • need of growth aids can be determined by using a simple and automated image analysis system.
  • the invention enables a fast determination of the nutritional status of vegetation to be analysed and does not require from the user advanced technical skills or equipment.
  • the invention also provides the information in easily accessible and understandable format.
  • the present invention provides also the possibility to obtain information about need of growth aids in uncomplicated manner for multiple locations.
  • an image of the vegetation to be analysed, an identification code and optionally an image attribute are received by the communication module of the program.
  • the received image is preferably produced by using a mobile end station, such as mobile phone, having a camera function.
  • the image is sent as a Multimedia Message Service (MMS) message.
  • MMS Multimedia Message Service
  • other imagining devices such as digital camera, suitable for producing colour digital images. If the image is produced by using other imagining device, the image can be sent by using a network, such as internet or the image can be sent by using electronic mail system, ftp-upload or image upload via a web page.
  • the communication module is monitoring the various delivery locations, such as MMS server, electronic mail-, ftp- or http-server, and collects the received image, identification code and possible image attribute and forwards them for further processing.
  • the identification code is used for identification of the image sender.
  • the identification code can be a telephone number if a mobile end station, such as mobile phone, is used for transferring the image.
  • the identification code may also be a password, usemame, e-mail address and/or IP address when other data delivery systems are used.
  • the pre-determined message and/or vegetation status information which are obtained as a result of the determination process, are sent to the address from which the original image was received, but it is also possible to send the pre-determined message and/or vegetation status information to a different recipient address if the service user has so defined. For example, a farmer living further away from his fields may ask a local person residing near the fields to take and send the image to be analysed.
  • the communication module may send pre-determined message and/or vegetation status information to his mobile phone or e-mail address, i.e. to different address than from which the image was originally received. This makes it easier, for example, for city-based farmers to be aware of the nutritional conditions of their fields, without needing to visit the fields personally.
  • the image attribute which may be sent together with the image of the vegetation to be analysed and the identification code, may comprise additional information about the image.
  • the pre-determined format of the image attribute enables the program to identify the content of the image attribute.
  • the image attribute may be a letter or number code that provides the program with the information that the received image is meant to be used as a reference image from which reference values for vegetation index or indices are obtained. Usually the same reference is used as long as a new reference image is submitted by using the same identification code.
  • the image attribute may also comprise information about the location of the vegetation to be analysed.
  • the image sender may send the coordinates of the vegetation, ⁇ or the name of the field, or both, together with the image.
  • position-determining means such as Global Positioning System (GPS)
  • GPS Global Positioning System
  • the possibility of knowing the exact location of the vegetation to be analysed makes it easier to provide more precise predictions and recommendations.
  • Use of position coordinates provided by GPS can be used to recognize the name of the field, on which the vegetation to be analyzed is growing, by combining the position information provided by the GPS and electronic field vector data. In that case the user does not need to write the name of the field or position coordinates of the vegetation to the image attribute. Consequently, the image attribute may comprise an image content attribute and/or image position attribute, such as field name or coordinates.
  • an imagining device producing normal RGB-images is used for imagining the vegetation to be analysed.
  • an imaging device designed for infrared imaging or use a suitable filter together with a normal RGB imagining device in order to produce infrared images.
  • Infrared colour images correlate usually better with nutritional status of the vegetation, especially with the nitrogen status, than normal colour images, because vegetation chlorophyll absorbs significant amounts of red light and reflects infrared light.
  • the amount of chlorophyll is closely related to nitrogen status, the difference in these two reflections can be used in estimating the nitrogen status of the vegetation (Hoffmann & Blomberg 2004).
  • the image to be analysed is taken so that it comprises as much vegetation as possible. Typically 60%, more typically 70%, preferably 80%, more preferably 90%, most preferably 95%, sometimes even 100% of the image area comprises vegetation to be analysed.
  • the image is provided perpendicularly to the ground, normally at a distance of 0.1 - 2 m, preferably 0.2 -
  • the image to be analysed is taken so that the area and vegetation to be imaged is protected from direct sunlight.
  • the image is preferably taken on cloudy day or the area and vegetation to be imaged is shadowed.
  • the image taker may, for example, cover the vegetation to be imaged by his shadow. This approach makes the obtained results even more reliable.
  • the image received by the communication module is further forwarded to the image analysis module comprising means for dividing the image into sub-areas comprising a number of image units, such as pixels; means for determining the amount of certain colours and their ratios in the sub-areas of the image; and means for calculating vegetation index or indices on basis of the determined colour amounts and ratios.
  • the image can be divided into sub-areas in a desired manner.
  • the number of image units forming an image sub-area can be chosen for example on basis of image units comprised in the original received image. If the original image has a high resolution, one sub-area can comprise 2, 3 or 4 image units. If the resolution of the original image is low, one sub-area comprises one image unit. Preferably the image to be analysed is dived into sub-areas, each of which comprises one image unit.
  • the amount of certain colours and their ratios are then determined in the sub-areas of the image.
  • relative amounts of red, green and blue colours in the image and the ratios between red and green, red and blue and green and blue colour bands are used for determining vegetation index or indices.
  • a typical digital image contains three colour bands, i.e. red, green and blue.
  • Each image unit of an image typically comprises a value ranging from 0 to 255 for each band.
  • VARI (G-R)/(R+G-B). These indices are preferably calculated for each image unit. An average value for each index is then calculated for the whole image sub-area under analysis. Optionally, other statistical parameters like most common and median of each index may be calculated.
  • the colour ratios are used in calculations instead of absolute colour digits in order to minimize the disturbing effect the amount of incoming light in the image to be analysed.
  • the vegetation index or indices for the received image are determined on basis of the determined colour amounts and ratios.
  • a Bayes model is used to classify whether the vegetation of the received image is sufficient or deficient in growth aid by using the calculated variables as independent variables.
  • Other models like common multiple regression models using vegetation indices as independent variables and growth aid sufficiency index as a dependent variable can also be used for classifying the vegetation.
  • multiple classification models, such as Bayes model usually perform better compared to single variable model commonly used in image analysis applications, e.g., a method used by Hoffmann & Blomberg (2004).
  • the effect of errors caused, e.g. by different kind of imagining devices, imagining conditions and imagining persons can be generally minimized by using multiple data instead of one variable.
  • the image is filtered before determination of vegetation index or indices.
  • the filtering is performed by filtering means adapted to differentiate the image sub-areas comprising vegetation information from sub-areas with less information content.
  • the contents the sub- areas are evaluated so that only sub-areas mainly describing vegetation are accepted for determination of vegetation indices. For example, only sub-areas of which over 50%, typically over 60%, more typically over 70%, preferably over 80%, more preferably 90%, sometimes 100% of the area describes the vegetation are accepted for vegetation indices determination.
  • Sub-areas not fulfilling the criteria are removed from further determination. In this way parts of the image that could distort the final result can be filtered away.
  • the apparatus comprises a database module for storing the obtained vegetation index or indices, together with the identification code, and optionally the image attribute, which was received with the image.
  • the information relating to the imaging location can be saved as data defined by position coordinates and/or the field name.
  • the analysis data can be stored for further use. For example, farmers benefit more of the information obtained by the image analysis if the analysis is conducted at the same field/location every year and the obtained information is stored.
  • the information stored covering a longer time period, for example a whole vegetation period, or two or more vegetation periods, can be obtained by sending a special command to the system.
  • Database module can then compile the required information, whereby it can be sent to the defined receiver by the communication module.
  • This optional service may help farmers to identify the years with good/poor yield amount as well as yield quality. This may then help them to adjust the management actions during the rest of the season according to this information.
  • the stored data/information may also act as a backup data source from which farmers can provide data for authorities offering in some countries agricultural subsidy if this kind of crop status analysis has been conducted.
  • the vegetation index or indices are optionally compared with reference values in order to obtain vegetation status information for the vegetation to be analysed.
  • the image analysis module instructs the database module to retrieve the reference data associated with that identification code.
  • the image analysis module performs a comparison between the index/indices of the received image and reference index/indices. The comparison can be done by using statistical methods, such as naive Bayes classification model (Kontkanen et al., 1998).
  • the analysis model can also be developed using, e.g. a common discriminant analysis which exists in most commercially available softwares, which are designed for statistical analysis.
  • vegetation status information is obtained for the received image.
  • the vegetation status information is usually classified, for example in number of different classes, such as "high”, “above average”, “average”, “below average”, “low”.
  • Each class comprises a certain range of vegetation index values.
  • the ranges determining the classes can be different for different parts of the country, for example depending on the prevailing climate or soil type. If the coordinates of the vegetation to be analysed are received together with the image to be analysed this can be taken into account and the classification system adapted accordingly.
  • a message from the group of pre-determined messages is selected on basis of the image attribute and/or the vegetation status information by using a message selection module.
  • a number of pre-determined messages such as "Nutrition status good, no action necessary", "Nitrogen status low, apply N-fertilizer 40 kg/ha", "Reference image received and analysed” or "No reference data can be found, please send first reference picture”.
  • the pre-determined messages which are chosen on basis of the vegetation status information, i.e. depending on into which class the obtained vegetation status falls, tell about the status of the vegetation and give recommendations about the use of different nutrients and/or about the suitable amounts to be used.
  • the pre-determined message can be chosen also to inform the image sender about the functional status of the program, malfunction of the program or about error of the image sender.
  • the pre-selected message can inform, for example, if the image quality is too low, or if no reference image is found.
  • the pre-selected message also comprises the information included in the image attribute of the original received image, such as the name of the field or position coordinates of the vegetation.
  • the message selecting module instructs the communication module to send the selected message and/or vegetation status information to a recipient identified by the identification code.
  • the selected message and/or vegetation status information is sent as Short Message Service (SMS) message.
  • SMS Short Message Service
  • the nitrogen status of the vegetation is analysed.
  • the use of reference plot which is fertilized with phosphorus or nitrogen more than the rest of the vegetation, enables the determination of phosphorus or nitrogen status, respectively. It is possible to analyse from one image status of one nutrient at a time. The number of analyses that is performed on the received image may be determined on basis of the service level subscribed by the image sender.
  • the whole procedure for determining the need for growth aids is very fast. If the reference data already exists in the program's database module, it typically takes only a few seconds from the sending of the image to the receiving the selected message and/or vegetation status information, provided of course that the means with which the information is transferred is functioning without disturbances. In practice, the information is typically obtained instantaneously in real time. Typical response times from sending the image to receiving the selected message and/or vegetation status information are from 3 to 40 s, more typically from 4 to 20 s, often 3 - 1O s. According to one preferred embodiment of the invention the nitrogen status of corn/maize, wheat, rye, oat, barley, oil seed rape, sugar beet, potato and grasses, especially lawns such as golf course lawn, is determined.
  • the end station comprising imagining means can be arranged in connection to an agricultural machine, such as tractor. When the machine is used on the field it can simultaneously take images of the vegetation.
  • the imagining means are arranged in connection with wireless radio frequency terminal, which is arranged to send information in image format, an identification code, and optionally an image attribute.
  • the imagining means can be arranged to take images at predetermined time intervals, for example every 15 minutes, every half an hour, every hour, every two hours.
  • the imagining means can also take images continuously.
  • the wireless radio frequency terminal sends the images to a central unit for determination and storage of vegetation index or indices.
  • the wireless radio frequency terminal is also arranged to receive selected pre-determined message and/or vegetation status information from the central unit.
  • the amount of nutrients spread to the field can be controlled by the vegetation status information received by the wireless radio frequency terminal.
  • the end station can be arranged to give an alarm signal if the received information differs from the assumed nutrient need, which have been indicated by the user in advance.
  • the process is conducted when the velocity of the agricultural machine is below a defined limiting value, such as 15 km/h, typically ⁇ 10 km/h.
  • the imagining means are arranged in the front part of the agricultural machine, and the nutrient spreading means in the rear end of the machine.
  • Farmer A establishes a trial area having a size of 10 m 2 within his wheat field on June 10 th .
  • Wheat is at growth stage 31 , at which growth stage it starts to grow in height (Zadoks et al., 1974). He applies 40 kg N/ha more nitrogen (N) fertilizer to this area in order to ensure that the crop of the trial area does not suffer for nitrogen deficiency.
  • Farmer A goes to the field three weeks later, on July 1 st , at flag leaf growth stage to check if the wheat field requires more nitrogen to achieve maximum yield and maximum grain protein content under prevailing conditions. He goes first to the trial area.
  • Farmer A checks that the photo is visually of good quality and sends the photo as MMS (Multimedia Messaging Service) message with letter "r" and the name of the field on which he is as message header, the letter "r” symbolizing a reference image, to the phone number of the Growth Check Service Provider. Teleoperator forwards the MMS message to the service computer of the Service Provider. The service computer receives the message and stores it into a photo folder.
  • MMS Multimedia Messaging Service
  • Software having communication, photo image analysis, image database and vegetation index analysis modules is running on the service computer.
  • Software's communication module is monitoring if any photo images are coming in.
  • the communication module notices that the photo image sent by Farmer A has arrived, and it starts the photo image analysis module.
  • the photo image analysis module reads the received photo image pixel-by-pixel and calculates vegetation indices, i.e. relative amounts of red, green and blue colours and ratios between red and green, red and blue and green and blue colour bands, for the received photo image.
  • the Farmer A has marked the received photo image to be a reference image by indicating letter "r" in the message header, the image analysis module instructs the database module to store the telephone number from which the message was sent and the calculated vegetation indices. Furthermore, it instructs the communication module to notify the Farmer A with Short Message Service (SMS) message that the reference image has been received and analysed.
  • SMS Short Message Service
  • the Farmer A receives the SMS message sent by the software's communication module few seconds after he sent the original MMS message comprising the reference image to the Growth Check Service Provider. During this time the
  • Farmer A has moved to an area outside the trial area. He takes another photo image in similar way as described above, and sends the MMS message comprising the photo image to the Service Provider, but without writing any header to the message. The photo is received and treated by Service Provider's software in similar way as described in connection with the reference image until the stage where the photo image analysis module has analysed the photo image.
  • the vegetation analysis module is started instead of database module.
  • This module decides according to the vegetation indices if the photographed crop is suffering from the nitrogen deficiency.
  • the vegetation index module asks the database module for the vegetation indices of the reference image.
  • the database module finds the vegetation indices of reference image by comparing the telephone numbers from which the image to be analysed was sent and the telephone number stored together with the reference indices.
  • the determination if the crop to be analysed is suffering for nitrogen deficiency is made by comparing the vegetation indices obtained from the image under analysis to reference indices stored in the database. This comparison can be made by using a naive Bayes classification model (Kontkanen et al., 1998).
  • the analysis gives as a result that the crop to be analysed seems to be suffering from severe nitrogen deficiency as its vegetation indices are far from the reference indices obtained by analysis of the trial area, which was sufficient for nitrogen.
  • the vegetation index module instructs the database module to store the telephone number and vegetation index data and the communication module to send to Farmer A an SMS message instructing him to apply 40 kg N/ha for the crop of which he had taken the photo image to be analysed. Farmer A receives this SMS message few seconds after the sending the MMS message comprising the image to be analysed. He decides to apply N-fertilizer in recommended amount.
  • Farmer A harvests the crop both in the field in which he had used the photo analysis service and in the neighbouring field.
  • the yield is 5% higher and protein content 2 protein units higher in the field in which was fertilized according to the recommendations obtained from photo analysis service.
  • Farmer A receives better economical profit for the field because of higher yield and higher grain price due to higher grain quality.
  • the Farmer 1 of the case example 1 visits on the next day, July 2 nd , another wheat field. He does not have to send a reference image this time as he has already a reference photo for a wheat crop at the similar growth stage. Instead, he places his mobile phone with camera function 40 cm above the crop perpendicular to the ground and takes a photo image. He checks the photo quality and sends the photo as Multimedia Messaging Service (MMS) message to the phone number of the Growth Check Service Provider. Teleoperator forwards the message directly to the Service Provider's computer. The computer greets the message and stores it into a photo folder.
  • MMS Multimedia Messaging Service
  • the photo image analysis module reads the photo pixel-by-pixel and calculates vegetation indices, i.e. relative amounts of red, green and blue colour and ratios between red and green, red and blue and green and blue colour bands for the photo.
  • the vegetation analysis module is immediately started, as the MMS message is not indicated as reference.
  • the vegetation analysis module decides according to the calculated vegetation indices if the photographed crop is suffering from the nitrogen deficiency.
  • First the vegetation analysis module asks the database module for the vegetation indices of the reference crop.
  • the database module finds the vegetation indices of reference crop by comparing the telephone numbers from which the image to be analysed is sent and the telephone number stored together with the reference indices.
  • the decision if the photographed crop is suffering for nitrogen deficiency is made by comparing photographed crop vegetation indices to the earlier received reference crop photo vegetation indices. This comparison is made using a naive Bayes classification model, which was trained earlier to differentiate N sufficient and deficient crops with photos taken both of N sufficient and deficient crops. On basis of the comparison the photographed crop seems to have a similar nitrogen status as the reference crop, the vegetation indices being close to the reference vegetation indices.
  • Vegetation index module instructs the database module to store the telephone number and vegetation index data and the communication module to send Farmer A an SMS message in which he is instructed not apply any nitrogen for the location in which he has taken the photo. Farmer A receives this SMS message few seconds after sending the MMS-message and decides not to do the nitrogen application. In autumn he harvests the crop both in the field in which he has used the photo analysis service and in the neighbouring field and realizes the yield and grain protein content are similar. So he has made the right decision and saved money by saving in fertilizer costs. Case example 3
  • Farmer B goes to his wheat field at growth stage flag leaf. He places his mobile phone 30 cm above the crop perpendicular to the ground and takes a photo. He checks the quality of the photo image and sends the photo image as Multimedia Messaging Service (MMS) message to Growth Check Service Provider's phone number. Teleoperator forwards the MMS message to the Service Provider's computer. The computer greets the message and stores it into a photo folder.
  • MMS Multimedia Messaging Service
  • the photo analysis module reads the photo pixel-by-pixel and calculates the vegetation indices, i.e. relative amounts of red, green and blue colours and the ratios between red and green, red and blue and green and blue colour bands.
  • the vegetation analysis module is started, as the message did not have the header "r".
  • the vegetation index module asks the database module for the vegetation indices for the reference crop. The database module tries to find reference data by using the telephone number from which the image was received as an identification code.
  • the database module notices that there is no reference photo sent from that telephone number.
  • the module instructs the message selection module to select a corresponding message.
  • the message selection module selects the message and the communication module sends the Farmer B an SMS message in which instructions are given to send a reference photo first.
  • the farmer receives the SMS message few seconds after sending the MMS and decides to follow given instructions.

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  • Life Sciences & Earth Sciences (AREA)
  • Soil Sciences (AREA)
  • Environmental Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Chemical & Material Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Closed-Circuit Television Systems (AREA)
  • Sowing (AREA)

Abstract

La présente invention concerne un procédé, un appareil et un système permettant de détecter un besoin en substances de croissance pour promouvoir la croissance de végétaux. Le procédé consiste à recevoir une image, un code d'identification et éventuellement un attribut d'image, à analyser l'image, à détecter des indices relatifs aux végétaux, et à envoyer un message prédéterminé, sélectionné, et/ou des informations relatives à l'état des végétaux, à un destinataire. Ce procédé permet de détecter facilement et rapidement un besoin en substances de croissance sur la base d'une analyse d'images reçues.
EP07858323A 2006-12-22 2007-12-20 Procédé, appareil et système permettant de détecter un besoin en substances de croissance pour promouvoir la croissance de végétaux Withdrawn EP2094074A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FI20061153A FI20061153L (fi) 2006-12-22 2006-12-22 Menetelmä, laite ja järjestelmä kasvun apuaineiden tarpeen määrittämiseksi kasviston kasvun edistämiseksi
PCT/FI2007/000299 WO2008077996A2 (fr) 2006-12-22 2007-12-20 Procédé, appareil et système permettant de détecter un besoin en substances de croissance pour promouvoir la croissance de végétaux

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EP2094074A2 true EP2094074A2 (fr) 2009-09-02

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CN103018180B (zh) * 2012-12-11 2015-04-22 江苏大学 一种基于多源光信息技术的棉花病害检测方法和装置
CN103472009B (zh) * 2013-09-16 2015-11-18 南京农业大学 一种不同植株氮含量水平下小麦植株含水率的监测方法

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US6115481A (en) * 1998-10-22 2000-09-05 Centrak, Llc User modifiable land management zones for the variable application of substances thereto
CA2272444C (fr) * 1999-05-19 2006-10-10 Douglas Snider Systeme et methode de distribution d'engrais
US6889620B2 (en) * 2001-02-28 2005-05-10 The Mosaic Company Method for prescribing site-specific fertilizer application in agricultural fields
US6813544B2 (en) * 2002-08-19 2004-11-02 Institute Of Technology Development Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data
US20060271262A1 (en) * 2005-05-24 2006-11-30 Mclain Harry P Iii Wireless agricultural network
US7610122B2 (en) * 2005-08-16 2009-10-27 Deere & Company Mobile station for an unmanned vehicle

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FI20061153L (fi) 2008-06-23
FI20061153A0 (fi) 2006-12-22
WO2008077996A3 (fr) 2008-12-24

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