78 results about "Crop management" patented technology

An example machinery includes an automated crop management motorized vehicle having an intelligent, modularized image sensor (e.g. camera or video) system that is portable to other crop management vehicles such as a combine, planter or a tillage machine. The image sensor system includes a framework having a bank of procedures for monitoring and control of navigation, spray application, weeding, seeding, machine configuration, in real time as the machines go through a crop field throughout a crop cycle. One example implementation includes electronic circuits, with more than one set mounted on a platform that facilitates moving the setup to other agricultural machines. The framework captures, preserves and corrects the captured images for real time analysis and response, and for spray management to improve crop yield that is correlated with the machine settings and crop management practices.

A geoposition is determined at a point using a geoposition determining mobile communication device. A crop management zone is identified based on one or more predetermined crop management boundaries and the geoposition of the point. Information about the field is wirelessly communicated between the geoposition determining mobile communications device and a remote site. Analysis may be performed at the remote site with the results of the analysis communicated to the mobile communication device at the growing point. Information may be collected at the point which is stored or analyzed at the remote site. Information may include digital images of plant conditions which may be analyzed to determine conditions such as disease or pest infestation. Contextual information from a number of different types of sources may be used to provide meaningful analysis and feedback to the producer. The producer may define crop management zones using the geoposition determining mobile communication device.

The invention provides for a vertical takeoff and landing capable aerial vehicle with multiple rotors that is designed to carry agricultural sensors and telemetry allowing for real time control of agricultural equipment in accord with sensor data. The ability to carry a suite of agricultural sensors combined with multiple rotors will allow the craft to operate quickly in hovering and longitudinal flight over rows of farm fields and other vegetation and use an NDVI imager and other sensors to take data readings and real time imagery which will allow farmers and other personnel to determine vegetation type, need for chemical applications, plant fertilization, irrigation requirements, and other vegetation features including types of vegetation present. This will allow for precision agricultural, vegetation, and crop management and for farmers it will increase the efficiency of precision agriculture operations.

A pest and disease modeling framework for precision agriculture applies weather information, pest biological characteristics, and crop management data to anonymous crowd-sourced observations of pest presence for a reporting field. A risk assessment profile of pest occurrence for targeted fields in proximity to reporting fields is modeled to generate field-specific measures for pest management of pest infestation. The pest and disease modeling framework matches and filters weather and crop information in infested and pest-free fields based on the anonymous, crowd-sourced reporting of an existing pest presence, by evaluating similarities in pest-relevant data. Fields that are similar to infested fields have the highest risk of infestation, and the modeling framework provides output data in the form of a prediction of pest occurrence based on the risk assessment profile.

An agricultural system includes a sensor positioned forward of an agricultural implement relative to a direction of travel of the agricultural system. The sensor is configured to output a first signal indicative of at least one soil property associated with an operation of the agricultural implement. The system also includes a controller communicatively coupled to the sensor. The controller is configured to output a second signal indicative of instructions to control the operation of the agricultural implement based on the first signal.

An apparatus and method of determining the optimal plant canopy temperature of a plant by measuring chlorophyll a variable fluorescence is described. Leaf samples taken from the plant are placed on a temperature gradient device, exposed to light for an amount of time, and the variable fluorescence emitted from the leaves is measured along with the temperature. Calculations of Fv / Fo over a period of time are used to determine the optimal plant canopy temperature for a plant or a crop. The apparatus and method can be used to compare specific cultivars, to assess the results of plant breeding programs, and to assist in crop management procedures.

A system and method for applying risk analysis to identify optimal crop varieties for use in a particular field with particular environmental characteristics and soil techniques is disclosed herein. The method adapts financial portfolio analysis methods for use with agricultural production to take into account the variability of soil, environment, and crop management. A system for supporting the use of the method is also disclosed.

The invention relates to a method for monitoring and controlling growth parameters of facility crops based on a wireless sensor executing network. The method is characterized by comprising three states, namely a clustering formation stage, an intra-cluster update stage and a cluster head re-election stage. According to the method, a wireless sensor and actor network (WSAN) technology is applied to the facility crops, a cooperate routing protocol-a dynamic clustering-based angle forwarding routing protocol suitable for the WSAN is provided, and a real-time task distribution algorithm RTAA-SFPA based on sealing first price auction is also provided. By the method, automation, networking and intelligentization of facility crop application can be realized, and real-time performance, reliability and low energy consumption of facility crop management can be realized.

An example machinery includes an automated crop management motorized vehicle having an intelligent, modularized image sensor (e.g. camera or video) system that is portable to other crop management vehicles such as a combine, planter or a tillage machine. The image sensor system includes a framework having a bank of procedures for monitoring and control of navigation, spray application, weeding, seeding, machine configuration, in real time as the machines go through a crop field throughout a crop cycle. One example implementation includes electronic circuits, with more than one set mounted on a platform that facilitates moving the setup to other agricultural machines. The framework captures, preserves and corrects the captured images for real time analysis and response, and for spray management to improve crop yield that is correlated with the machine settings and crop management practices.

An elevation and horizontal-moving type greenhouse high-density bed-cultivation mechanical equipment is to arrange a plurality of suspending cultivation beds in certain distance and a movable cart of the cultivation bed in a greenhouse basic unit (the cultivation bed generally refers to a metal profile supporting bed and a plastic cultivation bed that is provided with the crops and arranged inside the metal profile supporting bed). When needing the crops management, the suspending cultivation bed is lifted by an electric-controlled elevation system (or other ways), then the T-shaped cultivation cart is horizontally moved by an electric-controlled horizontal-moving system (or other ways) to the position below the suspending cultivation bed, thereby leaving an operation channel required for the crop cultivation management, which improves the cultivation density of the crops.

The invention relates to the field of the agriculture greenhouse cultivation, and provides a greenhouse crop vine hanging device, and also provides a greenhouse crop cultivating method adopting same and further provides a greenhouse cultivated crop management method adopting the vine hanging device. A vine hanging cord in the vine hanging device can be controlled to open and to close, when a plant is branched, a main vine is separated from the branch through the vine hanging cord, so the main vine and the branch can be uniformly illuminated; since the crop cultivating method utilizes the vinehanging device, the crop branches can be adequately grown, and the utilization rate of the light source in summer can be improved according to the seasonable nature of crops; and since the managementmethod utilizes the vine hanging device, row spacing of plants is controllable, the utilization rate of a cultivating space can be improved, and the yield of the crop per elemental area can be increased.

Information of plant based on color of a surface of plant is acquired from image data obtained by imaging plant, allowing to acquire information of plant at low cost, compared to chlorophyll meter or spectroscopic analyzer. In crop production like rice plant, fertilization management including fertilizer application management like fertilizer amount determination, or other agricultural works, is supported through a smart phone or the like based on data to be observed, like converted leaf color value is calculated from image data obtained by crop imaging. Camera is connected to smart phone. Converted leaf color value can be obtained from image data obtained by imaging leaf of rice plant by camera. Converted leaf color value is transmitted to management server, for example, amount information of applied fertilizer is required in case where converted leaf color value is less than standard, can be obtained as management information for fertilizer application management.

The managing and controlling system for crop in green house includes at least one of the sub-systems for controlling temperature, irrigation, applying fertilizer, spraying pesticide, monitoring and controlling sunshine separately. The temperature controlling sub-system has light controlled switch to control the day and night temperature controller combination to control the heater and ventilator; the sub-system for irrigation, applying fertilizer and spraying pesticide has radio emitter, radio receiver and first control switch to control the irrigation unit, the fertilizer applying unit and the pesticide spraying unit; the monitoring sub-system has the second radio receiver, second switch, etc for image taking and sending; and the sunshine sub-system has the third radio receiver, the third control switch, etc to control lighting and shading. The present invention can realize the automatic management of crop in green house in raised agriculture utility.

A system uses an optical sensor and an image processing apparatus to map emerged plants in a field. The optical sensor collects at least one image of a field of emerged plants. The image processing apparatus analyzes the image to detect areas of vegetation and creates a vegetation map indicative of the detected areas. The image processing element then analyzes the vegetation map to identify emerged plants within the image and creates at least map indicating locations of the emerged plants in the field. Such map may be used to make efficient crop management decisions based on the actual layout of emerged plants in the field.

The invention provides a crop growth prediction method and system. The crop growth prediction method comprises the steps of obtaining a normalized vegetation index corresponding to a current year anda normalized vegetation index corresponding to each historical year; carrying out fitting reconstruction on the normalized vegetation indexes corresponding to the current year and each historical yearto obtain a current NDVI fitting curve and each historical NDVI fitting curve; normalizing the current NDVI fitting curve and each historical NDVI fitting curve by using a DTW algorithm to obtain a current NDVI growth curve and each historical NDVI growth curve; calculating the shortest distance between the current NDVI growth curve and each historical NDVI growth curve, taking the year corresponding to the historical NDVI growth curve with the smallest distance as the optimal NDVI growth matching year, and predicting the growth of the target crops in the current year; and predicting the later growth vigor of the target crop according to the obtained optimal matching year, and guiding the crop management.

The present invention relates to the fields of agriculture, plant breeding or genetic engineering for plants with increased yield, crop forecasting and crop management. In particular, the methods herein describe novel methods of predicting a plant's yield through the measurement of specific metabolites either individually or in combination with one another in a specific plant reproductive tissue. The plant predictive methods described herein may be used to predict yield of plant populations as well as allow for more efficient crop management practices (e.g. amount and timing of chemical applications or amount of irrigation water applied to a field).

The invention discloses a crop planting structure monthly scale dynamic extraction method, which comprises the following steps of S1, determining an analysis region space range, performing data preparation, collecting a time sequence satellite remote sensing data set which is not greater than a monthly scale, performing unified processing in time to obtain monthly scale data, and simultaneously finishing pre-acquisition of sample data in a research region; S2, calculating texture features and normalized vegetation indexes by utilizing the preprocessed monthly-scale satellite remote sensing image data; S3, selecting high-information-richness texture features, and combining the high-information-richness texture features with the vegetation index to form a new image. The problems of long revisit period, difficulty in obtaining the optimal time phase, high price and difficulty in meeting the requirement of dynamic crop management of the conventional method are solved.

The invention discloses a method for making a precise crop cultivation scheme through a smart mobile phone and a GPS (global positioning system). According to the method, basic information data of an agricultural area is loaded through the smart mobile phone, a GPS receiving device is utilized in an agricultural production field for positioning field blocks, the field block cultivation management stage is selected, in addition, the field block crop variety type, yield target and cultivation management measure data or real-time seedling condition data are input, the operational decision is made through a crop management knowledge model module of smart mobile phone processing programs, and a precise management scheme is generated. The method has the advantages that the implementation method is simple, mainstream intelligent mobile phone equipment is used as a decision tool, the carrying is convenient, and the made scheme has practicability and reliability. The invention further discloses a system for making the precise crop cultivation scheme through the smart mobile phone and the GPS, and the system is used for realizing the method disclosed by the invention.

An automated management tool is provided for crop management including the application of all primary agricultural production inputs, including fertilizers, nutrients and other agricultural chemicals, as well as for retrieval and analysis of data pertaining to the site / farm.

The invention relates to a selenium-rich grape field management technology, and belongs to the technical field of crop management. The selenium-rich grape field management technology is characterized in that a sod culture method is adopted for management in the planting of selenium-rich grapes to finally obtain a field management technology for selenium-rich grapes which is less polluted and high in selenium content by being combined with fertilization management, supplement of microelements and spraying. Due to the implementation of a selenium richening technology, the growth is promoted, the leaf function is enhanced, cold resistance, drought resistance, disease and pest resistance and other resistance are improved, the fruit volume is promoted to be expanded, the content of sugar of the fruit is increased and the sweet and sour rate is improved; furthermore, the storing resistance and the transportation resistance are improved; the organic selenium content in the fruit is increased obviously (10 to 50 mcg / kg) in comparison with local ordinary grapes and the mouth feel is excellent; and the residual pesticides and the environmental pollution are reduced.

The invention relates to a management method of ratoon sugarcanes and belongs to the technical field of crop management. According to the management method, stubble shoveling, fertilizer application, solution spraying and film lamination steps are finished in sequence through utilizing a stubble shoveling and ridge breaking machine; the management method specifically comprises the following steps: setting the position of a bottom cutter of the stubble shoveling and ridge breaking machine to be 5cm-8cm higher than a ridge top; then shoveling off sugarcanes higher than the bottom cutter and remaining sugarcane piles to be 7cm-10cm, so as to increase the air permeability of soil and reduce diseases and insects; applying fertilizers after shoveling stubbles, and applying 748kg / ha-752kg / ha of single superphosphate, 297kg / ha-301kg / ha of urea and 298kg / ha-302kg / ha of potassium sulfate; meanwhile, applying 75kg / ha-90kg / ha of bisultap; after applying the fertilizers, spraying an atrazine water solution; and finally, covering a mulching film. According to the management method provided by the invention, the air permeability of the soil is easy to improve and the oxygen content of the soil is improved; the emergence rate and the tillering rate are improved; and meanwhile, the occurrence of plant diseases and insect pests can also be reduced and the yield of the sugarcanes is finally improved.

The present invention provides a crop remote monitoring system based on a wireless sensor network. The system includes a farmland environment telemetering system, an on-site control system, a crop management expert system and a customer service system. The farmland environment telemetering system includes a wireless sensor group arranged at the scene of the crops. The crop management expert system includes a crop planting history database and a crop planting decision-making database. The customer service system is used for receiving data acquired by the farmland environment telemetering system, calling the crop management expert system and executing decisions through the on-site control system. According to the invention, though arrangement of the wireless sensor group network, an information acquisition area forms, so that a scientific basis is provided for regulating and controlling of a green house environment. Existing planting records are utilized by means of utilizing the crop management expert system, and present planting processes are synchronously updated. Crop planting resources are effectively utilized, and purposes of raising economic benefits and agricultural intensive production degree are realized.

The invention discloses an agricultural ecological data management system comprising a crop management unit, an agricultural material and agricultural condition sharing unit, an internet platform and a personal mobile terminal. The crop management unit transmits data to a crop data management host through various kinds of sensors; the agricultural material and agricultural condition sharing unit comprises an agricultural material and agricultural condition data host and various kinds of data subsystems connected with the agricultural material and agricultural condition data host; and by means of big data calculation and classification management of the crop data management host and the agricultural material and agricultural condition data host, the information is finally transmitted to the internet platform or the personal mobile terminal, and omnibearing management and interaction of crops from field plantation, production, logistics and sales are realized. According to the invention, lands are changed from production material to agricultural capital, agricultural production activities are docked with the capital market, the problem that the farmer individual information is asymmetric is solved, and the organization flattening, the asset intensification, the benefit maximization and the information cloud of the agricultural platform are realized; an agricultural product quality tracing system is established; and the economic and social benefits are inestimable.

The invention provides a crop growth monitoring system with accurate monitoring, comprising a sensor monitoring module, a remote sensing and monitoring module, a data transmitting module, a crop management module, and an early warning module. The sensor monitoring module is used for collecting the parameter information showing the crop growing situation, and the collected parameter information issent to the crop management module through the data transmitting module. The remote sensing and monitoring module is used for collecting different remote sensing source images of crops, which are processed in the manner of blending. The blended images are sent to the crop management module through the data transmitting module. The crop management module conducts monitoring on the crop growing situation based on the parameter information and the blended images. The early warning module is used for sending early warning based on the monitoring situation of the crop growth. The invention is advantageous in that accurate monitoring of crop growth can be realized, and crop yield can be increased.

The invention discloses an NFC-certified agricultural product traceability method based on real-time data acquisition of the Internet of Things. The method comprises the following steps: 1 setting a multi-point meteorological and environmental information automatic collecting device in a field or an orchard, and collecting necessary basic data of crops and fruit trees in real time during the growth process, and transmitting the necessary basic data to a receiving end via a wireless network transmission module. By adopting the NFC-certified agricultural product traceability method based on thereal-time data acquisition of the Internet of Things disclosed by the present invention, compared the paper records of the cooperative in the process of collecting basic information of crops in the past, higher convenience and accuracy are achieved, information is abundant, plant protection experts can remotely read data collected on the farmland or orchard and perform remote guidance of plant protection according to the actual situation, the process in the agricultural production process is optimized, the efficiency of crop management is improved, and the application of NFC encryption chip improves the risk resistance of easy-to-copy performance of core data, thereby improving the agricultural product market premium capacity.

The invention relates to a self-adaptive crop management system and method based on a low-power-consumption sensor and a Boost model. The self-adaptive crop management system comprises a crop growth environment data real-time acquisition device, a real-time data analysis processing device and a crop management decision execution device. The crop growth environment data real-time acquisition devicecomprises a low-power-consumption soil sensor, a spectrum camera and a crop growth covariable data acquisition device. The real-time data analysis processing device comprises a preprocessing server,a modeling calculation server, an experience knowledge base, a model base and a data transmission communication network. The crop management decision execution device comprises a user interaction device, a production decision support server and a decision execution mechanism. According to the method, the defects that an existing agricultural data modeling and decision-making method cannot be updated in real time according to data changes, model construction and evaluation depend on manual intervention, and models and methods are insufficient in generalization in different regions and backgrounds can be overcome.