94 results about "Corn field" patented technology

The invention belongs to the technical field of unmanned aerial vehicle remote sensing and agriculture combination, and discloses an intelligent decision-making system and method for corn fertilization based on mechanism-data dual-drive fusion. The system comprises a mechanism simulation module, a data preprocessing module, a feature engineering module, a modeling module, a visualization module, a decision support module, a dynamic feedback correction module and a report generation and push module. According to the mechanism-data double-drive fusion-based intelligent decision-making system and method for corn fertilization, a large-area corn field block image is obtained in a short time through an unmanned aerial vehicle multispectral system, and the nitrogen diagnosis efficiency is improved; through a lightweight machine learning agent model, corn canopy leaf nitrogen nutrition parameters are accurately predicted, and a basis is provided for accurate fertilization; the system monitors the nitrogen nutrition status of the corn in real time, and provides possibility for dynamically adjusting a fertilization strategy; the multispectral remote sensing technology can perform nitrogen nutrition diagnosis under the condition of not damaging corn plants, and the corn growth environment is protected.

The invention discloses a corn field weed detection method and device based on improved YOLOv11. The method comprises the following steps: acquiring and constructing a weed image data set for model training; replacing a backbone network of the YOLOv11n baseline network with a double-flow visual network, and taking the replaced network as a first optimized network; replacing the original pyramid pooling module with an enhanced receptive field module at the tail end of the backbone network of the first optimized network to obtain a second optimized network; in a neck feature fusion layer of the second optimization network, a self-adaptive context guide fusion module is used for replacing traditional splicing, and a third optimization network is obtained; and taking the third optimization network as a final lightweight high-precision weed detection model DEA-YOLO11, and detecting field weeds based on the model. According to the method, the problem of low detection precision caused by insufficient global context sensing capability, fine-grained feature loss and low multi-scale feature fusion efficiency of a weed detection model in a complex agricultural scene in the prior art is solved.

The invention discloses a corn disease recognition method based on an improved generative adversarial network. The corn disease recognition method comprises the steps that S1, an initial low-resolution image of a corn field is collected and obtained through an unmanned aerial vehicle; s2, performing super-resolution reconstruction on the initial low-resolution image by using an improved generative adversarial network model; the model construction comprises the following steps: S2.1, constructing a shallow feature extraction layer; s2.2, constructing a deep feature extraction network based on a plurality of RRDB nested residual dense blocks; s2.3, constructing an attention module based on a space and channel dual attention mechanism; s2.4, a multi-scale texture enhancement module is constructed through multi-scale convolution and smooth branches; s2.5, constructing a global residual connection layer; s2.6, constructing an adaptive hybrid up-sampling module based on transposed convolution and stable up-sampling; s2.7, performing mapping output on the features after up-sampling; and S3, carrying out disease prediction on the high-resolution reconstructed image. According to the method, details such as spatial resolution and texture of the unmanned aerial vehicle high-altitude flight remote sensing image are improved, and then the corn disease monitoring precision is improved.

The invention provides a corn disease and insect pest detection method based on MTA-YOLOv11. The problem that an existing detection method is insufficient in small target recognition and edge feature perception in a complex environment is solved. According to the method, on the basis of YOLOv11n, an MERDEM module, a TK-Focus Block module and an MLKD module are introduced and used for enhancing a detail edge, focusing a key area and fusing multi-scale global semantics respectively, and therefore the model can more accurately detect pest and disease damage targets under the complex background; the method comprises the following steps: constructing a Corn-d corn disease and insect pest image data set, dividing the Corn-d corn disease and insect pest image data set into a training set and a verification set in proportion, evaluating a training process of an MTA-YOLOv11 model through the verification set and storing an optimal model weight, and reasoning a corn field image to be detected according to an optimal model corresponding to the optimal model weight, and outputting a detection result containing the disease and pest category, the positioning frame and the visual label. The corn disease and pest detection precision is improved, and the method is light in weight and high in adaptability to complex scenes.

The invention discloses a corn field weed detection method and device based on improved YOLOv11, and the method comprises the steps: collecting a weed picture, marking with a LabelImg marking tool, and constructing a data set with various types of weeds; based on the weed data set, performing structure optimization on the YOLOv11 target detection network to obtain a first optimized network; integrating a parameter-free space attention mechanism SimAM module in the first optimization network to obtain a second optimization network; on the basis of the second optimization network, designing an ACC3k2 module, obtaining a third optimization network, and constructing a feature enhancement network; on the basis of the third optimized network, introducing a DySample up-sampling operator to obtain a fourth optimized network; and taking the fourth optimized network as a final lightweight weed detection network, and detecting weeds in the corn field based on the lightweight weed detection network. The device comprises a processor and a memory. According to the invention, a feasible path is provided for realizing agricultural field intelligent weeding, and a technical support is provided for promoting automatic, efficient and green development of agricultural production.

The invention discloses a nicosulfuron-containing herbicidal composition and application thereof. The herbicidal composition is prepared from the following components: nicosulfuron, amicarbazone, and dimethyltetrachloroisooctyl ester as well as a dispersant, an emulsifier, a wetting agent, a thickening agent, an antifreeze, and a dispersion medium, wherein the dosage form belongs to a dispersed oil suspension agent. Through the combination of the three active ingredients, the herbicidal composition has an obvious synergistic effect, the use amount of pesticides is reduced, the cost and environmental pollution are reduced, the drug resistance of corn field weeds can be delayed by the application of the composition, and the control spectrum is expanded.

The invention discloses an efficient corn straw returning method, which belongs to the technical field of agriculture and comprises the following steps: layering soil of a large-scale corn field along the vertical direction, and acquiring the organic matter concentration of each soil layer; obtaining a soil middle layer organic matter concentration value in the corn field to obtain corn field subareas of the large-range corn field; based on the organic matter concentration historical numerical value of each soil layer in the corn field subareas, obtaining an organic matter transfer rule between the soil layers; on the basis of an organic matter transfer rule between soil layers, the returning straw amount of the corn field subareas is obtained; based on the amount of returning straw of the corn field subareas, the putting amount of a corrosion promoting agent of the corn field subareas is obtained; the method comprises the following steps: preparing returning straws and a corrosion promoting agent based on the returning straw amount of corn field subareas and the corrosion promoting agent putting amount of the corn field subareas, and setting a new soil bottom layer in autumn; and constructing a new soil middle layer and a new soil surface layer based on the new soil bottom layer. The problem that in the prior art, the amount of returned straw is set unreasonably is solved. And the obtaining effect of straw returning operation is fully improved.

The invention belongs to the technical field of agricultural information, and discloses a rapid detection method and system for the plant number of high-oil corn in the seedling stage, and the method comprises the following steps: selecting a high-oil corn monitoring field; the multi-dimensional data of the high-oil corn field is obtained through carrying image acquisition equipment by an unmanned aerial vehicle; performing multi-dimensional data preprocessing; seedling segmentation and identification; performing plant number statistics and verification; and storing and analyzing data. According to the rapid detection method and system for the plant number of the high-oil corn in the seedling stage, data support is provided for analysis and prediction of the growth condition of the corn, field management measures are optimized, and the yield and quality of the corn are improved; the plant number of the high-oil corn in the seedling stage can be rapidly and accurately detected, and the efficiency and accuracy of field management are improved; the method has wide applicability and can be used for corn field management in different growth stages and growth environments.

The utility model relates to a corn field operation seeder capable of adjusting plant spacing. The device comprises a rack, a ditching mechanism, a sowing mechanism, a soil covering disc and a pressing mechanism, the ditching mechanism is installed at the front end of the rack, and seed ditches can be formed through the ditching mechanism; the seeding mechanisms are mounted on the rear sides of the ditching mechanisms and are in one-to-one correspondence with the ditching mechanisms; the soil covering disc is mounted on the rear side of the seeding mechanism, and soil covering can be performed on the seed furrows through the soil covering disc; the pressing mechanism is installed on the rear side of the soil covering disc, and covering soil can be pressed through the pressing mechanism. The scheme provided by the utility model is simple in structure, low in manufacturing cost and suitable for small-scale corn seeding, and manual seeding is replaced, so that the labor intensity of workers is reduced, and the seeding plant spacing can be adjusted.

The dropper fertilization device comprises a filtering assembly, the filtering assembly comprises a water storage tank, the top of the water storage tank is connected with a feeding port, a filtering cylinder is installed on the inner wall of the top of the water storage tank, a plurality of sets of filtering holes are formed in the filtering cylinder in sequence, and the feeding port is matched with the filtering cylinder in position. The top of the water storage tank is connected with a water adding opening which is matched with the filter cartridge in position, an adjustable-speed motor is installed on the top of the water storage tank, and the output end of the bottom of the adjustable-speed motor is connected with a transmission shaft. The filter cartridge arranged on the filter assembly can be used for filtering when a fertilizer mixed solution is mixed, impurities can be effectively filtered, the problem that a dripping hole is blocked when the fertilizer mixed solution is conveyed due to the fact that the impurities cannot be filtered out without a filter device in a traditional mode is solved, and normal fertilization is prevented from being influenced; the scraping plate is attached to the inner wall of the filter cartridge to rotate, so that the filter cartridge can be cleaned, impurities attached to the inner wall of the filter cartridge are scraped, and the condition that filter holes are blocked is avoided.

The invention discloses a corn field nitrogen element visualization method and platform based on an unreal engine, and relates to the technical field of intelligent agriculture. The method comprises the following steps: firstly, obtaining and processing nitrogen element three-dimensional data of a target plot; establishing a three-dimensional space model of the target plot in the unreal engine; and importing the three-dimensional data of the nitrogen elements into the three-dimensional space model, and respectively driving particle systems which represent different colors of spatial distribution conditions of different types of nitrogen elements to realize visualization of the nitrogen elements in the three-dimensional space model. According to the method, the multi-category nitrogen element three-dimensional data is obtained through obtaining and processing, and visual and diversified interactive presentation is performed based on the unreal engine, so that comprehensive and efficient utilization of the collected nitrogen element data is realized, and beneficial effects of visualization in aspects of data analysis and management decision are exerted.

The invention discloses a compound herbicide and a preparation method thereof and relates to the technical field of pesticides. The compound herbicide is compounded by taking rimsulfuron, pyroxsulam and fluroxypyr-mepthyl as effective components and supplementing a safener, a surfactant, an emulsifier, a stabilizer and a solvent. The action mechanisms of the three active ingredients are complementary and synergistic, and annual gramineous weeds and broadleaf weeds in a corn field can be effectively prevented and removed. Through scientific compounding, the application dosage of a single component is remarkably reduced, pesticide residues in the environment and crops are reduced, meanwhile, potential phytotoxicity to the crops is effectively relieved by adding the safener, and the bactericidal composition has the advantages of being efficient, safe and environmentally friendly.

The application belongs to the technical field of pesticide weeding, and discloses a weeding composition containing icafolin and application thereof. The weeding composition contains active ingredient A and active ingredient B. The active ingredient A is icafolin, the active ingredient B is any one of benzenesulfonamides or thiophenesulfonamides, and the mass ratio of the active ingredient A to the active ingredient B is 1:2-200:4.5. The weeding composition provided by the application has high weeding activity, and the mixture of the two has superimposition effect, complementary mechanism, and an expanded weed spectrum. The weeding composition has good weed control effect in corn fields, wheat fields, peanut fields and soybean fields.

The disclosed apparatus, systems and methods relate to a physical stalk sensing system comprising at least one resilient member. Sensors having the resilient member or members are able to estimate the size of the stalks of row crops as they pass through a field, such as a corn field. The sensors can be mounted on a corn head and the results can be analyzed and visualized. A system for predicting crop yields in real-time or near real-time. A system for adjusting a stripper plate gap.

The invention provides a method for improving field growth performance of corn and application. The application of the GLK1 gene or the G2 gene disclosed by the invention can be used for remarkably improving the characters of gramineous plants for the first time, including stalk greening and / or stalk thickening, plant height increasing, biomass increasing, starch content increasing, soluble sugar content and / or yield increasing, and / or photosynthetic ability improving. The invention provides a new way for improvement of gramineous plants.

The application discloses a corn straw efficient returning method, and belongs to the field of agricultural technology, which comprises the following steps: layering the soil of a large range of corn field along the vertical direction, and obtaining the organic matter concentration of each soil layer; obtaining the organic matter concentration value of the middle layer of the soil in the corn field, so as to obtain the corn field partition of the large range of corn field; obtaining the organic matter transfer rule between the soil layers based on the historical value of the organic matter concentration of each soil layer in the corn field partition; obtaining the returning straw amount of the corn field partition based on the organic matter transfer rule between the soil layers; obtaining the put-in amount of the rotting agent of the corn field partition based on the returning straw amount of the corn field partition; configuring the returning straw and the rotting agent based on the returning straw amount of the corn field partition and the put-in amount of the rotting agent of the corn field partition, and setting a new soil bottom layer in the autumn; and constructing a new soil middle layer and a new soil surface layer based on the new soil bottom layer. The problem of unreasonable returning straw amount setting in the prior art is solved, and the effect of the straw returning operation is fully improved.

The invention discloses a crop growth detection system for agricultural cultivation, and relates to the technical field of growth detection, and the system comprises a triangular ridge line generation module which is used for generating a triangular ridge line based on a remote sensing image of a furrow-ridge film-covered corn field; the wet printing point extraction module is used for generating wet printing points based on the remote sensing image and defining a pseudo line center line based on the wet printing points and the triangular ridge line; the forbidden band construction module is used for constructing a forbidden band region based on the pseudo row center line; the seedling candidate detection module is used for determining candidate seedling points based on the prohibited zone area; and the target seeding line determination module is used for determining a target seeding line based on the triangular ridge line, the wet printing points and the candidate seedling points. According to the invention, the stability and spatial purity of crop seedling point detection are improved.

The utility model relates to the technical field of fertilization and irrigation, in particular to a double-channel fertilizer mixing drip irrigation corn field combined application device, which is characterized in that fertilizer conveying pipes are respectively and fixedly arranged at the bottoms of two fertilizer storage barrels, and flow control valves are arranged on the fertilizer conveying pipes and are in electric control connection with a controller; the mixing cylinder is fixedly arranged on the supporting frame and located in the middle position below the two fertilizer storage cylinders, one ends of the two fertilizer conveying pipes are connected with the mixing cylinder, the bottom of the mixing cylinder is connected with a drip irrigation pipeline through a conveying pipeline, the motor is fixedly arranged on the upper portion of the mixing cylinder, and a stirring shaft is rotatably inserted into the inner top wall of the mixing cylinder through a bearing. A first stirring paddle is fixedly arranged at the lower end of the stirring shaft, and an efficient mixing mechanism connected with the stirring shaft is arranged in the mixing cylinder, so that precise mixing and combined application of two fertilizers can be realized, the utilization rate of the fertilizers is increased, the growth requirements of corn are met, and the fertilizers can have better mixing effect and efficiency.

The invention belongs to the technical field of agricultural machinery technology and agricultural technology popularization and application, and discloses a pest control device for agricultural technology popularization, which comprises a vehicle body, a stirring device is arranged in the vehicle body, and a swing structure and an automatic steering device are arranged on the outer side of the vehicle body. According to the invention, an additional stirring motor is not needed, the advancing power of the driving wheel is directly utilized for linkage stirring, and the energy consumption of the equipment is reduced by about 20%; the two-way reverse rotating stirring rod can avoid precipitation and layering of missible oil and suspending agents, the mixing uniformity is improved by 25% compared with one-way stirring, it is ensured that the concentrations of the pesticides at all parts of crops are consistent after spraying, and the pest control effective rate is improved by 15%; the spraying head swings by 35 degrees in a reciprocating manner, so that the covering area of single spraying is increased by 40% compared with that of a fixed spraying head; in the operation of 1 mu of corn field, the consumed time is shortened from 20 minutes to 12 minutes, and the operation efficiency is improved by 40%; and through the limiting design of the arc-shaped groove, the swing track deviation of the sprinkler head is smaller than or equal to 2 degrees, the spraying leakage rate of an edge area is reduced to 5% or below, repeated operation is avoided, and actual application and operation are facilitated.

An apparatus, system, and method that relate to a physical stalk sensing system comprising at least one resilient member. Sensors having the resilient member or members are able to estimate the size of the stalks of row crops as they pass through a field, such as a corn field. The sensors can be mounted on a corn head and the results can be analyzed and visualized. A system for predicting crop yields in real-time or near real-time. A system for adjusting a stripper plate gap.

The application discloses a corn field pest identification method based on underground pest image feature recognition. The method effectively suppresses uneven internal soil illumination through homomorphic filtering, highlights pest edge details, improves detection stability, introduces causal feature decoupling and intervention learning, makes the model learn the morphological characteristics of pests rather than background pseudo-correlation, maintains high recognition rate under different soil types and humidity conditions, and fuses near-infrared texture features, uses the spectral difference between biological tissues and soil in the near-infrared wave band, and enhances the distinguishing ability of pests and sundries with similar colors.

The invention provides a lightweight corn-weed accurate detection algorithm based on improved YOLOv10s, and the algorithm comprises the steps: collecting corn seedling and weed images, and constructing a corn field weed data set; an improved lightweight corn-weed detection model of YOLOv10s is constructed, a D-PP-HGNet lightweight network is constructed to replace an original trunk part of the YOLOv10s model, and an improved RCS-OSA module is introduced into a neck network. Using the corn field weed data set to train and evaluate the improved lightweight corn-weed detection model of YOLOv10s, and using the improved lightweight corn-weed detection model of YOLOv10s after training and evaluation to perform classification detection on to-be-detected corn seedlings and weed images. The technical problems that an existing algorithm is low in recognition accuracy, high in calculation intensity and difficult to deploy at a mobile terminal are solved.

The utility model provides a portable device for releasing noctuid black egg bees in a corn field, which comprises a release box and a vertically arranged support rod, a box cap is arranged above the release box, and the box cap is connected with the release box through a screw fixing port; one corner of the box cap is movably installed on the supporting rod and can move up and down along the connecting rod. According to the portable device for releasing the noctuid black egg bees in the corn field, the problems that when the noctuid black egg bees are released in a large scale in the field, the eclosion rate of the noctuid black egg bees is reduced due to the damage of rainfall, direct sunlight and other natural enemy organisms and the over-high field temperature are solved; secondly, the device can be repeatedly used for 5-10 years, so that the cost is reduced; in addition, the device is small in size, light in weight and convenient to carry, transport and store.

The utility model provides a corn field pesticide sprayer device, which belongs to the technical field of pesticide spraying and comprises a base and a protection assembly arranged on the outer wall of the base, the protection assembly comprises a first protection cover, a second protection cover, a pesticide spraying pipe, a sliding plate, two sliding columns, a pipe and a second fixing frame, the two sliding columns are fixedly arranged at the top of the outer wall of the base, sliding grooves are formed in the two sliding columns, the sliding plate is arranged on the inner walls of the two sliding grooves in a sliding mode, the second fixing frame is fixedly connected with the sliding plate, and the first protective cover is fixedly connected with the second fixing frame. By means of the protection assembly, it can be ensured that pesticide liquid can be directly sprayed to leaves and stems of crops through the spray head, the spraying range and the spraying amount of the pesticide liquid can be controlled by adjusting the opening and closing degree of the protection cover, the pesticide liquid is sprayed in the area more intensively, and the adjustment mode is beneficial for preventing the pesticide liquid from drifting away to a non-target area; and the spraying precision is further improved.

This invention discloses a corn planting machine, aiming to solve the problems of high labor costs, low operating efficiency, poor planting accuracy, and low seedling survival rate in traditional corn planting. The planting machine mainly consists of a seed box, a push handle, transmission gears, a press wheel, a pulley assembly, a furrow opener, and traveling wheels. The push handle allows the operator to grip and control the entire machine. The traveling wheels provide walking power and transmit force to the transmission gears, which drive the pulley assembly to operate the seed dispensing mechanism inside the seed box. The furrow opener opens seed furrows at the front, and the press wheel compacts the soil at the rear. This invention, through the coordinated operation of its components, achieves orderly operation throughout the entire corn planting process, reduces manual labor intensity, improves planting accuracy and efficiency, ensures a good foundation for seed growth, and is suitable for large-scale corn field planting scenarios.

The application discloses a corn waterlogging damage reduction method, and belongs to the technical field of intelligent agriculture, which comprises the following steps: setting a water supply and drainage system in a corn field; acquiring weather data in a future time; predicting precipitation in the future time, and adjusting the soil moisture content of the corn field during non-precipitation; when it is raining, acquiring the drainage demand of the corn field in real time; when the drainage demand of the corn field is true, acquiring the water content increase rate of the soil of the corn field, and acquiring the drainage speed grade of the water supply and drainage system; based on the drainage speed grade of the water supply and drainage system, adjusting the drainage speed grade of the water supply and drainage system during precipitation in real time; when the precipitation ends and the water supply and drainage system is draining, acquiring the soil moisture content after precipitation in real time, and draining the soil of the corn field. The method solves the problem that the whole-process soil moisture content adjustment of the corn field from before precipitation to after precipitation cannot be realized in the prior art, and thus the corn waterlogging damage is reduced through reasonable water supply and drainage of the corn field.

The invention provides a corn field multi-element compound water dispersible granule and a preparation method thereof, the corn field multi-element compound water dispersible granule is a water dispersible granule prepared by compounding aminopyridine salt, mesotrione and nicosulfuron salt, the control effect is good, the physical and chemical properties are stable, the corn field multi-element compound water dispersible granule is not easy to decompose and deteriorate to generate phytotoxicity, and the suspension rate reaches more than 96%; in the use process, the water dispersible granule only needs to be dispersed once, the use process is simple, and the water dispersible granule is a granular solid, is good in flowability, does not stick to the wall after being poured, and does not remain in a packaging container to form secondary pollution.

The invention discloses a corn waterlogging damage reduction method, and belongs to the technical field of intelligent agriculture. The method comprises the following steps: arranging a water supply and drainage system in a corn field; acquiring weather data in future time; predicting precipitation based on future time, and adjusting the soil moisture content of the corn field during non-precipitation; during rainfall, the drainage demand of the corn field is obtained in real time; when the drainage demand of the corn field is true, the water content growth rate of the corn field soil is obtained, and the drainage speed grade of a water supply and drainage system is obtained; based on the drainage speed grade of the water supply and drainage system, the drainage speed grade of the water supply and drainage system in the rainfall period is adjusted in real time; when the rainfall is finished and the water supply and drainage system drains water, the soil moisture content after rainfall is obtained in real time, and the corn field soil is drained. The problem that in the prior art, the water content of corn field soil cannot be adjusted in the whole process from before rainfall to after rainfall, and then waterlogging damage of corn cannot be reduced is solved, and therefore waterlogging damage is reduced through reasonable water supply and drainage of the corn field.

The embodiment of the invention provides a construction method and system of a knowledge graph of silage corn and a storage medium, and belongs to the technical field of knowledge graphs. The method comprises the following steps: extracting a context statement of a candidate entity, and obtaining a confidence coefficient of the candidate entity for a certain entity type; calculating the vector similarity between the vector of the context statement and the corresponding entity type vector; performing weighted calculation on the confidence coefficient and the vector similarity to obtain an output probability that the type of the candidate entity is a certain entity type, and selecting the candidate entity corresponding to the maximum value of the output probability as an output entity; and mapping the output entities and the relation mapping rule base to obtain an entity relation, and obtaining the knowledge graph according to the output entities and the entity relation. Through the method, the entity recognition capability and extraction performance of the entity extraction model in the field of silage corn are effectively improved.

The application discloses a silage corn moisture content online detection system and method, and belongs to the technical field of online detection of agricultural equipment, machine vision and near-infrared spectrum analysis. The system comprises a near-infrared spectrum acquisition module, a visual perception module, a synchronous corresponding module and a data processing output module. The method is to synchronously acquire near-infrared spectrum and image data of materials in a throwing pipeline of a silage harvester and to time-align the data. A stem and leaf mask is extracted through an instance segmentation network to calculate a component area ratio, and a leaf yellowing rate is extracted based on an HSV color space. After being preprocessed and batch corrected, the spectrum is input into a first prediction model to obtain an initial moisture content. The component ratio and the yellowing rate are used as correction features, and a two-stage regression correction model is used to fuse and output a final moisture content. The application solves the problem of large detection error caused by non-homogeneous materials, maturity difference, batch drift and dust interference, has high detection precision and strong robustness, and is suitable for online real-time detection of silage corn in a field.