49 results about "Field plot" patented technology

The invention discloses a farmland field segmentation method and system based on multispectral SAM model and multitask learning guidance, and belongs to the field of field segmentation. The problem that in the prior art, channel number matching is conducted in a simple channel compression or deep convolution mode, and the challenges that the boundaries of cultivated land parcels are complex, diversified and subtle are difficult to effectively deal with is solved. The method comprises the following steps: performing spectrum compression on a multispectral remote sensing image through a U-Net structure fused with a CBAM attention mechanism to generate a three-channel pseudo visible light image; the image is input into an SAM-ViT encoder subjected to LoRA fine tuning, and global semantic features are extracted; a task token sequence is constructed, explicit interaction between the token and the image features is realized through a bidirectional Transform module, and high-resolution fusion features are generated; calculating cross-task attention, and outputting a multi-task mask through inner product operation; and performing post-processing by using a watershed algorithm to generate a field boundary. The method is used in the field of cultivated land identification.

The invention relates to the technical field of intelligent fertilization, and discloses an organic fertilizer fertilization method and system, and the method comprises the steps: obtaining crop fertilizer demand data and soil fertilizer supply data of a target field, and fertilizer supply data and mineralization characteristic parameters of candidate organic fertilizers; performing dynamic nutrient balance analysis on the crop fertilizer demand data and the soil fertilizer supply data to obtain nutrient demand gap data; according to the mineralization characteristic parameters and soil environment factors in the soil fertilizer supply data, deducing a release rate and an accumulated release amount of nutrients in the candidate organic fertilizer converted to an effective state along with growth time so as to fit nutrient release dynamic curve data of the candidate organic fertilizer; performing space-time matching analysis on the nutrient demand gap data and the nutrient release dynamic curve data so as to determine the optimal application amount and the fertilization opportunity; adaptively adjusting the input amount and the application time point of the candidate organic fertilizer; a specific fertilization arrangement is determined and integrated into an organic fertilizer fertilization scheme; the precise fertilization efficiency of the organic fertilizer can be improved.

The invention relates to the technical field of grain loss monitoring, in particular to a wheat harvesting loss monitoring system and method, and the system comprises an unmanned aerial vehicle monitoring module, a multi-mode sensor array, a signal processing module, an intelligent control module and a man-machine interaction terminal. The unmanned aerial vehicle monitoring module is used for scanning a field parcel, identifying a lodging area and a high-density area and generating a loss risk thermodynamic diagram, the loss risk thermodynamic diagram is imported into a harvester navigation system, and the high-risk area is harvested preferentially; the multi-mode sensor array comprises a piezoelectric grain sensor and an image sensor; the piezoelectric type grain sensor is mounted at the tail part of the cleaning sieve, adopts a vibration isolation device (such as a rubber pad) to reduce mechanical vibration interference, and detects a grain impact signal through a piezoelectric element; the image sensor is arranged on a header and a threshing outlet and is used for identifying missed cutting of wheat ears and damaged grains based on a deep learning algorithm; the intelligent control module comprises a loss rate calculation unit and a parameter optimization unit; the precision and the real-time performance are improved.

The application discloses a reverse making method of terraced rice picture and belongs to the field of straw picture, and comprises the following steps: S1, breeding color rice varieties with different color and plant height, and carrying out planting and management according to the characteristics of terraces; S2, designing a plane pattern by using PS and AI; S3, importing the plane pattern into CAD and adjusting the angle and perspective; S4, measuring the position and range of the rice field picture area field plot and the height difference of the field ridge; S5, discharging the whole pattern in the reverse direction of the field ridge by using the Ovi interactive map, and adjusting the position and angle of the field ridge in the picture to be optimal; and S6, placing the converted pattern in the rice field by using a positioning instrument and placing and planting. The terraces are curved, the field ridge is high, the field plot surface is small, and the rice field picture cannot be made like the basin or the plain, the application adopts a reverse terraced picture making technology, the technology overcomes the disorder and the broken feeling caused by the large height difference of the terraces, the small field plot and the large bending degree, and improves the overall viewing effect of the picture.

The invention relates to the technical field of plant breeding, in particular to an asexual high-yield coffee breeding method which comprises the following steps: screening superior plants to obtain a core stock plant, and preparing an asexual propagation material based on the core stock plant; carrying out seedling culture on the vegetative propagation material to obtain primary clonal seedlings, and carrying out seedling stage identification on the primary clonal seedlings to obtain healthy clonal seedlings; performing a field plot test on the healthy clonal seedlings to obtain candidate clones, and performing a multi-point regional test on the candidate clones to obtain stable clones; according to the method, asexual propagation technical parameters are optimized, composite hormone treatment is combined with a temperature control intermittent spraying technology for cutting seedling raising, and the rooting rate is larger than or equal to 80%; the tissue culture technology adopts an optimized culture medium formula, the propagation coefficient is greater than or equal to 5 times, the consistency is greater than or equal to 99%, and the problems of low propagation coefficient and low rooting survival rate of the traditional asexual propagation technology are solved.

The application discloses a rice and wheat lodging three-dimensional attribute detection and distribution map construction method for a combine harvester, an electronic device and a computer readable storage medium. The method uses a vehicle-mounted binocular vision to obtain field images and depth information, segments a lodging area through a deep learning model, and then calculates three-dimensional attributes such as the area, position, angle and direction of the lodging area. Through displacement-based key frame screening and overlap degree judgment, multiple frame detection results are fused in a global coordinate system, and finally a spatial distribution map reflecting the overall lodging condition of a field plot is constructed, thereby providing a precise sensing basis for intelligent operation of the combine harvester.

The invention relates to the technical field of crop nutrition regulation and control, in particular to a precise water and fertilizer coordinated regulation and control system and method for corn high-protein cultivation under high-temperature and drought conditions, and the method comprises the following steps: acquiring a soil moisture content value and a root layer nitrogen reservoir level of a target field in real time from a corn jointing stage to a filling stage; when the soil moisture content value is lower than a preset threshold value, calculating a water-nitrogen collaborative deficit index in combination with a root layer nitrogen reservoir level; matching a water and fertilizer regulation and control strategy library according to the indexes, and generating a precise water and fertilizer scheme containing the irrigation amount, the nitrogen fertilizer type and the amount; in the process of executing the scheme, an enzyme activity activating substance composition composed of hydroxyproline and zinc ethylenediaminetetraacetate is synchronously injected through an irrigation system. The method realizes dynamic response regulation and control of corn moisture and nutrients under high temperature and drought stress, effectively improves nitrogen utilization rate and protein synthesis efficiency, and promotes high quality and stable yield of corn.

The invention discloses a farmland plot automatic extraction method and system, electronic equipment and a storage medium, relates to the technical field of remote sensing image processing, and realizes accurate extraction of a farmland plot based on a remote sensing image. Acquiring a high-resolution remote sensing image of a target area, and performing sample construction on the high-resolution remote sensing image to obtain an edge detection sample set; performing sample enhancement on the edge detection sample set to obtain an enhanced edge detection sample set; based on the enhanced edge detection sample set, training an improved RCF network model, and obtaining a final improved RCF network model after training; reasoning the high-resolution remote sensing image of the target area through the improved RCF network model to obtain an edge probability graph; and post-processing the marginal probability graph to obtain closed plot data of the target area, and completing automatic extraction of the farmland plot. The method is suitable for automatic extraction of large-area farmland plots.

The invention provides a tobacco field straw dissolving progress monitoring method, electronic equipment and a storage medium, and relates to the field of data processing, and the method comprises the steps: obtaining the preceding crop information of a tobacco field plot according to a first image sequence, obtaining the irrigation information of the tobacco field plot according to a second image sequence, and obtaining the tobacco field dissolving progress according to the preceding crop information and the irrigation information; and field dissolving reminding is carried out on the tobacco field parcels meeting the preset conditions, so that the straw field dissolving process is monitored, and the monitoring efficiency is improved.

1. Name of the product in this design: Field Ridge. 2. Purpose of this design: For the longitudinal and transverse division of field plots. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D rendering 1.

The invention provides a tobacco plant missing positioning method, electronic equipment and a storage medium, and relates to the field of data processing, and the method comprises the steps: obtaining a vector point set of tobacco plants and vector line boundary data of a to-be-detected tobacco field plot, vector points in the vector point set being vector points corresponding to each tobacco plant in the to-be-detected tobacco field plot; obtaining a vector point total set according to the vector point set; the vector point closest to each vector point in the vector point total set and the vector point closest to the vector point in the opposite direction are connected to generate vector lines, the length of each vector line is obtained, if the length of the vector line is larger than a length threshold value, it is considered that the position where the vector line is located is the tobacco plant missing position, and the searching efficiency is improved.

The invention discloses a Chinese wolfberry cultivation method for improving paddy field soil, which comprises the following steps: a, paddy field soil improvement: selecting a paddy field plot, digging a planting ditch, deeply digging for 40-100cm downwards, loosening soil, mixing organic fertilizer, and breaking the original plow pan of the paddy field; after loosening the soil, fermenting for 25-35 days; b, soil preparation and fertilization: before transplanting the wolfberry seedlings, leveling the fermented land, raking the land to be fine, ridging, and applying a ternary compound fertilizer at the same time; an operation ditch is arranged between the two ridges; every two ridges form a group, a drainage ditch is arranged between every two adjacent groups, and surrounding ditches are arranged around; c, transplanting Chinese wolfberry seedlings: transplanting the cultivated Chinese wolfberry seedlings into each ridge according to the plant spacing of 0.8-1.2 m, and thoroughly watering after field planting; d, drip irrigation cultivation: performing drip irrigation with water every 3-5 days; applying microelements to promote rooting during the period; the fruit can be obtained in about half a year. According to the wolfberry cultivation method, the improved paddy field soil is adopted for planting, the survival rate is high, the cultivation period is short, cost is low, and the problem that in the prior art, paddy field soil is not suitable for wolfberry growth is solved.

The application provides a tobacco field rice straw field dissolving progress monitoring method, an electronic device and a storage medium, and relates to the field of data processing. The method comprises the following steps: obtaining information of a previous crop of a tobacco field plot according to a first image sequence, obtaining irrigation information of the tobacco field plot according to a second image sequence, and reminding the tobacco field plot that meets a preset condition to dissolve the field according to the information of the previous crop and the irrigation information. The method realizes monitoring of the rice straw field dissolving progress and improves the monitoring efficiency.

The invention discloses a grassland field quadrat investigation device and method. The investigation device comprises a plant three-dimensional information acquisition box and a camera. The plant three-dimensional information acquisition box comprises a camera bracket and four groups of light-blocking illumination curtains; the camera support is of a frame structure. Each group of light-blocking illumination curtains comprises a side wall shading outer sleeve, a top end shading outer sleeve, a light-emitting part and a dodging lining; the top end shading outer sleeve, the light-emitting piece and the dodging lining are sequentially connected to form a top film. The top film is connected with the side wall shading outer sleeve; the four side wall shading jackets sequentially cover the four side faces of the camera support, and the four top films cover the top end of the camera support. The camera is arranged in the plant three-dimensional information acquisition box; the survey device provided by the invention can reduce the professional skill threshold, improve the survey efficiency of the grassland quadrat, and ensure the accuracy of the collected data, and the collected data can be archived and rechecked for a long time.

The invention discloses an in-field path planning method of a returning machine for soil mechanical compaction and reduction, solves the problem of how to improve the soil improvement effect during path planning, and belongs to the field of agricultural machinery scheduling. The method comprises the following steps: acquiring multispectral remote sensing images of field parcels, and processing the multispectral remote sensing images to obtain images of the field parcels; the image of each field parcel is input into a pre-trained operation area classification model, the category of each field parcel is obtained, and the category comprises a common area, a compaction sensitive area and a non-returning straw obstacle area; and according to the position and the category of each field parcel, taking the path length, the rolling area of the sensitive area and the rolling times of the sensitive area as objective functions, and performing path planning. According to the application, soil compaction and the particle swarm optimization algorithm are combined, a novel returning machine path planning strategy capable of reducing the furrow compaction area and the repeated rolling times on the basis of ensuring the shortest path in the field is provided, and the dual purposes of returning to the field and protecting soil are achieved.

The application discloses a use of carvacrol as a nitrification inhibitor, a use method of carvacrol as the nitrification inhibitor, and a fertilizer manufacturing method and a fertilizer formed by the method. The application finds through indoor simulation, field plot and field tests that the carvacrol has a good inhibiting effect on soil ammonia-oxidizing bacteria when the use amount of the carvacrol is 5.0-15.0 g per mu, can effectively delay the conversion of ammonium nitrogen into nitrate nitrogen, and has an advantage over a traditional nitrification inhibitor in inhibiting a late nitrification stage.

The invention provides a corn base fertilizer variable fertilization prescription map generation method, system, device and medium, and the method comprises the following steps: obtaining multi-source spatial data of a target field, rasterizing the multi-source spatial data, and generating a plurality of influence factor grid layers corresponding to spatial positions; performing standardization processing on the plurality of influence factor grid layers, and adopting an information entropy-based weighting method to distribute an initial weight for each influence factor; dynamically correcting the initial weight based on the spatial correlation between each grid unit and the neighborhood thereof by using a spatial domain Kalman filtering algorithm, and generating an evaluation grid map; and carrying out space partitioning based on the comprehensive evaluation grid map to obtain a fertility management partition map. According to the technical scheme provided by the invention, accurate distribution of the fertilizer according to needs can be realized.

The invention discloses a field scale soil organic matter spectrum inversion modeling-oriented sample transfer learning method and program product, and the method comprises the steps: carrying out the first-order differential processing of spectrum data in a source domain data set and a target domain data set, environment variables with Spearman correlation coefficients and variance expansion factors higher than threshold values in the source domain data set are eliminated, and target domain samples are divided into a training set and a test set; calculating environment similarity and spectrum similarity between the source domain and the training set samples, further obtaining comprehensive similarity between each source domain sample and each training set sample, and obtaining an intersection of the source domain samples with the comprehensive similarity larger than a threshold value and the source domain samples with the organic matter content within a preset range to serve as a source domain migration sample set; and obtaining a union set of the source domain migration sample set and the training set as an amplification training data set of soil organic matter spectrum inversion learning. The test precision obtained by performing field scale organic matter spectrum inversion based on the amplification training data set formed by the method is higher.

The invention belongs to the technical field of agricultural remote sensing, and relates to a fine field extraction method based on multi-dimensional feature fusion and a semantic guidance watershed. The method comprises the steps of performing multi-dimensional feature extraction, and constructing a feature subset corresponding to each dimension; splicing all the feature subsets in a channel dimension; constructing a double-branch multi-scale convolution module to perform semantic segmentation on the multi-channel feature tensor; taking the plot boundary probability map as an energy topographic map, and generating a constraint mask; extracting instance seed points; generating a mark map, and performing watershed transformation in combination with the energy topographic map and the constraint mask; and superposing to obtain a farmland plot segmentation result. According to the method, multi-channel input is constructed, and the perception and analysis capability of the model is improved; through a double-branch multi-scale convolution module, the instance segmentation precision and robustness of the farmland plot are significantly improved; taking the plot boundary probability graph as an energy topographic map of a watershed algorithm, and finding a unique instance seed for each independent plot; the method can effectively prevent the segmented region from leaking to the background.

This invention discloses a method, apparatus, and device for field extraction based on multi-task deep learning. The method includes: acquiring remote sensing time-series images of the phenological stages of agricultural crops within a region to be identified; inputting the remote sensing time-series images of the phenological stages of agricultural crops within the region to be identified into a trained farmland field extraction framework for prediction, thereby obtaining farmland field identification results; wherein, the farmland field extraction framework is trained based on a remote sensing time-series image training set, which is a dataset within the study area after data preprocessing. This invention solves the problems of poor accuracy and low efficiency in field identification.

Provided is an unmanned radish harvesting system, relating to the field of agricultural artificial intelligence technologies. The system, using an unmanned radish harvesting control subsystem, an unmanned radish harvesting operation subsystem, and a radish agronomic parameter configuration subsystem, allows for intelligent control of the movement of a radish harvester and optimal operation path planning by integrating the shape and terrain of a vegetable field plot and planting agronomic practices. On the basis of various parameter configurations, a computer vision algorithm is employed to accurately identify radish fruits and radish tops. The unmanned radish harvesting system realizes more intelligent, delicate, and accurate operations of the unmanned radish harvester, thereby saving human resources, material resources, and time, and improving the efficiency and quality of unmanned radish harvesting as well as the green and intelligent levels of unmanned radish harvesting.

The invention relates to the field of ecological environment protection, and discloses a field drainage filtration and purification device which comprises an inflow water precipitation bin, a module filtration bin and a water retention purification bin, field drainage enters the inflow water precipitation bin to be mixed, stabilized and precipitated; the water enters the module filtering bin, the water in the module filtering bin is filtered by the module filtering assembly and then enters the water-retaining purifying bin, and after the water-retaining purifying bin is full of water, the water is filtered and settled in a return mode, so that field drainage is further purified, and the blocking risk is reduced. The type of the filtering filler can be adjusted according to the actual filtering working condition, the module filtering assembly fixes the filtering filler through a module filtering frame, the arrangement of different filtering fillers is facilitated by adopting a modular structure, the field drainage filtering and purifying effect is enhanced, and the maintenance convenience of the device is improved. The module filtering bin and the water retention purifying bin are matched with each other, so that a mixed flow state such as plane return flow and vertical up-down flow can be formed, the filtering, precipitation and adsorption effects are enhanced, and favorable conditions are created for inhabitation and reproduction of microorganisms.

The invention relates to the technical field of agricultural sowing equipment, and discloses a single coated seed sowing device and a seed-by-seed sowing method. The device comprises a seed cylinder, a feeding hopper, a sliding block type grain separating mechanism, a seed separating disc mechanism, a discharging hopper, a shell and a circuit module which are sequentially arranged from top to bottom, and the problems that coated seeds are prone to adhesion and blockage and multiple seeds are sown are solved in a targeted mode through the integrated design of filtering and screening, two-time grain separating and automatic control. The method comprises the orderly steps of screening, primary grain separation, secondary grain separation, real-time counting and single grain output. The device is compact in structure, portable, easy to use, high in seeding precision, high in efficiency, capable of counting in real time and suitable for laboratory germination rate detection, field plot tests and other scenes, the labor intensity is effectively reduced, and the small-batch high-precision seeding requirement is met.

The invention provides a method and a device for determining a main field operation direction of an agricultural machine, and the method comprises the steps: fitting a fitting polygonal region of a field plot through employing the mathematical theories of concave points, edges and included angles, and then determining an allowable edge through employing the mathematical theories of edges, slopes and the like on the basis of the fitting polygonal region, thereby planning the main operation direction of the agricultural machine. According to the method, the real field plot area can be restored with high precision, the method can be suitable for various field plots which do not need to be segmented and can be completed in one time in different shapes, the generalization ability is high, it can be ensured that the optimal path is planned, and the operation efficiency is improved.

The invention discloses a tobacco leaf yield and quality evaluation method and system fusing unmanned aerial vehicle multispectral and a WOFOST model. The method comprises the steps of obtaining unmanned aerial vehicle multispectral data of a tobacco leaf growing period; preprocessing the unmanned aerial vehicle multispectral data to obtain canopy characteristic parameters of the tobacco leaves; a WOFOST model is calibrated through the canopy feature parameters of the tobacco leaves, and the calibrated WOFOST model is obtained; inputting meteorological data and field management data of the target field into the calibrated WOFOST model to obtain growth process parameters output by the model; inputting the growth process parameters into a pre-trained mapping model to obtain a tobacco yield and quality evaluation result output by the model; according to the method, the unmanned aerial vehicle multispectral data is combined with the WOFOST model, so that the growth condition and the quality change of the tobacco leaves are comprehensively reflected, the defect that the growth condition of the tobacco leaves is difficult to comprehensively reflect by single remote sensing data is overcome, and the accuracy and the comprehensiveness of tobacco leaf yield and quality evaluation are improved.

The invention relates to the technical field of fertilization, in particular to a precise wheat fertilization method which comprises the following steps: acquiring agricultural production basic data of a target field to adjust a recommended fertilization amount, and generating an initial fertilization scheme containing nutrients; based on the initial fertilization scheme, fertilization is executed in the field planting area, and wheat is planted after fertilization; the method comprises the following steps: before wheat ripening, collecting plants at multiple rows and multiple points in each area, air-drying, and measuring the weight ratio of grains, the weight ratio of straws and the nutrient content of the grains and the straws; calculating the grain yield of wheat harvest in each area; fertilization does not depend on regional experience, an initial fertilization scheme is formulated according to field data, nutrient absorption and soil fertilizer supply amount are accurately measured and calculated in combination with a multi-region contrast test, and chemical fertilizer waste and non-point source pollution are reduced; the fertilizing amount is adjusted through whole-growth-period monitoring, fertility change and weather data, supply and demand imbalance of one-time fertilization is avoided, and finally the wheat yield and the fertilizer utilization rate are effectively increased.

The application relates to the technical field of image processing, and discloses a field water depth determination method and system based on image intelligent identification. The method comprises the following steps: performing multi-period image acquisition and processing on a field plot to obtain pretreatment image data; inputting the pretreatment image data into a two-stage network for matching to obtain water gauge three-dimensional coordinates; performing segmentation based on the water gauge coordinates to obtain scale reading and water surface intersection point data; performing interpolation processing on the reading data and field plot point cloud to obtain a water depth model and performing decision analysis to obtain a heterogeneity distribution map and a diagnosis matrix; and inputting the distribution map and the matrix into a learning framework for optimization processing to obtain an irrigation control parameter set. The application can accurately identify the water gauge scale by using the image intelligent identification technology under complex field environment conditions, realize high-precision automatic determination of the field water depth, organically combine the determination result with the irrigation control decision, form an intelligent closed-loop management system, and thus improve the utilization efficiency of irrigation water resources.

The application discloses a zero-sample field plot segmentation method for complex farmland landscape, and relates to the technical field of remote sensing image intelligent interpretation and agricultural informatization. The method comprises the following steps: acquiring a target region RGB remote sensing image and cutting the image into a preset size image set, segmenting the image set through a SAM method to obtain a ground feature mask and a confidence score, constructing a field plot sample set, dividing the sample set to train an instance segmentation model, and finally applying the trained model to target region field plot segmentation. The application realizes zero-sample field plot segmentation, breaks through the limitations of traditional deep learning sample dependence and poor cross-region migration, supports regional modeling, and balances segmentation accuracy and efficiency, thereby providing a new technical solution for complex terrain region agricultural remote sensing application.

The utility model relates to the technical field of field irrigation, in particular to a movable field irrigation head part, which comprises a frame fixedly provided with an irrigation head part, and is characterized in that the irrigation head part comprises an irrigation mixing tank and a plurality of adding tanks which are fixedly arranged on the upper surface of the frame; conveying pumps are installed on the adding tanks and used for conveying materials in the adding tanks into the irrigation mixing tank, a water inlet pipe is fixedly connected to one side of the irrigation mixing tank, and a main pump is fixedly installed on the other side of the irrigation mixing tank. According to the movable field irrigation head, a worker can hold a handle and push a device body to move on ridges through moving wheels, the distance between the two moving wheels can be conveniently adjusted through work of a double-head motor in an adjusting assembly, and the movable field irrigation head can conveniently adapt to the ridges with different widths and can move in different field parcels; the practicability of the device is improved.

The utility model belongs to the field of agricultural machinery, and particularly relates to a corn ploughing and sowing self-shearing drip irrigation belt all-in-one machine which comprises a rack, and a first fertilization mechanism, a rotary tillage mechanism, a second fertilization mechanism, a drip irrigation belt laying mechanism, a sowing mechanism and a drip irrigation belt pressing mechanism which are sequentially arranged on the rack in the advancing direction of the rack, the drip irrigation tape laying mechanism comprises soil penetrating assemblies and a traction tape cutting assembly. The soil penetrating assemblies are arranged on the rack at intervals in the direction perpendicular to the walking direction of the rack. The traction belt cutting assembly comprises a mounting rod piece, a mounting shell, a belt pulling wheel set, a belt cutting knife and a driving piece, the traction belt cutting assembly is arranged, the situation that the two ends of a drip irrigation belt are buried again manually is avoided when the drip irrigation pipe is dragged through the traction belt cutting assembly, and when the drip irrigation pipe reaches the other end of a field plot, the drip irrigation belt does not need to be cut off manually, so that the labor intensity of workers is reduced. And directly cutting off the drip irrigation tape by using a tape cutter, and then starting the next drip irrigation tape laying operation.