12 results about "Digital agriculture" patented technology

The application provides a water-carbon coordinated scheduling low-carbon ecological circulation agricultural system and method, relates to the field of ecological circulation agriculture, and specifically aims at the range of a target agricultural system, generates a digital agricultural ecological model according to the range of the target agricultural system; collects corresponding ecological parameters in the range of the target agricultural system, and adjusts the digital agricultural ecological model in real time according to the ecological parameters; divides the target agricultural system into multiple subsystems, analyzes carbon sink parameters in each subsystem and the target agricultural system, and obtains a carbon fixation index of the current target agricultural system; sets a carbon sink target, simulates by using the digital agricultural ecological model, analyzes a circulation strategy required for realizing the carbon sink target, and realizes the water-carbon coordinated scheduling agricultural system according to the circulation strategy. The water-carbon coordinated scheduling low-carbon ecological circulation agricultural system and method can realize the cooperation of the maximization of agricultural carbon sink and the efficient use of water resources.

The invention relates to the technical field of ecological monitoring and digital agriculture, in particular to a grassland ecological restoration digital evaluation system and method. The method comprises the following steps: collecting a remote sensing vegetation index sequence and ground quadrat biomass data, and aligning the remote sensing vegetation index sequence and the ground quadrat biomass data according to a unified time index to obtain a synchronous observation sequence; constructing an adaptive calibration relationship between the vegetation index and the ground quadrat biomass based on the synchronous observation sequence; therefore, by constructing a full-link digital process from multi-source data fusion, adaptive calibration, multi-scale dynamic feature extraction to quantitative score generation, the problems that traditional grassland ecological restoration assessment depends on manual interpretation, the static model deviation is large, and the process is non-traceable are solved; the objectivity, the accuracy, the timeliness and the decision support capability of the evaluation result are improved.

A soil nutrient detector for digital agriculture, comprising a workbench (1), characterized in that a water tank (24) is mounted on the top of the workbench (1), a water supply line (26) is connected to a side surface of the water tank (24), a water pump (25) is mounted on the outer surface of the water supply line (26), wherein an end surface of the water supply line (26) is fixedly connected to an annular sprinkler line (27); a passage channel (28) is formed below the annular sprinkler line (27), a mounting bracket (29) is attached to the inner wall surface of which a connecting rod (30) is attached to the outer surface of the mounting bracket (29); a scraper blade (31) is fixedly connected to the outer surface of the connecting rod (30); a cleaning brush (32) is attached to the inner surface of the scraper blade (31).

The application discloses an intelligent digital aquaculture management system and method, and particularly relates to the technical field of digital agriculture management, and is used for solving the problem that the long-term coordination of local dynamic adjustment and overall production plan is insufficient in the existing breeding management, which causes the production process to gradually deviate from the expected target; the breeding production plan, production state data and management operation data are acquired and continuously monitored; the response logic between the management operation and the production state is analyzed to determine the deviation trend; when the deviation occurs, the historical and current causal relationship networks are constructed and compared to identify the change of the key causal relationship; meanwhile, the uniformity change mode of the individual size in the breeding population is analyzed; the specific management adjustment instruction is generated and executed according to the above analysis results; finally, the breeding production plan is dynamically updated according to the instruction execution effect; the closed-loop adaptive management of the breeding process is realized, and the predictability and stability of the production result are ensured.

This invention discloses a method and system for posture estimation and cutting point localization of rhizome medicinal materials, belonging to the field of digital agriculture technology. The method includes: acquiring training data; constructing a YOLO model; training recognition and localization models for each part; inputting the RGB image of the rhizome medicinal material to be identified into the model; preprocessing the image using a multi-frame optimization strategy, obtaining the contour of the largest connected region after denoising, and calculating the centroid; using a geometric constraint strategy, recovering the root-stem transition zone detection box based on the spatial position of the root and stem, obtaining its largest connected region contour, and calculating the centroid; based on the root-stem transition zone and the optimized stem and root detection boxes and centroids, using a root-stem opposite-direction clipping algorithm and weighted least squares fitting iteration to obtain the posture angle of the rhizome medicinal material; finally, locating the cutting point of the rhizome medicinal material based on the posture angle and the structural geometric features of the root-stem transition zone. This invention offers the advantages of accurate, efficient, and rapid posture estimation and cutting point localization of rhizome medicinal materials, enabling automated root-stem separation and processing of rhizome medicinal materials.

The application belongs to the technical field of digital agriculture, and particularly relates to a blockchain traceability data management platform for digital agriculture, wherein the system comprises an agricultural product supply chain informatization module, a trust value quantification module, a two-dimensional code generation module, a local two-dimensional anti-fraud verification module and a traceability query module. The scheme constructs a distributed blockchain ledger network suitable for the agricultural product supply chain, allocates unique on-chain identity and permission to each link participant, generates a basic two-dimensional code bearing core data through a two-dimensional code generation library, triggers a smart contract to calculate a trust value in real time and uploads the trust value to the chain during traceability query, calculates a local hash value by extracting an on-chain identity embedded in a two-dimensional code to be detected, and compares the local hash value with a preset authorization list to complete legality verification, realizes real-time two-dimensional anti-fraud verification of the two-dimensional code without network dependence, can accurately trace and immediately intercept a counterfeit behavior, and provides a full-process anti-counterfeiting and traceable trust guarantee for agricultural product traceability.

The utility model relates to the technical field of agriculture and animal husbandry waste fermentation, in particular to a digital agriculture and animal husbandry waste fermentation device which comprises a fermentation box, the device further comprises lower supporting plates, an upper right side plate, an upper left side plate, a [-shaped supporting frame, an X-shaped supporting frame, a mounting plate, an air cylinder, a mounting frame, a motor and a hook. The two lower supporting plates are symmetrically arranged at the front ends of the left side and the right side of the fermentation box. The air cylinder drives the mounting frame to move towards the classified fermentation boxes, the mounting frame drives the hook to move towards the classified fermentation boxes until the hook is attached to the front sides of the classified fermentation boxes, then the motor drives the hook to rotate until the hook is buckled with the grip, and then the air cylinder drives the mounting frame to move towards the mounting plate. Meanwhile, the classified fermentation boxes are pulled out of the fermentation box through buckling of the hooks and the grips until the classified fermentation boxes are located at the top of the X-shaped supporting frame, finally, the right-angled U-shaped supporting frame is driven by the lead screw to drive the classified fermentation boxes to move downwards to the ground, and the function of taking goods at a fixed point is achieved.

This application relates to the field of computer information processing, and provides a method for constructing a geographic information system (GIS) application system for digital agriculture, and a computer program product. The method includes: integrating a GIS function with a digital agriculture application demand, and dividing a GIS application for digital agriculture into a plurality of components based on an integration relationship; developing the components separately and constructing a digital agricultural GIS application component library; and selecting a component from the digital agricultural GIS application component library for assembling, and building a navigation module and various functional modules for the GIS application system for digital agriculture to complete construction of the GIS application system for digital agriculture. This application can adapt to various different digital agriculture application scenarios and personalized user demands.

The invention discloses an unmanned aerial vehicle DSM-based paddy field positioning model construction method, positioning method and system, and relates to the technical field of agricultural monitoring camera geographic calibration based on unmanned aerial vehicle images. The problems that in the prior art, in high-precision geographical calibration of a fixed PTZ camera of a paddy field, manual control points are depended, the efficiency is low, and an existing unmanned aerial vehicle technology is not applicable, so that a feasible scheme is lacked are solved. The method comprises the following steps: acquiring digital surface model DSM data of a paddy field area through a sensor carried by an unmanned aerial vehicle; three-dimensional morphological characteristics of the paddy field are extracted based on DSM data, and an analysis model special for paddy field identification and boundary positioning is constructed; the invention also provides a construction method of the model, a positioning method based on the model and a system for realizing the positioning method. The method is suitable for precision agriculture and intelligent farm management, and especially suitable for the fields of agricultural machinery automatic operation, farmland informatization, digital agricultural construction and the like.

This invention provides a method, apparatus, medium, and device for discovering time-series causal relationships in digital agricultural information, belonging to the field of agricultural information technology. The apparatus includes: an acquisition module for acquiring a dataset comprising multiple observable time series of digital agricultural information; a decomposition module for expanding the dataset into multiple window representations and decomposing the time-series causal mechanism of the dataset into a summation form with mechanism-invariant and time-invariant modules; a first calculation module for outputting causal numerical transformation relationships through the mechanism-invariant modules; a second calculation module for outputting a window causal graph through the time-invariant modules; and a training module for acquiring the time-series causal relationships of different variables in the digital agricultural information based on the causal numerical transformation relationships and the window causal graph. This invention overcomes the problems of diverse noise and small data volume in digital agricultural information time-series data, and has promising application prospects in agricultural mechanism research.

The invention discloses a bee-keeping intelligent optimization method and system with adaptive bee species and nectar sources, and aims to solve the problems of nectar source information lag, blindness in bee species selection, low efficiency in transition decision, extensive bee colony management and the like in traditional bee-keeping. According to the method, a honey source space-time database is constructed through fusion of remote sensing and ground survey, and the honey secretion peak period is predicted in combination with meteorological and phenological models; establishing a bee species characteristic knowledge base covering dimensions such as collection radius, flowering phase adaptability, nectar source preference and the like; a bee species-nectar source adaptation degree evaluation model is constructed based on machine learning, and multi-target intelligent recommendation is achieved; the integrated Internet of Things sensor monitors the swarm state in real time, and dynamically optimizes a transition path and a time window; and services such as a nectar source map, yield prediction and abnormity early warning are provided through a user visual platform. The system forms a'sensing-analysis-decision-execution-feedback 'closed loop, so that bee colony loss is reduced, invalid transition is reduced, and ecological sustainable bee keeping is promoted. The method is suitable for smart bee industry, digital agriculture and rural revitalizing application scenes.

This invention provides a grassland carbon sink management decision support system based on a multi-factor weighted regression model, belonging to the field of digital agriculture and ecological information decision technology. The system comprises: a multi-source data integration and processing module that standardizes multi-source data; a multi-factor weighted regression model engine module that employs the multi-factor weighted regression model algorithm; a carbon sink accounting and dynamic assessment module that translates the output of the MWRM model engine module into business language; a scenario simulation and decision support module that provides carbon sink hotspot identification and protection priority delineation, grazing pressure optimization analysis, and pre-assessment of management measure benefits, capable of directly generating quantitatively assessable grazing ban plans, rotational grazing schemes, and engineering layout suggestions based on spatial heterogeneity; and a visualization and interactive output module that provides a graphical interface on a web or desktop to present the results of all the above modules. This invention establishes an automated and intelligent decision support system integrating high-precision accounting, scenario simulation, and spatial planning.