268 results about "Tea garden" patented technology

The invention discloses a smart tea garden resource dynamic scheduling system and method integrated with environment monitoring, and the method comprises the following steps: S1, collecting environment and operation data, processing the environment and operation data, and generating a standardized data set; s2, carrying out discrete modeling and environment field generation, carrying out topological analysis on humidity and pest and disease damage intensity, judging abnormity and triggering local scheduling; s3, generating a task, resource and environment set, constructing a task-resource-environment hypergraph, establishing a time expansion graph and forming constraints; s4, dynamic game solving is introduced, and a scheduling scheme and a control instruction are generated; s5, issuing an instruction to an execution end, collecting an execution state and environment data, and forming a feedback data set; and S6, constructing a double-layer memory scheduling unit, and generating a parameter set of a next period. According to the invention, precise allocation and efficient management and control of tea garden resources are realized by fusing environmental monitoring and dynamic scheduling, so that the production efficiency is improved and ecological sustainability is guaranteed.

The invention relates to the technical field of tea garden fertilization, in particular to a soil loosening, ditching, fertilizing and soil covering all-in-one machine for tea garden land, which comprises a vehicle body, a handrail part fixedly connected to the top of the rear end of the vehicle body in the moving direction, and a controller; the top of the vehicle body is fixedly connected with a fertilizer box; a fertilizing pipe is fixedly connected to the bottom of the vehicle body and communicated with the bottom of the fertilizer box, an electromagnetic valve is communicated in the fertilizing pipe, and the controller is used for controlling operation of the electromagnetic valve; a soil loosening assembly for loosening soil, an adjusting assembly for adjusting the soil loosening depth of the soil loosening assembly and a ditching assembly for ditching the soil after soil loosening are arranged on the fertilization pipe; a V-shaped bracket is fixedly connected to the side wall of the fertilizing pipe, and a soil covering assembly for performing soil covering operation on the furrowed soil is arranged on the bracket. The soil loosening device can adjust the soil loosening operation depth through the adjusting assembly.

The invention relates to the technical field of selenium-rich white tea production, and discloses an intelligent control system and method for automatic production of selenium-rich white tea. The system comprises a selenium-rich white tea growth environment regulation and control module, a tea growth stage recognition module, a selenium content self-adaptive supply module, a production equipment cooperative control module and a quality closed-loop feedback module. The growth environment regulation and control module collects tea garden multi-region environment parameters and establishes a dynamic monitoring set; the growth stage identification module divides growth stage identifiers in combination with the environment parameters, the bud and leaf morphological image sequence and the growth cycle time sequence data; the selenium content self-adaptive supply module generates a supply scheme and an equipment control instruction set according to the growth stage identifier and the soil selenium content data; the production equipment cooperative control module is linked with related equipment to execute a cooperative operation time sequence control process; and the quality closed-loop feedback module generates a correction amount according to the finished product detection data, and feeds the correction amount back to the growth environment regulation and control module for parameter iterative updating.

The invention relates to a tea-picking robot autonomous navigation method based on tea ridge composite boundary identification and driving area adjustment, and belongs to the technical field of robot navigation. The method comprises the steps that tea ridge growth state information is evaluated, and a global path planning strategy is made; a root-ground intersection ground navigation datum line and lateral boundary constraints are established, the ground navigation datum line, the lateral boundary constraints and tea tree growth density and distribution characteristics are integrated, a tea ridge three-dimensional drivable road network model is established, and key geometric characteristics of the model are analyzed to establish an adaptive risk assessment system. Dividing the drivable area into areas with different risk levels; and establishing a multi-objective optimization function in combination with the risk region distribution diagram, fusing the multi-objective optimization function through an exponential weighted fusion mechanism, and generating an optimal navigation path under the risk gradient constraint. Guiding of intelligent navigation of the tea garden is achieved, the tea leaf picking efficiency and quality are improved, and technical support is provided for mechanical and intelligent picking of the tea garden.

The invention discloses a tea bud screening method based on multi-modal information fusion, which is characterized in that on the basis of multi-modal data acquisition, feature information of different modal data is integrated and analyzed through a mode of feature level fusion and decision level fusion by using a mode recognition technology, and an accurate tea bud recognition model is constructed. Finally, in combination with an automatic control technology, screening execution mechanisms such as a mechanical arm are controlled, and automatic screening and picking of the tea buds are achieved. The technology is mainly applied to the tea production process of a modern tea garden, and aims to solve the problems that traditional manual screening is low in efficiency and high in cost, and single machine vision screening is insufficient in accuracy. And an efficient and reliable technical solution is provided for large-scale and automatic production of high-quality tea leaves.

The present application relates to a kind of methods for mass propagation of tea corner miridae in laboratory, comprising the following technical steps: collecting tea garden tea corner miridae adult, cultivating fall kui seedling, putting seedling and leading insect, tea corner miridae habitat and feeding, mating and oviposition and nymph hatching and feeding.The present application uses fall kui seedling as the main body of feeding raw material, and the leaf of raw material is relatively thick, strong in harm resistance, not easy to dry, which helps to improve the hatching rate of tea corner miridae eggs, reduce the frequency of raw material supply and replacement, at the same time, the present application saves time and effort, can be realized in laboratory low cost and sustainability fast, efficient, mass propagation of tea corner miridae test insect source.

The invention relates to the technical field of intelligent tea garden management, and provides an intelligent tea garden service collaborative management system, which comprises a tourist picking reservation module used for receiving a reservation picking request of a tourist through a terminal and intelligently arranging autonomous picking time and region of the tourist; the picking behavior processing module is used for analyzing, processing and prompting picking behaviors of tourists; and the comprehensive management docking module is used for integrating all module data, generating a multi-dimensional report to be docked with the tea garden enterprise ERP system, generating a collaborative scheme of management personnel, planting personnel and customer service personnel, and completing collaborative management of data integration-role adaptation-decision landing. A full-chain tea garden management system from data acquisition and integration, growth and variety analysis to visual decision making is constructed, comprehensive improvement of yield increase, quality improvement, cost reduction and efficiency improvement of the tea garden is achieved by means of multi-source data fusion and intelligent technologies, economic benefits are enhanced, and the resource utilization efficiency and ecological sustainability are improved.

The invention provides a tea garden drought prediction method and system fusing LightGBM and LSVM in the technical field of smart agriculture. The method comprises the steps of S1, collecting a large amount of historical monitoring data to construct a data set; s2, the data set is analyzed through a Limma algorithm, a COX survival regression model, a GLM generalized linear model and an SHAP, and an environment factor correlation graph is obtained; s3, creating a tea garden drought prediction model; s4, dividing the data set into a training set, a verification set and a test set to train, verify and test the tea garden drought prediction model, and deploying the tea garden drought prediction model passing the test; and S5, collecting real-time monitoring data from the tea garden, inputting the data into the tea garden drought prediction model to obtain a tea garden drought prediction result, and displaying the tea garden drought prediction result on a visual interface. The tea garden drought prediction method has the advantages that the timeliness, accuracy and generalization ability of tea garden drought prediction are greatly improved.

The invention relates to the field of agricultural machinery, in particular to multifunctional tea garden weeding, soil loosening and fertilizing integrated mechanical equipment which comprises a mounting frame, a driving module is mounted at the bottom of the mounting frame, a weeding module, a soil loosening module and a fertilizing module are mounted at the top of the mounting frame, and the weeding module comprises a power part which is fixedly connected with the top of the mounting frame; an output shaft of the power part is connected with a roller, the outer side wall of the roller is fixedly connected with a plurality of wave-shaped blades, the soil loosening module is installed in the roller, and an opening is formed in the side wall of the roller and used for loosening tea garden soil based on the centrifugal force effect; the driving module is in signal connection with a controller, the controller is in signal connection with the power piece and the fertilization module, and the controller is used for adjusting the power of the driving module and the rotating speed and the output power of the power piece according to preset terrain information. The method is used for improving the efficiency of weeding, soil loosening and fertilizing operation of the tea garden and enhancing the collaboration of all operation links.

The application provides a tea garden identification method and device based on satellite images, which comprises the following steps: determining a evergreen vegetation area of a to-be-identified area based on Sentinel-2 image data and Landsat image data of the to-be-identified area; and identifying a tea garden area from the evergreen vegetation area through a decision tree model; wherein the decision tree model is constructed based on the following features and the classification threshold values corresponding to the features: a tea leaf phenology feature index, a terrain feature, and a spectral index determined by a separability index, wherein the SI is used to reflect the spectral reflectance separability of the tea garden and other evergreen vegetation; wherein the tea leaf phenology feature index is determined by an enhanced vegetation index in month N and a land surface water index in month M; the SI between the enhanced vegetation index in month N and the land surface water index in month M is the largest compared with the SI between the EVI in any other month and the LSWI in any other month, and N and M are integers greater than 0 and less than 13.

The invention belongs to the technical field of carbon sink evaluation, and discloses a typical weather-oriented tea garden carbon sink dynamic profit and loss evaluation method and system. Historical meteorological information and historical carbon sink monitoring information of the tea garden are collected, and a typical weather type library of the tea garden is constructed; determining a typical weather type corresponding to the current day of the tea garden, and calculating a carbon sink fixed amount and a carbon sink output amount of the tea garden; generating a correction factor for correction according to the management activity information of the tea garden to obtain a net carbon sink value; generating a total score based on comprehensive analysis of the net carbon sink value, and evaluating the carbon sink profit and loss condition of the tea garden; the carbon sink meteorological influence parameters before and after the monitoring time point are collected for comprehensive analysis to calculate the carbon sink fixed quantity and the carbon sink output quantity, calculation deviation caused by parameter fluctuation at a single time point can be avoided, and therefore the method better fits the continuous physiological process of photosynthesis / respiration of the tea trees, and the detection accuracy is improved. And the calculation result of the carbon sink fixed quantity / output quantity is closer to the actual condition.

The invention provides a multi-mode remote sensing tea garden automatic identification method and system integrating phenolic indexes and phenological characteristics. According to the method, the growth amplitude GA reflecting tea phenological characteristics is calculated through medium-resolution time sequence radar data, and the normalized vegetation index NDVI, the phenolic compound index PCI and the phenol high-value dominant index PHD are calculated from optical remote sensing images so as to represent the growth condition of the tea tree and the change rule of the phenol content. A double-branch lightweight deep learning model is constructed, a first branch processes a high-resolution remote sensing image, and a second branch processes multi-modal tea garden remote sensing features; and then multi-modal geoscience knowledge of the tea garden is fully extracted and fused through a double-branch fusion module, refined and automatic extraction of large-area tea garden distribution is realized, and key technical support is provided for tea garden resource monitoring, management and the like.

The invention discloses a tea garden soil moisture physical simulation and data driving fusion prediction method and device, and relates to the field of soil moisture prediction.The method comprises the steps that based on soil basic attributes and multi-depth soil moisture time sequence observation data, a soil moisture physical baseline sequence is obtained in combination with boundary conditions and initial conditions; respectively extracting data of a target soil layer in a preset time window from the soil water content physical baseline sequence, the multi-source driving data and the multi-depth soil water content time sequence observation data so as to splice the data into an input feature set; obtaining a water content prediction value of the target soil layer on the prediction day based on the input feature set and a preset soil water content prediction model; according to the method, the HYDRUS-1D simulation result is taken as a baseline, the time sequence dependence of soil moisture, especially the lag response of different soil layers, is effectively learned, and the modeling capability of a complex nonlinear relationship is improved.

The invention, which relates to the technical field of the tea garden safety monitoring system, discloses a smart tea garden safety monitoring system based on the Internet of Things technology, comprising a sensing layer, a network transmission layer, a platform layer and an application layer. The system constructs a space-air-ground integrated stereoscopic perception network through the environment monitor, the unmanned aerial vehicle cluster and the ground inspection robot, realizes comprehensive acquisition of tea garden multi-source data, introduces a digital twinborn technology, constructs a virtual model synchronized with a physical tea garden in real time, and combines a multi-target game algorithm and a reinforcement learning mechanism to realize comprehensive acquisition of tea garden multi-source data. Meanwhile, the environment monitoring instrument adopts a liftable stand column design and is provided with multiple automatic reinforcing devices, and through linkage mechanisms such as a spring clamping ring, a telescopic supporting rod and a side inserting structure, the stability and the anti-overturning capacity of equipment in a complex environment are remarkably improved; and the safety and the reliability of data acquisition are effectively ensured.

The invention discloses a smart tea garden block chain traceability system and method, and the method comprises the following steps: carrying out the standardization processing and aggregation of data of each link, and generating an event set identifier; performing compact commitment on the event set by adopting an RSA accumulator to generate a staged commitment value; introducing a BLS threshold signature mechanism, and performing joint signature on the event set by a plurality of trusted nodes to generate an aggregation signature; binding and writing the commitment value and the aggregation signature into a block chain; in traceability query, the existence of events is verified through an RSA accumulator, and node consensus is verified through a BLS threshold signature, so that a safe, transparent and verifiable traceability system is constructed. The system covers the whole process information management of tea from planting, processing, storage, transportation to sales.

The invention discloses a tea garden ecosystem health evaluation method and system based on landscape multifunctionality. The method belongs to the technical field of tea garden management and ecological environment evaluation, and comprises the following steps: determining tea garden ecological system health evaluation indexes in four aspects based on an'vitality-organization power-restoring power 'framework and in combination with an ecological system service theory; a three-layer hierarchical structure model is constructed through an analytic hierarchy process, index weights are calculated in combination with an entropy weight method, feature importance sorting is performed on indexes by adopting a random forest algorithm, and an evaluation index system is constructed; carrying out dimension reduction processing on the indexes by utilizing a principal component analysis method and calculating weights; and based on the evaluation index and the weight after dimension reduction processing, calculating a comprehensive health score of the tea garden ecosystem by adopting a weighted summation method, and performing grading. By integrating various theories and methods, the health condition of the tea garden ecosystem is evaluated comprehensively and objectively, a scientific basis is provided for management and protection of the tea garden, and sustainable development of the tea garden ecosystem is promoted.

The invention relates to the technical field of tea intelligent consultation, and discloses a tea expert remote consultation method based on artificial intelligence. The method comprises the following steps: processing growth environment data through a tea tree physiological status dynamic analysis module to generate a tea tree physiological status feature vector; historical agronomic operation nodes are extracted based on management records, and the physiological state feature vectors are associated to construct a tea tree response mode knowledge base; triggering a consultation request according to tea tree phenotypic data collected in real time, and integrating the physiological status feature vector and the response mode knowledge base through a cross-dimension feature fusion engine to generate a multi-factor association decision tree; performing iterative adjustment on the node weight of the decision tree by adopting a self-adaptive decision optimization module, and outputting a tea tree growth abnormality diagnosis result and an agricultural intervention scheme; and transmitting the scheme to terminal equipment through a remote consultation interface, and updating an operation validity mark of the response mode knowledge base. The method realizes remote precise consultation of tea planting and assists scientific management of a tea garden.

The invention discloses a tea garden cultivation intelligent management method and system based on a block chain, and relates to the technical field of intelligent agriculture, and the system distributes a unique Ta-Chain ID for each tea tree through a block chain data storage module, guarantees the non-tampering and traceability of tea production, and verifies the data integrity and non-tampering. The environment and tea tree data are collected in real time through the Internet of Things sensing module, and the processed information is uploaded to the block chain. And the intelligent contract module triggers farming tasks based on the data, such as intelligent irrigation, fertilization and pest control. And through the intelligent market analysis module, tea leaf demands are predicted through an AI model, and a production strategy is optimized. Through combination of an information service platform and a cross-chain technology, tea garden data sharing is promoted, whole-course tracing of tea leaves is provided through a block chain + NFT technology, and market transparency and consumer trust are enhanced.

The invention provides a tea garden drought grading prediction method and system based on machine learning in the technical field of smart agriculture. The method comprises the steps of S1, collecting a large amount of historical monitoring data from a tea garden; s2, preprocessing each historical monitoring data and then constructing a data set; s3, analyzing the data set through an L-imma algorithm, a COX survival regression model and a GLM generalized linear model to obtain an environmental factor correlation graph; s4, creating a tea garden drought prediction model based on the multi-modal feature extraction layer, the feature fusion layer, the soil entropy prediction layer and the drought mapping output layer; s5, training the tea garden drought prediction model through the data set, and deploying the trained tea garden drought prediction model; and S6, predicting the drought of the tea garden through the deployed tea garden drought prediction model. The method has the advantages that the accuracy of tea garden drought prediction and the refinement degree of irrigation decision are greatly improved.

This invention discloses the application of organic household waste biochar in tea garden soil improvement and tea quality enhancement, belonging to the field of soil improvement technology. This application uses organic household waste as raw material, and the biochar prepared through pretreatment, oxygen-limited carbonization, and product collection is applied to tea garden soil to achieve soil improvement and / or tea quality enhancement. During the biochar preparation process, the target temperature for the oxygen-limited carbonization stage is 300℃~500℃, the heating rate is 7~9℃ / min, and the holding time is no less than 60 hours. The biochar is applied by trenching and fertilizing between tea rows followed by landfilling, with an application rate of 0.8~1.2kg / m², which is particularly suitable for tea garden soil. This invention overcomes the limitations of a single resource utilization path for organic household waste and poor adaptability of materials for tea garden soil improvement, achieving synergistic effects of solid waste resource utilization and tea garden quality enhancement. The technology is simple, low-cost, suitable for large-scale promotion, and has both environmental and agricultural application value.

The utility model relates to the technical field of soil humidity measuring instruments, and discloses a portable tea garden soil humidity measuring instrument which comprises a machine body, the top of the machine body is fixedly connected with a connecting pipe, the other end of the connecting pipe is fixedly connected with a connecting round rod, and the bottom of the connecting round rod is fixedly connected with a telescopic rod. A connecting square plate is fixedly connected to the middle of the left side of the connecting round rod, a threaded rod is connected to the middle of the connecting square plate in a threaded mode, the bottom of the threaded rod is rotationally connected with the bottom of the telescopic rod through a connecting short rod, and a recycling mechanism is installed on the right side of the connecting round rod and used for recycling the telescopic rod. According to the utility model, firstly, the connecting round rod is mounted to soil and is supported by the connecting straight plate, the rotating round plate is rotated to enable the threaded rod to descend and drive the telescopic rod to move downwards to a required position, and after the rotating round plate arrives, data is displayed on the machine body through the connecting pipe, so that the required position can be measured.

The utility model discloses a novel tea garden ditching deep fertilizer applicator which comprises a vehicle body, a lifting system, a ditching system, a first driving system, a second driving system, a third driving system and a fertilizer applying system, the vehicle body comprises a mounting platform and crawler-type chassis, and the front end and the rear end of the bottom of the mounting platform are each provided with a crawler-type chassis; the first driving system is arranged at the upper end of the mounting platform and used for driving the vehicle body to walk, the second driving system is arranged at the lower end of the mounting platform and used for driving the lifting system to ascend and descend, one end of the lifting system is fixed to the two ends of the left side of the mounting platform, and the other end of the lifting system is connected with one end of the ditching system; the ditching system is used for providing power for the ditching system, and the other end of the ditching system is connected with the fertilizing system which is located at the left upper end of the ditching system; the furrow opener has the advantages that furrow opening and fertilization can be continuously carried out, the furrow opening effect is stable, the furrow opening depth can be adjusted, and the furrow depth and the furrow width can meet agricultural requirements.

The invention discloses a retreating type electric tea garden ditching device, and relates to the field of tea garden operation, the retreating type electric tea garden ditching device comprises a main frame, the front part of the main frame is fixedly connected with a traction head, the bottom of the main frame close to the front part is symmetrically and fixedly connected with two universal wheels, the bottom of the main frame close to the rear part is rotatably connected with a main shaft, and the two ends of the main shaft are fixedly connected with walking wheels; a plough share is arranged at the bottom of the main frame, and a lifting storage structure is arranged in the main frame in a penetrating mode. By arranging the lifting storage structure, automatic lifting and storage of the plough share after ditching operation are achieved, the structure converts walking power into vertical lifting of the sliding frame through transmission of the main shaft driven by the walking wheels and meshing of a belt, a bevel gear, a first gear and a toothed plate, and therefore the plough share is stored in the main frame; dragging and damage of the plough share in a non-working state are effectively avoided, and convenience and safety of equipment transfer are improved.

This invention relates to the field of sightseeing tea garden landscape technology, specifically a structure for creating a sightseeing tea garden landscape. The structure includes tea trees, planting areas, partitions and guide plates, roads, auxiliary sightseeing and maintenance units, and partition walls. The planting areas are evenly and symmetrically distributed, roads are located between the planting areas, and partitions and guide plates are located at the edges of the planting areas. The tea trees are evenly distributed within the planting areas, and the partition walls are located around the perimeter of the planting areas. The auxiliary sightseeing and maintenance units are located on the planting areas. This invention, by setting auxiliary sightseeing and maintenance units in each planting area, utilizes the viewing section within these units to achieve automatic detection and irrigation of the tea trees, as well as to provide different colors of light, making the tea garden visually appealing. Furthermore, the viewing section can automatically move back and forth, causing the light to oscillate, greatly enhancing the visual appeal.

The utility model relates to the technical field of tea tree planting, and discloses a water-fertilizer mixing tank for tea garden planting, which comprises a mixing tank and a base, a support seat is mounted on the upper surface of a cover plate, a motor is mounted on the upper surface of the support seat, a connecting shaft is mounted at the output end of the motor through a coupler, and one end of the connecting shaft extends into the mixing tank. A water inlet pipe is arranged on the outer surface of the mixing tank, a feeding assembly, a pretreatment assembly and a scattering assembly are arranged on the outer surface of the connecting shaft, the scattering assembly comprises a connecting piece, a connecting disc is arranged on the lower surface of the connecting piece, a plurality of first scattering teeth are arranged on the outer surface of the connecting disc, and every two adjacent first scattering teeth are staggered in opposite directions. According to the fertilizer mixing device, agglomerated fertilizer can be scattered through the arranged scattering assembly, so that the fertilizer can be fully mixed with water, meanwhile, the fertilizer adsorbed on the inner wall of the mixing tank can be scraped through the arranged scraping plate, the fertilizer is prevented from being adsorbed on the inner wall of the mixing tank, and a good cleaning effect is achieved.

The utility model relates to the technical field of green tea gardens, and discloses a green tea garden fixed-distance lamp panel insect expelling device which comprises an installation plate. The positioning part is arranged on one side of the mounting plate; the adjusting part is arranged on one side of the positioning part; the positioning part comprises fixing seats fixedly connected to one side of the mounting plate, and the fixing seats are symmetrically arranged; and the fixed rail is fixedly connected to one side of the mounting plate. A sliding block is held by hand, a clamping ring is inserted into an adaptive opening, then the clamping ring extrudes a U-shaped clamping block, so that the U-shaped clamping block slides downwards along the track of the adaptive opening, after one side of the clamping ring abuts against a limiting block, the U-shaped clamping block bounces upwards under the action of a first spring, and therefore the U-shaped clamping block and the clamping ring are connected in a clamped mode; on the contrary, the fixing frame is pressed to drive the U-shaped clamping block to slide downwards, and therefore the effect of rapidly releasing the fixed connection between the sliding block and the first telescopic scale column is achieved.

The invention relates to a tea tree nitrogen nutrition diagnosis method based on unmanned aerial vehicle multi-source remote sensing. The method comprises the following steps: S1, setting a gradient nitrogen application experiment; s2, collecting tea tree shoot samples, and measuring biomass and nitrogen content data of overground parts; collecting and preprocessing tea tree canopy remote sensing data; s3, constructing a critical nitrogen dilution curve, and calculating to obtain a nitrogen nutrition index NNI; s4, constructing a multi-source fusion feature set; s5, performing feature optimization selection on the multi-source remote sensing fusion feature set; s6, taking the optimal subset in S5 as input, taking the NNI in S3 as output, training an NNI estimation model by utilizing a machine learning algorithm, and selecting and determining an optimal estimation model through model precision; s7, performing inversion and spatial mapping on the tea garden NNI, and performing nitrogen nutrition status diagnosis according to the NNI value; and S8, topdressing the nitrogen fertilizer in a flat cabinet for the diagnosed nitrogen-deficient area. The method can realize large-area, lossless and rapid diagnosis of the nitrogen condition of the tea garden, guide variable fertilization, save fertilizer and increase yield, and has remarkable environmental protection benefits.

The invention discloses a rolling drilling type tea garden deep ploughing fertilizer applicator which comprises a machine table, an adjusting mechanism is arranged on one side of the lower portion of the machine table, a deep ploughing soil breaking mechanism is arranged on one side of the adjusting mechanism and comprises a power box and a rolling-in drill bit, and the rolling-in drill bit is fixedly installed on one side of the power box. A fertilizer spreading mechanism is arranged below the deep ploughing ground breaking mechanism, the fertilizer spreading mechanism comprises a soil shoveling plate, a fertilizer spreading pipe and a telescopic pipe, the soil shoveling plate is fixedly installed below the power box, the fertilizer spreading pipe is fixedly installed in the soil shoveling plate, and the telescopic pipe is fixedly installed on one side of the fertilizer spreading pipe. The deep ploughing and soil breaking capacity is achieved, practicability is improved, and therefore the problems that when a tea garden is fertilized, fertilizer cannot be directly spread to the deep position of soil, and consequently the fertilizer is exposed outside, is prone to being washed away by rainwater and is difficult to be fully absorbed and utilized by tea tree roots are solved.

The invention discloses a tea garden identification method and system based on an unmanned aerial vehicle image. The method comprises the steps that an improved UNet model is adopted as a segmentation network, and the improved UNet model comprises a visual Transform module and a cavity convolution module in an encoder: A, the visual Transform module is utilized to segment an input image into patch sequences, and global semantic dependency features are established through a multi-head self-attention mechanism; b, extracting multi-scale local features by using the cavity convolution module and adopting a multi-stage expansion rate combination; and C, the decoder fuses the global semantic dependency features and the multi-scale local features output by the encoder through jump connection to generate a tea garden segmentation result.

1. Name of the product in this design: Tea Garden Management Machine (Tea Garden Operation Power Platform). 2. Application of this design: This design is intended for use in tea garden cultivation, tea garden management, tea picking and other production operations. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model. 5. The design for which protection is sought includes color. 6. The bottom surface of this product is a part that is not easily seen or cannot be seen during use, so the bottom view is omitted.