171 results about "Tea garden" patented technology

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 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 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.

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 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 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 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.

This utility model discloses a device for suppressing weeds in tea gardens, including tea tree planting strips, shading strips, and a set of symmetrically arranged shading components. The shading strips are arranged between the tea tree planting strips, forming strip-shaped areas that are parallel to and alternate with the tea tree planting strips. The shading components include a support frame and a holding frame. The bottom of the support frame is fixed in the soil by anchor rods, and the top of the support frame is connected to the holding frame by hinges. The top surface of the holding frame is covered with a shading net. This utility model uses shading components to cover the weed growth area, thereby controlling light and blocking the photosynthesis of weeds to suppress weed growth. At the same time, the shading strips are used to further suppress weeds. The structural configuration of the shading strips suppresses the growth of weeds in the area below and adjacent to them by physically blocking light.

The utility model discloses an unmanned aerial vehicle take-off and landing platform and tea garden equipment. The unmanned aerial vehicle take-off and landing platform comprises a main body and a storage mechanism used for storing an unmanned aerial vehicle. Wherein the main body is composed of a group of bottom plates and four groups of side plates, the bottom plates are used for taking off and landing of the unmanned aerial vehicle, and the side plates surround the unmanned aerial vehicle on the bottom plates; the storage mechanism comprises four sets of top covers and four sets of electric push rods, the four sets of top covers are arranged at the upper ends of the four sets of top plates correspondingly, and the four sets of electric push rods are used for driving the four sets of top covers to turn over correspondingly. The device is simple in structure and convenient to use, through cooperation of the main body and the storage mechanism, the unmanned aerial vehicle can be stored in situ after the unmanned aerial vehicle lands, the unmanned aerial vehicle is effectively prevented from being accidentally damaged from the outside, only the top cover needs to be opened during subsequent use, and the convenience and the use efficiency of the unmanned aerial vehicle in tea garden planting are improved.

This application discloses a method, apparatus, equipment, and storage medium for tea garden identification based on multi-temporal remote sensing imagery, relating to the field of agricultural remote sensing technology. The method includes the following steps: determining the phenological stage and agricultural operation period of tea; collecting multi-temporal remote sensing image data corresponding to the area to be identified; calculating the normalized vegetation index (NVI) and a pre-constructed normalized target crop difference index (NCR) based on the remote sensing image data, and obtaining their altitude values ​​and spectral feature values ​​for each band; calculating the weights of the NVI, NCR, altitude features, and spectral features based on the obtained feature values; and classifying the area according to the weight of each feature value to obtain the identification result of the area to be identified. This application fully considers the growth period of tea and the time characteristics of important agricultural operations, and constructs new feature indices based on the remote sensing spectral characteristics of the tea garden during this time period. Combined with a classification algorithm, it can accurately identify tea garden information.

The water-saving irrigation device for the tea garden relates to the technical field of tea garden planting and comprises a water collecting tank, the top of the water collecting tank is of an opening structure, and a liquid collecting tray is arranged at the opening and used for collecting rainwater; a support frame is arranged outside the water collecting tank; a drainage pipe is arranged at the bottom of the water collecting tank, a flow dividing pipe is arranged at the tail end of the drainage pipe and provided with a plurality of irrigation pipes, and electromagnetic valves are arranged on the irrigation pipes. A middle bin is arranged on the drainage pipe and is hollow, an opening is formed in the top of the middle bin, and a filtering assembly is detachably arranged at the opening. By means of the arrangement, the water-saving irrigation device for the tea garden solves the problems of water resource waste and uneven irrigation in an existing irrigation mode through natural rainfall, and the irrigation effect of tea trees is improved.

The invention relates to the technical field of carbon sink prediction management, and discloses an LCA-based tea garden full-flow carbon metering system, which comprises the following steps: analyzing a tea garden into ladder surfaces, ladder walls and inter-row landform units, and constructing a runoff transportation network; calculating chemical activity parameters representing residual polyphenol release potential and mineral interface reaction sensitivity parameters representing interaction of organic carbon and iron; the primary soil carbon mineralization is checked based on the positive excitation effect in the vertical dimension, and the lateral organic mineral leaching flux which is driven by a ligand dissolution promoting mechanism and has a nonlinear amplification attribute is quantified in the lateral dimension; and generating a management optimization scheme for avoiding the lateral leaching risk. According to the method, the problem of carbon footprint accounting distortion caused by neglecting a tea garden microtopography hydrological process and a soil chemical mechanism in the prior art is solved, and accurate prediction and low-carbon management of carbon emission in a complex mountain tea garden scene are realized.

This invention relates to the field of artificial intelligence technology, specifically a method and apparatus for digital in-situ yield estimation of Yinghong No. 9 tea gardens. The method includes: matching the correspondence of tea shoots between images of various tea gardens to obtain matching relationships; calculating the viewpoint-position relationship of each tea garden image based on the matching relationships to obtain a set of viewpoint-position relationships; performing modeling and reconstruction operations on a set of shoot objects based on the set of viewpoint-position relationships to obtain a set of shoot object models; obtaining key information sequences for each shoot object model in the set of shoot object models to obtain a set of key information sequences; and calculating the weight composition sequence of each shoot object model based on a yield conversion empirical model and the set of key information sequences to obtain a set of weight composition sequences and perform tea yield estimation operations to obtain the estimated tea yield. This invention can improve the accuracy and efficiency of tea yield estimation.

The invention discloses a tea garden identification method and system based on multi-source remote sensing data. The method comprises the following steps: S1, obtaining time sequence radar data and optical remote sensing data of a target area; s2, extracting key growth periods of the tea garden based on radar data, wherein the key growth periods comprise a growth season starting period and a growth season ending period; s3, calculating a vegetation index VI and a water body index WI by using the optical data, and screening a combination of the VI and the WI with the optimal distinction degree through a time-weighted dynamic time warping method; s4, determining a tea garden identification index according to the following method: omega1 is linear operation, omega2 is nonlinear operation, T represents a tea garden sample, G represents an evergreen vegetation sample, and DTW is a dynamic time warping method; and S5, realizing tea garden identification based on the tea garden identification index and the integrated learning model.

The utility model relates to the field of measuring rulers, and discloses a handheld tea bud length measuring instrument which comprises a ruler body. The fixed measuring claw is mounted at one end of the scale body; the sliding measurement assembly comprises a sliding block which is arranged on the outer wall of the scale body in a sliding and sleeving manner; the movable measuring claw is arranged at one end of the side wall of one side, close to the fixed measuring claw, of the sliding block, and is symmetrically distributed with the fixed measuring claw; the tea garden field operation is adapted through the handheld design, single measurement can be completed only through the three steps of sliding block pushing, rotating locking and reading, the consumed time does not exceed 5 seconds, compared with a traditional ruler, the measurement efficiency is improved by more than three times, the rotation angle is limited through cooperation of a three-quarter arc-shaped groove and an arc-shaped rotating plate, and the measurement accuracy is improved. Misoperation is avoided, the learning cost is reduced, accurate positioning of tea buds is achieved through the symmetrically-arranged measuring claws, and rolling or deformation of the tea buds is avoided; the meshing structure of the gear and the toothed plate ensures that the sliding block moves stably and does not deviate.

The application belongs to the technical field of carbon sink evaluation, and discloses a tea garden carbon sink dynamic profit and loss evaluation method and system facing typical weather; historical meteorological information and historical carbon sink monitoring information of the tea garden are collected to construct a typical weather type library of the tea garden; a corresponding typical weather type of the tea garden on the day is determined, and carbon sink fixation and carbon sink output of the tea garden are calculated; a correction factor is generated according to management activity information of the tea garden to perform correction, and a net carbon sink value is obtained; a total score is generated based on comprehensive analysis of the net carbon sink value, and the carbon sink profit and loss of the tea garden is evaluated; carbon sink fixation and carbon sink output are calculated by collecting and comprehensively analyzing carbon sink meteorological influence parameters before and after a monitoring time point, so that calculation deviation caused by single time point parameter fluctuation can be avoided, the calculation result of carbon sink fixation / output is closer to the actual situation by being more in line with the continuous physiological process of tea tree photosynthesis / respiration.

The application discloses a kind of lightweight multi-modal tea garden picking robot control systems, and the application relates to robot control system technical field.The lightweight multi-modal tea garden picking robot control system, including parameter loading module, tea leaf identification judging unit, tea leaf movement prediction module, picking direction planning module, robot motion control module;Tea leaf identification judging unit comprehensively uses image acquisition, pretreatment and computer vision algorithm, accurately identifies tea leaf and judges tender bud maturity.Tea leaf movement prediction module, when wind starts, uses relevant algorithm to predict the stable position of tender bud, to ensure that the cutting basis is reliable.Picking direction planning module under the condition of wind, through sensor monitoring branch sway, calculates relevant parameters and plans cutting path and direction, improves cutting accuracy.Robot motion control module according to the planning result, combined with kinematic model generates joint trajectory and speed curve, can also adjust the angle of scissors, realize smooth and accurate picking and collection.

The present application relates to the technical field of intelligent tea garden management, and proposes an intelligent tea garden service collaborative management system, comprising: a tourist picking reservation module, used for receiving a reservation picking request of a tourist through a terminal, intelligently arranging a time and an area for the tourist to pick tea leaves independently; a picking behavior processing module, used for analyzing, processing and prompting a picking behavior of the tourist; a comprehensive management docking module, used for integrating all module data, generating a multi-dimensional report, and docking with a tea garden enterprise ERP system to generate a collaborative scheme for management personnel, planting personnel and customer service personnel, and completing data integration-role adaptation-decision landing collaborative management. By constructing a full-chain tea garden management system from data collection and integration, growth and variety analysis to visual decision-making, and with the help of multi-source data fusion and intelligent technology, the comprehensive improvement of yield increase, quality improvement, cost reduction and efficiency increase of the tea garden is realized, which not only enhances economic benefits, but also improves resource utilization efficiency and ecological sustainability.

The application provides a kind of annual green manure interplanting method for tea garden soil improvement and fertilization, by interplanting summer green manure dichondra and winter green manure white clover in tea rows, combined with seamless interplanting and timely plowing technology, significantly improve the soil improvement effect and ecological regulation effect and the yield and quality of tea, through the synergy of two specific green manure variety combination, space-time configuration optimization and plowing management and other key links, not only fundamentally curb soil erosion, improve soil, fertilize soil fertility, reverse the trend of soil degradation, but also provide a stable habitat and food chain foundation for soil microorganisms, arthropods and other organisms, improve the biodiversity of tea garden, enhance the resistance to drought, cold and other adversity, promote the tea garden from a "soil consumption system" that relies on external input to a "fertile land and land system" that can self-nourish and recycle, which is of great significance to promote tea garden soil health management and promote green development of tea industry.

The invention discloses a tea garden early warning management system based on big data analysis, which relates to the technical field of tea garden early warning management and comprises a data acquisition module, a feature set generation module and a distributed analysis module. According to the method, a distributed collaborative learning framework is constructed, each tea garden locally trains a model and only uploads encryption parameters to the cloud, and a universal knowledge base is formed through fusion, so that a single tea garden can use experience of multiple regions for reference, and the early warning capability for novel diseases and insect pests and complex water stress is remarkably improved; the system realizes strategic transformation from passive response to active prevention and control by combining a self-evolution risk assessment rule and a near-end strategy optimization algorithm based on multi-source data acquisition and a spatio-temporal joint perception model, can generate future risk prediction, provides decision support for preventive management, forms a closed-loop optimization mechanism through strategy execution feedback, and improves the risk assessment efficiency. The early warning precision and decision effectiveness are continuously improved, and the intelligent level and the anti-risk capability of tea garden management are comprehensively enhanced.

The application discloses a spring tea low-temperature frost monitoring and disaster early warning method, which comprises the following steps: S1, obtaining the ground surface temperature, air humidity and air temperature at the sampling points distributed in a tea garden; S2, calculating the canopy temperature at each sampling point; S3, carrying out gridization on the tea garden, and obtaining the canopy temperature of each grid point by adopting an inverse distance weighted interpolation algorithm based on the canopy temperature of each sampling point; S4, calculating the temperature mean value of all the canopy temperatures, and judging whether the temperature mean value is greater than a preset mean value; if yes, returning to the step S1 after a preset time length, otherwise, entering the step S5; S5, calculating the temperature drop speed according to a plurality of continuous temperature mean values; S6, judging whether the temperature drop speed is less than a preset threshold value; if yes, starting a film covering device and an anti-frost fan; otherwise, entering the step S7; S7, starting the film covering device and the anti-frost fan, and switching the inlet end of a drip irrigation pipe to be communicated with a hot air heating system, and the hot air is introduced into the ground surface of the tea garden.

The invention relates to the technical field of exposure control, in particular to a tea garden camera dynamic exposure control method and system based on a random forest prediction model, and the method comprises the steps: S1, collecting image data of a tea garden under different illumination conditions, and extracting image quality parameters of a tender shoot region; s2, synchronously acquiring ambient light parameters when each image is shot; s3, constructing and training a random forest prediction model; s4, acquiring a current ambient light parameter and an image quality parameter of a previous frame of image in real time; s5, inputting the current ambient light parameter and the image quality parameter of the previous frame of image into the prediction model, and predicting the optimal exposure parameter of the current frame; and S6, adjusting camera exposure setting according to the optimal exposure parameter, and collecting a current frame image. And S7, collecting the local light-induced response difference spectrum, performing comparison to generate an exposure compensation sensitivity spectrum, and performing local offset correction. The image definition is improved, and the method is suitable for an image acquisition task highly sensitive to exposure quality.

The invention relates to the technical field of agricultural environment monitoring, and discloses a tea garden GIS (Geographic Information System) visual early warning system for carbon emission monitoring, which comprises the following steps of: firstly, extracting terrace ridge foot boundaries based on a digital elevation model, locking a uniform terrace spacing of the whole garden, and discretizing a slope into monitoring strips distributed along a contour line; then calculating an interflow intensity index by using the soil moisture content at the ridge foot, and determining a basic discharge potential by combining a biochemical inhibition attenuation model input by the pruned residues and a soil acidity constraint coefficient; further analyzing transmission time lag between adjacent strips by utilizing a step-by-step cascade transmission model, and performing space-time accumulation on the emission potential in the uphill direction to the downhill direction to generate final strip emission intensity with a time lag effect; and finally, mapping the data into an early warning level and carrying out striped dynamic rendering. The problems of space aliasing and time dislocation in slope tea garden monitoring are solved, and high-precision space-time dynamic early warning is achieved.

The invention discloses a method for improving the quality of ground tea produced in a tea garden in summer, which comprises the following steps: 7-10 days before picking tea leaves in summer, carrying out shading treatment on tea trees, mechanically harvesting fresh leaves at one time after the shading treatment is finished, carrying out steam enzyme deactivation without rolling, and directly drying to prepare ground tea; the shading rate of the shading treatment is 85-90%, a shading net is a black-and-white double-color single-layer shading net or a black-and-white double-layer shading net, and the shading net is located at the position 40-50 cm above the tea trees. The method can significantly reduce the scorched leaf rate caused by high temperature in summer, improve the quality and yield of the ground tea, and improve the utilization rate of summer tea.

This invention relates to the field of image detection technology and discloses a machine vision-based intelligent detection method and system for tea garden buds. The method includes: acquiring and preprocessing tea garden images; constructing a dual-branch parallel structure to extract multi-scale bud features; repairing occluded / overlapping bud features; establishing a dual-branch feature interaction channel; allocating feature weights through multi-dimensional attention; cross-scale matching and fusion of features for adaptive prediction; and outputting the detection result after adaptive parameter cropping or parameter fusion processing. This invention achieves accurate and efficient detection of tea garden buds through dual-branch collaborative feature extraction and repair, multi-dimensional attention to enhance bud features, cross-scale modeling for accurate prediction, and adaptive parameter cropping or parameter fusion to simplify the structure, thus adapting to the bud recognition needs in complex tea garden environments.

The utility model relates to the technical field of acid soil improvement, and discloses a tea garden acid soil conditioner spraying device which comprises a bearing platform fixedly connected to the upper portion of a frame, a lime bucket is installed on the upper portion of the bearing platform, and a suction pump, a conditioner bucket and a water suction pump are installed on the upper portion of the bearing platform. The device is reasonable in structure, the electric push rod is used for controlling the spraying frame to ascend and descend so as to spray acid soil at high pressure at the distance closest to the ground, and a modifier can deeply permeate into the soil to be better absorbed and improved; after being blocked by residues in a pipeline, the quick-release spray head can be quickly detached and put into one side, provided with the ultrasonic motor, of the cleaning tank to be cleaned, and meanwhile, the clean quick-release spray head in the cleaning tank is replaced to the original position to perform uninterrupted spraying operation; and after the spraying operation is finished, the water suction pump is started to pump the cleaning agent in the cleaning agent barrel into the modifier barrel, and residues in the barrel and the pipeline are flushed to keep the pipeline of the device not blocked.

The invention discloses an intelligent tea garden comprehensive operation system which comprises a rack assembly, a walking module and a multi-mode operation mechanism. The walking module comprises two sets of walking units, the two sets of walking units are arranged on the two sides of the bottom of the rack assembly respectively, the multi-mode operation mechanism comprises a picking module and a water and fertilizer spraying module, the walking module can automatically walk along each row of tea trees and can be automatically switched between every two adjacent rows of tea trees, and the intelligent degree is high; the multi-mode operation mechanism integrates a picking operation mode and a water and fertilizer applying operation mode, the picking module can complete automatic picking of tender leaves and leaf buds, and the tender leaves and the leaf buds are collected in a picking box through negative pressure collection after picking; the water and fertilizer spraying module sprays water and fertilizer to the tea trees in the self-walking process.

The utility model provides a portable electric tea picker belongs to tea picker technical field, including walking assembly, including frame, the connecting plate hinged in frame end, the adapter plate hinged in the connecting plate end, and the wheel of rotary installation in the lateral wall of adapter plate, tea picking assembly, including the casing of inserting in frame end, rotary installation in the lateral wall of casing drive shaft, fixedly connected in the lateral wall of drive shaft's the pole, and fixedly connected in the casing lower end lateral wall's blade, the pole end extends to above the blade, the utility model has the advantages that: the hinged structure of connecting plate and adapter plate can adjust the wheel angle, and the complex topography is adapted, the height of support plate is adjustable, and the tea tree of adaptation different height is promoted to pick the range, the synchronous operation of symmetrical installation's tea picking assembly can be whole machine push operation, also can be individually hand-held casing picking, and the tea garden area of adaptation wide and narrow is different, and the flexibility is high.