528 results about "Growing region" patented technology

The invention relates to the technical field of agricultural informatization and intelligent decision making, and discloses a vegetable growth cycle pest control decision making system and method based on a knowledge graph. According to the method, an unstructured agricultural data stream including vegetable varieties, growth stages, environmental parameters, pest and disease records and geographic information is collected from an original database. A data tuple set with a time stamp is generated by performing scanning identification and content extraction on a data stream. Then, clustering is carried out according to the growth stages to which the tuples belong, and stage feature clusters sorted according to the growth cycle are formed; and performing multi-dimensional feature correlation analysis on the stage feature cluster, and establishing a dynamic coupling relationship among the environmental parameters, the disease and pest history and the geographic space features under the growth cycle dimension. And based on the dynamic coupling relationship, generating disease and pest control decision parameters of the vegetables in the specific planting area in each growth cycle stage. According to the invention, accurate matching between the control decision and the crop physiological time sequence and regional characteristics is realized.

The invention belongs to the field of crop yield estimation, and discloses a corn yield remote sensing estimation method and system based on multispectral data coupling radiation transmission and a crop growth model, and the method comprises the steps: obtaining and preprocessing a Sentinel-2 multispectral remote sensing image, and obtaining the reflectivity data of a corn planting region; constructing a PROSAIL forward simulation spectrum library, and performing domain correction on the simulation spectrum by using an auto-encoder and a residual error alignment network; establishing a machine learning inversion model based on the corrected simulated spectrum and the actually measured spectrum, and generating regional leaf area index (LAI) distribution; key agronomic parameters are obtained, a localized WOFOST crop growth model is constructed, the LAI state of the model is assimilated by adopting ensemble Kalman filtering at a remote sensing observation moment, and the crop growth process is dynamically corrected; and advancing the model to a mature period, outputting the dry weight of the corn kernels, and realizing remote sensing estimation of the regional corn yield. The method can effectively improve the LAI inversion precision and yield prediction reliability, and is suitable for the fields of agricultural monitoring, grain evaluation, agricultural condition management and the like.

The invention discloses a knowledge graph construction method for alternative planting of poppy, which comprises the following steps: acquiring soil humidity, illumination intensity, air temperature and rainfall data from Internet of Things sensing nodes deployed in an alternative planting area, analyzing a crop growth state in combination with a remote sensing image, and generating a structured environment observation tuple; entity recognition and relation extraction are carried out on policy and regulation texts, agricultural technology manual and historical planting records, and an initial triple set is constructed; inputting the structured environment observation tuple and the initial triple set into a graph neural network encoder to generate a node embedding vector; on the basis of the node embedding vectors, calculating semantic association weights among entities by adopting a graph attention mechanism, and constructing a dynamic adjacency matrix; the objective of the invention is to solve the problems of lack of semantic association, fragmentation of knowledge expression, weak reasoning ability and insufficient cross-domain collaboration of multi-source heterogeneous data in existing alternative planting management.

The invention discloses a tobacco planting area suitability evaluation method and device, electronic equipment and a storage medium. Comprising the steps of obtaining multi-dimensional detection data of a target tobacco planting area, and determining at least one piece of ecological factor data of each grid unit of the target tobacco planting area based on the multi-dimensional detection data; for each grid unit, determining a target dynamic weight of each ecological factor based on the at least one ecological factor data of the grid unit; obtaining a plurality of pre-constructed preset levels and membership function parameters corresponding to the preset levels, and determining target membership data of each ecological factor based on the membership function parameters corresponding to the preset levels and the at least one ecological factor data; determining a suitability evaluation result of the grid unit based on the target dynamic weight and the target membership data of each ecological factor in the grid unit; and generating a suitability spatial distribution diagram of the target tobacco planting area based on the suitability evaluation result of each grid unit. According to the scheme, the accuracy of the suitability evaluation result is improved.

The invention provides a soybean growth monitoring method based on satellite remote sensing, and relates to the technical field of crop growth monitoring, and the method specifically comprises the steps: setting two monitoring nodes according to a soybean growth period, and collecting multispectral and thermal infrared remote sensing images and normal growth leaf area density and stem diameter sample data; a soybean area and a non-soybean area are distinguished by using a vegetation index threshold, cloud / shadow pixels are eliminated by using a multiband combination-threshold method, effective pixels are screened, and two types of remote sensing data are matched. Extracting leaf area density, canopy temperature and collaborative inversion stem diameter from the effective data; calculating the relative growth rate of the two types of indexes based on samples, and constructing a collaborative growth reference equation and a residual standard deviation; and substituting the growth rate of the planting area into an equation to obtain a theoretical value, calculating a deviation value, and judging the soybean growth state by combining the comparison between the deviation and a normal fluctuation interval and the positive and negative characteristics of the growth rate.

The invention relates to a facility crop transplanter which comprises a rack, a front walking mechanism arranged at the front end of the rack and a rear walking mechanism arranged at the rear end of the rack, a seedling taking mechanism, a duckbilled planting device and a seedling feeding mechanism are sequentially arranged at the upper end of the rack at intervals from front to back in the length direction of the rack, and the seedling feeding mechanism is used for conveying hole trays in the length direction of the rack; a transverse moving mechanism is arranged at the lower end of the seedling taking mechanism, the transverse moving mechanism is used for driving the seedling taking mechanism to move in the width direction of the rack, and the seedling taking mechanism is used for taking out pot seedlings from the hole tray and can drive the pot seedlings to reciprocate between the transverse moving mechanism and the seedling conveying mechanism; a seedling blocking piece is arranged above the duckbilled planting device, and when the seedling taking mechanism takes out the pot seedlings from the hole tray and moves towards the transverse moving mechanism, the seedling blocking piece is used for blocking the pot seedlings and enabling the pot seedlings to fall into the duckbilled planting device. According to the transplanting machine, flexible operation and efficient transplanting in scattered small planting areas can be achieved, and the applicability problem that a large field transplanting machine cannot be applied in facilities is solved.

The invention relates to the technical field of intelligent agriculture, in particular to an agricultural seeding machinery automatic control system based on a ground environment, and the system comprises a data collection module which is used for collecting the environment data of a target planting area, the soil data of a plurality of collection points, and the previous crop data of a plurality of previous crops; the soil analysis module is used for dividing the target planting area into a plurality of planting sub-areas; the environment analysis module is used for determining an environment influence index; the crop analysis module is used for determining crop distribution characteristics of a single planting sub-region and determining an edge influence index corresponding to each adjacent planting sub-region; and the seeding analysis module is used for determining an initial seeding parameter of a single planting sub-region, and determining whether to adjust the initial seeding parameter of the single planting sub-region or not based on the environment influence index and the edge influence index corresponding to each adjacent planting sub-region. According to the invention, multi-dimensional data sensing can be realized, the seeding parameters are accurately determined, and the seeding quality is improved.

The invention discloses an intelligent wheat disease diagnosis method and system based on a multi-modal large model. The method comprises the following steps: constructing a knowledge graph; obtaining a geographic position and current time of a user, positioning a wheat planting area based on the geographic position, calculating a wheat growth period in combination with the current time and the wheat planting area, and selecting a corresponding knowledge graph sub-graph according to the wheat growth period and the planting area; collecting texts and pictures input by a user through guiding type interaction; extracting text keywords, and identifying disease sites, disease types and disease symptoms in the pictures by using a deep learning model; fusing the text analysis result and the image analysis result to form a multi-modal feature; the optimized features are screened from the multi-modal features; a keyword set is decoded from the optimized features; generating a query statement based on the keyword set; and retrieving answers from the knowledge graph sub-graphs based on the query statements, and generating response contents based on the answers and feeding back the response contents to the user. The accuracy and efficiency of wheat disease diagnosis are improved.

The invention relates to the technical field of agricultural data visualization, in particular to a salinized cotton field visual multi-point salinity collection and analysis method and system.The method comprises the following steps that soil conductivity distribution data of a salinized cotton field area is obtained, a high-salinity accumulation area and a low-salinity dilution area are recognized, particle gap distribution characteristics are collected, and a salinized cotton field is obtained; and screening areas with loose or compact particle structures, executing temperature gradient analysis, screening surface thermal environment abnormal subareas, detecting wind speed distribution, removing wind field disturbance areas, and obtaining a recommended planting area list. According to the method, high and low salt areas are accurately identified through salt space distribution analysis, distribution precision is improved, humidity dynamic expression is refined, structural abnormal blocks are screened by using a particle gap change trend, soil management is optimized, surface temperature and wind speed data analysis is superposed, thermal disturbance and wind field abnormity are eliminated, and agricultural management precision is improved through multi-dimensional data fusion. The capability of coping with a complex environment is enhanced, efficient decision making is effectively supported, and the overall agricultural production benefit is improved.

The invention belongs to the technical field of planting of herbal coffee beans, particularly relates to a planting method of herbal coffee beans, and provides the following scheme aiming at the problems of unstable pest control effect, soil ecology damage and poor crop stress resistance caused by excessive dependence on chemical pesticides in the planting process of existing herbal coffee beans. The method comprises the following steps: S1, deeply treating soil in a planting area, and disinfecting fine soil to obtain medicine soil; s2, spreading the pesticide soil on the soil surface, and spreading a bio-organic fertilizer; s3, raking the pesticide soil and the bio-organic fertilizer into the middle layer of the ridge soil, and covering the planting ridge with a plastic film; s4, selecting seeds, soaking the seeds in warm water, and coating the seeds; s5, sowing the treated seeds to the planting ridges, and performing health management; according to the method, in the planting process of the herbal coffee beans, effective microbial communities are introduced after soil disinfection, diseases can be effectively prevented, and meanwhile the soil is improved.

The invention discloses a highland barley rhizosphere microbial community regulation and control method, which comprises the following steps: clustering sequencing sequences of microbial data in rhizosphere soil data of mature highland barley to obtain taxonomic information and an operable classification unit, performing zero-model analysis on the soil data and the operable classification unit according to planting data, and determining whether the soil data and the operable classification unit are in zero-model analysis. The method comprises the following steps: acquiring a ratio of nitrogen fertilizer data to environmental screening contribution and drift contribution of microbial community composition, performing diversity analysis on an operable classification unit according to taxonomy information to obtain dominant species data, extracting a nitrogen fertilizer amount and a fertilization period corresponding to the dominant species data, and performing parameter optimization through a Bayesian optimization algorithm. The rhizosphere soil is fertilized according to the fertilization period and the optimization parameters of the planting area, and the regulation and control result of the microflora is obtained. According to the method, the optimal nitrogen application amount gradient is determined through zero model analysis and Bayesian parameter optimization, so that the rhizosphere microorganism function adapts to the growth requirement of highland barley, and an interpretable basis is provided for optimizing nitrogen fertilizer management.

The invention discloses a dry land wheat green high-yield cultivation optimization method and system, and relates to the technical field of agricultural cultivation. The method comprises the following steps: firstly, obtaining typical rainfall characteristic data and soil characteristic data of a target planting area, constructing a micro-furrow simulation model, and carrying out optimization solution by taking predicted water catchment maximization as a target to obtain optimal micro-furrow parameters. And calculating a confidence wetting depth by combining rainfall characteristic data and an optimization result, and determining furrow sowing parameters according to the optimization result and wheat water demand characteristics. Finally, cultivation operation is executed based on the micro-furrow parameters, the furrow sowing parameters and the confidence wetting depth, wherein the fertilizer application depth is determined based on the confidence wetting depth. Precise matching of a micro-furrow structure, crop layout and water and fertilizer management is achieved, the problems that in traditional cultivation, the water utilization efficiency is low, and water and fertilizer space matching is poor are solved, and the rainfall utilization efficiency and the yield level of dry land wheat are improved.

The invention discloses a soybean planting pollution reduction and carbon reduction measure effect prediction method based on machine learning scenario simulation, and belongs to the field of pollution reduction and carbon reduction, and the method comprises the steps: firstly collecting root system and microorganism data of a soybean planting area, and quantifying the interaction intensity through a random forest algorithm; the nitrogen circulation state is judged, and the acceleration degree is determined; predicting the carbon storage change in combination with a support vector machine model; further extracting ecological influence variables, and evaluating the environmental benefit optimization potential through cross-planting condition comparison; performing simulation adjustment on the measure combination with high potential to generate a combined index of nitrogen cycle and carbon storage change; determining a correction coefficient through clustering analysis trend data; and finally, multi-source simulation results are fused to generate a precise ecological influence assessment report. According to the method, the problems of insufficient root-microorganism interaction quantification, weak nitrogen-carbon process coupling analysis and large dynamic prediction deviation in the prior art are solved.

A cultivating and planting device comprises a planting frame provided with a plurality of layers of planting areas, first conveying mechanisms are arranged in the planting areas in the length direction of the planting frame in an extending mode, and planting plates are arranged on the first conveying mechanisms; a conveying frame is arranged at one end or two ends of the planting frame, and a plurality of second conveying mechanisms corresponding to the first conveying mechanisms are arranged on the conveying frame; when the conveying frame is in butt joint with the planting frame, the first conveying mechanism and the second conveying mechanism are matched with each other to convey the planting plates in the conveying frame into the planting frame, or convey the planting plates in the planting frame into the conveying frame, or convey the planting plates in the planting frame from one end of the planting frame into the conveying frame at the other end of the planting frame. According to the cultivation and planting device, efficient and stable transportation of the planting plates between the planting frame and the transportation frame is achieved, meanwhile, stable operation of a nutrient solution circulation system is guaranteed, the production efficiency and the automation level of agricultural planting are greatly improved, and manual intervention and labor intensity are reduced.

The invention provides a remote monitoring system for seedling cultivation, and belongs to the technical field of remote monitoring, and the system comprises a position analysis module which is used for carrying out the rough segmentation of a terrain structure of a seedling planting region and the extraction of growth good and bad positions; the deployment module is used for performing good and bad cutting on the segmented slope surface and the segmented plane to obtain a plurality of sub-cut surfaces and deploying a sensor group and an intelligent control group; the control end is used for capturing a multi-dimensional influence vector of the nursery stock planting area in real time based on a whole-process working camera deployed in the nursery stock planting area, triggering a monitoring condition to newly add a temporary moment, controlling a corresponding sub-cutting surface to carry out newly-added monitoring for one time, and meanwhile, according to a delay attribute and an influence attribute of the triggering monitoring condition, controlling the corresponding sub-cutting surface to carry out newly-added monitoring for one time; updating the monitoring subset of each sub cutting surface; and carrying out nursery stock growth analysis on the multi-dimensional monitoring data to determine a control instruction aiming at the corresponding sub-cutting surface, and issuing the control instruction. And fine management of seedling cultivation is ensured.

The invention relates to the technical field of jerusalem artichoke breeding and planting, and discloses a jerusalem artichoke variety breeding and planting method and system. The method comprises the following steps: collecting phenotype data of jerusalem artichoke plants at different growth stages Constructing a multi-dimensional growth model containing an incidence relation between environmental factors and phenotypic data, wherein the environmental factors are obtained by monitoring a planting area sensor array in real time; screening candidate jerusalem artichoke strains in the target environment parameter interval based on the phenotype-environment response curve; hybridizing and matching the candidate strains to obtain filial generation seeds, and sowing the filial generation seeds in a controllable environment test field; extracting gene expression profile data of offspring seeds, and establishing a genotype-phenotype incidence matrix in combination with the response curve; transplanting the dominant group to a field, and collecting growth dynamic data to update the multi-dimensional growth model; an environment control strategy is adjusted according to the updated model, and dominant groups are directionally cultivated; tubers are harvested and subjected to quality detection, and the result is fed back to the incidence matrix to optimize the next breeding process.

The utility model provides an arid area saline-alkali land treatment structure, which is characterized in that saline-alkali land is divided into a plurality of planting areas and a saline-alkali water collection and treatment area, each planting area comprises a planting layer, a water drainage and salt guide layer, a permeation-resistant air layer and an original layer, and the water drainage and salt guide layers are respectively positioned at the upper part of the permeation-resistant air layer and inside the original layer; the drainage salt guide layer, the permeation-resistant gas layer and the original layer are all in an inverted V shape with the high middle and the low two sides, and the hydraulic gradient of the slopes on the two sides is 1%-2%. The saline-alkali water collecting and treating area is composed of an alkali discharge channel, a filtering and collecting tank, an electro-adsorption tank, a water storage tank and an evaporation tank, the alkali discharge channel comprises an alkali discharge channel slope, an alkali discharge channel bottom surface and a water level sensor, and the hydraulic gradient of the alkali discharge channel bottom surface is 3%-5%. A filtering and collecting tank, an electro-adsorption tank, a water storage tank and an evaporation tank are arranged at the lowest-gradient end of the bottom surface of the alkali discharge channel. According to the utility model, a planting area layered improved structure is combined with a saline-alkaline water collection, treatment and storage integrated structure, so that the salt content of soil is reduced, and the recycling of saline-alkaline water is realized.

The invention relates to the technical field of intelligent agriculture, and discloses a traditional Chinese medicine organic planting management method based on big data analysis. A space coordinate system is established in a planting area, regular partitioning is carried out, a unique land parcel identifier is formed, a soil humidity sensor is arranged in the center of each land parcel, meteorological observation points are matched to continuously collect air temperature, wind speed and illumination, and an evapotranspiration potential index is generated through sliding window statistics and normalization. The system performs dynamic balance prediction and state correction according to the soil moisture content, the irrigation volume and the evapotranspiration loss, extracts a reference evapotranspiration rate by using an unirrigated sample, determines a threshold interval and a real-time deviation in combination with a historical quantile, and smoothly improves the stability through a sliding window. The threshold value is updated hour by hour within a feasible range, irrigation is triggered when the water content is lower than the threshold value, and the irrigation amount is limited within a reasonable range through depth and flow conversion. Structured logs are generated in the whole process, and irrigation whole-process trace reserving is achieved.

The invention discloses an agricultural planting soil parameter analysis system, which relates to the technical field of soil intelligent analysis, and comprises a data acquisition module, a data determination module, a quality evaluation module and a dynamic optimization module, the data acquisition module is used for acquiring soil parameters and farming operation record data of each planting area; the data determination module is used for analyzing the soil component difference value of each planting area to generate a first influence difference; the quality evaluation module is used for analyzing the spatial correlation of the first influence difference by using the interaction correlation to obtain a soil spatial distribution prediction map; and the dynamic optimization module is used for dynamically regulating and controlling the soil content according to the soil spatial distribution prediction map. The farmland ecological environment is protected, agricultural sustainable development is promoted, and the intelligent level of soil parameter adjustment is improved.

The invention discloses a tobacco leaf quality improving method and system based on planting soil management. The method comprises the following steps: firstly, acquiring historical soil quality and root growth data of a tobacco plant, and analyzing root growth preferences under different soil conditions by using a clustering algorithm to form soil quality-preference data; combining the soil quality data of the target planting area to construct a root growth probability distribution map, and predicting root distribution according to the planting target; determining the arrangement position of a soil monitoring sensor according to a prediction result, and establishing a monitoring network to realize real-time acquisition of soil substance change; and finally, adjusting and managing nutrient substances in the tobacco planting process according to the monitoring data. According to the method, the adaptability of root systems and soil is improved, nutrient supply is optimized, balanced growth and stable quality of the tobacco leaves are promoted, and therefore tobacco leaf quality improvement and planting benefit optimization are achieved.

The invention provides a time-space early warning method, system and device for early spring freezing injury of fruits and vegetables and a medium, and relates to the technical field of agricultural production. The method comprises the following steps: acquiring real-time meteorological data of a fruit and vegetable planting area, and generating a four-dimensional data tensor through preprocessing and spatial interpolation; establishing a multi-factor freeze injury grade index fusing daily minimum temperature and duration according to fruit and vegetable flowering phase physiological characteristics, and calibrating historical data to train an early warning model according to the multi-factor freeze injury grade index; the model extracts spatial and temporal characteristics through a 3D convolution layer, after sampling is carried out through a pooling layer, a bidirectional LSTM layer captures time sequence dependence, and finally freeze injury grade prediction of each spatial position is output. According to the method, high-density meteorological monitoring, crop physiological indexes and a deep learning model are fused, the problems that a traditional early warning method is insufficient in precision and poor in timeliness are solved, and dynamic, accurate and advanced early warning of freeze injury risks can be achieved.

The invention belongs to the technical field of seed cultivation, and discloses a traditional Chinese medicine seed cultivation device and method.According to the technical scheme, the traditional Chinese medicine seed cultivation device comprises a breeding box, a plurality of supporting plates are fixedly installed in the breeding box, a plurality of placement holes are formed in the supporting plates respectively, and first motors are fixedly installed in the placement holes respectively; a square rod is fixedly installed on the first motor, a square pipe is arranged on the periphery of the square rod in a matched and sleeved mode, an internal thread is formed in a placement hole, a stud is installed in the placement hole in a threaded mode, the stud is fixedly installed on the square pipe, an electric aperture structure is fixedly installed on the stud, a stirring cavity is formed in one side of the placement hole, and a second motor is fixedly installed in the stirring cavity. According to the device, medicinal material seeds can be conveniently cultivated, the whole with soil can be conveniently and rapidly buried into a planting area after cultivation, damage to seedling root systems is avoided, the planting quality is improved, and seedling inclination caused by plant phototaxis can be avoided through periodic rotation in the seedling cultivation process.

The invention provides a tail water relay treatment method for fish and rice rotation in a pond. The tail water relay treatment method comprises the following steps: injecting new water into a pond culture area before the beginning of a pond culture period, stocking fish fries, periodically patrolling the pond, measuring water quality, feeding baits, and carrying out fish culture operation; rice is planted in the rice planting area, sowing is conducted in early May, rice transplanting is conducted in mid-to-late May, bottom mud in the pond culture area is used as base fertilizer, and water circulation between the pond culture area and the rice planting area is completed through a first water path system and a second water path system which are arranged between the pond culture area and the rice planting area. By means of in-situ management and control of the water body and ex-situ purification after discharge, the environment of the aquaculture water body is kept stable, discharged tail water is ecologically utilized and treated, up-to-standard discharge is achieved, healthy growth of fishes and reduction of the aquaculture cost are guaranteed, a technical path and support are provided for innovation of an ecological agricultural product production mode, and the method is economical and practical.

The utility model discloses a third-generation hot air anti-freezing device which comprises a fan device. The fan device comprises a combustion chamber, one end of the combustion chamber is provided with an air supply fan, and the other end is provided with a guide plate connected with a heat conduction pipe; the heat conduction pipe is connected with a heat supply device, the heat supply device comprises a main pipe, two sides of the main pipe are respectively connected with a plurality of branch pipes, the branch pipes are connected with plant planting areas, and the main pipe and the branch pipes are provided with a plurality of heat supply through holes. Remote simultaneous frost prevention and freezing prevention of a plurality of plant planting areas can be achieved, frequent moving of the fan device through a moving device is not needed, labor cost is saved, and waste of labor cost and fuel resources of re-ignition caused by flameout and waiting for cooling of the fan device in order to prevent workers from being scalded by moving the fan device during combustion is not needed. The risk of frost damage and frostbite of vegetation due to the fact that the movable fan device cannot provide heat for the vegetation area in time is also avoided; and the heat can be accurately conveyed to the vegetation area needing the heat, and heat waste is avoided.

This shelter provides a centralized storage or plant cultivation area for the movable shelves during normal times, and can be moved to the side to create a large open space in the center of the living area during emergencies. [Solution] The shelter 1 comprises a structure 3 located underground with a living space formed inside, a second door 31 having a radiation shielding function for entering and exiting the living space, a ventilation device for ventilating the living space, a plurality of movable shelves 42 including wheels, and guide means installed inside the living space for moving the plurality of movable shelves 42, the guide means being a rail 41 that guides the wheels, the plurality of movable shelves 42 being movable along the rail 42, and the plurality of movable shelves 42 being configured to move between a first state where they are located in the center of the living space and a second state where they are located towards the edge of the living space.

The invention relates to the technical field of planting equipment, in particular to a peanut planting film laying device which comprises a film roll, a plurality of rolling wheels used for pressing a film output by the film roll on the ground and a plurality of guiding and conveying structures used for laying soil on the film. The rolling wheel is located between two adjacent ridge planting areas on the ground, and the guiding and conveying structure is aligned with the rolling wheel; the rolling wheels are used for pressing the film output by the film roll, the working effect of automatically and continuously outputting the film can be achieved when the device moves, the film can be continuously laid on the ground, the rolling wheels can press and lay the film output by the film roll on multiple ridges, the laying area is effectively increased, and the laying efficiency is improved. Ground grinding of agricultural machinery is reduced, manpower, equipment and other cost input is reduced, and working efficiency is improved.

The invention relates to the technical field of polygonatum sibiricum cultivation devices, in particular to a polygonatum sibiricum cultivation device which comprises a cultivation box, multiple sets of planting areas are arranged in the cultivation box, clamping grooves are formed in the two sides of the middle of each planting area, a movable plate is clamped in the clamping grooves, two sets of vertical blocks are arranged on the movable plate, and multiple sets of planting grooves are formed in the vertical blocks. A planting box is elastically connected into the planting groove, and the two sides of the planting box are connected with swing plates through hinge shafts; the polygonatum sibiricum cultivation device has the beneficial effects that after polygonatum sibiricum seedlings are mature, a handle is synchronized, a movable plate is pulled out again, then shifting plates, extending out of the two sides of a planting groove, of the top of a vertical block are shifted one by one, the shifting plates drive limiting plates to extrude springs and drive the limiting plates to retract into telescopic grooves, and the polygonatum sibiricum seedlings are planted in the telescopic grooves; at the moment, the planting box pops up from the planting groove through the tension of the first spring connected with the bottom of the planting box.

The invention relates to the technical field of intelligent agriculture and artificial intelligence, and discloses an AI-based avocado nutrition diagnosis method and system.The AI-based avocado nutrition diagnosis method comprises the steps that multi-source sensor data and multispectral image data of an avocado planting area of a farm are collected, and data preprocessing is carried out; carrying out nutrient deficiency intelligent identification; a space-time prediction model is constructed, and the future change trend of the nutrition state is predicted; analyzing nutrition state change reasons, and formulating and implementing a regulation and control strategy and optimizing the regulation and control strategy; constructing a decision support module driven by the knowledge graph and providing interpretable intelligent suggestions; carrying out system integration and real-time optimization; according to the invention, through the four-dimensional space-time prediction model technology based on the Transform architecture, accurate prediction of the future change trend of the nutrition state is realized.

The embodiment of the invention provides a method for planting festuca arundinacea based on a coastal area grey yard, which comprises the following steps: selecting a planting area; soil improvement is conducted on the planting area; planting the festuca arundinacea according to the seeding rate; field management and harvesting are conducted after sowing. According to the method, the forage grass varieties suitable for being planted in the coastal area grey yard are screened, the forage grass growth environment is improved through the proper covering soil and the modifying agent, and the forage grass activity is improved. In addition, through integration of a scientific cultivation technology and field management, germination and growth of forage grass seeds are promoted, water-saving irrigation is achieved, the yield of high-quality forage grass is increased, the problem of dust raising of the ash yard is solved, and meanwhile greening of the coastal ash yard is achieved for ecological restoration.

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.