27788 results about "Agricultural science" patented technology

The invention relates to the technical field of agricultural equipment state monitoring, and discloses an agricultural equipment state monitoring system based on the Internet of Things, which comprises an acquisition unit, an analysis unit, a stripping unit, a fusion unit and a decision unit, and is characterized in that vibration, rotating speed, torque, soil hardness and environmental data are acquired in multiple dimensions through an Internet of Things sensor network; a physical compensation factor is generated through working condition synchronous analysis, interference of soil hardness on vibration data is effectively stripped, a coupling wear index is generated through fusion of a residual feature vector and environment temperature and humidity, a state threshold value is dynamically adjusted through combination of historical fault data, and then interference of soil hardness changes on a vibration spectrum is accurately eliminated. The misjudgment of the abrasion degree caused by frequency spectrum distortion is avoided, the dynamic and accurate monitoring of the abrasion state of the harvester blade is realized, and the accuracy of monitoring the state of agricultural equipment in dry farmland operation is improved.

The invention discloses an intelligent livestock breeding traceability method and system, and the method comprises the steps: building an overall framework of the intelligent livestock breeding traceability system based on a micro-service architecture, and employing Spring Cloud Al ibaaba as a micro-service technology stack; livestock physiological data and environmental parameters are collected through Internet of Things equipment, and a livestock electronic file is established; an AI intelligent analysis engine is constructed, and livestock health state evaluation, oestrus prediction and abnormal behavior recognition are achieved; the whole life cycle data of livestock from breeding to selling is recorded based on the block chain technology, and a full-chain traceability system is constructed. The method further comprises the functions of integrating a financial service interface, designing a multi-terminal collaborative application platform, constructing a matchmaking transaction platform and the like. According to the invention, the problems of data islanding, incomplete traceability system, low intelligent level, insufficient system expandability and the like in the prior art are solved, and the accuracy, traceability and system stability of livestock breeding are improved.

The invention relates to an agricultural biomass characteristic intelligent detection method, system and device based on multi-frequency conductance coupling and a medium, and the method comprises the following steps: applying an electric excitation signal to an agricultural biomass sample, and synchronously collecting multi-physics coupling response data; based on the multi-physics field coupling response data, constructing a multi-scale equivalent circuit model comprising a resonance unit, a constant phase unit and a diffusion impedance unit; synchronously optimizing a resonance unit parameter, a constant phase unit parameter and an impedance unit parameter of the multi-scale equivalent circuit model through a Bayesian joint inversion algorithm to obtain an optimal parameter combination; and according to the optimal parameter combination, calculating a preliminary detection result of biomass components containing cellulose crystallinity, lignin crosslinking degree and water content, combining the collected environment temperature and humidity sensing data to implement dynamic compensation, and outputting a final detection result. Therefore, the detection precision, the environment robustness and the operation reliability are synergistically improved in three aspects of hardware design, model construction and algorithm optimization.

The invention discloses a sugarcane germplasm resource evaluation and breeding method for smart agriculture. The sugarcane germplasm resource evaluation and breeding method comprises the following steps: step 1, collecting materials with wide genetic diversity; establishing an intelligent incubator and a greenhouse, and monitoring environmental parameters by using an Internet of Things sensor; 2, performing data acquisition on the related germplasm resources by using an unmanned aerial vehicle, a robot and a near infrared spectrum technology, and constructing a phenotype database for data management; meanwhile, genotype identification is carried out by combining molecular marker-assisted selection and genome selection technologies, molecular markers of key genes are mined, and the genetic value of related germplasm is evaluated; step 3, constructing a hybrid combination prediction model by using an AI algorithm, optimizing parent matching of the related germplasm and the cultivated sugarcane, monitoring and collecting the filial generation at the same time, and analyzing and screening in combination with smart agriculture; 4, demonstration planting is conducted on the bred excellent sugarcane strain, and application of the excellent strain is improved through government-enterprise-scientific research institution collaborative popularization and in combination with farmer technical training.

An intelligent fertilization and water supply method and system. The method comprises the following steps: step a, comprehensive soil monitoring, involving: comprehensively monitoring various soil indexes by means of a plurality of sensors, so as to obtain real-time data of the soil indexes; b, consideration of crop-specific requirements, involving: for the varieties and growth stages of different crops, thoroughly studying the unique moisture and nutrient requirements of the crops, so as to ensure the rationality and accuracy of a fertilization amount; c, comprehensive consideration of environmental factors, involving: collecting data of surrounding environmental factors; d, utilization of an intelligent irrigation mode, involving: by using a cyclic irrigation mode, an intermittent irrigation mode, etc., in combination with the water requirement pattern of each crop and a change in soil moisture, realizing efficient water utilization; e, implementation of a dynamic fertilization plan, involving: on the basis of a change in a crop growth condition and in soil fertility, dynamically adjusting fertilization time, frequency and dosage, so as to ensure that the nutrient supply matches the requirements of each crop; and f, implementation of a precise fertilization technique, involving: precisely delivering fertilizer to an absorption part of each crop, so as to improve the efficiency of nutrient utilization.

The invention discloses an unmanned agricultural machine path navigation method based on farmland environment perception judgment, and relates to the technical field of path navigation, and the method comprises the steps: continuously perceiving farmland topographic relief features, gradient changes, and agricultural machine current attitude and wheel speed information before and during the operation of an agricultural machine; identifying a terrain disturbance potential risk area based on the sensing data, and predicting the offset and rollover risk value of the terrain fluctuation to the agricultural machine trajectory; according to the method, a pre-correction model fusing terrain prediction data and agricultural machinery dynamic characteristics is called, a pre-correction path containing the terrain compensation amount is generated, and navigation control parameters are adjusted in advance, so that the pre-correction path containing the terrain compensation amount is actively generated by sensing terrain fluctuation and predicting risk and offset in advance; the problem of causal malposition of risk prior to control is avoided from the source.

The invention discloses a garlic disease and insect pest dynamic diagnosis system based on temperature and humidity time sequence data, relates to the technical field of agricultural information processing, and solves the problems that in the prior art, a fixed parameter model is prone to sensitivity sudden drop, false alarm sudden increase and systematic deviation under sudden or semi-sudden changes of field environment and management variables. According to the scheme, semantic processing of temperature and humidity and farming events is carried out through an acquisition module, a system coupling module carries out segmented identification on distribution mutation caused by environment and operation, a domain representation module constructs causal threatening features, a prediction calibration module carries out dual-path drift decomposition and rapid correction, and a prediction result is obtained. The sample adding and label collecting module generates anti-fact samples and actively collects labels, and the decision attribution module outputs a structured evidence chain; according to the method, the dynamic adaptive capacity and reliability of the diagnosis system under the conditions of non-stationary distribution and concept drift are remarkably improved.

The present disclosure relates to different techniques of controlling an agricultural system, as for example a controlled agricultural system, an agricultural light fixture and a method for agricultural management.Furthermore, the disclosure relates to an agricultural system, which comprises a plurality of processing lines for growing plants of a given plant type, wherein a first processing line in the plurality of processing lines is configured to move a first plurality of plants through the agricultural system along a route; and apply a first growth condition to the first plurality of plants to satisfy a first active agent parameter for the first plurality of plants.

The invention relates to the technical field of edible mushroom culture, in particular to an edible mushroom culture environment multi-dimensional monitoring system, which comprises an environment parameter acquisition module, a dynamic data preprocessing module, a multi-dimensional environment characteristic parameter extraction module, an environment abnormity evaluation module, a regulation and control decision generation module and an execution mechanism control module, the environmental parameter acquisition module acquires an original environmental parameter set; the dynamic data preprocessing module generates preprocessing environment data; the multi-dimensional environment characteristic parameter extraction module is used for extracting multi-dimensional environment characteristic parameters; the environment abnormity evaluation module outputs an evaluation result; the regulation and control decision generation module generates a regulation and control instruction sequence including priority ranking; and the execution mechanism control module converts the regulation and control instruction sequence into an execution mechanism driving signal. According to the method, the response efficiency of environmental regulation and the resource utilization rate are improved, and stable growth of edible mushrooms under variable environmental conditions is guaranteed.

The invention relates to an intelligent agricultural management system based on a planting-harvesting-distribution full link, and belongs to the field of agriculture, and the system comprises an online seed selection module, an order tracking module, an environment monitoring and early warning module, a pest and disease identification module, a market prediction module, a logistics scheduling module, a product estimation module and a growth state evaluation module. In the planting link, intelligent monitoring and abnormal early warning are carried out on the crop growth environment through the intelligent agent, accurate planting schemes for different crops can be formulated for farmers, and irrigation and fertilization schemes suitable for different regions can be formulated; in the production process, the intelligent agent can intelligently identify bad fruits and give out a treatment scheme, accurately identify diseases and pests and provide an effective prevention and treatment means; in the marketing link, the market trend can be predicted, the production scheme is reasonably arranged, and the production and marketing balance of agricultural products is ensured.

The invention relates to the technical field of tobacco leaf storage, in particular to an intelligent regulation and control method and system for a tobacco leaf storage environment, and the method comprises the following steps: based on a tobacco leaf storage bin, fusing temperature, humidity and oxygen concentration sensor data, obtaining environment characteristics, analyzing airflow velocity and stacking density, identifying abnormal regions, counting variety deviation, and carrying out the control grading of associated equipment. And environment regulation and control are optimized. According to the method, multiple types of sensor data are integrated, the environment states of different storage partitions are reflected through space correlation and weighting operation, the sensitive partitions with local abnormity are effectively locked by means of correlation analysis of airflow and stacking density, tobacco variety characteristics and storage stage parameters are combined, grading dynamic recognition of environment sensitive points is achieved, and the method is suitable for large-scale popularization and application. The equipment response sequence is configured in a layered manner, and the regulated and controlled parameter trend adjustment operation is combined, so that the long-term quality stability of various tobacco leaves in the storage space is enhanced, and the quality deviation risk caused by environmental disturbance is reduced.

The invention discloses a unit area irrigation water consumption estimation method and system based on multi-source data fusion, and relates to the field of irrigation water consumption estimation. Multi-source heterogeneous data such as remote sensing images, meteorological data, soil humidity and crop growth information are fused, and observation and model errors are reduced through data assimilation; estimating crop evapotranspiration under an energy balance principle; estimating daily-scale irrigation water consumption by adopting a water balance method; a crop actual irrigation area identification model based on deep learning is introduced, actual irrigation areas of different crop types are effectively distinguished, and the influence of temporal and spatial changes on irrigation efficiency is dynamically reflected. According to the method, high-precision and rapid estimation of the comprehensive unit area irrigation water consumption of a single crop and multiple crops on different regional scales can be realized, the timeliness and accuracy of irrigation water quota evaluation are remarkably improved, and the method has strong adaptability to climate change, soil difference and crop diversity and is suitable for popularization and application. Powerful technical support is provided for precise irrigation and intelligent water conservancy management.

The invention discloses landscaping cultivation equipment, and belongs to the technical field of greening cultivation, the landscaping cultivation equipment comprises a base, the upper side of the base is provided with a water leakage plate, the upper end of the water leakage plate is slidably provided with a plurality of side plates, one end of each side plate is fixedly provided with a first sliding block for sliding, and one side of each side plate is provided with a first sliding groove; the side plates provided with the first sliding blocks are slidably connected with the first sliding grooves in the adjacent side plates, planting cavities used for planting plants are formed among the side plates, grooves are formed in the lower ends of the side plates, adjusting assemblies are installed in the grooves and used for adjusting the positions of the water leakage plates, and a plurality of limiting assemblies are further installed at the upper end of the base. The side plates can automatically move outwards when plants grow, so that the space of the planting cavity is enlarged, the planting pot does not need to be replaced, the situation that the plants cannot adapt to the planting pot due to pot replacement is reduced, the step of pot replacement in the planting process is also reduced, and the planting efficiency is improved. The planting is simpler and more convenient.

The invention discloses a water and fertilizer integrated drip irrigation system for cotton growth period physiological index monitoring based on Internet of Things, and is applied to the technical field of cotton drip irrigation. Comprising an Internet of Things module, an edge computing device, a cloud platform decision module and a water and fertilizer drip irrigation device, the Internet of Things module is used for monitoring environmental data and physiological index data of cotton, a growth period recognition algorithm is built in an edge computing terminal, and the growth period of the cotton is automatically judged according to the physiological index data; the cloud platform decision-making module generates a water and fertilizer formula based on the environmental data, the physiological index data and the growth period of cotton, and the water and fertilizer drip irrigation equipment controls the drip irrigation amount in different areas and time periods based on a soil permeation model. According to the method, the problems that water and fertilizer control and physiological stages are disjointed in traditional cotton planting, and the requirement difference of different growth periods cannot be adapted are solved, corresponding drip irrigation schemes are set for different growth periods, switching is conducted through growth period recognition, and the adaptation degree of the drip irrigation schemes is improved.

This application provides a wind-resistant, stable power generation agricultural-solar hybrid system, including pillars, beams, photovoltaic supports, and photovoltaic panels erected in farmland. The photovoltaic panels are equipped with a buffer mechanism and an overload release device. The buffer mechanism effectively absorbs kinetic energy and reduces the swaying amplitude and speed of the photovoltaic panels through its elasticity, and automatically resets the photovoltaic panels after strong winds. The overload release device protects the photovoltaic panels from damage caused by strong winds. This application overcomes the technical defects of existing static wind-resistant systems, reduces system wind resistance, can withstand super typhoons, provide stable power generation and irrigation, and promote agricultural production.

The invention belongs to the technical field of agricultural supervision, and particularly relates to an intelligent agricultural planning decision-making system based on the Internet of Things, which comprises a planting plan decision-making unit, a resource allocation decision-making unit, an irrigation and fertilization monitoring unit, an agricultural planting management and analysis unit and an agricultural management and control terminal, planting plan decision-making information is generated through the planting plan decision-making unit to improve planting benefits, and monitoring analysis of the resource distribution decision-making unit and the pest and disease damage monitoring decision-making unit is beneficial for achieving precise irrigation and fertilization and timely preventing and treating pest and disease damage. The irrigation and fertilization monitoring unit analyzes the nutrient water content suitability abnormal performance of the corresponding area in the detection period, enhances subsequent irrigation and fertilization supervision when an irrigation and fertilization alarm signal is generated, and comprehensively evaluates the planting management performance of the corresponding area when an irrigation and fertilization qualification signal is generated; and subsequent planting supervision is enhanced when the planting management alarm signal is generated, so that the growth of crops in corresponding areas is ensured, and the intelligent level is high.

The invention discloses a photovoltaic auxiliary greenhouse cultivation system which comprises a greenhouse body composed of a framework system and a photovoltaic ceiling, and the photovoltaic ceiling is laid on the top of the framework system, provided with a light splitting type solar thin film cell panel set with adjustable light transmittance and laid in a partitioned mode according to the illumination requirement. The dynamic light compensation system, the temperature balance system and the energy storage system are arranged at the top of the framework system, the energy storage system is used for storing energy and supplying power, the dynamic light compensation system is used for supplementing light for each indoor crop area according to photosynthetically active radiation and sun illumination conditions, and the temperature balance system is used for ventilating and humidifying the greenhouse; and the control machine is arranged on the greenhouse main body and is electrically connected with the dynamic light compensation system, the temperature balance system and the energy storage system so as to receive the monitoring data and control the operation of each electric appliance element. According to the system, lithium battery energy storage and a grid-connected inverter are integrated, the energy self-sufficiency rate is optimized, and the space utilization rate is increased through spectrum customization and three-dimensional planting; the method is suitable for tilled land shortage areas, and gives consideration to clean energy production and agricultural efficient output.

The invention is suitable for the field of crop fertilization control, and provides a fertilization control method and system based on corn protective farming, and the method comprises the steps: synchronously collecting time-space multi-dimensional data of a target planting region, and constructing a multi-modal data cube; generating a seed fertilizer ratio decision vector; according to the seed-fertilizer ratio decision vector, controlling the multi-channel ratio of mechanical precision seed-fertilizer simultaneous sowing equipment, so as to realize the dynamic ratio and variable fertilization of the seed fertilizer; a multi-spectral image and soil moisture content data are collected through an unmanned aerial vehicle group, and a space-time continuous crop growth monitoring network is constructed; dynamically adjusting the topdressing amount and the water and fertilizer concentration of the unmanned aerial vehicle group based on the growth monitoring network data; according to the method, by constructing a multi-modal data cube, the dynamic proportioning and variable fertilization of seeds and fertilizers are realized, the proportioning precision is improved by utilizing fuzzy PID and machine vision, a space-time monitoring network is constructed by virtue of an unmanned aerial vehicle group, the dynamic adjustment of topdressing is realized, and a data-driven closed-loop fertilization system is formed.

The invention discloses a Chinese herbal medicine intelligent drip irrigation regulation and control system based on end-cloud cooperation, and relates to the technical field of agricultural intelligent irrigation, and the system comprises an edge equipment end which is deployed in a Chinese herbal medicine planting area, comprises a multi-mode sensor module, a communication module and an irrigation execution mechanism, and is used for collecting soil humidity, illumination intensity and meteorological data in real time, and sending the collected data to a cloud server; and the drip irrigation valve is controlled through the irrigation executing mechanism. According to the Chinese herbal medicine intelligent drip irrigation regulation and control system based on end-cloud collaboration, through an end-cloud collaboration architecture and a hierarchical decision-making mechanism, the drip irrigation regulation and control accuracy and real-time performance in a Chinese herbal medicine planting environment are improved. A local AI inference engine of the edge equipment end is combined with a dynamic learning module, an optimization instruction can be automatically generated during network fluctuation, dependence on real-time communication of the cloud end is reduced, and continuity and reliability of irrigation operation in complex terrains are ensured.

The invention provides a multi-dimensional data fusion soil fertilizer application system and method, and relates to the technical field of soil fertilizer application, and the system comprises a data collection module which is used for collecting multi-source original data including soil, weather, crops and fertilizer in real time; the data preprocessing module is used for preprocessing the multi-source original data; the data fusion module is used for generating a comprehensive index reflecting the soil fertility state and the crop demand; the fertilization decision module is used for generating an optimal fertilization scheme; the execution control module is used for controlling the variable fertilizer applicator and the drip irrigation equipment to execute precise fertilization operation; and the effect monitoring and feedback module is used for evaluating the decision effect and optimizing the nutrient leaching model. According to the invention, through multi-objective optimization based on the nutrient leaching model and the genetic algorithm, the fertilizer cost, the environmental risk and the agricultural machinery operation constraint are considered while the fertilizer requirement rule of crops is met, and the optimal fertilization scheme considering both the economical efficiency and the ecological property is output.

The invention relates to the field of agricultural fertilization, in particular to a corn straw returning-to-field and fertilization operation path collaborative scheduling optimization method, which comprises the following steps: performing standardization processing on farmland multi-source original data to obtain a field piece unit standardization feature vector; performing imbalance degree analysis on the feature dimension distance component to obtain a feature contribution balance factor; performing activeness evaluation on neighborhood membership distribution of the field units to obtain a spatial membership smoothing factor; obtaining adaptive distance measurement by combining a feature contribution balance factor and a space membership smoothing factor; and performing hardening processing on the final membership matrix to obtain an agricultural machinery path collaborative scheduling instruction set, thereby solving the problems of misalignment of a zoning result, fragmentation of a management boundary and unreasonable agricultural machinery path scheduling in an abnormal straw accumulation region based on a standard FCM clustering algorithm in the prior art.

The invention relates to the technical field of quality detection, in particular to an agricultural product quality detection method and system. The method comprises the following steps: carrying out multi-plane spectrum scanning on an apple through a near-infrared spectrometer to obtain a reflection spectrum and carrying out baseline correction; then, analyzing the mildewing degree of the apple pulp through cellulose spectral band identification and peak intensity attenuation index deduction; thirdly, identifying a preposed abnormal spectrum risk factor based on the mildew degree data, generating a mildew preposed abnormal spectrum risk factor, and constructing a quality detection model through sequential evolution traceability association of the abnormal factor and the mildew degree; finally, the detection model is sent to a terminal to execute agricultural product quality detection. According to the invention, the quality detection technology is optimized, so that the quality detection technology is more accurate.

A grain loss detector disposed on a combine harvester to detect grain loss within crop material being discharged by a separating or cleaning stage component of combine harvester while harvesting a crop. The grain loss detector includes at sensor generating sensor data output. A computing device receives the sensor data output for processing via software which compares the sensor data output against crop data characteristics to identify any grain kernels from among material other than grain. In one embodiment the sensor is a camera and the generated sensor data output is a digital image frame capturing the grain kernels and material other than grain passing the camera.

The invention discloses a livestock feed proportioning method based on livestock growth, and relates to the technical field of feed proportioning, and the livestock feed proportioning method comprises the following steps: collecting the body temperature and motion track data and environmental temperature and humidity data of livestock individuals, monitoring the concentration of amino acids in digestive tracts, preprocessing the collected data, and generating a standardized biological data set; analyzing the compensation amount of vitamins and trace elements according to the metabolic fingerprint spectrum, and constructing a multi-objective optimization function in combination with an individual growth curve; solving the multi-objective optimization function through a quantum annealing algorithm, and matching local raw material inventory data of block chain evidence storage to generate an optimization strategy; and executing the optimization strategy and detecting the mixing uniformity, and when the mixing uniformity index exceeds a preset mixing uniformity threshold, starting the compensation device to adjust the optimization strategy. According to the invention, through a cooperation mechanism of dynamic nutritional requirement identification and multi-constraint optimization, the precise regulation and control capability of livestock breeding is significantly improved.

The invention provides an agricultural seeding machine, and relates to the technical field of seeding equipment, the agricultural seeding machine comprises a profiling frame installed on a rack, a furrow opener and a press wheel, the furrow opener and the press wheel are connected to the profiling frame, the profiling frame is a four-bar mechanism and is provided with a lower connecting rod and a first side connecting rod, and the furrow opener is rotatably connected to the first side connecting rod; a pressing wheel frame is hinged to the first side connecting rod, the pressing wheel is rotationally connected to the pressing wheel frame, and a pressing wheel spring is connected between the pressing wheel frame and the first side connecting rod; a locking rod is hinged to the first side connecting rod, a locking rod spring is connected between the locking rod and the first side connecting rod, a first locking tooth is arranged on the upper portion of the locking rod, a second locking tooth meshed with the first locking tooth is arranged at the end of the lower connecting rod, and a material stirring baffle is connected to the end of the locking rod. The material stirring baffle can rotate when stirring soil, so that the profiling frame is locked, the furrow opener cannot float upwards, the press wheel can roll and cross soil blocks, and the influence of vertical floating of the furrow opener in a short time on the furrowing depth can be reduced.

The utility model discloses an intelligent straw which is characterized in that an induction electrode is coated and attached in the pipe wall of a hollow pipe along the length direction of the hollow pipe to collect the data of the amount of liquid passing through the hollow pipe, the hollow pipe can be made of food-grade materials such as silica gel and food-grade plastics, and the intelligent straw has the function of digitizing drinking water. The system can transmit data to a mobile phone or a cloud end, carries out health analysis through the data, achieves recording reminding, affects healthy diet of young people from behaviors, serves as an intelligent terminal of the Internet of Things, builds a digital connection between a merchant and a user, and further optimizes customer services better.

An insect monitoring system for use in agricultural fields is provided. The monitoring system has a chemical lure to attract insects to the monitoring system, and an adhesive material on which insects drawn to the lure can be trapped for later evaluation. The monitoring system also has a three-piece canopy made of two opposing sides and a cover. The parallel sides are roughly triangular and the cover sits above, and is attached to, the sides. The adhesive trap is held vertically between the two opposing sides of the canopy. The lure is held horizontally above the adhesive trap by being inserted through slits in the cover. The canopy can be assembled from a flat sheet of a prepatterned rigid material.

The technical scheme of the invention discloses a photovoltaic power generation and greenhouse agriculture integrated system. According to the photovoltaic agricultural integrated technology disclosed by the invention, photovoltaic power generation and greenhouse planting are innovatively combined, and a solar panel with adjustable light transmittance of 30%-90% is mounted at the top of an agricultural facility, so that sunlight is utilized for power generation, and illumination required by crop growth is reserved. The system disclosed by the invention is provided with an intelligent sensor and an AI algorithm, environment data is monitored in real time, the angle, light supplementing intensity, temperature and humidity of the photovoltaic panel are dynamically adjusted, and different crop requirements (such as low illumination of leaf vegetables and medium and strong illumination of fruits and vegetables) are accurately matched. Residual electricity is stored or connected to a grid, photovoltaic waste heat is recycled in winter for heat preservation, sun shading and cooling are conducted in summer, and efficient circulation of energy is achieved.

In order to solve the problems of planting liquid storage and scientific planting liquid supply under the long-time unattended condition and realize controllable long-time unattended planting liquid supply, the invention discloses a planting auxiliary device which comprises a liquid storage container body and an integrated liquid supply assembly, and belongs to the field of planting devices. The liquid storage container body is provided with a surrounding or semi-surrounding hollow penetrating type structure to form a hollow space for vertically arranging the planting pots side by side; the upper opening is used for ventilating, adding or extracting planting liquid; a hanging hook, a supporting leg, scale marks, a handle, a partition plate and other components can be selectively arranged. The liquid storage container body can also integrate a water absorption rope, a capillary rod, an intelligent liquid supply device and other components. The problems of planting liquid storage and supply under the unmanned condition for a long time can be solved, a large placing space cannot be occupied, drainage and ventilation of the planting pot cannot be disturbed, and the problems that the water content of the bottom of soil is too high, and roots are rotted due to liquid supply from the bottom can be effectively solved by vertically arranging the planting pot side by side.

The invention relates to the technical field of image detection, in particular to a pest and disease identification method and system based on unmanned aerial vehicle remote sensing. The method comprises the following steps: acquiring health indexes of each plant; marking suspicious points; spraying preset hormones to the suspicious points; after a first preset time interval, obtaining the health index of the hormone-induced plant again, and distinguishing whether the plant is pathological abnormality or physiological abnormality according to the change of the health index; on the basis of the pathology and physiology distinguishing result, a definite diagnosis threshold value in a preset range of the suspicious point is adjusted, so that when the plant at the suspicious point is pathologically abnormal and the health indexes of other plants in the preset range adjacent to the suspicious point are abnormal, the condition that the other plants are pathologically abnormal can be detected more sensitively; and using the adjusted pest and disease damage early warning threshold value to identify pest and disease damage conditions of plants of which suspicious points are adjacent to a preset range. According to the invention, the pest and disease states of crops can be detected more accurately.