71 results about "Greenhouse crops" patented technology

The invention relates to the technical field of crop transpiration calculation, and particularly discloses a greenhouse crop transpiration calculation method based on an improved Penman-Monteith model, which comprises the following steps of: researching convection types in a greenhouse under different ventilation by setting a ventilation mode of the greenhouse; an improved calculation method for an aerodynamic resistance parameter ra and a canopy resistance parameter rc is obtained according to a convection type in combination with meteorological data and plant growth data in a greenhouse, and the improved calculation method is combined with a Penman-Monteith model applied to greenhouse crop ET simulation to obtain an improved greenhouse crop transpiration calculation model. After verification, the model is proved to have relatively high simulation precision; the improved Penman-Monteih greenhouse crop transpiration calculation model is used for predicting the transpiration of the greenhouse tomatoes in different growth periods and comparing the transpiration with the measured value, the influence degree of ventilation on the water consumption of the greenhouse crops in different growth periods can be determined, and the method has practical significance in guiding natural ventilation management of the greenhouse tomatoes in different growth periods.

The invention relates to the field of greenhouse planting, and discloses a method for calculating the irrigation volume of greenhouse tomato series harvest according to the liquid return volume and the weather condition, and the method comprises the following steps: data collection: collecting greenhouse environment data through monitoring equipment, including illumination cumulant, air temperature, relative humidity and rainfall, and matrix humidity data, comprise the maximum weight, the minimum weight and the liquid return amount of the matrix; and theoretical irrigation volume calculation: calculating the theoretical irrigation volume for tomato series harvesting based on the illumination cumulant and the environmental factors. According to the method, the multi-dimensional data is combined with the dynamic adjustment strategy, so that precise irrigation is realized, and the resource utilization efficiency is optimized; through a real-time feedback and optimization mechanism, the environment change is dynamically adapted, and the response capability of the irrigation system is improved; the crop yield and quality are guaranteed; water and fertilizer integrated expansion is supported, and the device adapts to various greenhouse crops; and through abnormity monitoring and long-term optimization, the reliability and adaptability of the system are ensured.

The invention provides a greenhouse production model construction method and device based on mechanism model mapping. The method comprises the following steps: acquiring initial crop state data, initial greenhouse environment state data, a greenhouse control input sequence and an outdoor environment state sequence of a greenhouse; inputting the initial crop state data, the initial greenhouse environment state data, a greenhouse control input sequence and an outdoor environment state sequence into a greenhouse crop production system mechanism model to obtain a crop state sequence and a greenhouse environment state sequence, large-scale acquisition of crop growth data and greenhouse environment data in the greenhouse is realized in a low-cost mode; a data set is constructed based on the crop state sequence, the greenhouse environment state sequence, the greenhouse control input sequence and the outdoor environment state sequence to train a neural network model, and a greenhouse crop production system data model for predicting the crop state and the greenhouse environment state at the next moment is obtained. Accurate construction of the greenhouse crop production system data model is realized.

The invention provides a greenhouse crop habitat optimization method, system and device and a storage medium, and belongs to the technical field of intelligent agriculture, and the method comprises the steps: continuously obtaining greenhouse internal environment multi-element data, greenhouse external meteorological data, crop root zone current soil moisture data and device state data; predicting greenhouse internal environment multi-element data and soil moisture content of different soil layers in a future time period based on the data; predicting photosynthetic physiological habitat conditions of crops in the greenhouse in the future time period based on the multi-element data of the internal environment of the greenhouse in the future time period and soil moisture contents of different soil layers in the crop root zone; and taking the predicted habitat condition as an optimization target, performing optimization decision on current irrigation and environment multi-element regulation and control, generating a control scheme, further generating a regulation and control signal, and controlling greenhouse terminal equipment to operate according to the regulation and control signal. According to the invention, the accuracy, real-time performance, collaboration and intelligent level of greenhouse environment regulation and irrigation management are obviously improved, and the crop yield, quality and resource utilization efficiency are further improved.

The present invention provides an intelligent adjustment method and system for the growth environment of greenhouse crops, which relates to the technical field of intelligent adjustment and includes: obtaining the current temperature parameters, humidity parameters and light parameters of greenhouse crops as the current environmental parameter set, obtaining the adjustment feasible region according to the environmental parameter set within a preset historical time range, constructing a fitness function according to cost and growth conditions, setting constraint conditions for environmental parameter optimization to obtain the optimal environmental parameter set, wherein, based on image processing recognition, obtaining the growth conditions of greenhouse crops, and using the optimal environmental parameter set to adjust the environmental parameters in the growth environment. The present invention solves the technical problems existing in the traditional method for adjusting the growth environment of greenhouse crops, such as relying on manual adjustment, being easily affected by subjective factors, resulting in low efficiency and high cost, and at the same time being unable to meet the development needs of modern agriculture for high efficiency and intelligence.

The invention relates to a facility crop photosynthetic potential prediction method and system based on spectral characteristics, and the method comprises the steps: obtaining sample data through setting different illumination gradient culture environments, carrying out the conversion preprocessing of data through a standard normal variable, extracting a characteristic wavelength through employing a competitive adaptive reweighting algorithm and a continuous projection method, and carrying out the prediction of the photosynthetic potential of a facility crop. And establishing a prediction model by using a regression type support vector machine algorithm to predict the photosynthetic potential of the crops. The prediction system comprises a main control processing unit, a driving light source unit, a reflected light detection unit, a power supply unit, a communication unit, a control software unit, a display unit and the like. The main control processing unit controls operation of all parts and processes data, the light source unit is driven to provide detection light, the reflected light detection unit detects light intensity and converts and processes signals, the communication unit uploads data, and the control software and the display unit calculate and display results. According to the method, the photosynthetic potential of facility crops can be rapidly and accurately evaluated at low cost, a scientific basis is provided for agricultural production, and crop growth state monitoring is facilitated.

The invention discloses a greenhouse closed-loop energy-saving heat supply system based on biological waste fermentation, and relates to the crossing field of agricultural intelligent planting and waste resource utilization, the system comprises the following components: a fermentation unit, a biogas collection and utilization module, a waste heat and fertilizer recovery module and an intelligent management and control system; biogas is generated through fermentation of biological waste, heat generated by combustion of the biogas is used for supplying heat to a greenhouse and a living room, meanwhile, waste heat generated in the fermentation process is recycled for auxiliary heat supply, and the energy utilization efficiency is remarkably improved; according to the invention, residues after fermentation can be converted into a decomposed organic fertilizer for greenhouse crops to use, so that cyclic utilization of resources is realized, the use amount of chemical fertilizer is reduced, the production cost is reduced, and meanwhile, environmental protection is facilitated.

1. The name of the design product: cyclone air cooler. 2. The use of the design product: to release to realize yield increase and quality improvement for greenhouse crops. 3. The design points of the design product: in the perspective view. 4. The picture or photo that best indicates the design points: perspective view. 5. The bottom of the design product is not easy to see or not visible during use, omit the top view.

The invention relates to the field of greenhouse operation management and control, and provides a greenhouse operation management and control method, device and equipment, a medium and a computer program product, and the method comprises the steps: receiving crop visual information and environment information sent by greenhouse monitoring equipment; inputting the crop visual information and the environment information into a greenhouse crop planting knowledge graph to obtain a greenhouse operation management and control macroscopic decision; inputting the greenhouse operation management and control macroscopic decision into a greenhouse model to obtain an operation decision result output by the greenhouse model; the greenhouse model is obtained based on historical greenhouse operation data training. On the basis of the received crop visual information and environment information, the crop visual information and the environment information are analyzed through the established greenhouse crop planting knowledge graph, a greenhouse operation management and control macroscopic decision is obtained, the greenhouse operation management and control macroscopic decision is further combined with a greenhouse model obtained based on historical greenhouse operation data training, and a greenhouse operation management and control result is obtained. Therefore, the accuracy and efficiency of greenhouse operation management and control are improved.

The invention belongs to the technical field of agricultural intellectualization, and provides a multi-angle and multi-strategy-based greenhouse crop production environment monitoring control method, which comprises the following steps: collecting environment and soil crop data to construct a matrix and pre-processing the matrix; extracting time sequence characteristics by adopting Res-BiLSTM, and constructing a yield prediction model in combination with the improved XGBoost; integrating multi-dimensional features to construct a feature matrix, completing standardization, and determining an optimal cluster number and a cluster affiliation label by adopting an improved K-means clustering algorithm; for each cluster, nonlinear features are extracted through improved SVR, and a temperature and humidity prediction model is constructed by combining with a GBDT model fitting residual error; the key parameters of the model are optimized by adopting Chebyshev chaotic mapping for the CEO algorithm; and a layered cooperative regulation and control mechanism of MPC global optimization and feedforward PID real-time correction is adopted. According to the control method, multi-source data acquisition, precise prediction model construction and a layered cooperative regulation mechanism are integrated, precise monitoring and dynamic regulation of the greenhouse environment are realized, and the crop yield and quality stability are improved.

The invention relates to the technical field of crop patrol, and discloses a greenhouse crop patrol robot system comprising a patrol robot configured to cruise along a preset path in a greenhouse and collect crop images and environmental parameters; the cloud server is configured to receive the data uploaded by the patrol robot and execute image recognition and environment data analysis; the remote management terminal is configured to display the data and early warning information processed by the cloud server in real time; and the patrol robot, the cloud server and the remote management terminal are interconnected through the wireless communication module to form a closed-loop management architecture. According to the patrol robot system for the greenhouse crops, automatic, high-precision and datamation closed-loop management and control are achieved, the efficiency and yield of greenhouse planting can be remarkably improved, and powerful technical support is provided for development of intelligent agriculture.

1. The name of the design product: irrigator. 2. The use of the design product: used as a walkable irrigator installed in a greenhouse, for spraying greenhouse crops. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention discloses a greenhouse crop disease image segmentation method and system, relates to the technical field of image processing of ground scenes, solves the problems of low segmentation precision and the like in agricultural scenes with complex disease spot forms and the like in the prior art, and improves the segmentation precision, the processing speed and the robustness. Disease images of greenhouse crop disease plants are obtained and preprocessed; performing graying and non-local mean filtering processing on the disease image to obtain a two-dimensional histogram; taking the maximized two-dimensional Kapur entropy function as a target function, and segmenting the two-dimensional histogram by using a Kapur entropy threshold method to obtain an initial threshold set; searching the initial threshold value set by utilizing an improved rime algorithm to obtain an optimal threshold value set; and carrying out multi-threshold segmentation to obtain a disease image in which a lesion area is segmented, and completing greenhouse crop disease image segmentation. The method is suitable for processing strawberry disease images in the field of greenhouse crop disease image processing.

The utility model belongs to the technical field of greenhouse pesticide spraying, and discloses an automatic pesticide spraying device for a greenhouse, which comprises a support, a pesticide box is arranged at one end in the support, a weighing mechanism is directly arranged on the pesticide box and the inner bottom surface of the support, and a battery is fixedly arranged at the other end in the support close to the pesticide box. A spraying device is arranged at the end, close to the water pump, of the outer portion of the support, the spraying device is communicated with the water pump, and a driving device for driving the spraying device to operate is arranged at the position, close to the spraying device, of the support; a swinging head position sensor is arranged on the inner wall of the support corresponding to the spraying device, an electric control system is arranged in the support and located above the water pump, a walking mechanism is arranged on the upper portion of the support, and a position detection sensor is further arranged on the walking mechanism; according to the utility model, full-automatic pesticide spraying can be realized in the pesticide spraying process of greenhouse crops, the pesticide dosage can be monitored, and the use effect is improved.

The present invention relates to the field of intelligent agriculture technology, and specifically relates to an intelligent greenhouse crop growth status monitoring and management system based on the Internet of Things, which includes a multi-source perception module, a spatio-temporal calibration module, a physiological parameter calculation module, a growth coupling analysis module, a regulation decision-making module, and a closed-loop execution module; among which: The multi-source perception module: collects canopy spectral data, stem pressure fluctuation data, and root conductivity data; The spatio-temporal calibration module: is used for spatio-temporal alignment; The physiological parameter calculation module: calculates the effective root activity in combination with the root conductivity data; The growth coupling analysis module: dynamically calculates the growth coordination index value; The regulation decision-making module: is used to generate a regulation instruction set; The closed-loop execution module: is used to dynamically correct the parameters of the regulation instructions. The present invention realizes precise environmental regulation based on the real-time growth status of crops through multi-source perception, dynamic calculation, and a closed-loop feedback mechanism, and improves the resource utilization efficiency.

The invention discloses a greenhouse disease propagation monitoring and optimizing system based on a physical information neural network. The method belongs to the cross technical field of intelligent agriculture and artificial intelligence. The technical problem that a conventional mechanism model-based method and a pure data-driven machine learning method are difficult to deal with a complex and dynamically changing greenhouse environment is solved. The system comprises a multi-mode sensor module which is used for monitoring greenhouse environment data in real time, obtaining greenhouse crop images in real time and inputting the information into an edge calculation module; the edge calculation module is used for defining a multi-stage disease propagation physical model, designing a physical information neural network architecture and defining a loss function of a physical information neural network based on the multi-stage disease propagation physical model; the decision module is used for carrying out severity level division on the predicted disease degree and generating a dynamic regulation and control parameter regulation instruction according to different severity levels; and the optimization module is used for receiving the instruction for dynamically adjusting the regulation and control parameters and regulating and controlling the greenhouse environment.

The invention relates to the technical field of agricultural meteorological early warning, and discloses a greenhouse crop meteorological early warning system based on artificial intelligence. The system comprises a data acquisition module, a data analysis module, a model training module, an early warning generation module, a strategy adjustment module and a feedback verification module. The data acquisition module optimizes an acquisition process and acquires parameters such as air temperature and humidity; the data analysis module obtains an analysis result through sliding window statistics; the model training module predicts model parameters and rules through particle swarm optimization; the early warning generation module combines a genetic algorithm to calculate a meteorological risk and converts the meteorological risk into an early warning control signal; the strategy adjusting module automatically adjusts an early warning strategy through dynamic planning and a branch and bound method; and the feedback verification module verifies the data through Bayesian filtering and feeds back and corrects the data. According to the system, intelligent early warning and strategy optimization of greenhouse meteorological risks are realized, the early warning accuracy and timeliness are improved, the system adapts to dynamic changes of a greenhouse environment, and reliable guarantee is provided for growth of greenhouse crops.

The present invention relates to a method for improving the growth environment of greenhouse crops, in which soil around crops or around places in which the crops are to be planted is finely crushed by a subsoiler in a state in which the crops are planted in the soil or before the crops are planted, a plurality of through-holes deeper than the root depth of the crops are formed at regular intervals around the crops or around the places in which the crops are to be planted by using a through-hole drilling tool or an air supply pipe of the subsoiler, and water pipes connected to a water tank are inserted into the through-holes so as to reach the ground, and then supplied with water so that the water flows out from the bottom of the through-holes to form a wide water retention layer under the roots. The method can provide not only stable growth of the crops but also sufficient water, oxygen, and nutrients, and minimizes the humidity in indoor air, thereby creating the most suitable environment for crop growth.

The invention discloses an ozone atomization sprayer for preventing and treating powdery mildew of greenhouse crops, which comprises a moving mechanism, a water suction pump, a controller, a support frame, swing arms, a clamping mechanism, a spray pipe, an atomization piece and an elastic traction mechanism, the moving mechanism is provided with the water suction pump, the controller and the support frame, and the left and right parts of the support frame are respectively provided with the swing arms; clamping mechanisms are installed at the ends, away from the supporting frame, of the two swing arms, and the two swing arms can controllably drive the two clamping mechanisms to swing left and right correspondingly. When the device is used, due to the fact that the clamping mechanisms have the height difference, the two ends of the spray pipe also have the height difference, when the two swing arms swing away from each other, the clamping mechanisms can pull the spray pipe to tend to be straight, at the moment, the moving mechanism drives the supporting frame to move up and down, and meanwhile the water suction pump is controlled to suck ozone water to supply the ozone water to the spray pipe; and when the swing arms are controlled to swing close to each other, the middle parts of the spray pipes droop and are loosened.

The invention relates to the technical field of facility environment regulation and control and greenhouse energy saving, and provides a greenhouse environment comprehensive regulation and control system based on multi-source heat storage and release and a greenhouse. A greenhouse environment comprehensive regulation and control system based on multi-source heat storage and release is used for regulating the temperature in a greenhouse and comprises a wet curtain ventilation and underground heat exchange device, a solar hot water soil heat collection device, a water body passive heat storage and release device, a heat storage wall and control equipment. The greenhouse environment comprehensive regulation and control system based on multi-source heat storage and release can solve the problems that an existing greenhouse is insufficient in heat storage capacity, low in photo-thermal resource utilization efficiency, poor in temperature regulation and control effect and difficult to guarantee annual efficient and high-quality production of greenhouse crops.

This invention discloses a greenhouse environment control system and method based on crop organ phenotypic information, belonging to the field of greenhouse environment control technology. The method includes: acquiring historical datasets and weather forecast data; constructing a greenhouse environment prediction model; inputting the historical datasets and weather forecast data into the greenhouse environment prediction model to obtain greenhouse environmental data for the next 24 hours; constructing a crop growth prediction model; combining current environmental information and crop organ phenotypic growth information from the previous 7 days to predict crop organ phenotypic growth information to obtain predicted crop growth values; obtaining crop target values; acquiring actual crop growth values ​​using a crop organ phenotypic information acquisition platform and comparing them with the predicted values ​​to obtain the difference; determining whether to adjust the crop target values ​​based on the difference, and thus adjusting greenhouse environmental parameters. This invention incorporates crop organ phenotypic information feedback into greenhouse environment optimization and control technology, improving the yield and quality of greenhouse crops.

The invention discloses a rural household energy supply method and system and a fire wall. The system constructs a comprehensive energy system framework of a rural planting and breeding combined mode based on biological marsh gas energy, distributed photovoltaic power supply (light energy), air energy and the fire wall. One part of the biogas serving as driving energy is used for burning and heating the fire wall to supply heat to the greenhouse, and the other part is used for daily cooking of farmers; solar power generation drives the heat pump to produce hot water, one part of the hot water is used for heating farmer residential areas and supplying domestic hot water, and the other part of the hot water is used for enhancing the heating effect of a fire wall. According to the comprehensive energy system constructed by the invention, electricity utilization and heat supply of farmers can be met in a clean and low-carbon manner, and the yield of crops in the greenhouse can be increased at the same time. The light-gas synergistic ecological agricultural system provided by the invention realizes sustainable agricultural development with low carbon emission, low cost, high yield and resource circulation, and has important significance for constructing a clean and low-carbon energy system in rural areas in the future.

The utility model relates to the technical field of agriculture, and discloses a pesticide spraying device for disinsection of greenhouse crops, which comprises a machine body, a signal receiver is fixedly assembled at the top of the machine body, one end of a connecting rod is mounted on the outer wall of the machine body, and a propeller is mounted at the other end of the connecting rod. A supporting spraying frame is fixedly installed at the bottom of the connecting rod, a deinsectization and insecticide spraying assembly is arranged at the bottom of the machine body, and a ventilation groove is formed in the outer wall of the machine body. According to the pesticide spraying device for disinsection of the greenhouse crops, by remotely controlling the terminal controller, the motor can start the cabinet, so that the motor can pump disinsection pesticide liquid on the inner wall of the box body to the inner wall of the first liquid outlet pipe and the inner wall of the second liquid outlet pipe, and finally the pesticide liquid is dispersed into fine mist points through the spraying head to be evenly sprayed to the greenhouse crops; the device can adapt to greenhouse crops with different heights, and is high in practicability, convenient to operate remotely and high in convenience.

The application relates to the technical field of facility environment regulation and greenhouse energy saving, and provides a greenhouse environment comprehensive regulation system based on multi-source heat storage and release and a greenhouse. The greenhouse environment comprehensive regulation system based on multi-source heat storage and release is used for regulating the temperature in the greenhouse and comprises a wet curtain ventilation and ground heat exchange device, a solar water-soil heat collection device, a water body passive heat storage and release device, a heat storage wall and a control equipment. The greenhouse environment comprehensive regulation system based on multi-source heat storage and release can solve the problems that the existing greenhouse has insufficient heat storage capacity, low light and heat resource utilization efficiency, poor temperature regulation effect and difficulty in guaranteeing the year-round efficient and high-quality production of the greenhouse crops.

The utility model relates to an irrigation device, belongs to the technical field of greenhouse agricultural irrigation, and particularly relates to an automatic irrigation device for a greenhouse. The device comprises a transverse pipe which is suspended at the indoor top through a lifting hook, and one end is connected with a water inlet pipe. The drainage pipes are distributed on the transverse pipe in the length direction at equal intervals, lower end outlets of the drainage pipes are vertically downward, the irrigation nozzle mechanism is connected to the lower portions of the drainage pipes through hoses, and the supporting assembly is located at the bottom of the irrigation nozzle mechanism. The irrigation nozzle mechanism is composed of an irrigation main pipe, a conveying pipe which rotates in an annular mode and is distributed upwards and an atomizing nozzle which is detachably connected to the conveying pipe. The device achieves the effect of spraying and irrigating greenhouse crops from bottom to top in all directions, and solves the problems of non-uniform irrigation and low efficiency caused by shielding of plant branches and leaves in a traditional irrigation mode.

The utility model relates to the technical field of greenhouse light supplementing equipment, in particular to LED lamp light supplementing equipment for greenhouse crops. The LED lamp light supplementing equipment for the greenhouse crops comprises a greenhouse support, lifting assemblies, lamplight rods and light supplementing supports, wherein the greenhouse support is provided with supporting frames at intervals, the supporting frames are connected through supporting rods, the lifting assemblies are arranged on the supporting rods at intervals, the lamplight rods are arranged on the lifting assemblies, and the light supplementing supports are arranged on the lamplight rods at intervals and are in sliding connection with the lamplight rods. The multiple lifting assemblies are arranged in the greenhouse support, the lamplight illumination range and temperature are controlled by controlling the lamplight rod to ascend and descend, the adjustable light supplementing supports are arranged on the lamplight rod at intervals, when the positions of the light supplementing supports need to be moved, the clamping assemblies at the top are opened, the abutting pieces are made to be separated from the lamplight rod, and under the assistance of the idler wheels on the two sides, the light supplementing supports can be adjusted. The lamplight support can move freely along the lamplight rod, the mode of adjusting the lamplight position is simple and rapid, and a worker can achieve rapid adjustment without going to the high position of a greenhouse.

This application provides a method and related equipment for greenhouse control command decision-making, belonging to the field of greenhouse automatic control technology. The method includes: performing environmental deviation analysis based on various environmental indicator data within the greenhouse to determine environmental deviation results; the environmental deviation results include the deviation degree of each environmental indicator data; detecting control conflicts based on the environmental deviation results, and, in the presence of control conflicts, identifying the crop growth stage based on greenhouse crop images to obtain the current crop growth stage; querying indicator weights based on the crop growth stage to obtain the control weights of each conflicting indicator; determining the priority indicator score of the conflicting indicator based on the control weight and deviation degree of the conflicting indicator; and making a priority adjustment decision for each conflicting indicator based on the priority indicator score to determine the greenhouse control command. This application can improve the efficiency and effectiveness of greenhouse environmental control.

The application provides a greenhouse environment regulation method and system, electronic equipment and storage medium, and belongs to the technical field of agricultural automatic control. The method comprises the following steps: acquiring indoor temperature of a greenhouse at a first time and target temperature at the first time; the target temperature at the first time is determined based on a crop type planted in the greenhouse, a latitude where the greenhouse is located, a time period to which the first time belongs, and average outdoor temperature of a target time period before the first time; based on a comparison result of the indoor temperature at the first time and the target temperature at the first time, each execution device of the greenhouse is controlled to act in a multi-level sequential rolling regulation mode, and the multi-level sequential rolling regulation mode is used for rolling regulation of temperature and humidity balance in the greenhouse. The application can greatly reduce energy consumption of the greenhouse, and meanwhile, realizes fine greenhouse environment automatic regulation mode, and can provide a high-quality growth environment for greenhouse crops.

The utility model relates to the technical field of monitoring equipment, in particular to a greenhouse crop growth environment recording and monitoring device which comprises a soil monitoring assembly, the soil monitoring assembly comprises a controller, a multi-section telescopic rod is fixed to the bottom of a shell of the controller, and a soil sensor is installed at the telescopic end of the multi-section telescopic rod; and the cleaning mechanism comprises a fixing ring, the fixing ring is coaxially fixed to the multi-section telescopic rod, rotating shafts are rotationally installed on the two sides of the fixing ring correspondingly, fixing plates are fixed to one ends of the rotating shafts, the two fixing plates are jointly rotationally provided with a brush roller, and a third servo motor is fixed to one fixing plate. After the soil sensor detects the soil, the soil sensor is pulled back through the multi-section electric telescopic rod, and after the soil sensor is pulled back, the brush roller in the cleaning mechanism cleans the contact end of the soil sensor, so that the accuracy of the soil sensor for detecting the soil in the next area is ensured.

The present invention discloses a method for classifying airborne disease spores of greenhouse crops based on microscopic polarization image features, which is applied to the technical field of classifying and identifying airborne disease spores, and includes: preprocessing the microscopic polarization image of airborne disease spores by using the Stokes vector method to obtain the polarization degree image and polarization angle image of airborne disease spores; adopting Gabor transform to convert the polarization angle image from the spatial domain to the frequency domain, extracting the texture features of the polarization angle image, and jointly using the relative light intensity distribution value of the polarization degree image as the input of the neural network to train and obtain an airborne disease spore classification model; inputting the image to be measured into the airborne disease spore classification model to obtain a classification result. The present invention can effectively reduce the interference of external environmental light, improve the recognition rate of disease spores with similar morphologies, and effectively improve the classification and recognition accuracy of airborne disease spores.