1343 results about "Agricultural irrigation" patented technology

The invention discloses a water-saving control method for agricultural irrigation, a cloud platform and equipment, and relates to the technical field of irrigation water-saving control, and the method comprises the steps: determining the historical rainfall of the geographic position of a target farmland and the historical soil moisture content parameter of the target farmland; determining farmland water demand rule characteristics of the target farmland based on the historical rainfall and the historical soil moisture content parameters; constructing a farmland water-saving control model according to the farmland water demand rule characteristics; dividing a water demand area of the target farmland based on the crop information; based on the farmland water-saving control model and the soil moisture content parameter of each water demand area, obtaining a predicted irrigation value of each water demand area; acquiring a real-time irrigation value of each water demand area; and based on the predicted irrigation value and the real-time irrigation value, performing real-time regulation and control on a preset intelligent irrigation water valve in each water demand area. The problem that the utilization rate of water resources is low can be effectively solved.

The present invention relates to the technical field of agricultural irrigation. Disclosed are an intelligent irrigation strategy formulation method and system. The method comprises: determining the current irrigation strategy on the basis of a preset irrigation decision-making model and a Q-learning intelligent agent and according to the current agricultural state; on the basis of the current irrigation strategy, performing irrigation simulation on a target growing region to obtain a corresponding irrigation reward value and the next agricultural state, wherein the irrigation reward value is determined on the basis of the crop yield, the crop water demand, and the annual economic cost after irrigation, the current agricultural state, the current irrigation strategy, the irrigation reward value, and the next agricultural state form an empirical four-tuple, and a plurality of empirical four-tuples form an experience pool; and randomly sampling the empirical four-tuple from the experience pool as a training sample to train the Q-learning intelligent agent so as to obtain an optimal irrigation Q-value table which is used for determining a corresponding optimal irrigation strategy on the basis of any agricultural state of the target growing region. The present invention can efficiently obtain an accurate irrigation strategy.

The invention provides a dynamic self-optimization and adaptive learning method for a large model of a water conservancy system, and the method comprises the steps: data collection and preprocessing, model construction and initialization, real-time monitoring and model evaluation, difference analysis and adaptive adjustment strategy generation, model updating and optimization, continuous learning and knowledge accumulation, etc. According to the method, through dynamic data driving, intelligent difference analysis and self-adaptive optimization, conversion of a water conservancy system model from static passive to dynamic active is realized. Compared with the prior art, the method has accuracy, real-time performance, economical efficiency and sustainability, provides a landing technical path for intelligent upgrading of a water conservancy system, and has wide application potential in the fields of flood control and disaster reduction, agricultural irrigation, clean energy production and the like.

The invention discloses an agricultural irrigation area water resource intelligent management system and method, and relates to the field of intelligent management, and the method comprises the steps: building a correlation model of a crop growth stage and a basic irrigation threshold value through real-time collection of original weather station data, future 24-hour weather forecast, crop types, planting dates and other multi-dimensional data; and in combination with soil humidity sensor data and a channel pump station state, the basic irrigation starting threshold is dynamically adjusted by using an FAO formula or a deep learning algorithm to form a dynamic irrigation decision threshold. And then multi-source data is input into an irrigation decision module, an irrigation starting and stopping instruction is generated by judging the relation between the irrigation state and the soil humidity threshold value, and closed-loop management is achieved. Thus, the limitation of traditional irrigation static threshold management is broken through, and through meteorological data dynamic adaptation and multi-source data fusion decision making, on the premise of guaranteeing crop growth water demand, the water resource allocation efficiency is optimized, and the intelligent management level of an agricultural irrigation area is improved.

The invention relates to the technical field of agricultural irrigation, and particularly discloses a farmland irrigation control method and system, and the method comprises the steps: constructing a multi-sensor fusion monitoring network, and collecting soil, weather and plant physiological data in real time; transmitting data to an edge computing node through LoRa wireless communication; utilizing a lightweight neural network model deployed by edge computing nodes to calculate and predict crop water demand and accurate irrigation volume in combination with evapotranspiration; the irrigation strategy is executed through the intelligent irrigation execution system; and remote monitoring and abnormity alarm are realized by means of a remote monitoring and management platform based on WebGIS. Precise and intelligent management of farmland irrigation is realized, the utilization rate of water resources and fertilizers can be effectively improved, irrigation abnormity can be timely handled, the labor management cost is reduced, and the growth requirements of crops are guaranteed.

The invention relates to the technical field of soil physical property detection, in particular to a soil moisture content intelligent monitoring control method and system, and the method comprises the steps: multi-modal sensor data collection: deploying a multi-modal sensor array in a to-be-detected soil area; interference compensation and correction; self-adaptive calibration is carried out; water phase state distinguishing and soil moisture content index calculation; 4, soil moisture content evaluation: comprehensively evaluating the actual water content, the effective water content, the soil moisture content index and the water phase state information obtained in the step 4, and setting different grade threshold values to obtain a soil moisture content evaluation result; and intelligent control decision and execution: taking the soil moisture content evaluation result as input, and generating a corresponding control decision. The intelligent monitoring and controlling system for the soil moisture content can monitor the soil moisture condition in real time and can improve the precision and efficiency of agricultural irrigation through intelligent compensation, calibration and decision optimization, and therefore the purposes of water saving and efficient crop management are achieved.

The invention discloses an intelligent agricultural water-saving irrigation system and a control method, and relates to the technical field of agricultural irrigation. Comprising the following steps: a land area planning module performs equal-area division on a farmland, sets a detection node array, and monitors water retention conditions of different soil depths; the moisture gradient characterization module calculates the vertical moisture gradient and the direction of the vertical moisture gradient of the evaluation area in real time through edge calculation. And the irrigation water amount correction module fuses and generates a target water-holding capacity based on the leaf stomatal conductance signal and the moisture gradient. The irrigation circulation termination control module uses pulse type infiltrating irrigation, and sets double termination conditions of the water-holding capacity change rate and the permeability. The closed-loop feedback adjustment module detects the soil water content after irrigation, characterizes the water leakage risk and feeds back and adjusts the irrigation water amount, closed-loop control is formed, and effective utilization of water resources is ensured.

The invention belongs to the field of water resources and water ecological protection, and aims to provide a water resource collaborative configuration reservoir ecological flow checking and scheduling method, so as to scientifically and reasonably check the ecological flow target, realize coordinated management of reservoir water supply, ecological protection and agricultural irrigation, and effectively improve the comprehensive utilization efficiency of the water resources. According to the technical scheme, the method comprises the steps of 1, analyzing and determining a downstream influence river reach of a reservoir project, investigating the distribution condition of ecological protection objects in the downstream influence river reach, and further analyzing ecological protection requirements; 2, calculating ecological flow targets step by step according to ecological protection requirements of various protection objects in the reservoir project influence river reach; 3, carrying out multi-functional reservoir water resource collaborative configuration, and comprehensively determining a reservoir ecological flow target; and 4, optimal scheduling of the ecological flow of the multifunctional reservoir. On the basis of the water resource collaborative configuration result of the multifunctional reservoir, the ecological flow scheduling rule of the multifunctional reservoir is perfected by formulating a coordination degree mechanism of ecological, living, industrial, agricultural and other industries.

The invention provides an intelligent agricultural irrigation optimization method and system, and relates to the technical field of agricultural management. The method comprises the following steps: acquiring first irrigation monitoring data of a plurality of sub-irrigation areas in a target planting area, calculating a temperature influence parameter and a humidity influence parameter of each sub-irrigation area, and constructing an irrigation feature vector of each sub-irrigation area; clustering the plurality of sub-irrigation areas to construct a plurality of irrigation area sets, calculating a water demand urgency factor of each irrigation area set and optimizing an initial irrigation scheme to obtain a first target irrigation scheme, and collecting second irrigation monitoring data of the plurality of sub-irrigation areas, and calculating an irrigation gain parameter of each irrigation area set, and optimizing the first target irrigation scheme to generate a second target irrigation scheme. According to the invention, accurate and efficient irrigation water distribution is realized.

The invention relates to the technical field of intelligent agriculture and precise irrigation, in particular to an intelligent control system for agricultural irrigation. Comprising a water-saving valve module, a sensing layer module, a control layer module, an execution layer module and a data and application layer module, and the water-saving valve module is used for achieving microsecond level flow regulation and control through piezoelectric ceramic driving and energy recovery and integrating a self-maintenance function. According to the invention, the LSTM network and the Duelling DQN algorithm are utilized to accurately discriminate the soil type and formulate an extreme weather coping scheme, dynamic optimization of an irrigation strategy is realized based on low-power-consumption edge calculation and an intelligent control algorithm, the adaptability and decision accuracy of the system are greatly improved, multiple advanced technologies are integrated, and the system is suitable for large-scale popularization and application. Comprising a magneto-rheological buffer, a TSN valve controller, an SMA emergency pressure release valve and a variable frequency water pump driver, pressure balance of a pipe network, high-precision synchronization of valves and safe treatment of sudden failures are ensured, and the stability and flexibility of an irrigation system are comprehensively improved.

The invention discloses an agricultural irrigation control method and system, and relates to the technical field of irrigation control, and the method comprises the following steps: constructing a crop water demand model based on the fusion of crop physiological sensing data and a data driving model, and outputting a target irrigation flow; calculating a control error between the target irrigation flow and the actually acquired flow, and generating a control signal through a model prediction control strategy; inputting a static mapping model fitted by a Sigmoid function, and superposing the output of a dynamic correction model driven by state sensing data to generate a final driving signal; feedback data is collected, a driving signal and the feedback data are subjected to closed-loop comparison, and irrigation control strategy parameters are adaptively optimized through a reinforcement learning controller; according to the method, the crop physiological sensing data and the data driving model are fused, the space and time sequence feature fused water demand model is dynamically constructed, and the problems that agricultural irrigation cannot be accurately controlled and the irrigation strategy is rigid are solved in combination with a static and dynamic composite control mapping mechanism.

An irrigation pipe network system layout optimization method, an apparatus, a medium, and a product, relating to the technical field of smart agricultural irrigation. The method comprises: acquiring a system state of a target rotational irrigation pipe network system at the current moment (S10); inputting the system state of the target rotational irrigation pipe network system at the current moment into a trained deep Q network mode to obtain a control action at the current moment, wherein the process of determining the trained deep Q network model comprises: pre-training a deep Q network model on the basis of a virtual rotational irrigation pipe network system, and then re-training a preliminarily trained deep Q network model on the basis of a real rotational irrigation pipe network system (S20); and optimizing the target rotational irrigation pipe network system on the basis of the control action at the current moment (S30). In the method, the deep Q network model is pre-trained and re-trained by using the virtual rotational irrigation pipe network system and the real rotational irrigation pipe network system, thereby ultimately optimizing the target rotational irrigation pipe network system on the basis of the trained deep Q network model.

The invention relates to the technical field of agricultural irrigation, in particular to an intelligent biological irrigation system and method based on remote control, and the system comprises a biological sensing unit, a neural computing decision engine, a driving execution unit, and a communication optimization architecture. Wherein the biological sensing unit is used for monitoring multi-modal data of plant physiological status, rhizosphere microenvironment and meteorological parameters in real time; the neural computing decision engine is used for constructing a pulse neural network, fusing a plant dimensional management system signal transduction mechanism and a multi-agent optimization algorithm, and generating a millisecond-level dynamic irrigation strategy; the driving execution unit is used for millimeter-level water quantity adjustment and pipe network self-repairing of the irrigation execution unit; the communication optimization architecture is used for seamless coverage and secure transmission of irrigation data, and meanwhile, a strategy is optimized by applying algorithms such as reinforcement learning and the like. Therefore, the problems of water resource waste, poor irrigation effect, untimely irrigation strategy adjustment and the like in the prior art are solved.

The invention relates to a micro-spraying system irrigation uniformity control method and system, and belongs to the technical field of agricultural irrigation energy saving. Calculating the flow data of each nozzle according to the data of the flow meters of the branch pipes; calculating the pressure distribution of each node under the condition of no throttle valve by using the irrigation area pipe network hydraulic model, and finding out the part with too high or too low pressure in the pipe network; a throttle valve is installed on a main pipe of a pipe network in an irrigation area, and the opening degree of the throttle valve is adjusted and the pressure rise of a water pump is calculated by taking the most disadvantageous spray head in the pipe network as a pressure reference; the flow condition in the pipe network is monitored in real time through the flow meter, and data are uploaded; the pressure is calculated through the pipe network hydraulic model, when the water pressure in the pipe network is abnormal, the throttling valve needing to be adjusted and the opening degree are calculated, workers are informed, and early warning is conducted in time. The service life of the system is prolonged, and the irrigation efficiency and the water resource utilization rate are improved.

The invention provides an intelligent self-adaptive agricultural irrigation servo ball valve control system, which belongs to the technical field of irrigation control, and comprises a sensing layer, a control layer and an execution layer, the sensing layer is connected with the control layer, the control layer is connected with the execution layer, and the sensing layer comprises a soil parameter monitoring unit, a crop physiology monitoring unit and a space environment monitoring and prediction unit. The non-linear mapping relation between the light-temperature-humidity three-dimensional parameter space and the irrigation amount is established through the control layer, the water demand quantity of crops is accurately matched, meanwhile, the control precision of + / -2.5% of the irrigation amount is achieved, water data needed by plant growth are accurately analyzed by collecting the growth state, soil data and environment data of plants, and the water quality of the crops is improved. The water demand quantity control is more accurate, meanwhile, effect evaluation is carried out after irrigation, feedback data and timely adjustment opportunities are provided for later-stage control, and plant data of corresponding types can be set for learning to form a self-adaptive function of at least three types of crop growth models.

The invention relates to the technical field of GNSS-R remote sensing, in particular to a satellite-borne GNSS-R soil humidity fusion inversion method and system based on machine learning, and the method comprises the steps: obtaining multi-source data composed of satellite-borne GNSS-R internal feature value data and SMAP external auxiliary data; the method comprises the following steps: performing preprocessing based on acquired multi-source data, taking a matched data set as input to construct a machine learning inversion model, performing track point soil humidity inversion by using an optimized inversion model, performing grid point fixed weight fusion according to a track point soil humidity inversion value, calculating the weight of each GNSS system by using an improved self-adaptive CRITIC weight method, and calculating the weight of each GNSS system according to the weight of each GNSS system. And result verification and application are carried out based on the soil humidity inversion value of the grid point, weight-fixed fusion is carried out on the characteristic value of each GNSS system track point in each grid, abnormal value interference is effectively resisted, and the output continuous grid data can be directly adapted to agricultural irrigation zoning, hydrological model input, climate research and other business scenes.

A comprehensive power supply method for agricultural irrigation equipment relates to the technical field of agricultural irrigation equipment power supply, and comprises the following steps: constructing a comprehensive power supply unit which comprises wind power generation equipment, photovoltaic power generation equipment and energy storage equipment; defining a water pump motor in the irrigation equipment as a critical load, and defining other equipment in the irrigation equipment as non-critical loads; adopting an ARI MA model to obtain prediction data of wind speed and illumination intensity; calculating the predicted power generation power of the wind power generation equipment based on the wind speed prediction data, and calculating the predicted power generation power of the photovoltaic power generation equipment based on the illumination intensity prediction data; constructing a comprehensive power supply strategy model; according to the comprehensive power generation power of each device in the comprehensive power supply unit and the consumption power of the irrigation device, a power supply mode with high irrigation stability is dynamically selected after analysis of the comprehensive power supply strategy model; according to the dynamically selected power supply mode, power is supplied to the irrigation equipment through a bidirectional inverter; the problem that traditional irrigation equipment is unstable in operation is solved.

The invention relates to the technical field of agricultural irrigation, and discloses an intelligent agricultural water-saving irrigation and fertilization device which comprises an irrigation box, sliding rails, an irrigation assembly, a self-walking stirring assembly, a scraping and blowing assembly and a cylindrical filter part, the irrigation box is arranged on the two sliding rails, the cylindrical filter part is arranged in the irrigation box, the irrigation assembly is installed on one side of the irrigation box, and the self-walking stirring assembly is installed on the other side of the irrigation box. The spraying device is used for spraying water and fertilizer to crops; the self-walking stirring assembly comprises a rolling wheel, a rod type stirring piece and a driving piece. Water-soluble fertilizer water beads on the surfaces of seedlings are scraped and blown through the scraping and blowing assembly, water-soluble fertilizer attached to the surfaces of leaves and stalks of the seedlings can be effectively removed and shaken off to the bottoms of the seedlings, and therefore waste of the water-soluble fertilizer is reduced, meanwhile, the water-soluble fertilizer can directly act on root systems of the seedlings and is fully absorbed by crops, and the water-soluble fertilizer can be applied to the roots of the seedlings. The utilization rate of the water-soluble fertilizer is increased, and the problem of volatilization of nutritional ingredients caused by strong quick-acting property and short lasting period of the water-soluble fertilizer is reduced.

The invention discloses an intelligent accounting platform for agricultural water consumption, and relates to the technical field of agricultural Internet of Things. The agricultural water consumption intelligent accounting platform comprises a multi-sensor data acquisition module which is used for acquiring multi-dimensional data of an agricultural field environment in real time through multiple sensors, comprises at least one flowmeter, at least one soil humidity sensor and at least one meteorological sensor, and ensures that the acquired data is comprehensive and accurate; interference of external factors on data is eliminated, data reliability is ensured, normal operation and immediate response of the system can be ensured by edge calculation under the condition that a network is unstable, efficient closed loop from data acquisition to decision execution is realized, high efficiency and accuracy of agricultural irrigation in a complex environment are ensured, and the method is suitable for popularization and application. The problems that an irrigation plan cannot be matched with the actual water demand of crops and multi-dimensional changes of a field environment cannot be reflected in real time due to the fact that single flowmeter equipment cannot provide finer data are solved.

The invention relates to the technical field of agricultural irrigation, in particular to an intelligent irrigation dynamic decision-making method and equipment, and constructs an intelligent irrigation fuzzy reasoning and dynamic decision-making method by fusing multi-source remote sensing data and rainfall data and combining water demand characteristics of crops in different growth stages. It can be understood that the method is based on regularly updated remote sensing data, the moisture state of crops is dynamically monitored, and plot-level irrigation decision suggestions are generated. A manager can scientifically formulate an irrigation strategy according to suggestions in combination with the local actual water resource condition and the irrigation system, precise irrigation regulation and control are achieved, and the irrigation efficiency and decision scientificity are improved.

The invention relates to the technical field of agricultural irrigation, and discloses a high-efficiency water-saving intelligent drip irrigation system which comprises a soil humidity sensor used for monitoring the humidity level in soil in real time; the meteorological sensor is used for monitoring environment temperature, humidity, wind speed, wind direction and rainfall; the central controller is connected with the soil humidity sensor and the meteorological sensor and used for receiving and processing sensor data and dynamically adjusting the irrigation area and the irrigation amount based on the data; and the partition control valves are mounted on branch nodes of the irrigation pipe network, are connected with the central controller and are used for controlling the water flow of each irrigation area according to instructions of the central controller. By monitoring soil humidity and meteorological conditions in real time, the system can accurately control irrigation time and water volume according to actual requirements. According to the demand-driven irrigation strategy, waste of water resources is greatly reduced, it is ensured that irrigation is conducted at the most needed time, only the needed water is supplied, and the use efficiency of the water resources is further optimized.

The invention discloses a soil oxygen dynamic prediction method for precision agriculture, and belongs to the technical field of soil oxygen prediction, and the method comprises the following steps: S1, collecting key parameters of different soil depths in a research area, and S2, calculating a soil oxygen diffusion coefficient according to the key parameters of different soil depths in the research area; s3, calculating the respiration rate of the soil root system; s4, constructing a soil oxygen consumption model; and S5, carrying out iterative calculation to obtain soil oxygen concentration distribution at different moments and different depths. The method can solve the problem that the oxygen concentration of the soil is influenced by complex factors such as moisture, temperature, porosity, root respiration and microbial activity, and provides a scientific basis for precise agricultural irrigation, soil health assessment and oxygenation irrigation strategy optimization.

The invention belongs to the technical field of agricultural irrigation devices, particularly relates to an integrated intelligent water and fertilizer integrated device, and aims to solve the problems that an existing device is relatively low in granular fertilizer dissolving efficiency and cannot realize dynamic filtering adjustment of a water body. A water body filtering assembly, a fertilizer conveying all-in-one machine and a water and fertilizer mixing barrel are arranged in the integrated compartment, so that the device is compact in structure and convenient to move, field assembly during use is not needed, and the water and fertilizer mixing device is convenient to use. The maneuverability and the operation convenience of the device can be greatly improved, and during use, the pumped water body is filtered through the water body filtering assembly, and the required fertilizer is quantitatively conveyed through the fertilizer conveying all-in-one machine, so that accurate proportioning and mixing of the water and the fertilizer can be realized, and different use requirements are met.

The utility model discloses an agricultural irrigation device which comprises a water tank, a water inlet pipe connected to the right end of the water tank, an irrigation pipe connected to the left end of the water tank, a through hole formed in the upper end of the water tank, a nut fixed to the upper end of the water tank and located on the outer side of the through hole, a rain cover arranged at the upper end of the water tank and located on the outer side of the nut, and a sleeve fixed to the upper end of the rain cover and integrated with the rain cover. A hand wheel is fixed to the upper end of the sleeve, a connecting column is installed in the sleeve, and the lower portion of the connecting column is in threaded connection with a nut. According to the agricultural irrigation device, after a hydrogen rod is installed on the lower portion of a connecting column, the hydrogen rod can penetrate through a nut and a penetrating hole, the hydrogen rod is moved into a water tank, then the lower portion of the connecting column is screwed into the nut, a rainproof cover moves downwards to cover the nut at the moment, and rainwater and soil can be prevented from entering the position between the nut and the connecting column through the rainproof cover; in addition, an observation window is arranged, the surface state of the hydrogen rod can be observed, and therefore a user can conveniently replace the hydrogen rod in time.

The invention relates to the field of agricultural irrigation, in particular to an intelligent water distribution system and method for root space-time competition of an intercropping system, and is applied to agricultural precise irrigation, efficient utilization of water resources and management of the intercropping system. According to the system, the ground penetrating radar and the multispectral laser technology are fused, and crop root system distribution, activity and nutrient data are accurately obtained. Based on transfer learning and multi-agent reinforcement learning algorithms, a root system competition model is constructed, and an optimal water distribution strategy is intelligently decided. The deformable drip irrigation execution module achieves precise irrigation, the water consumption is greatly reduced by 20%-35%, and waste is effectively avoided. Meanwhile, the system balances the growth requirements of intercropping crops, relieves root competition, improves the overall yield and stability, and the amplification reaches 15%-25%. According to the system, the utilization efficiency of water resources is remarkably improved, and powerful support is provided for sustainable development of modern agriculture.

The invention provides an agricultural irrigation control method, system and device driven by an AI large model, and a medium, and belongs to the technical field of agricultural irrigation control, and the method comprises the steps: building an irrigation knowledge base and an irrigation decision set for a target crop based on the AI large model; constructing a target crop parameter set and a water demand prediction model, and training the water demand prediction model by using the target crop parameter set in combination with the irrigation knowledge base; target crop parameters collected in real time are input into the trained water demand prediction model, and target crop water demand prediction is carried out; and screening out an irrigation strategy from the irrigation knowledge base and the irrigation decision set according to the predicted value of the water demand of the target crop, and controlling the irrigation equipment based on the irrigation strategy. Through the combination of the AI large model and the deep learning model, the water demand of the crops is accurately predicted, the irrigation strategy is generated, the irrigation decision accuracy is improved, the waste of water resources is reduced, and the irrigation efficiency is improved.

The invention belongs to the technical field of agricultural irrigation, and particularly relates to a deep-buried drip irrigation tape laying device capable of preventing tape overturning, in the device, a tape winding drum is detachably connected to an unwinding mechanism, a drip irrigation tape is wound on the tape winding drum, the unwound drip irrigation tape is fed between a furrow opener and a tape pressing wheel along a guide mechanism, and along with advancing of a rack, the drip irrigation tape is wound around the tape winding drum. The drip irrigation belt is laid in a groove formed by the ditching mechanism, then soil is compacted through the soil pressing mechanism, laying is achieved, in the process, through the arrangement of the guide mechanism and the belt pressing wheel, the belt floating and belt turning phenomena in the unwinding and laying process can be effectively avoided, the height of the ditching device is adjustable, and the practicability is high. The ditching depth of the ditcher can be adjusted according to actual use requirements; according to the drip irrigation belt laying device, the phenomena of belt floating and belt turning in the drip irrigation belt laying process can be effectively avoided, and the drip irrigation belt laying depth is adjustable.

The invention discloses a liquid fertilizer mixing device for new energy irrigation, and relates to the technical field of agricultural irrigation, the liquid fertilizer mixing device comprises a mixing and stirring barrel, a main stirring blade and an auxiliary stirring blade are arranged in the mixing and stirring barrel, liquid is convected up and down under the action of the two groups of blades, and a reflux water pump is arranged to pump the liquid at the lower layer to the upper layer. Uneven mixing caused by sedimentation of the fertilizer at the bottom is avoided, the crushed fertilizer is discharged into a weighing bin to be weighed, when the required weight is reached, a rotating bin door is opened, the fertilizer falls into a pre-dissolving tank to be dissolved and mixed, fertilizer particles are crushed, so that the fertilizer dissolving time is shortened, and the mixing efficiency is improved; the pH detection assembly and the EC detection assembly are arranged to measure the pH value and the conductivity of liquid in the mixing and stirring barrel and detect the proportioning concentration of the fertilizer, the flow of the liquid fertilizer injected into the mixing and stirring barrel is measured and controlled in cooperation with the flowmeter, the proportioning concentration can be adjusted, and the proportioning accuracy is improved.

The invention relates to the technical field of agricultural irrigation, in particular to an intelligent irrigation control system and method based on an intelligent crop growth model. The method comprises the steps of collecting temperature, humidity, illumination and soil moisture data of a crop growth environment, and taking the data as input of a machine learning model; an LSTM machine learning algorithm is utilized to construct a crop growth model used for predicting the crop growth trend and calculating the irrigation water demand; in the crop growth process, crop image data are acquired in stages and compared with a standard growth image, similarity and a correction coefficient are calculated, and the predicted growth trend is corrected in real time; according to the corrected growth trend, the irrigation water demand is dynamically adjusted, and closed-loop feedback control is formed; according to the corrected irrigation water demand, the irrigation equipment is accurately controlled for irrigation, and intelligent monitoring of crop growth and efficient utilization of water resources are achieved.

The invention belongs to the technical field of agricultural irrigation, and discloses a precision agriculture water and fertilizer integrated distribution method, which comprises the following steps: S1, data acquisition; s2, data processing and analysis; s3, formulating a water and fertilizer formula; s4, water and fertilizer distribution and conveying The method has the beneficial effects that by comprehensively collecting farmland soil, weather and crop growth data, a crop growth and water and fertilizer demand model is constructed, and accurate prediction and scientific formula making of water and fertilizer demands are achieved; by utilizing a drip irrigation and intelligent irrigation control system, water and fertilizer distribution is accurately regulated and controlled, the resource utilization efficiency is remarkably improved, waste is reduced, healthy growth of crops is promoted, and the yield and quality are improved; in addition, due to precise management, use of chemical fertilizers is reduced, environmental pollution is relieved, the ecological environment is protected, the labor intensity of farmers is reduced due to the intelligent management characteristic, and the production efficiency and flexibility are improved.