24643 results about "Fertilizer" patented technology

The invention relates to the technical field of soil monitoring, in particular to a farmland irrigation management and control system based on the Internet of Things, and the system comprises a soil monitoring module, a crop water demand analysis module, an irrigation strategy making module, an irrigation execution control module, a water source management module, a fertilizer distribution module, an irrigation effect evaluation module and an adaptability adjustment module. According to the method, the crop water demand is analyzed by combining the decision tree, the water consumption is accurately calculated, the irrigation strategy optimizes the time and frequency based on the linear programming and simulated annealing method, the scheme adaptation degree is improved, the irrigation link adopts an automatic control and dynamic adjustment mechanism, the environment and crop demand changes are adapted in real time, and the irrigation efficiency is improved. Water source allocation ensures efficient distribution of multiple water sources on the basis of dynamic optimization, the type and quantity of fertilizer feeding are accurately controlled according to crop requirements, the irrigation effect is subjected to self-adaptive optimization of an irrigation plan after crop data evaluation, and accurate, flexible and efficient farmland resource management is integrally achieved.

The invention relates to the technical field of water and fertilizer integration, and provides an intelligent water and fertilizer integration optimization method and device based on the Internet of Things technology, and the method comprises the following three core stages and interaction mechanisms: 1, a data perception and edge processing stage; 2, an intelligent decision-making and dynamic optimization stage; and step 3, an accurate execution and closed-loop control stage. Soil parameters, meteorological parameters and crop physiological parameters are comprehensively collected through a multi-modal sensor network, the data transmission efficiency is improved by using an LoRa / NB-IoT hybrid transmission protocol, data cleaning and standardization processing are completed in combination with edge computing nodes, and the data fusion depth and quality are improved; a multi-objective optimization function is constructed based on a crop growth model, a water and fertilizer regulation and control strategy is dynamically generated through a machine learning algorithm, and collaborative optimization of water saving, yield increasing and environmental protection is achieved.

The invention discloses a crop sowing parameter control optimization method applied to multi-target precise fertilization, and relates to the technical field of agricultural crop sowing, and the method comprises the following steps: collecting a soil sample, carrying out spectrum scanning and analysis, combining with known soil nutrient data, building a soil nutrient content prediction model, and calculating a soil nutrient content prediction model; and combining spectral data to predict the nutrient content in the soil. According to the invention, through accurate evaluation of soil nutrient conditions and deep analysis of crop growth demands, fertilization and sowing parameters are optimized, so that crops can obtain required nutrients in the growth process, the optimized sowing depth, row spacing and plant spacing can effectively promote the development of crop roots, the absorption ability of the crops to moisture and nutrients is enhanced, and the quality of the crops is improved. And through real-time monitoring and adjustment of the intelligent fertilization equipment, the fertilization amount can be dynamically adjusted according to actual demands of crops, and the common problem of excessive or insufficient fertilizer in a traditional fertilization method is avoided.

The invention relates to the technical field of water and fertilizer drip irrigation, in particular to a biogas slurry, water and fertilizer integrated drip irrigation machine. Comprising a filter cartridge which is coaxially arranged in the outer cylinder, a coarse filter screen, a fine filter screen, a first scraper blade and a second scraper blade are arranged in the filter cartridge, water permeable holes are annularly and uniformly formed in the outer side wall of a lower cavity, and a water outlet is formed in the outer side wall of the lower cavity. And a blow-off pipe communicated with the filter cartridge is arranged at the bottom of the outer barrel. By means of multi-layer fine filtering combination, biogas slurry is purified at an irrigation inlet, impurities are reduced, a drip irrigation head is prevented from being blocked, and the irrigation efficiency is improved; the rotary driving mechanism regularly drives the scraping plate to accurately scrape impurities, and automatic cleaning and discharging are achieved by means of the locking opening and closing device and the movable sealing plate; the flow guide cover optimizes biogas slurry dispersion, deals with unstable supply and reduces pipe inlet pressure.

The invention relates to the field of saline-alkali soil water-fertilizer regulation, in particular to a saline-alkali soil soybean water-fertilizer-salt regulation dynamic decision-making method and system. A saline-alkali soil soybean water, fertilizer and salt regulation dynamic decision-making system comprises a region division module, a data monitoring module, an irrigation initial decision-making module, a fertilization initial decision-making module, an irrigation decision-making acquisition module and a fertilization decision-making acquisition module. By integrating an advanced sensor technology and an intelligent decision-making model, key parameters are accurately monitored, and the total amount of irrigation and fertilization required in a specific time window in the future is calculated in combination with crop growth stages and historical water and fertilizer records; meanwhile, the irrigation and fertilization frequency can be dynamically adjusted according to soil and environment data monitored in real time, waste of water resources and fertilizer is avoided, the possible soil salinization problem is solved, soil health can be maintained, and crop growth is promoted.

The invention relates to the technical field of intelligent detection of building materials, in particular to a real-time detection method for grain composition characteristics of muck. The method comprises the following steps: S1, acquiring original point cloud data; s2, particle point cloud clustering; s3, determining the particle size of the sieved particles; s4, particle morphological feature extraction; s5, correcting the mass of the particles; and S6, grading feature output. The method has the characteristics of high precision, high efficiency, low cost, wide applicability and the like in particle grading characteristic detection, is particularly suitable for grading characteristic detection of residual mud particles, can also meet the real-time detection requirements of related particulate matters in other fields, such as mineral particle screening, building gravel detection, agricultural granular fertilizer grading and the like, and has a wide application prospect. Rapid and accurate detection of grain composition characteristics in different industries can be realized, and the requirements of various industrial production and engineering application are met.

The invention relates to the technical field of crop cultivation, in particular to a water and fertilizer regulation and control method and system for saline-alkali soil grain-feed crops, and the method comprises the following steps: S1, soil preliminary improvement and crop selection: performing preliminary improvement on saline-alkali soil; s2, dynamically predicting, regulating and controlling the soil conductivity: monitoring and dynamically predicting the change trend of the soil conductivity in real time; s3, formulating a water and fertilizer management strategy: formulating the water and fertilizer management strategy; s4, dynamic optimization of saline-alkali soil moisture evaporation: acquiring environmental data in real time, and performing dynamic optimization management on the moisture evaporation process of the saline-alkali soil; s5, crop root health monitoring and feedback regulation and control: identifying salt damage or water and fertilizer absorption obstacles, and adjusting a water and fertilizer management strategy in real time; s6, final-period management and soil ecological restoration, wherein ecological restoration is conducted on the saline-alkali soil. According to the invention, salt damage or water and fertilizer absorption obstacles are identified and solved in time, and healthy growth of crops is further ensured.

The present disclosure provides guided microbial remodeling (GMR) methods for the rational improvement of plant-associated microbes to perform plant-beneficial functions. The GMR methods described herein allow for non-intergeneric genetic optimization of key regulatory networks within the microbes, which improve plant-beneficial functions over wild-type microbes but don't have the risks associated with transgenic approaches (e.g., unpredictable gene function, public and regulatory concerns, etc.). The present disclosure also provides remodeled microbes and compositions thereof. The utilization of remodeled microbes and compositions thereof will enable farmers to realize more productive and predictable crop yields without the nutrient degradation, leaching, or toxic runoff associated with traditional synthetically derived fertilizers.

The present invention relates to an intelligent material distribution and material taking device and method for solid fermentation of powdery and granular fertilizers, comprising at least one production line, the production line comprising: a longitudinal conveyor belt parallel to the length direction of the fermentation tank; a transverse conveyor belt arranged above the fermentation tank along the width direction of the fermentation tank; a discharge vehicle, including a longitudinal discharge vehicle and a transverse discharge vehicle; a material distribution conveyor belt for receiving the fermentation raw materials scattered by the longitudinal discharge vehicle; a longitudinal receiving hopper; a mobile spiral material taking machine, which is longitudinally slidably arranged in the fermentation tank to collect the intermediate products in the fermentation tank; a controller, which controls the intelligent material distribution and material taking device for solid fermentation of powdery and granular fertilizers to switch between the two working states of distribution and material taking, and controls the transverse conveyor belt and the longitudinal discharge vehicle to keep synchronous longitudinal movement. The controller is used to switch the working state of the material distribution and material taking device, so as to realize intelligent and automatic material distribution and material taking, so as to meet the needs of solid fermentation of powdery and granular fertilizers.

The invention relates to the technical field of irrigation control, in particular to a water and fertilizer integrated irrigation control method based on a wheat growth cycle, which comprises the following steps: collecting soil humidity and wheat growth state data, and screening key soil and biological parameters influencing wheat growth by applying a random forest algorithm; and predicting the requirements of the wheat on water and nutrition in the differential growth stage according to the key parameters. According to the method, the water and nutrition requirements of wheat in different growth stages are accurately predicted by adopting a random forest algorithm, resource allocation is directly carried out according to the actual needs of plants, the problems of resource waste and insufficient supply of a traditional irrigation system are effectively avoided, and a dynamic adjustment strategy is based on current soil and plant states and also based on a dynamic adjustment strategy. And a water and fertilizer supply plan is optimized by using historical and predicted data, the capability of responding to environmental changes is enhanced, irrigation and fertilization parameters are finely adjusted by combining real-time feedback circulation with a PID controller, and the accuracy and effectiveness of each time of irrigation and fertilization are further ensured.

The invention provides a high-standard farmland water and fertilizer integrated intelligent regulation and control method and system, and the method comprises the steps: obtaining terrain point cloud data and crop canopy water stress data of a high-standard farmland, generating an elevation gradient distribution feature set, and generating an elevation model according to the set; analyzing the crop canopy moisture stress data, and calculating a moisture stress index; performing spatial position matching on the terrain difference parameters and the micro-terrain difference parameters to generate a terrain compensation parameter set; establishing a time sequence optimization correlation model in the 5G edge computing node, and optimizing a pulse irrigation time sequence factor and a flow distribution weight by using the time sequence optimization correlation model according to the terrain compensation parameter set and the historical irrigation record so as to generate a multi-target irrigation control instruction; performing high-standard farmland water and fertilizer integrated intelligent regulation and control according to the multi-target irrigation control instruction and the water and fertilizer migration rate parameter corresponding to the microtopography difference parameter; water and fertilizer are accurately distributed according to needs, and the irrigation uniformity, the resource utilization efficiency and the crop yield are improved.

The invention relates to the technical field of automatic control, and further relates to a water and fertilizer integrated multi-objective optimization intelligent regulation and control system based on artificial intelligence driving, and the system comprises a water and fertilizer load analysis unit and a water and fertilizer combined regulation and control criterion generation unit. The water and fertilizer load analysis unit is used for acquiring meteorological data from a meteorological monitoring system; simultaneously receiving data from the soil sensor and the leaf surface sensor, acquiring growth state data of the crops, and evaluating water demand and fertilizer demand of the crops in unit area at each time; and the water and fertilizer combined regulation and control criterion generation unit is used for dynamically calculating the water application amount and the fertilization amount of the crops in unit area at each time according to the soil state and the root system absorption capacity of the crops by using an AI dynamic resource optimization engine. According to the invention, the utilization efficiency of moisture and nutrients is effectively improved, the waste of resources is reduced, and the intelligence, adaptability and robustness of regulation and control are enhanced.

The invention discloses a compound fertilizer production nutrient optimization method based on industrial data, relates to the technical field of compound fertilizer production, and firstly solves the problem of unbalanced nutrient release; through the steps S1 and S2, a compound fertilizer production process is decomposed, soil and crop growth related data are collected, an image data processing technology is combined, a plant growth rate Gs and a nutrient supply and demand difference Ns are calculated, and through evaluation of a first supply and demand difference threshold Q1 and a second supply and demand difference threshold Q2, a nutrient release rate is adjusted in time, matching of nutrients and a crop growth cycle is ensured, and the quality of the compound fertilizer is improved. Excessive or insufficient nutrients are avoided; secondly, the trace demand Mn is calculated and evaluated through the step S3, the problem of lack of trace elements is solved, trace element supply is adjusted in time, and it is ensured that crops obtain needed support; and finally, calculating a nutrient loss compensation index Li through the step S4, estimating nutrient loss and adjusting fertilization, so that the applicability of the compound fertilizer under complex climate conditions is improved.

The invention discloses a soil nutrient recycling method and system based on prediction driving, and belongs to the technical field of agricultural soil management.The method specifically comprises the steps that soil nutrient content data are obtained through sampling, and soil nutrient abnormal areas are preliminarily screened in combination with a geographic information system and a remote sensing technology; soil physicochemical properties are measured in the soil nutrient abnormal area, soil nutrient form distribution is measured through X-ray diffraction and near infrared spectroscopic analysis, and nutrient stability and release potential are evaluated; constructing a soil nutrient cyclic dynamic model based on multi-source data, and simulating nutrient evolution; according to simulation results, crop requirements, soil states and environmental factors, an accurate fertilization scheme is formulated; intelligent management and precise fertilization of soil nutrients are realized, and the fertilizer utilization rate and the agricultural production efficiency are improved.

To provide a new type of intelligent rice seeding machine with a water-saving membrane and drought resistance that solves the problem of high production costs. [Solution] The system includes a mobile body 1 and an implement system, which includes a main mounting frame 2, a drip irrigation belt laying mechanism 3, an implement frame lifting mechanism 4, a soil cover removing mechanism 5, a furrow forming mechanism 6, a seeding mechanism 7, a synchronous irrigation mechanism 8, and a laser film cutting mechanism 9. The implement frame lifting mechanism adjusts the lifting of various mechanisms. The soil cover removing mechanism can be used for soil cover removing and transportation. The furrow forming mechanism can dig the soil in the seeding zone and open it into a furrow shape, which enables concentrated positioning and side fertilization. The seeding mechanism moves following the integrated machine. The sowing holes in the hole sowing wheel can perform automatic sowing, but the synchronous irrigation mechanism irrigates a uniform, fixed amount of water only in each seeding hole.

The invention provides a fertilizer production energy consumption real-time optimization method, and particularly relates to the technical field of industrial process optimization control based on artificial intelligence, and the method comprises the steps: constructing a mechanism sub-model based on a chemical reaction kinetic equation, and outputting a theoretical energy consumption constraint value; and meanwhile, a data driving model is used for receiving temperature, pressure and raw material ratio data collected by a real-time sensor and outputting a real-time energy consumption predicted value. And inputting the theoretical energy consumption constraint value and the real-time energy consumption predicted value into a dynamic weight distribution module to generate a fused energy consumption predicted value. And generating a production parameter adjustment instruction through a rolling optimization algorithm according to the fused energy consumption predicted value, and sending the production parameter adjustment instruction to a production execution system. And if the deviation between the data acquired after the adjustment instruction is executed and the fused energy consumption predicted value exceeds a preset threshold value, performing online fine adjustment on the data-driven model parameters. The technical problems that real-time energy consumption optimization lags behind due to multivariable dynamic coupling in the fertilizer production process, and an optimal production parameter combination cannot be rapidly generated are solved, and the fertilizer production energy consumption is remarkably reduced.

The invention discloses an artificial intelligence rice water and fertilizer real-time monitoring method and system, and relates to the technical field of agricultural intelligent decision making, and the method comprises the steps: inputting a farmland feature data set into a soil thermodynamic diagram generation model, carrying out the high-resolution reconstruction of the farmland feature data set through a GAN adversarial network, and generating a whole-field high-precision soil thermodynamic diagram; based on the whole-field high-precision soil thermodynamic diagram, a collision relation between the fertilization amount and historical farming data is detected according to an FCL causal algorithm, a preliminary causal diagram is generated, and a causal diagram structure of the fertilization amount and the historical farming data is constructed by adopting a multiple linear regression method; based on a causal diagram structure, the multi-order causal effect of the fertilization amount, the soil parameters and the historical yield is analyzed through a dynamic allocation algorithm, and a water and fertilizer regulation and control strategy is formulated in combination with a multi-objective optimization algorithm. According to the method, the soil thermodynamic diagram generation model is constructed, so that the fuzzy problem of the edge of the field and the salinization area is solved, a high-fidelity soil space state substrate is provided for water and fertilizer regulation and control, and invalid irrigation is reduced.

The invention provides a soil sensor and fertilization execution mechanism linkage adjustment method of an intelligent grape deep fertilizer applicator, and relates to the technical field of fertilization execution mechanism linkage. Comprising the steps of performing weighted fusion based on obtained soil data to obtain soil comprehensive parameters, generating a fertilization amount instruction, a fertilization proportion instruction and a fertilization depth instruction through an adaptive optimization algorithm based on the obtained soil comprehensive parameters, and sending the obtained fertilization amount instruction, the fertilization proportion instruction and the fertilization depth instruction to a control module to be executed based on the obtained fertilization amount instruction, the obtained fertilization proportion instruction and the obtained fertilization depth instruction. Through a self-adaptive optimization algorithm, the technical scheme not only dynamically adjusts the fertilization amount, proportion and depth according to real-time soil data, but also can predict the soil change trend according to different environmental factors and perform optimization adjustment, and automatically supplements or reduces the fertilizer according to different soil requirements; therefore, the crops can obtain optimal nutrient supply in different growth stages, the fertilization effect is optimized, and the growth quality and yield of the crops are improved.

The invention relates to serratia marcescens XJ108 and application thereof, and belongs to the technical field of microorganisms. The serratia marcescens XJ108 is preserved in the China General Microbiological Culture Collection Center (CGMCC), the preservation number is CGMCC No.29557, the preservation date is January 10, 2024, and the address of the preservation institution is No.3, Yard 1, Beichen West Road, Chaoyang District, Beijing. The invention also provides application of the serratia marcescens XJ108 in acid environment, alkaline environment, high salinity environment and high chemical fertilizer environment soil tolerance and plant growth promotion. The serratia marcescens XJ108 provided by the invention has certain biological safety; meanwhile, the plant growth promoting function is achieved; and various extreme soil environments can be tolerated.

The invention discloses a growth-promoting bacillus velezensis FSUXF-717 capable of tolerating heavy metals and application of the growth-promoting bacillus velezensis FSUXF-717, and belongs to the technical field of agricultural microorganisms. The bacillus velezensis FSUXF-717 has the following advantages: (1) the bacillus velezensis FSUXF-717 has multifunctional metabolic characteristics: various carbon sources such as cane sugar, raffinose and aesculin can be utilized, and the bacillus velezensis FSUXF-717 has the functions of producing long-chain hormone, dissolving phosphorus, secreting ACC deaminase, efficiently forming a biological membrane and the like; (2) broad-spectrum adaptability: the strain has strong tolerance to heavy metal pollution (Cd / Pb / Cr / Ni), drought and broad-spectrum acid-base stress (pH 4.5-9.5); under the condition of relatively low bacterium concentration, the auxin can be stably synthesized in a heavy metal-acid-base composite stress environment. And (3) the activity of soil sucrase and soil phosphatase is enhanced. Excavation of the strain can provide an important germplasm resource basis for development and utilization of novel efficient microbial fertilizers and lay a foundation for green and high-quality development of agriculture.

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 relates to a water and fertilizer management control method based on image data processing, and the method comprises the steps: collecting a visible light image, a multispectral image and a thermal infrared image of a crop, carrying out the feature extraction, calculating the plant morphological parameters, vegetation indexes and vegetation canopy temperature distribution of the crop, creating a three-dimensional physiological feature matrix, creating an image segmentation network model, and carrying out the feature extraction. Inputting the visible light image, the multispectral image, the thermal infrared image and the three-dimensional physiological feature matrix into an image segmentation network model to segment plant organs, quantifying organ-level phenotypic parameters, and establishing a water and fertilizer decision model based on reinforcement learning; and taking real-time data of the three-dimensional physiological feature matrix, the organ-level phenotypic parameters and the soil specified parameters as state input, taking a water and fertilizer proportioning scheme as an action space, and implementing a water and fertilizer management scheme through a dynamic optimization control strategy. The technical problems that data integration of a single sensor is insufficient, phenotype analysis precision is limited, and adaptability of a decision model is poor in a traditional water and fertilizer regulation scheme are solved.

The invention relates to the technical field of fertilization and watering control, in particular to an automatic fertilization and watering control method and system for landscape garden seedlings. The method comprises the following steps: acquiring and analyzing morphological data and soil state characteristics of landscape garden seedlings through an electronic monitoring and soil monitoring sensor; then, the nursery stock root system density is predicted through the nursery stock form data, abnormal fluctuation of the soil salt content is monitored, and the root system absorption limitation condition is estimated; then, according to root system absorption limited data and soil salt content abnormal fluctuation, the dosage of a slow release fertilizer is matched, and sectional type drip irrigation proportion fusion is carried out; and finally, constructing a fertilization and watering control model based on a strategy gradient algorithm, and implementing automatic fertilization and watering control through a terminal. The fertilization and watering control technology is optimized, so that the fertilization and watering control technology is more perfect.

The invention relates to the technical field of agricultural information, discloses a corn precise topdressing prescription map generation method based on unmanned aerial vehicle multispectral remote sensing, and effectively solves the key problems of insufficient monitoring precision, poor environmental adaptability, low decision intelligent level and the like in the traditional fertilization technology. Through the unmanned aerial vehicle multispectral imaging technology, efficient and accurate monitoring of the corn nitrogen nutrition condition is achieved; in combination with a machine learning algorithm, an intelligent fertilization decision model adapted to different environmental conditions is established, and the fertilization precision in a complex farmland scene is remarkably improved; and a multi-source data fusion technology is adopted, and crop growth, soil characteristics and meteorological factors are comprehensively considered, so that the fertilization scheme is more scientific and reasonable. Compared with a traditional method, the method has the advantages that accurate variable fertilization can be realized according to actual needs of crops, the utilization rate of the fertilizer is increased, environmental pollution is reduced, and reliable technical support is provided for sustainable development of modern agriculture.

The invention relates to the technical field of sowing control, in particular to a precise control system and method for cooperative fertilization and sowing, and the method comprises the following steps: monitoring soil humidity distribution data of a target farmland by using a soil humidity sensor, and calculating a soil permeability coefficient based on the soil humidity distribution data in combination with a three-dimensional terrain model and a soil permeability coefficient; constructing a soil humidity gradient model by adopting a finite element analysis method; based on the soil humidity gradient model and in combination with target fertilizer characteristics, establishing a fertilizer diffusion model, simulating the diffusion range and concentration distribution of the fertilizer under the soil humidity gradient condition, and outputting the fertilizer diffusion radius and the concentration gradient distribution of the fertilizer in soil through multivariate regression analysis; and based on the fertilizer diffusion model, calculating the fertilization amount and the fertilization depth in combination with the crop demand parameters. According to the method, the soil humidity gradient model is established, and fertilizer waste and environmental pollution caused by non-uniform fertilization or excessive fertilization amount are avoided.

The present disclosure provides a decision-making method and apparatus for water and fertilizer stress of crops, and a mobile phone terminal, and belongs to the technical field of intelligent agriculture. The method includes: determining a current crop coefficient and canopy temperature of a crop to be identified on the basis of a first crop image and a second crop image; determining a water stress state and a nutrient stress state on the basis of the current crop coefficient and canopy temperature of the crop to be identified; and processing the water stress state and the nutrient stress state with a fuzzy control algorithm, and determining a water and fertilizer stress decision result of the crop to be identified.

The invention relates to the technical field of agriculture, and discloses an intelligent fertilization technical measure and method for improving the fertilizer utilization rate, and the intelligent fertilization technical measure comprises a soil sensor module which is used for monitoring various parameters of soil in real time, including but not limited to soil nutrient content, soil humidity, soil acidity and alkalinity, soil temperature and soil texture; the soil sensor module can collect monitored parameter data with high precision and high frequency, and transmit the data to the central control unit through the wireless communication module; the fertilizer storage and conveying module is internally provided with a plurality of independent fertilizer storage bins, and each storage bin can store different types of fertilizers. According to the present invention, the type, the use amount and the application time of the fertilizer can be precisely controlled according to the growth requirements of different crops and the soil state through the precise fertilization mode so as to ensure the efficient absorption of the fertilizer by the crops, such that the fertilizer utilization rate is significantly improved, and compared with the traditional fertilization mode, the fertilizer waste can be reduced, and the agricultural production cost can be reduced.

The invention relates to the technical field of soil fertility query analysis, and discloses a citrus orchard soil fertility query method and system based on artificial intelligence. The method comprises the following steps: collecting surface and deep soil samples in a citrus orchard for physical and chemical detection, and filling missing values with space-time dual interpolation to obtain a data set; extracting physicochemical and biological activity features, and forming feature vectors by adopting a fusion strategy; inputting a cascade forest model to carry out five-level classification; classifying the sampling points to generate a distribution diagram; intelligent diagnosis is carried out, the fertilization amount is calculated, and a differentiated fertilization recommendation map is generated. According to the application, soil fertility accurate evaluation, spatial distribution visualization and differentiated fertilization recommendation based on multi-source data are realized, so that the fertilizer utilization rate is improved, the environmental risk is reduced, and the citrus yield and quality are improved.

The invention relates to the technical field of agricultural fertilization, in particular to a precise fertilization method and system based on rice field nutrient real-time monitoring. The method comprises the following steps: acquiring map data of a rice field; dividing the rice field into a plurality of uniform areas by using a random sampling algorithm and an expansion algorithm; acquiring soil data and nutrient data of the rice field; constructing a rice field region comprehensive evaluation model used for comprehensively evaluating the difference between rice field region nutrients and soil characteristics; classifying the uniform regions according to the difference between nutrients and soil characteristics, and obtaining classified regions; constructing a rice field nutrient demand analysis model; constructing a rice field precise fertilization model; the fertilization amount is determined, and accurate graded fertilization is realized. According to the method, the nutrient and soil characteristics of the rice field are comprehensively evaluated in different regions, the fertilization priority sequence is determined, the nutrient requirements of all the regions are accurately matched to specific fertilizers and fertilization amounts, tight connection of the regions, the nutrients, the fertilizer types and the fertilization amounts is ensured, and precise fertilization management is achieved.

The invention discloses a liquid fertilizer application effect analysis method based on self-supervised learning. The method comprises the following steps: S1, generating initial feature data; s2, environment feature representation is generated based on a heterogeneous environment self-adaption module; s3, extracting short-term and long-term spatio-temporal characteristics of the liquid fertilizer application effect based on the dual spatio-temporal characteristic decoupling and dynamic fusion model, and generating comprehensive spatio-temporal characteristic representation; s4, generating fertilization characteristics in different situations by utilizing self-supervised learning, and eliminating environmental interference factors through a causal reasoning module; s5, generating a fertilization intention feature, and dynamically adjusting a fertilization strategy; s6, when the difference between the prediction result and the actual effect exceeds a threshold value, triggering a re-learning module to update model parameters; and S7, carrying out integrated optimization, realizing feature sharing and task coordination through multi-task collaborative learning, and carrying out automatic tuning by utilizing Bayesian optimization. The intelligent analysis of the liquid fertilizer application effect is realized through the self-supervised learning and multi-task collaborative optimization method.