13290 results about "Fertilizer" patented technology

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 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 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 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 discloses a multi-layer controllable degradation coating composition as well as a preparation method and application thereof, and belongs to the field of biodegradable high polymer materials and coating compositions. The coating composition comprises an outer protective layer and an inner functional layer, and the inner functional layer is arranged between a substrate and the outer protective layer and comprises a plurality of microcapsules. The key innovation lies in that the microcapsule encapsulates an enzyme capable of catalytically degrading the outer protective layer and is configured to be released after a predetermined delay time. The pH buffer system is integrated in the inner functional layer, and an optimal catalytic microenvironment is created for released enzyme, so that the outer protective layer is actively and quickly degraded, and programmable time-controlled removal is realized. The problem that the degradation rate of an existing biodegradable material is passive and uncontrollable is solved, and the coating has a remarkable application value in the field of seed coating or fertilizer controlled release by endowing the coating with a unique two-stage degradation characteristic.

The invention discloses a polymeric phosphorus slow-release compound fertilizer and a preparation method thereof, and relates to the technical field of agricultural fertilizers, the polymeric phosphorus slow-release compound fertilizer comprises an inner core and a coating layer, wherein the inner core is prepared from the following components in percentage by weight: 30 to 50 percent of modified ammonium polyphosphate, 15 to 25 percent of urea-formaldehyde slow-release nitrogen, 10 to 20 percent of potassium humate-coated potassium chloride, 2 to 5 percent of amino acid chelated trace elements and 1 to 3 percent of seaweed extract; through the synergistic effect of the citric acid modified ammonium polyphosphate and the three layers of functional envelopes, the phosphorus utilization rate is increased, and the problem that phosphorus is easily fixed by soil is effectively solved. The fertilizer can automatically adapt to different soil environments through the pH responsive coating design, and 30-40% of phosphorus can be quickly released in acid soil to meet the early needs of crops; phosphorus is continuously supplied through activation of the phosphate solubilizing bacteria under a neutral condition; and the fertilizer efficiency is prolonged to 120-150 days by virtue of an outer layer slow release mechanism in an alkaline environment.

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 discloses a karst underground river system multi-source pollution comprehensive quantitative traceability method, which comprises the following steps: S1, multi-dimensional sample collection and new pollutant screening: carrying out multi-period sampling on a water body, measuring conventional water quality indexes and nitrogen and oxygen isotopes, screening new pollutants, and carrying out targeted quantification on characteristic new pollutants; s2, principal component analysis dimension reduction and pollution factor identification: carrying out principal component analysis on conventional indexes and new pollutant data, extracting principal components of which the cumulative contribution rate exceeds 85%, identifying composite pollution factors, and eliminating secondary interference factors; s3, nitrogen and oxygen isotope auxiliary verification and denitrification elimination: eliminating denitrification interference by utilizing the ratio of delta 15N-NO3 <-> to delta 18O-NO3 <-> in combination with underground water burial depth and runoff velocity, and distinguishing the nitrate source as a chemical fertilizer, soil nitrogen or sewage and wastewater; and S4, PMF model optimization and pollution source quantification: inputting the conventional indexes and the new pollutant concentration matrix into a PMF model, and analyzing the contribution rate of each pollution source.

The invention relates to the technical field of fertilizer preparation, and discloses an ecological balance fertilizer for yield increase and disease resistance of peanuts and a preparation method of the ecological balance fertilizer. The preparation process comprises the following steps: constructing a PLGA core containing trichoderma harzianum spores and magnesium carbonate through a micro-fluidic chip low-temperature water-in-oil emulsion method; coating bacillus amyloliquefaciens and potassium silicate with ultraviolet-induced cross-linked temperature-sensitive hydrogel to form a middle layer; loading rhizobium by using aminated mesoporous S < iO2 >, and spraying and assembling an enzyme response shell through a fluidized bed; finally, the hydroxyapatite nanorod and a binder are combined and granulated and formed through a fluidized bed. Precise controlled release of functional bacteria and nutrients is realized by constructing a temperature-sensitive-enzyme response type release system, and the activity of a fungicide is guaranteed to be preserved by virtue of trichoderma harzianum-rhizobium synergistic interaction and silicon bond linkage soil remediation in combination with a low-temperature fluidized bed process, so that a'fertilizer-bacterium-soil 'ecological cycle system is finally constructed.

The invention relates to the technical field of intelligent control, and discloses a water-saving fertilization variable control method suitable for sandy soil, and the method comprises the steps: obtaining collection data based on a sensor; and establishing and updating an infiltration-storage-leaching loss prediction model of the sandy soil according to the collected data, performing state estimation on soil moisture and nutrient states, and calculating root layer moisture deviation, fertilizer concentration deviation and deep seepage risk. And executing model predictive control in the rolling time domain to obtain a control result. And executing water-saving fertilization operation according to the control result. In the execution process, the soil volume moisture content, the soil water potential, the soil conductivity and shallow layer leakage observation data are fused, the prediction model is corrected, the control result is dynamically adjusted according to the correction result, and when the environment wind speed exceeds a set threshold value, the spray irrigation parameters are corrected. The fine level of control is improved, deep layer leakage can be inhibited under the sandy soil condition, water and fertilizer balance of a root layer is guaranteed, and external disturbance is coped with.

The invention discloses a biomass charcoal composite hydrogel slow-release fertilizer as well as a preparation method and application thereof, and belongs to the field of composite hydrogel and fertilizer preparation. The invention provides a biomass charcoal composite hydrogel slow release fertilizer, which comprises biomass charcoal, hydrogel fixed on the pores and surface of the biomass charcoal, and an element fertilizer mixed in the hydrogel, and the hydrogel is prepared from metal cations and alginate. The invention provides a strategy of'in-hole in-situ gelation ', hydrogel is prepared in situ in gaps of the biochar, and the biomass charcoal composite hydrogel slow-release fertilizer is prepared. The biochar and the hydrogel in the slow-release fertilizer are high in bonding strength and mechanical strength, so that the slow-release fertilizer has the slow-release function of the fertilizer and also has the capability of improving soil.

The invention relates to the technical field of water and fertilizer application evaluation, and particularly discloses an intelligent evaluation method for water and fertilizer utilization efficiency and an operation system, and the method comprises the steps: obtaining a crop image of a crop corresponding to a fertilization parameter; identifying the crop image, outputting a growth evaluation report, and constructing a mapping relation from the fertilization parameters to the growth evaluation report for evaluating the fertilization parameters; fertilization parameters are recorded, meanwhile, crop images are obtained through a visual monitoring point, the crop images are recognized, the growth conditions before and after fertilization are determined, then the growth difference before and after fertilization is determined, and the mapping relation from the fertilization parameters to the growth difference is constructed; the growth difference of the fertilization parameters can be predicted before the fertilization behavior, and the prediction accuracy is high.

The invention relates to the field of microorganisms, in particular to a mortierella alpina strain MA with a plant growth promoting function and application of the mortierella alpina strain MA. The strain has remarkable nitrogen fixation, siderophore production, auxin (IAA) production and cellulase activity, can inhibit various soil-borne pathogenic bacteria such as phytophthora capsici and fusarium, and remarkably improves the disease resistance and growth performance of crops such as pepper. The strain has various functions and broad-spectrum action, is suitable for replacing part of chemical fertilizers and pesticides in intensive agriculture, and realizes green and efficient planting of crops.

The invention relates to the technical field of agricultural fertilizers, discloses a seaweed extract-functional microorganism compound slow-release fertilizer and a preparation method thereof, and solves the problems in the background art. The seaweed extract is a compound containing enteromorpha polysaccharide and alginic acid extract; the functional microorganism is a complex microbial inoculant composed of phosphate solubilizing bacteria, nitrogen-fixing bacteria, phosphate solubilizing bacteria and bacillus; the slow-release carrier is prepared by coating the seaweed extract and the functional microorganisms with sodium alginate-chitosan microcapsules; the signal molecule is selected from at least one of polyamine substances and jasmonic acid methyl ester; the fertilizer has the advantages that the utilization rate of the fertilizer can be increased, growth and reproduction of soil microorganisms are promoted, the stress resistance of crops is improved, and the requirements of different soil types and planting environments can be met.

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

The invention discloses a large-scale pig breeding wastewater purification treatment system, and relates to the technical field of wastewater treatment.The large-scale pig breeding wastewater purification treatment system is characterized in that the ion concentration of anaerobic liquid is monitored through a multi-ion sensing array, and a multi-channel feeding system is controlled to synthesize customized struvite compound fertilizer; the AI prediction control unit predicts the optimal medicament dosage and realizes millisecond-level closed-loop regulation; the multi-dimensional synergistic biochemical treatment module comprises an A / O biochemical treatment unit and an electric field enhanced anaerobic ammonia oxidation reactor, the electric field enhanced anaerobic ammonia oxidation reactor applies a direct-current electric field through an electrode pair, and engineering conductive biochar is used as a carrier to accelerate microbial metabolism; the sludge low-temperature pyrolysis self-consistent circulation module is used for pyrolyzing and converting residual sludge into biochar, biofuel and wood vinegar, and the biochar activation treatment unit is used for preparing engineering conductive biochar and forming a substance closed loop through a self-consistent circulation conveying system; and the digital twinning intelligent management and control platform realizes intelligent management and control of the system.

The invention relates to the technical field of image data processing, in particular to a chemical fertilizer packaging bag damage detection method and system based on machine vision, and the method comprises the steps: obtaining a packaging bag image and environment dust concentration, calculating the transmissivity through combining with the image local texture complexity, and carrying out the dynamic dust removal enhancement through employing an atmospheric scattering model; performing complementary detection on the enhanced image by adopting a frequency domain analysis first detection model aiming at structural damage and a texture analysis second detection model aiming at unstructured defects in parallel; and finally, according to the local periodic texture intensity of the image, carrying out adaptive weighted fusion on a double-model result to obtain a final defect score, and determining damage. According to the method, the interference of dust and complex textures is effectively overcome through a whole-process self-adaptive strategy from preprocessing, detection to fusion, and accurate and robust detection of various damages is realized.

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

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

Disclosed is a rice and wheat nitrogen nutrition multispectral diagnosis method for precise fertilization by unmanned aerial vehicles (UAVs), including: step 1, acquiring multispectral UAV remote sensing images and collecting agronomic parameters of rice and wheat, and establishing a nitrogen nutrition spectral diagnosis model; and step 2, calculating a critical nitrogen concentration in aboveground parts of rice and wheat based on a critical nitrogen concentration dilution model for amount of dry matter, and further obtaining a critical nitrogen uptake; calculating an actual nitrogen uptake in the aboveground parts of rice and wheat based on the nitrogen nutrition spectral diagnosis model; and obtaining a recommended nitrogen topdressing amount for rice and wheat during corresponding stages based on the critical nitrogen uptake and the actual nitrogen uptake. The present disclosure ensures stable yields of rice and wheat while reducing input of chemical fertilizers and labor, presenting a promising application prospect.

The invention discloses an intelligent fertilization and irrigation regulation and control device and method based on deep learning. The method comprises the following steps: S1, constructing an agricultural environment original data set; s2, preprocessing the original data set to generate an agricultural data set with consistent time and space; s3, constructing a multi-layer neuromorphic calculation model which comprises a photosynthetic layer, a root system layer and a transpiration layer; s4, performing correlation analysis based on the photosynthesis dynamic curve, the root system water and fertilizer absorption curve and the transpiration-moisture supply curve, and constructing a photosynthesis-root system-transpiration synergistic curve; s5, on the basis of the photosynthesis-root system-transpiration synergistic curve, calculating a promoting factor of photosynthesis on root system absorption and a regulating factor of root system absorption on transpiration intensity, and constructing a self-adaptive regulation and control function; and S6, carrying out time sequence analysis on the self-adaptive regulation and control function, and formulating a final fertilization and irrigation regulation and control scheme. According to the method, a multi-layer neuromorphic calculation method is adopted, the photosynthesis-root system-transpiration cooperative relation is accurately modeled, and intelligent fertilization and irrigation regulation and control are achieved.

The invention discloses a production method of distiller's grain fermentation liquid fertilizer specially applied to roxburgh rose. The distiller's grain fermentation liquid fertilizer is prepared bythe step of evenly mixing 50 to 80 parts of distiller's grain fermentation extracting solution, 0.5 to 1 part of microelement, 5 to 10 parts of seaweed meal, 5 to 10 parts of natural active organism,2 to 5 parts of potassium bicarbonate, 2 to 5 parts of natural active organism and 2 to 5 parts of natural surface active agent. A preparation method of the distiller's grain fermentation extracting solution comprises the steps: evenly stirring 50 to 80 parts of distiller's grain, 50 to 150 parts of rice washing water, 1 to 2 parts of EM microflora fermentation liquid and 0.5 to 1 part of sugar, performing composting fermentation at the room temperature to obtain a distiller's grain fermentation material, stirring and extracting through a sodium carbonate water solution, filtering and performing evaporation and condensation on obtained filtrate until the density is 1.1 to 1.2 to obtain distiller's grain fermentation extracting solution. The distiller's grain fermentation liquid fertilizerdisclosed by the invention has a good use effect, meanwhile can effectively prevent pest and disease damage to the roxburgh rose and is high-efficiency environment-friendly liquid fertilizer.

The invention belongs to the field of agricultural chemistry and bio-fertilizer, and discloses a fertilizer synergist based on polyaspartic acid, alginate oligosaccharide and mannan oligosaccharide and a preparation method of the fertilizer synergist. According to the synergist, polyaspartic acid derived from plant source amino acid, alginate oligosaccharide extracted from natural brown algae and mannan oligosaccharide extracted from plants are used as main raw materials, and the polyaspartic acid, the alginate oligosaccharide and the mannan oligosaccharide cooperate to form an induction-complexation-adsorption three-effect-in-one mechanism, wherein the alginate oligosaccharide and the mannan oligosaccharide induce plant root activity and stress resistance gene expression; the polyaspartic acid is dominated to form a multi-point weak complex network, so that slow release and controlled release of nitrogen and potassium ions are realized; the three components cooperate on the surface of soil colloid to form an adsorption layer, and nutrient leaching loss is reduced. The preparation process adopts a green process of'enzymatic pretreatment-segmented complexing-low-temperature forming ', so that the oligosaccharide activity is maintained, and the use of an organic solvent is avoided. The obtained synergist can significantly improve the nitrogen utilization rate and the root activity and prolong the fertilizer efficiency period, and is suitable for green and efficient agricultural production of various crops.

The invention relates to the technical field of intelligent agriculture, and particularly discloses an orchard intelligent water and fertilizer integration-based edge end fruit tree fertilizer demand prediction method, which comprises the following steps of: constructing each fruit tree as a graph node, and fusing canopy spatial characteristics extracted by unmanned aerial vehicle multispectral remote sensing and nutrient time sequence characteristics monitored by a soil sensor; space influence weights among nodes are calculated according to the terrain, the soil texture and the space distance, and a fruit tree individual relation graph is established; then, through a space-time diagram convolutional network, aggregating space neighborhood features and capturing time dynamic changes, and outputting target state features subjected to multi-scale enhancement; when the canopy conflicts with the soil characteristic indication, combined diagnosis is carried out based on a neighborhood consistency index and an adjacent node state, systematic nutrient stress and local non-nutrient factors are distinguished, and final fertilizer demand prediction is generated after the conflict is eliminated; a digital fertilization prescription map is generated through spatial interpolation, soil characteristics and slope correction, and the water and fertilizer integrated equipment is driven to execute precise operation.

The present application relates to the technical field of heavy-metal pollution remediation, and relates in particular to a soil heavy‐metal accumulation predicting method employing an emission inventory and a receptor model. The method comprises: using atmospheric dust deposition, irrigation water, chemical fertilizers and pesticides as input flux sources of heavy metals to farmland soil, using surface runoff and crops as output fluxes, and constructing an input-output flux inventory of heavy-metal pollutants to clarify a dynamic balance relationship of soil heavy-metal accumulation; and continuously collecting and monitoring of soil samples. The invention provides crucial assistance in determining the transport balance of heavy metals in farmland areas impacted by non-ferrous metal smelting and beneficiation slag sites and in identifying sources of soil heavy-metal pollution, and offers theoretical guidance for subsequent soil heavy-metal remediation and targeted control.

The invention provides a fertilization control method and system, and belongs to the technical field of smart agriculture, and the method comprises the steps: determining a target element-deficient region based on a multispectral remote sensing image of a target region crop, a crop type and a crop growth stage; inputting the multispectral reflectivity data, the soil nutrient data and the crop growth stage of the target nutrient-deficient area into a preset nutrition diagnosis model to obtain a deficient nutrient element type and a deficient degree; inputting the nutrient element type, the lack degree, the soil nutrient data, the crop growth stage, the planned irrigation water amount and the fertilizer mother liquor concentration into a water and fertilizer decision model, and calculating to obtain the target fertilizer liquor concentration and the total fertilizer demand; and controlling the fertilization device to adjust the mother liquor injection proportion and the irrigation flow based on the target fertilizer solution concentration and the total fertilizer demand. The fertilization control method and control system provided by the invention realize accurate regulation and control of water and fertilizer, not only can improve the utilization rate of water and fertilizer, but also can improve the yield and quality of crops.

The invention provides a remote sensing data analysis-combined fertilizer proportion management method and system, and relates to the technical field of remote sensing data, the method comprises the following steps: using an unmanned aerial vehicle to shoot an original data set of crops in a key growth period of a target field, and preprocessing the original data set to obtain a remote sensing image set; calculating a vegetation index according to the remote sensing image set, and generating a vegetation index map in combination with GIS software; obtaining a soil nutrient content data set and a crop nutrient content data set; performing correlation modeling on the crop nutrient content data set and the vegetation index map by using a random forest regression algorithm, and performing nutrient inversion calculation on the target field by using the model to obtain a nutrient spatial distribution map; generating a fertilizer ratio decision; spatial expression is carried out on the decision result through GIS software, and a digital fertilization prescription map is obtained. The technical problems of low efficiency, large error, incomplete coverage and slow response in the prior art are solved.

The invention relates to a particulate composition comprising, or substantially consisting of, urea, an inhibitor, preferably a urease inhibitor and / or a nitrification inhibitor, and an additive, wherein the additive comprises components (i) and (ii): (i) a carboxylic acid or an anhydride, salt, or derivative thereof; preferably a carboxylic acid salt or a carboxylic acid derivative, more preferably a carboxylic acid salt; and (ii) a polar polymer; preferably a water-soluble polar polymer. The invention further relates to a process for preparing the particulate composition, an additive for a particulate composition, and the use of the particulate composition as a fertilizer.

The invention relates to a field water and fertilizer intelligent control method based on the Internet of Things, and the method comprises the steps: carrying out the crop type recognition and growth stage recognition through collecting crop images, soil water and fertilizer data and meteorological prediction data, and generating an initial water and fertilizer control scheme of a current time node; a soil water and fertilizer prediction model is created to predict the soil water and fertilizer change trend in a specified time period, the initial water and fertilizer control scheme of the current time node is adjusted according to the predicted soil water and fertilizer change trend, growth cycle characteristics corresponding to crop types are obtained based on big data, and a dynamic water and fertilizer control scheme is formulated. A water and fertilizer adjusting control scheme is executed at a current time node, a dynamic water and fertilizer control scheme is executed at a specified time node, the field water and fertilizer intelligent control method integrating Internet of Things sensing, intelligent identification, trend prediction, dynamic planning and closed-loop feedback is realized, the whole process intelligence from data acquisition to scheme execution is realized, and the water and fertilizer utilization efficiency is improved. The agricultural production cost is reduced.