64 results about "Soil conductivity" patented technology

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 relates to the technical field of environment monitoring, in particular to an intelligent digital rural environment monitoring system and method based on big data, and the system comprises a layered water potential collection module, a gradient reverse correction module, a path inversion modeling module and a multi-dimensional diffusion modeling module, and the layered water potential collection module calculates and generates rural soil environment monitoring data; the rural soil environment monitoring data comprises layered soil water potential distribution, soil water content gradient and a soil conductivity characteristic value, and the soil water potential abnormal flow data comprises a vertical water potential difference value, an abnormal water flow direction vector and a water flow intensity grade; the moisture permeation path distribution diagram comprises a permeation path distribution structure, a soil water potential accumulation interval and a water flow propagation direction identifier, and the diffusion boundary space model comprises a pollutant diffusion boundary range, a moisture transverse migration region and multi-dimensional diffusion rate distribution. According to the scheme, the abnormal distribution range, the duration time and the development trend are quantitatively described, and the research and judgment accuracy of the abnormal penetration and diffusion process is improved.

The invention relates to an unbalanced data-oriented electric power system lightning disaster risk detection method, which comprises the following steps of: S1, gridding a target detection land parcel to obtain a plurality of grid units; S2, based on latitude and longitude coordinates of each grid unit, obtaining line parameters and environment characteristics of each grid unit in combination with a line database and a geographic information base, wherein the line parameters comprise tower height, span, grounding resistance, loop number, lightning arrester number and transformer capacity, and the environment characteristics comprise soil conductivity, building height and land utilization type; and S3, inputting the line parameters and the environment characteristics of each grid unit into a trained first detection model to obtain the thunder and lightning probability and the maximum peak current of each grid unit. Compared with the prior art, the multi-source data such as the tower height, the span, the grounding resistance and the soil conductivity are comprehensively considered, and the risk assessment result has higher regional adaptability and accuracy.

A power transmission tower grounding resistance non-contact measurement method based on the electromagnetic coupling principle comprises the following steps that transmitting and receiving electromagnetic coupling coils are arranged around an iron tower grounding body, and geometric calibration and spatial positioning of a measurement area are completed by combining grounding grid structure parameters and soil conduction characteristics; injecting a high-frequency alternating-current excitation signal into the transmitting coil, and synchronously acquiring the amplitude and phase response of the induced voltage at a receiving coil end; carrying out filtering processing on the induction signal by adopting a time-frequency analysis and phase decoupling algorithm, and solving a function relationship between electromagnetic response and grounding impedance by combining a coupling equivalent model; based on experimental calibration data and scene parameters, a nonlinear mapping model of induction response and grounding resistance is constructed, and real-time inversion calculation is carried out by combining a solving result obtained in the third step. According to the invention, the real-time accurate measurement of the grounding resistance under the conditions of no power failure and no wire breakage is realized, and the safety, the operation convenience and the anti-interference capability in a complex environment in the measurement process are obviously improved.

Methods, systems, and computer program products for implementing a soil analysis process. A set of soil data may be received at a device from one or more soil sensors. The one or more soil sensors may be coupled to a portion of an agricultural machine configured to be in contact with soil. The device may be configured to analyze soil when a portion of the one or more soil sensors is in contact with the soil. Spectral data and soil conductivity and / or capacitance data may be obtained based on the collected set of soil data. Analyzed soil data may be determined based on the spectral data and soil conductivity and / or capacitance data. The analyzed soil data may be provided to a user device configured to display a visual representation of at least part of the analyzed soil data.

The embodiment of the invention discloses a soil nutrient classification method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring soil attribute information of a target area within a preset duration; the soil attribute information comprises soil conductivity, soil temperature and spectral reflectivity; performing data preprocessing on the soil attribute information to obtain preprocessed multi-channel time sequence data; performing feature extraction and fusion on the multi-channel time sequence data based on a target feature extraction model to obtain hidden state features; the target feature extraction model is obtained by performing semi-supervised mutual learning on a preset feature extraction model by using different enhanced samples obtained by performing different data enhancement processing on unlabeled samples; and determining a soil nutrient classification result of the target region based on the target classification model and the hidden state features. Through the technical scheme of the embodiment of the invention, the soil nutrients can be accurately and conveniently analyzed, and efficient soil nutrient classification in a few-sample environment is realized.

The invention relates to the technical field of agricultural data visualization, in particular to a salinized cotton field visual multi-point salinity collection and analysis method and system.The method comprises the following steps that soil conductivity distribution data of a salinized cotton field area is obtained, a high-salinity accumulation area and a low-salinity dilution area are recognized, particle gap distribution characteristics are collected, and a salinized cotton field is obtained; and screening areas with loose or compact particle structures, executing temperature gradient analysis, screening surface thermal environment abnormal subareas, detecting wind speed distribution, removing wind field disturbance areas, and obtaining a recommended planting area list. According to the method, high and low salt areas are accurately identified through salt space distribution analysis, distribution precision is improved, humidity dynamic expression is refined, structural abnormal blocks are screened by using a particle gap change trend, soil management is optimized, surface temperature and wind speed data analysis is superposed, thermal disturbance and wind field abnormity are eliminated, and agricultural management precision is improved through multi-dimensional data fusion. The capability of coping with a complex environment is enhanced, efficient decision making is effectively supported, and the overall agricultural production benefit is improved.

This invention discloses a method for soil salinity inversion based on the fusion of remote sensing features at multiple time scales, comprising the following steps: A1 field sampling and soil conductivity measurement; A2 remote sensing data preprocessing and spectral index calculation; A3 environmental covariate acquisition and preprocessing; A4 determination of the optimal time scale feature combination; A5 feature variable screening and optimization; A6 soil salinity inversion model construction; fusing remote sensing features at different time scales, and constructing a soil salinity remote sensing inversion model based on the optimal feature combination using a random forest algorithm. By systematically integrating the instantaneous response features of single-period images with the features of seasonal composite images, the information of remote sensing data at different time scales is fully exploited, solving the problems of single time scale of remote sensing features, insufficient information utilization, and difficulty in coordinating multi-scale features in traditional modeling processes. This improves the model's ability to characterize the spatial distribution of soil salinity and its prediction accuracy, providing more scientific and reliable technical support for remote sensing monitoring of salinized areas.

The application discloses a soil salinity inversion method and system based on multi-modal remote sensing data fusion, a device and a storage medium, and is applied to the technical field of soil quality monitoring.The method comprises the following steps: acquiring radar and optical remote sensing data of a soil salinity area to be inversed, and performing conductivity determination as an inversion index of soil salinity; acquiring multi-modal remote sensing features based on radar and optical remote sensing data fusion, combining the radar and optical remote sensing data, and based on a random forest algorithm, using a recursive feature elimination method to optimize the remote sensing feature combination, using cross validation to evaluate the model performance of the remote sensing feature combination, and obtaining an optimal remote sensing feature combination; based on the optimal remote sensing feature combination, a soil conductivity prediction model based on the random forest algorithm is constructed and trained, inputting the data to be measured into the conductivity prediction model after hyperparameter adjustment, and the soil salinity inversion is completed.The application realizes more accurate inversion of soil salinity under the interaction influence of complex environment and human factors.

A solution for measuring soil moisture status and climate parameters in real time, and for providing users (irrigators, supervisors, researchers, etc.) with a dashboard to support decision-making regarding crop irrigation. It combines three complementary technologies: soil conductivity measurement, an intelligent and connected embedded system, computing servers, and web and mobile applications. The solution is presented as a single unit, easy to install, simple to activate with the push of a button, and provides instant access to results via a web and mobile application. This solution offers users, even those without expertise in new technologies (ICT, IoT), a user-friendly way to monitor their crop soils, optimize irrigation timing, and save water.

The invention relates to the technical field of rice stress-resistant cultivation, and discloses a rice root system salt tolerance adjusting method based on exogenous spermidine, which comprises the following core steps: in the critical period of rice root system development, directionally applying a spermidine solution subjected to purity verification to a rice root system area, by accurately regulating and controlling the application concentration, frequency, duration and application environment conditions of spermidine, the osmotic regulation capability and the anti-oxidation system function of a rice root system in a high-salt environment with the soil conductivity larger than or equal to 2 dS / m are improved, the salt tolerance of the root system is remarkably improved, and then growth and development of rice are guaranteed. The spermidine is a straight-chain polyamine compound with good biocompatibility, the chemical purity is not lower than 98%, no heavy metal is left, and the contents of lead, cadmium and mercury are all smaller than or equal to 0.1 mg / kg. According to the invention, precise targeted regulation and control of the salt tolerance of the rice root system are realized, and the regulation effect is stable and remarkable.

This invention relates to the field of environmental monitoring technology, specifically to a smart digital rural environmental monitoring system and method based on big data. The system includes a stratified water potential acquisition module, a gradient inversion correction module, a path inversion modeling module, and a multidimensional diffusion modeling module. The stratified water potential acquisition module calculates and generates rural soil environmental monitoring data. This data includes stratified soil water potential distribution, soil moisture content gradient, and soil electrical conductivity characteristics. Abnormal soil water flow data includes vertical water potential difference, abnormal flow direction vector, and flow intensity level. The water infiltration path distribution map includes the infiltration path distribution structure, soil water potential accumulation intervals, and flow propagation direction indicators. The diffusion boundary space model includes the pollutant diffusion boundary range, water lateral migration area, and multidimensional diffusion rate distribution. This solution quantifies the abnormal distribution range, duration, and development trend, improving the accuracy of judging abnormal infiltration and diffusion processes.

This application discloses a high-precision quantification method, equipment, and system for farmland salinity patches integrating multi-source near-ground sensing, relating to the field of soil salinization. The developed equipment utilizes a vehicle towing an electromagnetically transparent platform carrying sensors via a non-metallic flexible traction component. Measurement software synchronously records centimeter-level spatial position, vehicle speed, sensor attitude, and apparent electrical conductivity of soil at different depths at a unified timestamp while traveling along a planned strip path. Simultaneously, it cleans up uncertain readings, abrupt local anomalies, and data from abnormal instrument attitudes. Subsequently, the apparent electrical conductivity data at different depths is rasterized, and the soil electrical conductivity estimates at different depths are inverted using an electromagnetic induction Q-3D algorithm. A three-dimensional distribution map of total soil salinity is then drawn, and salt accumulation areas are extracted using soil salinization grading standards, accurately defining and visualizing the geometric boundaries of farmland salinity patches. This application enables rapid and accurate monitoring of the three-dimensional spatial distribution of farmland salinity patches, contributing to the precise improvement of saline-alkali land.

The application discloses a kind of for forestry nursery stock transplanting after pipe maintenance regulation and control system and method, belong to forest seedling raising technical field.The application obtains total value of fertilization authority by soil moisture content and soil conductivity, and judges whether it is higher than preset authority threshold, if not, then store fertilization task temporarily, if yes, then carry out fertilization regulation and control, after fertilization, the change condition of soil moisture content is continuously monitored, whether to dynamically adjust basic fertilization amount and fertilizer solution concentration is determined, then respectively obtain seedling absorption effect index and root health index, then judge whether seedling absorption effect index belongs to absorption effect range, determine whether to adjust fertilizer solution concentration, finally judge whether root health index belongs to preset stage interval, determine whether to adjust current fertilization amount, improve the linkage control relevance of water management and fertilization management, solve the problem that the linkage control relevance of water management and fertilization management in prior art is lower.

The invention discloses a multi-source remote sensing data soil salt content inversion method and system based on a stacking model, and relates to the technical field of soil salt content prediction.The method comprises the following steps that the boundary of a target region is clearly researched, target monitoring points are arranged, soil conductivity data of sample sampling points are extracted, and then the soil salt content is calculated; ground spectral data, unmanned aerial vehicle images and satellite remote sensing spectral data are collected and subjected to spectral band frequency alignment, spectral reflectivity is extracted for each sample sampling point, a spectral characteristic index is constructed, salt content sensitive variables are screened out, the sensitive variables serve as input, the soil salt content serves as a label, and the salt content of the soil is calculated through a stacking model. According to the method, a soil salt content prediction model is constructed, salt content estimation of image pixel points of a research target region is realized, the model uncertainty during inversion of a single model is effectively reduced, and the prediction accuracy is improved.

The application discloses a dual-configuration fused soil conductivity measuring device and method, belongs to the technical field of intelligent agricultural equipment detection, and mainly comprises a test system, a rack and a detection device, wherein the test system and the detection device are both installed on the rack, the test system is installed above the rack, and the detection device is installed below the inside of the rack; according to different configurations, sensor electrodes are inserted into soil; soil conductivity values obtained by two configurations are transmitted to a JESTON nano through a controller; and a dual-configuration fused soil conductivity calculation model established based on a BP neural network is used to take the soil conductivity values obtained by the two configurations as model input parameters, to perform real-time calculation through the JESTON nano, and to display and output the optimized soil conductivity values on a touch liquid crystal display screen. The application can realize accurate measurement and storage of soil conductivity values at different depths in soil, is simple to operate, and is high in practicability.

The application relates to a saline-alkali soil irrigation method, device, intelligent control system and saline-alkali soil treatment system, and is applied to the field of agricultural planting irrigation in a salinization area. The method comprises the following steps: periodically acquiring soil information of a target irrigation area and a current month, wherein the soil information comprises soil water content and soil conductivity; according to the current month, accurate irrigation quantity and soil information threshold values which are in line with the characteristics of the current month are determined from preset irrigation information, wherein the soil information threshold values comprise a soil water content threshold value and a soil conductivity threshold value; when it is determined that irrigation needs to be performed according to the soil information and the soil information threshold values, the irrigation system is controlled to automatically realize water source irrigation according to the irrigation quantity, irrigation efficiency is improved, and the saline-alkali soil treatment effect is improved.

The utility model relates to soil detection technical field. The utility model discloses a kind of farmland soil conductivity real-time detection probe of anti-interference, including protective shell, the side wall of protective shell is slidably connected with cover plate, the inside of protective shell is slidably connected with conductivity detector, the bottom of conductivity detector is fixedly connected with detection probe, the detection probe is set by setting pollution cleaning component, pull rod is pulled upward, piston plate is driven along the inner wall of protective shell to slide upward, while piston plate drives conductivity detector and detection probe gradually retract to inside protective shell, effectively protect the integrity of detection probe, air in protective shell can be extruded to gas guide pipe by air guide component at this time, subsequently sprayed on the surface of detection probe, to improve the impact force and cleaning effect of airflow on the surface of detection probe impurity, more effectively remove soil particles, organic matter and other impurities attached on probe.

The invention provides an arid mining area vegetation restoration configuration method based on shrub-grass positive interaction, comprising the following steps: S1, detecting physicochemical properties of soil in a to-be-restored area, and screening to obtain limiting factors; s2, improving the soil in the to-be-restored area according to the limiting factor obtained in S1; S3, selecting a corresponding shrub type according to the soil conductivity of the improved soil in the to-be-restored area, and selecting a corresponding herbaceous plant type according to the shrub type; s4, planting according to the plant species selected in S3; and S5, managing and protecting the planted plants. The method disclosed by the invention has the beneficial effects that by utilizing positive interaction between shrub and grass in the arid region and assisting with proper soil improvement measures, relatively rapid vegetation recovery in the coal mine area in the arid region in Xinjiang is realized, and the constructed plant community is high in stability and better in resistance to interference of the external environment, and the ecological restoration result is more long-acting.

The application discloses a nitrogen-potassium synergistic fertilization method suitable for alfalfa planting in saline-alkali soil and belongs to the technical field of agricultural fertilization. In view of the fact that alfalfa fertilization methods for saline-alkali soil are lacked in the prior art, the nodule bacteria nitrogen fixation cannot be excited by nutrient synergy, nitrogen fertilizer is highly dependent, and the utilization rate is low, the application scheme comprises the following steps: determining the rhizosphere soil conductivity before sowing or before the green stage to divide the saline-alkali stress degree, and determining the nitrate nitrogen content; according to the mass ratio of nitrogen to potassium oxide in the fertilizer is dynamically adjusted according to the nitrate nitrogen content and the saline-alkali degree, when the soil nitrate nitrogen is low, the standard ratio is selected according to the saline-alkali degree, when it is moderate, the nitrogen is halved, and when it is sufficient, the nitrogen fertilizer is stopped; the exogenous nitrogen fertilizer is applied twice from the green stage to the initial flowering stage, the potassium fertilizer containing potassium fulvate is once deep applied from the green stage to the branching stage, and the potassium supply amount of the potassium fulvate is not less than 30% of the total potassium amount. The method is mainly used for alfalfa planting in saline-alkali soil, realizes nitrogen-potassium synergistic high-efficiency utilization, and relieves the saline-alkali stress.

The application is a barley saline-alkali tolerant land cultivation method based on water-salt synergistic regulation and rhizosphere micro-ecological optimization, discloses a barley saline-alkali tolerant six-dimensional closed loop cultivation technical system for sustainable utilization of saline-alkali land, and specifically has the following contents: 1. hierarchical composite improvement: according to the soil conductivity and pH value, the mild saline-alkali area is improved by straw mulching and slow-release humic acid-calcium alginate granular fertilizer surface layer improvement; the moderate and severe saline-alkali area is improved by double-layer deep ploughing barrier breaking, deep application of gypsum combined with salt-removing functional bacteria biochar-based microbial inoculant, and salt-alkali obstacle is synergistically reduced. 2. whole-process adaptive regulation: the variety carrying HvNHX1 / HvSOS1 salt-tolerant molecular marker is selected, and the resistance is activated by the coating of fenhexamid-chitosan oligosaccharide-nano selenium; the double-mode irrigation of "drip irrigation + shallow buried infiltration irrigation" is matched, the salt threshold value is established to trigger leaching; the rhizosphere is strengthened by silicon-based amino acid water-soluble fertilizer, and green prevention and control is integrated. The technology can increase yield by 32.5% to 48.7% in moderate saline-alkali land, can reduce salt and improve soil year by year, is suitable for large-scale production in main saline-alkali areas, and has significant application prospect.

The application relates to the field of agricultural irrigation technology, in particular to a water conservancy facility irrigation data collection method and system. The method comprises the following steps: calibrating and storing a reference state of a target plot when soil moisture is sufficient and salt content is lower than a first preset value, wherein the reference state comprises a reference soil moisture content parameter and a reference soil conductivity parameter; comparing the real-time soil moisture content parameter and the real-time soil conductivity parameter with the reference soil moisture content parameter and the reference soil conductivity parameter in the reference state to determine whether physiological drought caused by salt accumulation exists in crops of the target plot, and generating a determination result; by comparing the real-time soil moisture content and conductivity of the crop root zone with the baseline reference state, whether the stress of the crops is caused by physiological drought caused by salt accumulation can be accurately determined, so that the irrigation water volume is prevented from being incorrectly increased when physiological drought occurs.

The utility model relates to the field of agricultural sensors, and discloses a field intelligent agricultural sensor device. According to the application, a data analysis main body is fixedly connected to the outer surface of the middle of a supporting storage battery plate, a soil temperature and humidity sensor is fixedly connected to the lower surface of the data analysis main body, a soil pH sensor is fixedly connected to the lower surface of the soil temperature and humidity sensor, and a soil conductivity sensor is fixedly connected to the outer surface of the supporting storage battery plate; the upper surface of the supporting storage battery plate is fixedly connected with a wireless transceiver, and a soil conductivity sensor is used for measuring soil salinity and nutrient content and evaluating soil fertility; the soil pH sensor monitors the soil pH value and guides soil improvement, two probes of the soil temperature and humidity sensor are sleeved with the soil pH sensor, the soil water content and the soil temperature are monitored through the two positions exposed out of the soil pH sensor respectively, irrigation decision optimization is helped, sowing and fertilization time is guided, and the soil temperature and humidity sensor is connected with the soil temperature and humidity sensor. And the data is transmitted out through the wireless transceiver, so that wired transmission is not needed.

The present application relates to cultivated land diagnosis and repair system, more specifically, cultivated land quality degradation intelligent diagnosis and adaptive repair system based on multi-source perception. In view of the problem that the existing cultivated land repair relies on artificial experience and cannot adaptively adjust the repair strategy according to the degradation degree, the system collects soil conductivity, pH, compactness, moisture content and spectral data in real time through a multi-source sensor array, calculates the cultivated land health index CHI by the on-board fusion computing controller, determines the health, light and moderate degradation and severe degradation of three grades according to the CHI value, and automatically matches the corresponding adaptive repair strategy: light and moderate degradation executes shallow deep loosening and synchronous spreading of organic fertilizer, and sprays microbial inoculum after 3 to 7 days; Severe degradation executes double-layer deep loosening, green manure seeding and straw mulching. After the repair operation for a crop growth period, the system retests CHI and calculates the improvement rate, and when the improvement rate is insufficient, the repair intensity is automatically improved and the next round of repair is entered.

The application relates to the technical field of saline-alkali soil improvement, and discloses a salt content dynamic prediction and regulation method for crop stress-resistant cultivation soil in saline-alkali soil, which predicts the soil salt content of the saline-alkali soil through a target soil salt content prediction model (including a ConvLSTM encoder, a physical constraint feature extraction layer and a Transformer encoder) to obtain a target soil conductivity prediction value and a target soil volume water content prediction value; then, the target soil conductivity prediction value, the target soil volume water content prediction value, a current soil volume water content and a preset salt content threshold are taken as inputs, a multi-objective optimization algorithm is used to solve a multi-objective optimization model which takes minimizing the soil conductivity exceeding value and the irrigation water consumption of the saline-alkali soil as a target and is constrained by the total daily irrigation amount and the dynamic soil volume water content, a target irrigation strategy is obtained, and the saline-alkali soil is irrigated; thus, a closed loop from prediction to regulation can be realized, and the saline-alkali soil management effect is improved.

The invention relates to the technical field of real-time monitoring and accurate improvement of soil conductivity in saline areas such as farmlands, grasslands and wetlands, and provides a saline soil conductivity dynamic monitoring and improvement method which comprises the following steps: deploying mobile monitoring nodes, and collecting field sensing data streams according to a dynamically planned path; processing the data by using a collaborative Kriging interpolation and data assimilation technology to generate a real-time conductivity distribution diagram and an uncertainty quantization diagram; inputting the chart into a salinization digital twinning environment, and simulating, deducing and outputting a variable operation prescription chart through a deep reinforcement learning agent; controlling an operation machine tool to perform variable operation according to the prescription map; and finally, collecting operation feedback data for updating a monitoring path and correcting model parameters to form a self-adaptive closed loop. According to the method, deep cooperation of monitoring and improvement links is realized, the salt space heterogeneity can be dynamically responded, the resource utilization efficiency is improved, and the ecological risk is reduced.

The invention relates to the field of agricultural data analysis, in particular to a windy desert area black land moisture and nutrient coordinated regulation and control method, which comprises the following steps: acquiring sensor data after a fertilization event and setting parameters to obtain basic data required by evaluation; performing multi-dimensional quantitative processing on the soil conductivity dynamic data profile to obtain a stress risk factor; carrying out collaborative deviation degree evaluation on the combined state of the soil conductivity and the soil water content to obtain an effective absorption factor; performing normalized comparison and fusion on the stress risk factor and the effective absorption factor to obtain a process quality adjustment index; the optimal injection rate and injection duration of the next fertilization event are obtained by performing fertilization execution parameter mapping on the process quality adjustment index, so that the problems of fertilization risk and absorption effectiveness distortion caused by the fact that the existing PI control based on fertilization average conductivity feedback cannot identify the impact trailing process form are solved.

The application discloses a phosphorus application method for improving salt-alkali resistance of cotton seedlings, and specifically comprises the following steps: S1, in the critical period from after cotton sowing to before true leaf unfolding, a small amount of phosphate solution is drip irrigated for multiple times; S2, the drip head position and drip irrigation depth of the drip irrigation system can ensure that the phosphate solution directly acts on the vicinity of the cotton root system, so that the root system is stimulated to develop to the deep soil, thereby enhancing the salt-alkali resistance of the cotton seedlings; S3, slow-release phosphate particles or phosphate in a wrapped form are used, which ensures that the cotton can obtain stable phosphorus nutrition supply in the whole seedling period; and S4, an online monitoring platform is established for collecting information such as soil conductivity, pH value and cotton growth condition in real time.

This invention belongs to the field of fertilization control technology, specifically relating to an adaptive fixed-point quantitative fertilization control system and method, including the following steps: S1, acquiring the real-time position, speed, and heading angle of the agricultural machinery, and simultaneously collecting multispectral images of the crop canopy and soil electrical conductivity data at the current position; extracting the crop canopy spectral index from the crop canopy multispectral image, and constructing a spatiotemporal influence weight matrix representing the spatial correlation of crop nutrient requirements based on the historical and current crop canopy spectral indices of multiple sampling points within the current position and a preset spatial neighborhood; S2, calculating a position correction vector to compensate for the spatial lag between the sensor measurement position and the fertilization actuator's action position, based on the agricultural machinery's speed and heading angle. This invention achieves dual precise correction of application position and application amount, ensuring that fertilizer can be accurately applied to the target point, and improving the positional and dosage accuracy of fixed-point quantitative fertilization operations.