317 results about "Soil characteristics" patented technology

The invention discloses a soil fertility intelligent assessment method and system based on image recognition, and relates to the technical field of data processing, and the method comprises the steps: obtaining land image information of a to-be-assessed region, the land image information comprising a multispectral image, a thermal imaging image and an RGB image of the to-be-assessed region; carrying out image preprocessing on the land image information, and carrying out vegetation coverage and health assessment according to the multispectral image: speculating soil characteristics according to the RGB image: speculating the humidity change of a soil surface layer according to the temperature distribution of a thermal imaging image, and identifying a drought region and a region with sufficient moisture; integrating the high-resolution texture features of the RGB image, the spectral information of the multispectral image and the speculation result of the temperature distribution of the thermal imaging image to generate a comprehensive analysis result; and classifying soil types and evaluating fertility grades according to a comprehensive analysis result. The problem that in the prior art, in intelligent soil fertility evaluation, workers need to carry out on-site sampling examination is solved, and the technical effect of improving the soil fertility evaluation efficiency is achieved.

The invention discloses an ecological pollution migration path analysis and early warning method and system based on soil heavy metals, and particularly relates to the technical field of ecological pollution. Monitoring points are arranged around a pollution source, micro CT scanning is combined to analyze permeability changes of soil under different humidity, a synchrotron radiation X-ray spectrometer is utilized to analyze dynamic changes of chemical forms of heavy metal, and the influence of humidity changes on migration paths and form transformation is comprehensively evaluated. The deviation degree of a model prediction result and an actual migration behavior is quantified, early warning signals of different levels are generated for the situation with the high deviation degree, corresponding measures are taken, the complex influence of abnormal soil characteristics on heavy metal migration is dynamically responded, and therefore the harm of soil pollution diffusion to the environment and ecology is effectively prevented and controlled.

The invention discloses a drip irrigation parameter dynamic regulation and control method combined with multi-point sensor monitoring, and relates to the technical field of irrigation regulation and control, the method comprises the following steps: monitoring a multi-point sensor arranged in a target area to obtain target monitoring data; performing actual demand analysis on the target crop to obtain actual demand data; analyzing the target soil permeability of the target area to obtain a target irrigation period; and performing irrigation processing according to the actual demand data and the target irrigation period to obtain irrigation data. The technical problems that in the prior art, real-time requirements of crops cannot be accurately obtained, irrigation is difficult to implement according to soil characteristics, and the agricultural production efficiency and sustainability are limited are solved. The effects that multiple types of monitoring data are obtained by arranging the multi-point sensors in the target area, precise irrigation is achieved, the crop growth environment is optimized, good physicochemical properties of soil are maintained, and the technical effects of high efficiency and sustainability of agricultural production are improved are achieved.

The invention discloses a microbiological culture scheme customization recommendation method and system based on soil data analysis, and relates to the technical field of microbiological culture plants.The method comprises the steps that soil samples at different positions and depths are collected, soil characteristic data are analyzed, and data processing is carried out; microbial community information is obtained through soil DNA extraction, PCR amplification and high-throughput sequencing, and distribution and functions of microorganisms are evaluated in combination with data preprocessing and diversity analysis; selecting proper microbial strains according to soil characteristics and microbial community analysis results; a microbial culture scheme is combined with agricultural management measures; the conditions of soil and microorganisms are monitored in real time, and a microorganism culture scheme is dynamically adjusted based on a feedback mechanism; through field trials and advanced performance evaluation indexes, the effect of the microbial culture scheme is verified for a long time. The method has high adaptability and sustainability, and customized microorganism management schemes can be provided in different agricultural environments.

The invention relates to the technical field of pipeline detection, in particular to an optimization method for improving cathode protection detection of a complex buried pipe network, which comprises the following steps of: extracting characteristic information in a pipeline area based on potential value and resistivity data in the pipeline area, performing aggregation analysis on corrosion risk through soil characteristic data, and calculating the corrosion risk of the pipeline. And determining the risk membership degree of the pipeline region, and generating a corrosion risk distribution diagram in the region. According to the invention, through calculation of the potential field around the pipeline and the dynamic change of the electric field, accurate identification of the corrosion risk area and optimization of the protection effect are realized. By establishing a three-dimensional space grid and an electric field model, the change trend of an electric field at different time nodes is captured, and formation and evolution of electric field hotspots can be tracked in space and time dimensions. And the response speed to the abnormal change of the local electric field is improved, so that the corrosion problem caused by overhigh local current density is effectively avoided.

The invention provides a regulation factor threshold effect evaluation method and device for vegetation response sudden drought characteristics, equipment and a storage medium. Relates to the technical field of drought risk prediction and influence evaluation. The method comprises the following steps: acquiring hydro meteorological data, vegetation productivity data, topographic feature data, soil characteristic data and biological variable data of a target area; constructing a drought suddenness index, extracting a drought suddenness event according to the drought suddenness index, and determining a drought suddenness feature of the drought suddenness event; extracting vegetation productivity abnormal data before and after the sudden drought event, and determining the response characteristic difference of the vegetation to sudden drought; the method comprises the following steps: determining influence factors of vegetation on sudden drought response characteristics, fusing XGBoost, a random forest regression model and an SHAP interpretability analysis method, analyzing regulatory factors of the vegetation response sudden drought characteristics, and determining a threshold effect of the regulatory factors. According to the method, the nonlinear cooperative regulation effect of multiple factors on vegetation response sudden drought characteristics can be disclosed more comprehensively.

The invention relates to the field of civil engineering, and discloses a foundation pit finite element model parameterization rapid modeling method which comprises the following steps: constructing a finite element model through foundation pit geometric information and soil characteristics, simulating soil response by adopting a nonlinear constitutive relation and a random process, and realizing foundation pit stability optimization and dynamic adjustment; the invention further provides a foundation pit finite element model parameterization rapid modeling system which comprises an input module, a modeling module, a constitutive model module, a random process module, a simulation module, an optimization module, a mesh refining module and a real-time monitoring module. According to the method, the foundation pit finite element model is automatically generated, the Kachanov-Delace nonlinear soil constitutive model is introduced, the soil elastic modulus random field is generated based on the Gaussian process, and the model parameters are dynamically adjusted in real time, so that the modeling process is simplified, the calculation precision is improved, the nonlinear behavior and dynamic response of the soil are accurately simulated, and the method is suitable for large-scale popularization and application. And the stability and the safety in the foundation pit design and construction process are obviously improved.

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 discloses a slope stability analysis method based on rock and soil characteristics, belongs to the technical field of traffic engineering modeling, and aims to solve the technical problems as follows: exploring a slope instability mechanism; analyzing the reliability of the slope sliding surface system; the influence of the hydraulic effect on the slope stability is avoided. The method specifically comprises the steps that the geological structure, the rock-soil body type and the distribution characteristics of the side slope are surveyed in detail; performing indoor and outdoor tests to obtain mechanical parameters of the rock-soil body; the influence of underground water level change, rainfall infiltration and underground water flow on the slope stability is investigated, then main factor parameters influencing the slope stability are determined, a slope two-dimensional finite element model is established on the basis, investigation parameters are input, and subsequent feedback and improvement are carried out. Therefore, the performance of the slope stability under the influence of complex geological conditions and external factors is explored.

The invention belongs to the technical field of meteorological disaster prediction, and discloses a flood early warning method based on rainfall multilayer perception. Comprising the steps of collecting meteorological parameter data, terrain parameter data, hydrological soil data and human activity data; preprocessing the collected meteorological parameter data, topographic parameter data, hydrological soil data and artificial activity data to obtain a meteorological feature data set, a topographic feature data set, a hydrological soil feature data set and an artificial activity feature data set; fusing the meteorological feature data set, the topographic feature data set, the hydrological soil feature data set and the human activity feature data set to obtain a comprehensive feature data set; training according to the comprehensive feature data set to obtain a flood risk prediction model, and predicting through the flood risk prediction model to obtain a flood risk index; the predicted flood risk index is compared with a preset flood risk index threshold value, and whether flood early warning needs to be carried out or not is judged; and a worker is helped to accurately make flood control measures.

The invention relates to the technical field of geotechnical engineering, in particular to a bedding side slope stability judgment method and system, and the method comprises the following steps: scanning a target bedding side slope by using an ultrasonic sensor based on the position information of the bedding side slope, recording a three-dimensional geological structure image of the side slope, detecting the positions of cracks and cavities, and generating a bedding side slope structure image. According to the method, an ultrasonic sensor is used for scanning a slope, internal cracks and cavities are recognized, stability problems are found in the early stage, side slope rock and soil characteristics are recognized in combination with physical and chemical attribute measurement, a three-dimensional geologic model is constructed through terrain scanning, and interaction between soil particles and rocks in multiple scenes is simulated; according to the method, the behaviors of the slope under various natural and artificial conditions are analyzed, the instability behavior of the slope is identified, the influence of various factors on the stability of the slope is evaluated, the ability of taking precautionary measures for various risk factors is enhanced, and a decision maker is helped to make accurate maintenance and intervention decisions.

The invention discloses a self-adaptive inclined excavator bucket system and a control method thereof. The self-adaptive inclined excavator bucket system comprises a bucket, an inclination sensor, a laser distance measuring sensor, a soil characteristic sensor, a main controller and an executing mechanism. The inclination sensor is installed on the rear side of the bucket and used for monitoring the inclination angle of the bucket in real time. The laser distance measuring sensor is installed on the front edge of the bucket and used for measuring the distance between the bucket and the ground. The soil characteristic sensor is installed on bucket teeth of a bucket and used for obtaining physical characteristic information of soil in real time. The main controller is electrically connected with all the sensors and the executing mechanism and is used for receiving and processing data of the sensors in real time and sending a control command to the executing mechanism; the executing mechanism comprises a hydraulic system and a servo motor and is used for receiving a control command of the main controller in real time and automatically adjusting the inclination angle and the digging force of the bucket. The inclination angle and the digging depth of the bucket can be automatically adjusted according to different conditions, and the working efficiency, precision and safety are improved.

The invention discloses an intelligent fertilizer distribution control system based on Beidou positioning, and relates to the technical field of agricultural automation, and the system comprises the steps: building a fertilization simulation model, and obtaining the relation data of the disc opening size and the fertilization amount of a fertilizer distributor through an experiment; soil analysis data and remote sensing image data are collected and preprocessed; generating a fertilization prescription map by using a multi-objective optimization model based on the preprocessed soil analysis data and remote sensing image data according to the soil characteristics and crop requirements of the field; high-precision positioning data are obtained through a Beidou positioning system, and the fertilization prescription map and the high-precision positioning data are fused to complete field space calibration; based on the field space calibration result and the high-precision positioning data, adopting a Dijkstra algorithm to generate an optimal fertilizer spreading path; in combination with the real-time speed of the tractor and the fertilization simulation model, the disc opening size of the fertilizer spreader is dynamically regulated and controlled, and the fertilization amount is accurately controlled by using a control algorithm; the tractor corner and the field boundary are monitored in real time, and the fertilizer distributor is automatically closed.

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 invention discloses a remote sensing image-based western plateau frozen soil hot melt disaster identification method. The method comprises the following steps of obtaining and preprocessing a satellite remote sensing image and a radar remote sensing image of a western plateau frozen soil preset area; performing multi-scale segmentation on the preprocessed satellite remote sensing image to obtain frozen soil characteristics of a preset area; performing time sequence InSA analysis on the preprocessed radar remote sensing image to obtain the earth surface deformation rate of the preset area; constructing a western plateau frozen soil hot melt disaster identification model based on the frozen soil characteristics and the earth surface deformation rate; and based on the western plateau frozen soil hot melt disaster identification model, completing western plateau frozen soil hot melt disaster identification based on the remote sensing image. According to the invention, the occurrence and evolution trend of frozen soil hot melt disasters can be found in time. By constructing a disaster recognition model, early warning and monitoring of potential disaster areas can be realized, and a scientific basis is provided for disaster prevention and control.

The invention relates to the technical field of agriculture, in particular to a precise fertilization variable control system and method applied to a spiral fertilizer applicator, and the method comprises five steps of data acquisition, data processing, variable control, fertilization optimization and execution control. Field environment data are collected in real time through various sensors, a field environment information graph is generated by adopting a multi-modal data fusion technology, and based on the information, the fertilization amount, the fertilization angle and the fertilization time are adjusted in real time by adopting a self-adaptive algorithm; further combining crop growth requirements and soil characteristics, optimizing a fertilization scheme through a genetic algorithm, and finally, accurately adjusting the fertilization amount and the fertilization area by a fertilizer applicator according to the optimized scheme, so as to ensure the precision and efficiency of the fertilization operation. According to the invention, through precise fertilization control, the efficient utilization of resources is realized, meanwhile, the negative influence of the fertilizer on the environment is reduced, and a sustainable fertilization solution is provided for agricultural production.

A method is provided for determining soil properties for an area of land, from soil spectrum data. In an embodiment, the method includes receiving soil spectrum data records from hyperspectral sensors that represent a mean soil spectrum of a specific geo-location of the area of land and removing interference signals from the spectrum data records to create soil spectral bands. The method also includes predicting a plurality of soil property datasets based on a partial least-square regression and the soil spectral bands and selecting specific soil property datasets from the plurality of soil property datasets to represent soil properties of the specific geo-location, wherein the specific soil property datasets include property data and spectral band data for spectral bands used to determine the property data. The specific soil property datasets may then be used to generate a crop prescription of recommended hybrid seeds or population densities for the specific geo-location.

The disclosure relates generally to methods and systems for ground water prediction using integration of satellite and auxiliary observations. Conventional techniques in the art for the ground water level prediction are not accurate and efficient for predicting the ground water level. The present disclosure combines time-series archived remote sensing data with a wide array of past auxiliary datasets specific to a given region for precise prediction of future ground water condition, to predict the ground water situation i.e. rising or declining for a given region. These encompass diverse information such as weather conditions, soil properties, agricultural data, population statistics, water resources information, industrial details, drought records, seismic data, and surface deformation patterns. The present disclosure also considers different future scenarios which can be built on future cropping patterns, forecasted weather conditions, use of irrigation system in future, and future population growth of the given region.

The invention discloses a soil fertility intelligent assessment method and system based on image recognition, and relates to the technical field of data processing, and the method comprises the steps: obtaining land image information of a to-be-assessed region, the land image information comprising a multispectral image, a thermal imaging image and an RGB image of the to-be-assessed region; carrying out image preprocessing on the land image information, and carrying out vegetation coverage and health assessment according to the multispectral image: speculating soil characteristics according to the RGB image: speculating the humidity change of a soil surface layer according to the temperature distribution of a thermal imaging image, and identifying a drought region and a region with sufficient moisture; integrating the high-resolution texture features of the RGB image, the spectral information of the multispectral image and the speculation result of the temperature distribution of the thermal imaging image to generate a comprehensive analysis result; and classifying soil types and evaluating fertility grades according to a comprehensive analysis result. The problem that in the prior art, in intelligent soil fertility evaluation, workers need to carry out on-site sampling examination is solved, and the technical effect of improving the soil fertility evaluation efficiency is achieved.

The invention provides a temperature regulation and control system and method based on earthworm breeding environment temperature prediction, and relates to the technical field of temperature prediction, and the system comprises a data collection module which is used for continuously collecting soil temperatures at T historical moments at equal time intervals and environment parameters which affect the earthworm breeding soil temperature; the characteristic matrix construction module is used for constructing a characteristic matrix at the same moment, and the environment influence model construction module is used for obtaining a soil prediction temperature; the data analysis module is used for processing the soil characteristic parameters, generating a soil influence coefficient and calculating a suitable coefficient of the soil temperature; and the comprehensive evaluation module is used for integrating the suitability coefficient of the soil temperature and the soil influence coefficient to generate a comprehensive evaluation coefficient so as to evaluate the suitability degree of the soil temperature, and executing a corresponding temperature regulation and control mode according to the coefficient. The method can truly reflect the influence of the environment and soil characteristic change on the temperature, and significantly improves the temperature prediction precision of the earthworm breeding environment.

The invention relates to the technical field of agricultural precise management, and discloses an unmanned aerial vehicle precise variable rate fertilization method, which comprises the following steps: collecting vegetation indexes and color feature data of crops in a target plot through an unmanned aerial vehicle carrying a multispectral sensor and an RGB camera; acquiring soil characteristic data of the target land parcel, wherein the soil characteristic data comprises nitrogen, phosphorus and potassium nutrient content, humidity and pH value in soil; the invention further provides an unmanned aerial vehicle precise variable rate fertilization system which comprises a data acquisition module, and the data acquisition module is configured to acquire vegetation indexes, color characteristics, soil characteristics and meteorological data of the target land parcel through a multispectral sensor, an RGB camera, a soil sensor and a meteorological sensor carried by the unmanned aerial vehicle. Through multi-source data fusion, dynamic fertilization adjustment and path optimization, precise variable fertilization is realized, the fertilizer utilization efficiency is improved, the scientificity and efficiency of fertilization operation are improved, and meanwhile, the environmental influence is reduced.

The present invention provides an emergency supervision method for a smart city lifeline project and an Internet of Things large model system, which relate to the field of emergency supervision technology. The Internet of Things large model system includes an emergency supervision user platform, an emergency supervision service platform, an emergency supervision management platform, an emergency supervision sensor network platform, and an emergency supervision object platform. The method is executed by the emergency supervision management platform, and includes: in response to the gas environment characteristics corresponding to the target pipeline meeting the early warning conditions, every preset period: based on the spatial connectivity information corresponding to the target pipeline, determining the target sensor and obtaining the corresponding air flow data; based on the gas transportation data, spatial connectivity information, air flow data and regional soil characteristics of the target pipeline, determining the estimated diffusion amplitude of the target gas; based on the estimated diffusion amplitude, determining the inspection frequency and sampling frequency to obtain soil samples during the inspection; and receiving leakage warnings. The present invention can achieve accurate identification of leakage risks and timely warnings.

The invention relates to the technical field of artificial intelligence, and provides a soil texture recognition model construction method, a soil texture recognition model construction device, a computer readable storage medium and electronic equipment, and the soil texture recognition model construction method comprises the steps: screening key soil texture features from a plurality of ocean soil texture features; the feature importance score of the key soil feature is higher than a preset score threshold; collecting training data associated with the key soil characteristics, and training a plurality of initial machine learning models by using the training data; and according to a preset performance evaluation index, screening out a final target machine learning model for ocean soil texture identification from the plurality of initial machine learning models. According to the invention, through an automatic modeling mechanism combining feature optimization and multi-model performance screening, the classification precision and engineering applicability of the ocean soil texture identification model are improved.

The invention discloses a slope stability analysis method and system based on data analysis, belongs to the technical field of slope safety analysis, and aims to solve the problems of dependence on hypothesis simplified model and neglect of real-time dynamic change in the prior art. S2, dynamic environment factor analysis; s3, slope stability analysis; s4, establishing an intelligent decision-making and early warning system; s5, system integration and user interaction; s6, performing system optimization and continuous learning; by comprehensively considering complex soil body characteristics such as heterogeneity and anisotropy of the slope and dynamic changes of environmental factors such as external rainfall, meteorology and earthquakes, the system can provide a more real and accurate slope stability analysis result, an intelligent algorithm and a data analysis technology are adopted, and the stability of the slope is improved. The dependence on a simplified physical model and a static hypothesis is reduced, so that the scientificity and the practicability of an analysis result are improved.

The invention discloses a rake head flushing parametric modeling system and method for a clay type rake head excavator, and relates to the technical field of excavators. In order to solve the problems of unstable dredging quality, high energy consumption, quick abrasion, low digging efficiency and the like caused by the fact that the traditional drag head design often depends on experience to adjust flushing parameters and lacks scientific theoretical guidance and parametric modeling. Through accurate parameter input and soil characteristic analysis, the optimal flushing parameter configuration can be provided for the drag head, so that the dredging efficiency is improved, the flushing amount and pressure are dynamically adjusted, it is ensured that efficient soil cleaning and soil adhesion reduction can be achieved under different soil conditions, and the cleaning and maintenance cost is reduced; the real-time monitoring and feedback system can respond to the change of soil characteristics in time, predict the soil change and the flushing effect, improve the prediction accuracy and reliability of operation, accurately control the flushing pressure and flow, adapt to different types of soil and improve the universality and adaptability of the dredger.

The invention provides a pile foundation structure optimization method and device based on a grey correlation analysis method, provides a method for determining the optimal structural form of a pile foundation, and effectively overcomes the design defects existing in a previous pile foundation structure design method. The method comprises the steps that pile foundation design is conducted on a to-be-driven area according to obtained geological profile data and soil characteristic data of the to-be-driven area, and multiple pile foundation structure combinations are obtained; corresponding pile foundation models are constructed on the basis of the multiple pile foundation structure combinations, the pile foundation models are simulated, and corresponding evaluation data are obtained; performing correlation degree calculation on the plurality of influence factors of the evaluation data through a grey correlation analysis method to obtain correlation degrees corresponding to the plurality of influence factors, and screening out influence factors meeting preset conditions based on the correlation degrees; and a target pile foundation combination of the pile foundations is determined based on the influence factors meeting the preset conditions, and the pile foundation structure of the to-be-driven area is optimized through the target pile foundation combination.

The invention provides a slope displacement monitoring method and system for a high and steep slope in a loess area, and the method comprises the steps: carrying out the preprocessing of data through a point cloud denoising algorithm according to an initial point cloud data set, filtering noise points and irrelevant reflection points caused by a complex terrain, and generating an optimized refined point cloud data set; aiming at the refined point cloud data set, constructing a digital surface model of the side slope by utilizing a three-dimensional reconstruction algorithm, carrying out local detail correction on the model in combination with soil loosening characteristics of a loess area, and determining a preliminary morphological structure of the side slope; performing time sequence data acquisition on the preliminary morphological structure to obtain slope three-dimensional model data of multiple time periods, and analyzing the dynamic evolution trend of morphological change to obtain slope deformation feature distribution; according to the slope deformation characteristic distribution, a finite element analysis method is adopted to conduct simulation calculation on stress distribution of the high and steep slope, the stability risk of a deformation area is judged, and potential landslide risk points are determined.

A computer-implemented method for generating a soil property map of a field includes the steps of receiving (S1) crop characteristic distribution data for the field, the crop-related parameter being within a predetermined range of the crop characteristic distribution data, determining (S2) equivalent areas having the crop-related parameter within a predetermined range of the crop characteristic distribution data, receiving (S3) soil data relating to the at least one soil parameter for each of the determined equivalent areas, and generating (S4) a soil property map of the field based on the soil data and the equivalent areas.

A system and method for characterizing matter, for example, soil organic content is disclosed. A radiation and electric field sensor measure sample properties before, during and after irradiation. Calibrations are developed relating those measurements to useful properties of matter, for example, soil density and organic content. As an example of an embodiment of the disclosed invention an instrument attachment for portable X-ray fluorescence instrumentation was prototyped enabling concurrent volumetric soil organic matter quantification. This primary prototype outperformed more expensive emerging visible-near infrared multivariate instrumentation using parsimonious soil specific simple linear regression (R2 ranged 0.85-0.97) enabling rapid, parallel, nondestructive, cost-effective acquisition of soil elemental concentrations together with organic content data.

The invention discloses a lolium perenne seedling returning nitrogen reduction amount regulation and control method based on soil multifunctional evaluation, and relates to the technical field of agricultural planting.According to the method, a closed-loop dynamic regulation and control system is constructed, aiming at the soil characteristic difference after lolium perenne seedlings are returned to the field, precise and personalized management of the application amount of nitrogen fertilizer is achieved, and the application amount of nitrogen fertilizer is improved. According to the method, the nitrogen fertilizer compensation amount is dynamically adjusted according to the soil multifunctionality real-time evaluation result of the key growth stage of crops, and the yield fluctuation caused by blind reduction of application is effectively avoided, so that the stability and improvement of the crop yield are ensured while the chemical nitrogen fertilizer input is remarkably reduced, and the economic benefit is increased. The technical scheme that physical, chemical and biological indexes of soil are comprehensively evaluated in the key growth stage of crops, and the nitrogen fertilizer correction amount is dynamically calculated based on the deviation between the evaluation result and the target function range is adopted, so that the accurate regulation and control of the nitrogen fertilizer application amount can be realized; therefore, the stable yield of crops is guaranteed and the soil health level is continuously improved while the application of chemical nitrogen fertilizer is reduced.