226 results about "Field soil" patented technology

The invention discloses a soil element spectrum detection analysis method and system based on machine learning, and belongs to the technical field of smart agriculture. Field soil element data, plant growth data and environment data are obtained, and an element mineralization release model, an element loss model, a plant absorption model and a pollution element influence model are constructed; the method comprises the following steps: evaluating element mineralization release amount, plant element absorption amount and influence of harmful elements on plant absorption, constructing a soil element content prediction model, introducing the mineralization release amount, element loss amount, plant absorption amount and pollution element influence into the soil element content prediction model to calculate future soil element content, and constructing a fertilization time prediction model. The future soil element content is introduced into the fertilization time prediction model to evaluate the fertilization time, the fertilization time is predicted by coupling the soil element dynamic evolution and plant growth absorption and combining the nutrient demand characteristics of the plant in different growth states, and the plant planting fertilization efficiency is improved.

The invention discloses a tobacco field soil acidification early warning treatment system based on Internet of Things, and relates to the technical field of intelligent agriculture Internet of Things, and the system comprises an Internet of Things sensor network which is deployed in a tobacco field area and is used for collecting soil pH value, temperature, humidity and calcium and magnesium ion concentration data in real time. According to the tobacco field soil acidification early warning treatment system based on the Internet of Things, the tobacco growth stage sensitivity coefficient, the regional acidification historical trend and real-time monitoring data are dynamically fused, a self-adaptive early warning threshold value is generated through a nonlinear product algorithm, and the problem of early warning lag or false alarm caused by a fixed threshold value is solved; according to the method, a dual verification mechanism of trend deviation test and virtual governance simulation is combined, abnormal fluctuation interference is screened out through a rigid rule, strategy feasibility is pre-judged, it is ensured that a governance scheme has both accuracy and robustness, and the problems that governance resources are mismatched and the effect is substandard are solved.

The invention discloses an ecological restoration effect evaluation method and system based on satellite remote sensing, and the method comprises the steps: collecting the satellite remote sensing data and field soil data of a preset region, and taking the remote sensing data of the preset region within a specified time as to-be-analyzed data; calculating a time sequence deviation and a contrast ratio based on the satellite remote sensing data to obtain a grading region; performing deviation correction on the satellite remote sensing data according to the field soil data in the grading region, and inputting the corrected satellite remote sensing data into a space-time ecological development prediction model to obtain ecological development prediction data; performing restoration uncertainty analysis according to the ecological development prediction data and the field soil data to obtain an ecological restoration effect confidence coefficient, and performing elastic capability analysis according to the ecological restoration effect confidence coefficient and the satellite remote sensing data to obtain an ecological elastic index; and constructing a time-varying ecological restoration effect evaluation model according to the ecological elasticity index, and outputting an evaluation result based on the to-be-analyzed data.

The invention provides a method and a system for estimating organic carbon reserve change of soil in a vegetable field in a short time, and belongs to the technical field of soil measurement. The method comprises the following steps: acquiring net ecosystem carbon income and expenditure (NECB); and estimating the organic carbon reserve of the vegetable field soil by using net ecosystem carbon income and expenditure (NECB). According to the method, the organic carbon reserve of the soil in the vegetable field can be quickly estimated, the influence of different farming measures on the organic carbon reserve of the soil in the vegetable field in a short period can be known, and farmers and agricultural managers can optimize management measures such as fertilization, irrigation and planting modes; carbon emission and fixed conditions of a farmland ecosystem can be determined, so that the speed and the degree of climate change can be better predicted, and reasonable vegetable planting management measures can be taken in time.

The invention discloses a winter wheat field soil fertility evaluation data processing method based on comprehensive weight calculation, and relates to the technical field of data processing, and the method comprises the steps: S1, collecting nutrient content and moisture retention data from field soil through a sensor network, performing grouping processing on the acquired nutrient content and moisture retention data by adopting decision node splitting and entropy calculation to obtain a soil fertility layering result; s2, according to a soil fertility layering result, acquiring root depth and leaf moisture content indexes of the winter wheat in different layers of soil from crop monitoring equipment, analyzing association strength of the root depth and leaf moisture content indexes and fertility layering by adopting leaf node classification and feature selection standards, and determining a fertility contribution coefficient; according to the winter wheat field soil fertility evaluation data processing method based on comprehensive weight calculation, efficient resource allocation and stable yield are realized, and the drought resistance and resource utilization efficiency of winter wheat in a drought environment are remarkably improved.

The invention discloses a method and system for evaluating the influence of long-term fertilization on rice field soil heavy metals, and the method comprises the steps: obtaining rice field soil data through a sensor, and obtaining a standardized soil physicochemical property data set and a heavy metal content data set; according to the standardized soil physicochemical property data set and the heavy metal content data set, obtaining a feature vector set reflecting correlation between soil physicochemical properties and heavy metal behaviors; aiming at the feature vector set, obtaining a prediction model for representing the influence of the fertilization mode on the heavy metal mobility; if the heavy metal effective state content output by the prediction model exceeds a preset bioavailability threshold value, classifying the soil physicochemical property data set, judging the influence weight of the soil pH value and the organic matter content on the cadmium mobility, and obtaining the classified soil environment risk grade; and according to the classified soil environment risk levels, obtaining comprehensive rice field soil heavy metal pollution evaluation indexes. The pertinence and effectiveness of pollution control are remarkably improved.

The embodiment of the invention discloses an unmanned aerial vehicle image-based hexagonal grid unit soil salinity assessment method, which comprises the following steps: acquiring multispectral images of a cotton field to be assessed through an unmanned aerial vehicle, including a red light image, a green light image, a blue light image and a near-infrared image; dividing a plurality of to-be-evaluated regular hexagon evaluation units according to the to-be-evaluated cotton field multispectral image; training a cotton field soil salinity evaluation model; and performing soil salinity evaluation on each to-be-evaluated regular hexagonal evaluation unit by adopting the trained cotton field soil salinity evaluation model. Compared with the prior art, the invention provides a method for calculating and evaluating the soil salinity by using an unmanned aerial vehicle image and a regular hexagon evaluation unit, and more image features related to the soil salinity strength can be captured, such as the area ratio of crops in the unit, the physiological and ecological indexes of the crops in the unit and the salt spot condition around the unit. More features are more beneficial to accurate evaluation of soil salinity, irrigation can be optimized, and the cotton yield can be increased.

The application provides a kind of intelligent temperature-regulated planting field soil temperature control system and method, related to soil temperature control technical field, obtains seedling planting field regional information, extracts all soil temperature monitoring sub-block according to seedling planting field regional information;Obtain the block environment data of soil temperature monitoring sub-block, determine soil temperature stress factor according to block environment data, obtain all soil temperature stress risk areas in seedling planting field based on soil temperature stress factor;Obtain the temperature control resource information in seedling planting field, determine resource area mapping matrix through temperature control resource information, determine temperature control response strategy through resource area mapping matrix and soil temperature stress factor;According to the soil temperature regulation of each soil temperature stress risk area according to temperature control response strategy.This application can realize the risk analysis and resource optimization control of soil temperature, to improve the temperature regulation precision and regulation efficiency of nursery stock cultivation environment.

The invention discloses an intelligent irrigation system and method for improving the utilization rate of cotton planting water resources, and the system comprises a data collection module which is used for obtaining the multi-source data of a cotton planting region in a preset time period, and carrying out the preprocessing of the multi-source data, so as to obtain a data set containing the three dimensions of soil, crops, and meteorology; the water demand prediction module is used for predicting the data set obtained by the data acquisition module by using a trained CNN-TCN-Attention model and generating a cotton field soil water demand; the irrigation module is used for formulating an intelligent irrigation strategy in combination with a cotton growth stage based on the data set obtained by the data acquisition module and the cotton field soil water demand predicted by the water demand prediction module, and irrigating a cotton planting area according to the intelligent irrigation strategy; the visual platform is used for monitoring the irrigation process in real time; efficient water saving and precise irrigation are achieved, and the utilization rate of cotton planting water resources is increased.

The invention belongs to the technical field of microbial resource development and straw biological decomposition. The invention discloses cold-resistant pseudoarthrobacter psychrotolans CKON-4, and the preservation number of the cold-resistant pseudoarthrobacter psychrotolans CKON-4 is CGMCC (China General Microbiological Culture Collection Center) No.29378. The cold-resistant pseudoarthrobacter psychrotolans CKON-4 has the advantages that the preservation number The strain CKON-4 is preserved in the China General Microbiological Culture Collection Center (CGMCC) on December 25, 2023, the China General Microbiological Culture Collection Center is called CGMCC for short, the address of the China General Microbiological Culture Collection Center is No.3, Yard 1, Beichen West Road, Chaoyang District, Beijing, and the preservation number of the strain is CGMCC No.29378. The strain disclosed by the invention has very high lignocellulose degradation activity, and the decomposition rate of straws can be remarkably improved; the strain is separated from rice field soil, can grow in the pH value range of 5-9 and the temperature range of 4-37 DEG C, can tolerate the salt concentration of 10%, and is a bacterium with wide pH application range, salt resistance and cold resistance. The strain can play an important role in lignocellulose degrading enzyme production, straw biological decomposition and compost fermentation.

The invention belongs to the technical field of soil improvement, and particularly provides a photovoltaic power generation field soil improvement method suitable for a high and cold gobi area. According to the method, the base material is laid on the pretreated soil firstly, then corresponding plant combinations are selected for mixed sowing according to habitat types of different areas, and finally regular irrigation and maintenance are performed, so that the water and fertilizer retention performance of the soil of the photovoltaic power generation field in the alpine and dry gobi desert area of the Tibet Plateau can be effectively improved; through comprehensive application of biological blankets, organic matter addition, microbial agent regulation and land covering technologies, the water and fertilizer retention performance of soil is improved, soil improvement and ecological restoration are promoted, and collaborative development of a power generation system and the ecological environment is achieved.

The invention relates to the technical field of soil profile recognition, in particular to a soil profile recognition method and system based on multi-source information fusion and artificial intelligence. Synchronously acquiring image data, physicochemical property sequence data and mechanical resistance sequence data of a field soil profile through a data acquisition assembly; performing data preprocessing and spatial registration on the data; extracting visual features of the image and sequence features of the sensor data, and then performing feature level fusion to form a multi-source fusion feature vector; inputting into a pre-trained soil layer identification model to obtain soil profile layering result information; according to the scheme, the reference image data, the physicochemical property sequence data and the mechanical resistance sequence data are fused, unified decision making is carried out through the soil layer recognition model, the problems that a traditional method is high in subjectivity and low in efficiency are solved, objective, efficient and accurate layered recognition of the soil profile is achieved, and the accuracy of layered recognition of the soil profile is improved. And the digitization and standardization process of soil investigation is powerfully promoted.

The invention discloses Pseudomonas aeruginosa KS1-2 and application thereof, the strain is separated from a soil sample in a rice field and is preserved in the China General Microbiological Culture Collection Center (CGMCC), and the preservation number is CGMCC NO.33996. The invention further discloses a method for preparing the Pseudomonas aeruginosa KS1-2. The Pseudomonas aeruginosa KS1-2 has the advantages that the Pseudomonas aeruginosa KS1-2 can be used for preparing the Pseudomonas aeruginosa. The pseudomonas aeruginosa KS1-2 has a remarkable inhibition effect on a plurality of rice pathogenic bacteria; the growth of various plant pathogenic fungi can be effectively inhibited, and the broad-spectrum antibacterial property is achieved; the strain and the microbial inoculum can be prepared into a biocontrol agent for preventing and treating plant pathogens, can reduce plant diseases, are green and environment-friendly, have good application potential, and lay a foundation for research and development of multifunctional biocontrol microbial inoculum and biopesticide.

The invention belongs to the technical field of cibotium barometz breeding, and particularly relates to a method for artificially breeding cibotium barometz by using spores, which comprises the following components in parts by weight: 100 parts of field soil, 20-25 parts of sawdust, 10-15 parts of perlite, 10-12 parts of plant ash, 0.05-0.15 part of manganese sulfate and 0.3-0.5 part of sodium selenite; spores germinate, and the environment temperature is 24-26 DEG C; and transplanting the germinated seedlings into a greenhouse for cultivation. According to the method, high spore germination rate and seedling survival rate are ensured, and the transplanted seedlings can grow smoothly.

The invention discloses a rice transplanter with a seedling depth self-adaptive adjusting function, belongs to the technical field of rice transplanters, and aims to solve the problems that the seedling insertion depths are different due to non-uniform hardness distribution of field soil and fluctuation of terrains, and the seedlings are inclined after being inserted due to unevenness of the field terrains. A push-pull rod is arranged in the supporting frame, two seedling boxes are oppositely arranged in the supporting frame, seedling outlets are formed in the seedling boxes in a penetrating mode, a first driving assembly is arranged in the supporting frame, a linkage assembly is arranged in the supporting frame and connected with the first driving assembly, and two dynamic adjusting assemblies are oppositely arranged in the linkage assembly. The seedling inserting depth can be conveniently and dynamically adjusted, it is guaranteed that each seedling inserting depth meets the transplanting requirement, the depth consistency is guaranteed, the transplanting quality is improved, and meanwhile it is conveniently avoided that due to inclination of the supporting frame, seedling inserting inclination is caused, and the transplanting quality is affected.

The invention provides a method for simulating and quantifying physical stress of field soil based on field in-situ monitoring and a model. The method comprises the following steps: step 1, acquiring soil bulk density, water content and penetration resistance values under different water potentials; step 2, fitting the transfer equation of each limiting condition by using each measured data in the step 1, and establishing soil transfer equations of four limiting conditions of LLWR; 3, field soil bulk density dynamic measured data are obtained; 4, constructing a field soil bulk density dynamic prediction model in the implementation stage and the expansion and shrinkage stage under the influence of cultivation and rainfall; step 5, acquiring actually measured data of field rainfall and soil water content of the research area; and step 6, obtaining the LLWR range of the research area and the dynamic change of each limiting condition. The method solves the technical problems that in the prior art, seasonal dynamic of soil bulk density, which is a key transmission variable influencing LLWR, is ignored, and it is difficult to accurately estimate dynamic changes of LLWR in seasons and quantify physical stress caused by the LLWR on crop growth.

The utility model provides a field soil crushing machine, which relates to the technical field of farming machinery and comprises a soil block collecting device, a primary screening device, a soil block transmission device and a soil crushing device. The soil block collecting device is connected with the soil crushing device through a soil block transmission device; the soil block collecting device goes deep into a soil layer to take soil, the soil block transmission device conveys the taken soil, and the primary screening device screens soil blocks on the soil block transmission device, so that the large soil blocks enter the soil crushing device to be crushed. Soil is taken through the soil block collecting device, soil blocks on the soil block transmission device are primarily screened through the primary screening device, small aggregates and soil particles meeting the farming standard are screened and fall back to the field without being crushed, and large soil blocks are left on the soil block transmission device and conveyed to the soil crushing device to be crushed. Therefore, large soil blocks can be accurately crushed, the physical structure of the soil is improved, and the granular structure of the soil is not damaged, so that hardened fields or fields with large soil blocks are easy to cultivate.

The invention relates to the technical field of ocean engineering, in particular to a laboratory calibration method for reducing the flow velocity of a gravity anchor recovery force nozzle. The method comprises the following steps: S1, obtaining a field soil body needing gravity anchor recovery operation through a thin-wall soil sampler, and preparing a triaxial test sample; s2, calculating confining pressure and axial pressure according to field conditions; s3, the prepared sample is installed on a triaxial apparatus, the calculated confining pressure and axial pressure are applied, initial back pressure is applied through a back pressure system of the triaxial apparatus, and the water injection amount changing along with time is recorded; s4, performing a multi-pressure-difference test and fluid viscosity correction based on the initial back pressure applied in S3; and S5, according to a test result, carrying out actual working condition flow velocity conversion. The back pressure value is changed, the corresponding water injection rate and time are recorded, and the flow velocity is corrected in combination with factors such as fluid viscosity, so that the accuracy of an experimental result is improved, and a scientific basis is provided for optimizing a nozzle design.

The invention discloses a solid waste landfill crack combination self-repairing material based on microbial mineralization and application, and belongs to the field of environmental geotechnical engineering. The method comprises the steps that firstly, a klebsiella liquid and a calcium source cementing liquid are prepared, grouting holes are formed in the side slope, the bacterial liquid and the cementing liquid are injected in batches, and internal cracks are filled with a microorganism induced calcium carbonate precipitation (MICP) technology; and then, a fiber reinforced guniting material formed by compounding field soil, active magnesium oxide and chopped fibers is adopted to spray and cover the surface layer of the slope, and a compact sealing layer is formed through carbon dioxide carbonization. By combining internal MICP curing and surface layer fiber reinforced magnesium oxide carbonization sealing, a synergistic protection system with strong inside and tough outside is constructed, the anti-permeability and stability of the slope are improved, meanwhile, the toughness, crack resistance and long-term durability of a surface layer sealing layer are remarkably enhanced, and the service life of the slope is prolonged. And the method is particularly suitable for slope treatment of projects with high anti-seepage requirements such as solid waste landfills and the like.

The application discloses a kind of rice field soil lead pollution analysis method and system, method includes: obtaining the current soil attribute data set of target rice field and soil moisture content distribution data, combine future expected water management parameters, simulate moisture content space-time variation sequence by soil water migration model;Dissolution-precipitation equilibrium tendency state index of each time step Pb is calculated based on moisture content change and soil attribute, the advancing track of Pb active front is identified;The front track is overlaid with the current rice Pb overproof risk spatial distribution, and the potential Pb activation amplification area is determined;Along the front advancing direction, strip-shaped analysis unit is divided, and Pb pollution risk evolution index is calculated by combining front arrival time and current risk value;Finally, the analysis report containing amplification area position, risk evolution order and leading factor diagnosis result is output.The technical leap of rice field Pb pollution risk from "static status evaluation" to "dynamic evolution prediction" is realized.

The present application relates to the field of agricultural environmental protection method, particularly to a method for reducing the pollution of vegetable field soil non-point source and N2O.The method provided by the present application fully considers the carbon and nitrogen content, C / N and cellulose content of different exogenous carbon materials, reduces the application of chemical fertilizer nitrogen under the premise of ensuring the nitrogen supply of vegetables according to the nitrate nitrogen content of vegetable field soil, increases the amount of effective state carbon and the content of holocellulose by optimizing the combination and proportion of different exogenous carbon materials, improves the nitrate nitrogen assimilation of vegetable field soil, reduces the nitrogen leaching and soil N2O emission, and realizes the coordinated reduction and regulation of the pollution of vegetable field soil non-point source and N2O.The method is clear, simple, convenient, easy to implement.

The application discloses a kind of rice field soil arsenic pollution reduction repair method, comprising the following steps: S1, rice seedling raising;S2, in 1-2 weeks before transplanting, to the arsenic pollution rice field soil to be repaired modified biochar is added, then waterlogging treatment is carried out;S3, 1-2 weeks later, shallow water rice transplanting is carried out, and 3-5 days are waited for rice seedling to return green, and water is intensified management;S4, in early heading stage of rice, aboveground rice straw is harvested from field, then soil ploughing is deep ploughing and broken, irrigation is carried out, so that root system floats to water surface, and is all collected from field;S5, level field and drain to surface layer contains shallow water, repeat steps S2-S4.The application is loaded on biochar by microorganism and combined with the method of water intensification management plant absorption, in heading stage of rice, aboveground straw enriched with arsenic is removed from field with underground root system as a whole, and combined with periodic repetition operation, the total amount of arsenic in soil is substantially reduced.

The application discloses a non-metallic mineral powder ball preparation method for loading plant nutrient factors, and comprises the following steps: kaolin is added into hydrochloric acid and stirred, washed with water, calcined at 400-460 DEG C for 1-2h, then added into water with gelatinized starch and stirred, added with silane coupling agent KH560 and continuously stirred, filtered, washed, dried, added with polyvinyl alcohol and pH regulator and stirred to obtain premix; fly ash and refined sugar are uniformly mixed and formed to obtain pretreated fly ash; potassium hydroxide is added into sodium silicate solution and stirred uniformly, then hydroxypropyl chitosan is added and stirred to obtain a precursor solution; the precursor solution is uniformly poured on the surface of the pretreated fly ash, and then placed, solidified, ultrasonic washed and dried to obtain a sponge-like carrier; field soil, organic fertilizer and plant fermented straw are added into a high-speed pulverizer and pulverized, and sieved to obtain granules; the premix and the sponge-like carrier are added and uniformly mixed, and then formed to obtain a seedling raising substrate.

The invention discloses a method for strengthening three-effect synergy of chloramphenicol degradation, rice yield increase and greenhouse gas emission reduction in rice field soil through sulfurized zero-valent iron, and belongs to the technical field of rice field soil pollution remediation. The sulfurized zero-valent iron (S-ZVI) is prepared according to the sulfur-iron ratio of 0.1-0.2; the S-ZVI is mixed with the contaminated soil, and rice is cultivated in cooperation with a specific fertilization and irrigation scheme. According to the method for strengthening the triple-effect synergy of chloramphenicol degradation, rice yield increase and greenhouse gas emission reduction in the rice field soil through the sulfurized zero-valent iron, by optimizing preparation and application of the sulfurized zero-valent iron, under the synergistic effect of chemical reduction and microbial degradation, the triple-effect synergy of chloramphenicol degradation, rice yield increase and greenhouse gas emission reduction is expected to be achieved, and the effect of strengthening the rice field soil chloramphenicol degradation, rice yield increase and greenhouse gas emission reduction is achieved. And an important means is provided for degradation of antibiotics in rice field soil.

The application provides a kind of bio-based degradable material to arid region field soil environment influence evaluation analysis method.The bio-based degradable material to arid region field soil environment influence evaluation analysis method includes a. Provide a multi-factor environment simulation model, the model combines different aridity, seasonal variation, long-term climate fluctuation factor, describes the dynamic process of soil change.The bio-based degradable material to arid region field soil environment influence evaluation analysis method, by introducing multi-factor environment simulation model, it is avoided that the problem that only single environmental condition is based on in the previous experiment by integrating a variety of variables such as aridity, seasonal variation, climate fluctuation into experimental design.This innovative design enables the method to verify the influence of bio-based degradable material on soil environment under a wider range of conditions, significantly improving the extrapolation and accuracy of experimental results.

The invention relates to the technical field of field character detection, in particular to a crop breeding-based field character detection method, which comprises the following steps of: determining an environment penalty value according to detected color data and soil data of field crops, determining a yield reward value according to the detected field crop growth data and the nutrition data stored in the crop management platform, and determining a fertilizer utilization value according to the detected field soil element data; performing weighted summation to generate a fertilization adjustment reward function, wherein a dynamic coefficient is determined according to crop breeding stage big data fitting of a crop management platform; the fertilization amount reinforcement learning model is updated regularly based on the fertilization adjustment reward function, and the fertilization amount reinforcement learning model determines the breeding multi-element recommended fertilization amount based on the Critic network and the Actor network. According to the method, collaborative closed-loop detection and field detection data mining of stress resistance, yield increase and fertilizer saving of the reinforcement learning model in combination with breeding are realized.

The invention relates to the technical field of soil pollution remediation, and particularly discloses a mineralization stable remediation method for soil heavy metal pollution. The remediation method strictly follows the principle of ecological compatibility of soil, in-situ remediation of farmland soil heavy metal pollution is achieved, and meanwhile the soil fertility can be effectively improved; the construction of a remediation system can be completed by virtue of soil-flora optimization proportion and formation of carbon-based compound bacteria with biochar, and by virtue of the carbon-based compound bacteria, pollution of heavy metals such as arsenic and cadmium in contaminated soil can be well remedied, and the content of organic matters in the soil can be remarkably increased, so that the soil fertility of the soil is improved; the remediation method provided by the invention has both ecological safety and wide applicability, provides a feasible solution for green and sustainable treatment of large-area moderate-light heavy metal polluted farmland, and can be popularized to field soil for application.

The application discloses a soil microwave uniform disinfection operation system and an operation method thereof, and belongs to the technical field of soil disinfection. The soil microwave uniform disinfection operation system comprises a power chassis, an on-board control box, a rolling microwave irradiation system, a conveying mechanism and a shovel mechanism. The shovel mechanism and the conveying mechanism are sequentially arranged at the front end of the power chassis, and the on-board control box and the rolling microwave irradiation system are arranged on the upper end of the power chassis. The rolling microwave irradiation system comprises a microwave resonance cavity arranged on the upper end of the power chassis, microwave generating units arranged on the two sides of the microwave resonance cavity and a roller mechanism arranged in the microwave resonance cavity. The rolling microwave irradiation system is adopted to perform efficient disinfection on field soil, effectively reduces the risk of local overheating caused by microwave irradiation, effectively improves the microwave irradiation efficiency and uniformity of soil, and realizes the microwave irradiation disinfection treatment operation on the field soil piece by piece.

The invention relates to a method for increasing the quantity and / or density of crops through optimized field soil treatment.

The application relates to the technical field of paddy field soil improvement, and discloses a paddy field soil detection and adjustment system and method based on multi-source sensing data analysis, which comprises a region division module, a data acquisition module, a soil health assessment module, a rice health assessment module, a comprehensive health index calculation module, a soil quality grade division module and an implementation and simulation prediction module. The application comprehensively evaluates the soil and crop health states of different regions of a paddy field, formulates corresponding soil adjustment strategies, effectively predicts the evolution trend of soil health under different climate scenarios in the future by combining a fuzzy logic relationship group and an artificial wolf swarm optimization algorithm, and outputs a clear soil health change curve, thereby providing technical support for agricultural managers.