260 results about "Sodication" patented technology

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

The invention provides a rice growth model construction method and system based on salt stress, and relates to the technical field of growth model.The rice growth model construction method comprises the steps that firstly, monitoring points are arranged in a planting sample area, and soil conductivity data of different depths are obtained through a multi-depth soil conductivity sensor and a Kriging interpolation method; collecting root system density, a multispectral remote sensing image and a leaf area index, and calculating a canopy salt stress index; measuring the concentration of related ions to obtain a sodium adsorption ratio, and establishing a salt stress coefficient by combining the soil conductivity and the irrigation volume; fusing canopy and soil stress indexes to generate a stress comprehensive index, and introducing a salinity feedback item to represent the crop compensation capability; and finally, constructing a hybrid machine learning model by adopting a convolutional neural network and a long-short-term memory network to realize rice growth dynamic prediction. According to the method, multi-dimensional salinity stress quantification of a soil-crop system is realized, and decision support is provided for salinization treatment in precision agriculture.

The invention discloses a salinization farmland crop yield prediction method, which is applied to the technical field of crop yield monitoring and prediction, and comprises the following steps: based on a vegetation index and a salinity index, inverting salinity by using a partial least square regression method; inverting the soil moisture based on an empirical relation model of the conditional vegetation temperature index and the actually measured soil moisture; inverting the leaf area index based on an empirical relation model of the normalized vegetation index and the actually measured leaf area index; the method comprises the following steps: constructing an HYDRUS-1D-EPIC coupling model considering salinity, carrying out sensitivity analysis by using an extended Fourier amplitude sensitivity test method, carrying out parameter calibration and posterior distribution inference on the coupling model by using an MCMC method, and sampling posterior distribution by using a DREAM method; and assimilating the inverted salinity, soil moisture and leaf area index to the coupling model by using an ensemble Kalman filtering method, and predicting the crop yield of the salinized farmland. According to the method, the yield prediction precision of the salinized crops is effectively improved.

The invention relates to the field of farmland ecological protection, in particular to a salinization farmland protection forest configuration optimization system and method, and the system comprises a salinization monitoring module, an edge calculation module, a database, a three-dimensional model module, a model optimization module and a configuration scheme optimization module. The salinization monitoring module acquires data through an unmanned aerial vehicle and a hyperspectral imaging spectrometer and determines a soil salinity distribution state, the edge calculation module receives the data and carries out protection forest configuration model calculation, the database stores a calculation model and soil salinity and vegetation growth state data, and the three-dimensional model module generates a three-dimensional spatial-temporal model of forest growth. The model optimization module utilizes deep reinforcement learning to optimize a soil salinity and underground water level simulation model, the protection forest configuration effect is improved, the configuration scheme optimization module generates an optimal protection forest configuration scheme, a complex interaction process is accurately represented, and an efficient and accurate technical means is provided for ecological protection of salinized farmland.

The invention discloses an application of a medicago sativa MsDGK5 gene and a protein coded by the medicago sativa MsDGK5 gene in salt stress resistance of plants, and belongs to the technical field of plant genetic engineering. The nucleotide sequence of the medicago sativa MsDGK5 gene provided by the invention is as shown in SEQ ID NO. 1. According to the application, MsDGK5 gene overexpressed arabidopsis thaliana and medicago sativa transformation plants are constructed, growth and development indexes and physiological and biochemical parameters of the plants under salt stress are systematically measured, and it is proved that overexpression of the MsDGK5 gene can significantly improve the salt tolerance of the transgenic plants. Based on the experimental results, the key regulation effect of the MsDGK5 gene in plant salt tolerance is defined for the first time, an important gene resource is provided for crop salt tolerance genetic improvement, and a new technical approach is also provided for coping with the increasingly aggravated soil salinization problem.

The invention discloses a saline-alkali cultivated land information monitoring method based on spectral analysis. The method comprises the following steps: step 1, data preparation: collecting and processing data covering a target area; step 2, spectral index calculation and fusion: carrying out unary linear regression fusion on the salt index subjected to ground hyperspectral transformation and the salt index subjected to simultaneous Sentinel-2 multispectral calculation to generate a high-multispectral fusion index data set, and constructing a characteristic variable library; 3, feature variable selection: screening out key features from a feature variable library; 4, constructing and training a support vector machine model: training a support vector machine regression model; 5, salinity inversion and precision verification: outputting a soil salinity prediction value, generating a soil salinity spatial distribution diagram of the cultivated land in the Hetao irrigation area according to the soil salinity prediction value, and dividing cultivated land salinization grades by combining an inversion result; and 6, dynamic monitoring: repeating the steps to the step 5, and generating a salinization dynamic change diagram.

The invention provides a saline-alkali soil improvement data analysis method and system based on remote sensing data, and relates to the technical field of land scientificity, and the method comprises the steps: collecting ground monitoring data and remote sensing data, and generating a comprehensive feature vector and a spectrum feature value; then, outputting a saline-alkali soil improvement grade by using a convolutional neural network model; a correction coefficient is generated through the soil salinization index, the spectral index and the pH value, an upgrading and downgrading mechanism is set in combination with a correction threshold interval, and the improvement grade is dynamically adjusted to make up for the model error and improve the evaluation accuracy. According to the method, the saline-alkali soil quantitative analysis model based on the convolutional neural network is constructed, and the ground monitoring data and the remote sensing spectrum characteristic data are combined, so that the improvement grade of the saline-alkali soil is scientifically evaluated.

The invention relates to the technical field of greenhouse vegetable planting environment regulation and control, in particular to an internet-based intelligent greenhouse vegetable environment regulation and control system and method, which comprises an acquisition module, a monitoring module, an analysis module, a decision module, an execution control module and a mobile terminal interaction module, in combination with a preset successive cropping obstacle threshold model, analyzing to obtain the soil secondary salinization degree, the nutritional imbalance state, the microflora disorder index and the allelochemical toxicity grade; and the decision module is used for generating a comprehensive regulation and control strategy including crop rotation suggestions, irrigation amount, a fertilization scheme, biological control measures and environmental parameter regulation instructions in combination with facility vegetable types and growth stage requirements. A continuous cropping obstacle analysis result is obtained through the analysis module in combination with big data and a machine learning algorithm, a comprehensive regulation and control strategy is generated, continuous cropping obstacles are effectively dealt with, and the planting efficiency and the vegetable quality are improved.

The utility model relates to a saline-alkali soil improvement system which comprises a monitoring mechanism, a salt discharging mechanism and an irrigation mechanism, the monitoring mechanism is erected above soil, the salt discharging mechanism and the irrigation mechanism are both buried in the soil, the irrigation mechanism is buried above the salt discharging mechanism, and the irrigation mechanism is communicated with a water and fertilizer integrated tank; the monitoring mechanism comprises a photovoltaic panel and a controller, the photovoltaic panel is in transmission connection with the photosensitive sensor driving motor, the photovoltaic panel is electrically connected with the controller and the irrigation mechanism, and the controller is in communication connection with the irrigation mechanism and the detection equipment. The technical problems that long-term effectiveness and sustainable development are difficult to achieve, water resources are wasted, and soil secondary salinization is caused due to the fact that drainage is not timely are solved.

The invention discloses a salinization remote sensing inversion method fusing crop information and data preprocessing. A land utilization data set is subjected to splicing, cutting and other processing to obtain a high-confidence-coefficient cultivated land range; point distribution sampling is carried out according to a regular grid method, and soil conductivity is measured; preprocessing the remote sensing image; dividing crop growth stages and constructing a multi-temporal spectral feature set; constructing an NDVI time sequence data set and extracting phenological characteristics; extracting planting structure information based on the multi-temporal spectrum and phenological characteristics; a planting structure is converted into crop type data through one-hot coding, and the crop type data is fused with multi-temporal spectrum and phenological characteristics to construct a crop information data set; the method comprises the following steps: constructing a salinity inversion model through data preprocessing and combining with ground actually measured salinity data, and verifying the salinity inversion model; evaluating the cross-year generalization ability of the model; and finally, the inversion result is visualized to generate a salinization map. According to the invention, the system integrates the multi-dimensional information of crops and optimizes the data preprocessing process, and significantly improves the salinization monitoring precision and the cross-space-time adaptability.

The invention relates to the technical field of soil ecological monitoring, in particular to a coastal saline soil dynamic monitoring and early warning system based on the Internet of Things, which comprises a collaborative monitoring unit, a fusion resolving analysis unit and an early warning trigger unit. The capillary water rising flux and the underground water seepage direction are synchronously monitored, the fusion resolving analysis unit dynamically corrects the capillary conductivity through a pore scale migration model in combination with three-dimensional pore structure parameters reconstructed through soil CT scanning, the salt exchange capacity is resolved, the salt increment is predicted through a long and short-term memory network, and a decision coefficient is calculated. The early warning trigger unit judges the secondary salinization risk when the conditions are met, activates drainage equipment and pushes early warning, the problems that traditional monitoring dimensions are single and the early warning precision is insufficient are solved, and the method is suitable for dynamic monitoring and risk prevention and control of coastal salinized soil.

The invention relates to a composite microbial inoculant for soil improvement, the composite microbial inoculant for soil improvement is composed of PGPR (Pseudomonas tianjinensis) and AMF (Amplified Macrophage Fungi), the PGPR is Pseudomonas tianjinensis and Pseudomonas oryzae, and the AMF is rhizophagus clarus. The composite microbial inoculant for soil improvement is characterized in that the PGPR is Pseudomonas tianjinensis and Pseudomonas oryzae, and the AMF is Pseudomonas oryzae, the PGPR is Pseudomonas tianjinensis and Pseudomonas oryzae. According to the invention, the Pseudomonas tianjinensis, Pseudomonas oryzae and AMF are compounded, so that a synergistic effect is exerted, an obvious growth promoting effect on the ryegrass in the saline-alkali soil is achieved, the content of photosynthetic pigments in the ryegrass is increased, the contents of soluble sugar, soluble protein, proline and malondialdehyde in the ryegrass are further increased, and the CAT enzyme activity is improved. In addition, the complex microbial inoculant is combined with ryegrass planting, a plant-microorganism synergistic system is formed, salinized soil is effectively improved, the conductivity and pH of the soil are reduced, the content of nitrogen, phosphorus and potassium in the soil and the content of rapidly available phosphorus and rapidly available potassium are increased, and meanwhile the activity of urease and phosphatase is improved.

The invention provides a soil salinization risk dynamic early warning method based on a graph neural network, and relates to the technical field of agricultural environment monitoring and geological disaster early warning. Comprising the steps of obtaining a multi-source data set of a to-be-detected area; preprocessing the multi-source data set through a self-adaptive data preprocessing technology to obtain preprocessed data; constructing a space-time diagram structure according to the preprocessed data; inputting the space-time diagram structure into a constructed soil salinization risk map neural network model to obtain a multi-level feature map set; by introducing a transformation learning mechanism, screening the multi-level feature image set by utilizing dynamic weight adjustment to obtain an effective feature set; and performing risk dynamic prediction on the effective feature set by using a multi-task learning method to obtain a prediction result. According to the method, the problem that the prediction performance of the model is limited due to the fact that most of methods based on spatial data in the prior art adopt a traditional machine learning algorithm and the spatial dependency and the nonlinear relationship among the data are often difficult to fully capture is solved.

The invention discloses a saline-alkali soil multi-water-source accurate salt control irrigation and drainage integrated system and equipment, and relates to the technical field of saline-alkali soil irrigation and drainage, and the system comprises a multi-water-source intelligent evaluation and dynamic allocation module, an accurate salt control-irrigation and drainage cooperative regulation and control module and an integrated anti-blocking salt discharge and tail water reuse module; by monitoring water source salinity, soil data and a crop salt demand model in real time, dynamically calculating an optimal water source combination, for example, low-salt rainwater is preferentially used for sensitive crops, and a valve is automatically regulated and controlled to switch water sources, the scheme has the advantages that high-salt brackish water is prevented from aggravating salinization, the water resource utilization rate is increased by 30% or above, and blindness of traditional artificial experience allocation is solved; meanwhile, decision making is driven through multi-module data linkage, for example, the irrigation and drainage proportion is regulated and controlled through water source data, and the control unit responds to salinity exceeding within 10 seconds; the scheme has the advantages that manual intervention is reduced by 90%, the engineering advantages of anti-corrosion flow guide design, water flow driving energy conservation, modularization, easy maintenance and the like are implied, and the method is suitable for various saline-alkali land terrains.

The invention belongs to the technical field of soil remediation, and discloses a secondary salinization soil leacheate sampling device which comprises a drill rod, a grouting main pipe is arranged in a sampling cavity of the drill rod, the outer wall of the grouting main pipe is communicated with a plurality of grouting branch pipes, and the grouting branch pipes are in transmission connection with a first driving assembly in the sampling cavity; the grouting branch pipe comprises an inner pipe communicating with the outer wall of the grouting main pipe, and an outer pipe in transmission connection with the first driving assembly is slidably connected to the inner pipe. A plurality of sampling barrels with openings are rotationally arranged on the outer pipe, and the sampling barrels are in transmission connection with a second driving assembly arranged on the outer pipe; and a spirally arranged cutting knife is arranged in the sampling barrel. The device is compact in structure and convenient to use, leacheate injection and later sampling can be carried out in secondary salinized soil through the same device, a sample obtained after soil leaching can be stably and effectively obtained, the influence of the sampling process on the sample is avoided, later detection and use are facilitated, and secondary salinized soil leacheate remediation is assisted to be completed.

The invention relates to a method for relieving soil salinization through combination of agriculture and forestry solid waste and hydrotalcite and application, and belongs to the technical field of soil improvement. The method comprises the following steps: stripping surface saline-alkali soil, crushing agriculture and forestry solid wastes, spreading the crushed agriculture and forestry solid wastes on the land to form a biomass layer, mixing hydrotalcite powder roasted at a high temperature with the stripped soil, covering the biomass layer with the mixture, and finally flattening and sprinkling water to moisten the soil. According to the invention, rising of soil capillary water is blocked through the biomass layer, salt accumulation is reduced, and meanwhile, the soil salinization degree is reduced by utilizing adsorption and ion exchange effects of hydrotalcite. In addition, the agriculture and forestry solid wastes are decayed to generate organic acid, salt is fixed through chelation, and the soil structure is improved. According to the method, soil salinization can be effectively relieved, the air permeability and the water permeability of the soil can be improved, a good environment is provided for crop growth, the crop yield is remarkably increased, the improvement period is short, the application range is wide, and economic benefits are remarkable.

The invention belongs to the technical field of soil inversion, and particularly relates to a soil total salt content inversion system and method based on an improved spectral index, and the method comprises the steps: obtaining a remote sensing image obtained through preprocessing of Sentinel-2; acquiring a sample of the soil sampling point and measuring the total salt content of the soil; analyzing spectral reflectivity characteristics of different salinized soil; analyzing the correlation between the spectral reflectivity and the total salt content of the soil; a wave band with the strongest correlation with the total salt content of the soil is introduced to improve a traditional spectral index; analyzing the correlation between the improved spectral index and the total salt content of the soil; constructing a nonlinear index inversion model of the total salt content of the soil based on the improved spectral index; and comparing different model precisions to obtain an optimal soil total salt content inversion model and drawing. According to the method, the problems that the precision of the soil total salt content inversion method based on the spectral index is low and the actual application requirement is difficult to meet are solved, and decision support is provided for dynamic monitoring of land salinization and sustainable utilization of land resources.

According to the coastal saline-alkali soil water storage system device and the application thereof, on the basis of the characteristics that water and salt in coastal saline-alkali soil are actively transported, and the salinity change amplitude in an irrigation canal is large, ground surface reservoirs of different sizes are laid between field parcels, and the water flow direction of the reservoirs is judged through real-time conductivity data of pond water, canal water and irrigation water; the salt gradient controllable water storage system is formed and controlled according to salt tolerance threshold values of nearby crops, so that the irrigation and salt leaching requirements of different crops in different seasons are met. The water storage device can input the capacities of different reservoirs, crop salt tolerance thresholds, irrigation water demand and the like, estimates the field covered by the water storage device, and optimizes the cultivation mode planning. The device can accumulate irrigation water in different salinity ranges under the condition that the salinity of a surface water body changes drastically, can fully utilize different water sources such as surface water and rainwater, and is very suitable for coastal salinization farmland with relatively rich water resources.

The invention relates to the technical field of soil treatment, in particular to an integrated saline grainfield soil improvement and remediation method. According to the method, precise irrigation, concealed pipe drainage, salt-tolerant crop planting and bioremediation technologies are comprehensively applied, and systematic treatment of the salinized soil is achieved. Precise irrigation dynamically regulates and controls the leaching depth and frequency on the basis of real-time soil salinity and moisture data, the underground water level is intelligently controlled in combination with an underground pipe drainage network, salt accumulation is effectively reduced, and water resource waste is avoided; according to the salt-tolerant crop and green manure rotation mode, salt damage is reduced through plant salt absorption and root system nitrogen fixation, soil organic matter accumulation and microbial community reconstruction are promoted through application of a microbial agent and biochar, and a sustainable soil improvement mechanism is formed. The intelligent monitoring system integrates multiple types of sensors, collects key indexes such as salinity, nutrients and pH values in real time, predicts the salinization trend and regulates and controls irrigation, fertilization and drainage equipment in a linkage mode, full-process automatic management is achieved, and the management precision and efficiency are remarkably improved.

The invention provides a method for measuring and calculating a collaborative safety index of a water-grain-ecological composite system in an arid region, and relates to the technical field of collaborative management of green agricultural resources in the arid region. The method aims at solving the technical problem that in the prior art, a system for evaluating the water-grain-ecology multi-element co-evolution relation with an arid region as a research object is lacked. The method comprises the following steps: constructing a state parameter index system of water resource, grain and ecological safety in the arid region, and measuring and calculating through an improved G1-CRITIC subjective and objective weighting method to obtain a subsystem safety index reflecting a state parameter of a composite system; and inputting the subsystem safety index into a pre-established Hakkine model, analyzing the co-evolution process of the water-grain-ecological composite system, and measuring and calculating to obtain a water-grain-ecological collaborative safety index reflecting the collaborative safety state of the water-grain-ecological composite system. According to the method, from the perspective of the compound system, the dynamic relationship among water-grain-ecology is revealed under the background of agricultural green development in the arid region, and the technical blank in the aspect of research on the evolution mechanism of the compound system in the arid region is effectively filled. According to the method, the water competition of the arid region can be relieved, the soil salinization and underground water mineralization process can be slowed down, a high-level cooperation mechanism of mutual promotion and dynamic adjustment among water, grain and ecology is formed, so that the green and sustainable development of agriculture in the arid region is promoted, and the method has important theoretical value and practical application prospects.

The invention belongs to the technical field of agricultural fertilizers, and particularly relates to a botanical fulvic acid fertilizer and a preparation method thereof, the technical scheme is that the botanical fulvic acid fertilizer comprises the following components: 35-40% of botanical fulvic acid, 6-8% of a humic acid-amino acid chelated microelement fertilizer, 4-5% of a compound microbial agent, 3-4% of a slow-release coating agent, and 22-25% of a modified charcoal carrier; the plant source fulvic acid purified by molasses fermentation can significantly enhance the nutrient chelating ability; the mobility of iron, zinc and other trace elements chelated by molasses amino acid and fulvic acid in soil is enhanced, and the crop absorption rate is increased; the straw carbon-vermiculite composite carrier adsorbs nutrients and slowly releases the nutrients, so that the potassium leaching loss is reduced by 40%, and the salinization risk is reduced; the straw carbon porous structure loads the microbial inoculum, the vermiculite supplements potassium and magnesium elements, and the survival rate of the microbial inoculum is increased after the microbial inoculum is stored for 6 months at normal temperature.

The invention discloses an optimal configuration method for land utilization of a cultivated wasteland in a salinization irrigation area, which mainly comprises two parts of land utilization quantity demand and cultivated wasteland spatial layout, and utilizes a method of coupling a water-salt equilibrium model SALTMOD and a land utilization CLUE-S model. The method comprises the following steps: combining an appropriate tillage and waste land ratio based on irrigation and drainage regulation and control and cultivated land salinity control with land utilization space distribution, and systematically exploring an appropriate salt wasteland space dynamic regulation and control scheme suggestion considering land utilization development and regional salinity income and expenditure balance from quantity constraint and space configuration; certain technical and data support is provided for saline-alkali soil treatment in arid and semi-arid irrigated areas.

This invention relates to the field of plant genetic engineering technology, and more particularly to... SsNHX1 and SsSOS2 Dual-gene plant expression vector and its application in improving salt tolerance in alfalfa. The plant expression vector uses pCAMBIA1300 as its backbone and inserts genes derived from Suaeda salsa. SsNHX1 Genes and SsSOS2 It is constructed from genes. SsNHX1 Genes and SsSOS2 The CDS coding sequence of the gene is shown in SEQ ID NO:1 and SEQ ID NO:2 of the sequence listing. Using Agrobacterium tumefaciens EHA105-mediated transformation, the vector was introduced into the leaves of sterile alfalfa seedlings. Positive transgenic plants were obtained through co-culture, callus induction differentiation, and PCR identification. The advantage lies in the synergistic effect of the two genes, which effectively enhances the salt tolerance of alfalfa, enabling it to grow normally under 200–300 mM NaCl stress, providing a new solution for forage cultivation in saline soils.

The invention provides a saline-alkali soil conditioner as well as a preparation method and application thereof, and belongs to the technical field of soil improvement. The saline-alkali soil conditioner is prepared from the following raw material components in parts by mass: 80 to 90 parts of edible fungus residues, 10 to 20 parts of humic acid and 0.1 to 0.3 part of a microbial agent. The saline-alkali soil conditioner provided by the invention can obviously reduce the pH and total salt content of the surface layer of soil, obviously improve the content of nitrogen nutrients in the soil, optimize the distribution structure of the nitrogen nutrients and reduce the risk of nitrogen leaching loss. Meanwhile, the water and fertilizer retention capacity of soil can be improved, soil nutrients can be supplemented, the soil fertility can be improved, the harm of soil salinity to crops can be reduced, and the stress resistance and the yield of the crops can be improved. The soil conditioner for the saline-alkali land can solve the problems that at present, soil of salinized farmland in Hetao irrigation districts is prone to hardening, the soil fertility is low, the soil water and fertilizer utilization rate is low, and the crop biomass is low.

The invention relates to the technical field of soil element determination, in particular to a method for determining potassium, sodium, calcium and magnesium in soil soluble salt, which comprises the following steps: S1, collecting and preparing a soil sample; s2, preparing a soil sample leaching solution; s3, instrument detection; and S4, data processing and calculation. According to the method, vacuum freeze drying is combined with an ultrasonic-microwave combined extraction technology, and plasma spectrum and ion chromatography combined analysis is adopted, so that the detection efficiency and accuracy are improved, meanwhile, reagent consumption and labor cost are greatly reduced, the problems that a traditional process is tedious, consumed time is long, and precision is insufficient are solved, and the method is suitable for industrial production. The method has the advantages of being convenient to operate, environmentally friendly and the like, can be widely applied to the fields of soil salinization monitoring, agricultural land quality evaluation and geological disaster prevention and control, and provides reliable technical support for environmental protection and resource management.

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.

The invention provides a water-soluble fertilizer and a compound fertilizer for promoting growth of oats in saline-alkali soil as well as a preparation method and application of the water-soluble fertilizer and the compound fertilizer, and belongs to the technical field of fertilizers and preparation thereof. The water-soluble fertilizer comprises the following components in parts by weight: 20-30 parts of urea, 25-35 parts of ammonium sulfate, 10-20 parts of ammonium polyphosphate, 40-50 parts of potassium sulfate and 5-15 parts of humic acid. The compound fertilizer comprises the water-soluble fertilizer and a seed embedding agent, the seed embedding medium is prepared from the following components in parts by weight: 0.5 to 1.5 parts of bacillus subtilis, 1 to 3 parts of plant lactobacillus, 3 to 5 parts of basophilic halomonas and 10 to 15 parts of kaolin. The components and contents of the water-soluble fertilizer meet the nutritional requirements of the oats in the growth and development period, and the growth of the oats in the saline-alkali soil is promoted. By adding the microbial agent, the pH and salt content of the saline-alkali soil are reduced, the salinization of the saline-alkali soil is improved, and the oat plant height, the overground plant quantity and the seed yield of the saline-alkali soil are obviously increased.

The invention discloses a soil water and salt dynamic prediction system and method. A data acquisition unit acquires soil underground water burial depth data of a to-be-predicted area; the model optimization unit determines a machine model for respectively predicting the soil water content and the soil salt content; and the coupling prediction unit predicts the soil water content and the soil salt content of the to-be-predicted region according to the soil groundwater burial depth data of the to-be-predicted region to obtain the soil water content and the soil salt content of the to-be-predicted region. According to the invention, the long-time-sequence, high-resolution and in-situ monitoring of key elements such as soil water content, soil salinity and underground water level is realized by constructing an Internet of Things monitoring network, and the defects of the existing method on temporal-spatial resolution and monitoring indexes are overcome. Meanwhile, a prediction model coupling underground water numerical simulation and machine learning is innovatively provided, the prediction precision and efficiency are improved, the nonlinear response relation between shallow soil water and salt and the buried depth of underground water is disclosed, and a new perspective is provided for understanding a soil salinization mechanism.

The invention belongs to the technical field of microorganisms, and particularly relates to a salt-alkali tolerant cladosporium sp. Ca38 and application thereof. The cladosporidium sp. Ca38 disclosed by the invention is preserved in the Guangdong Microbial Culture Collection Center on August 1, 2025, and the preservation number is GDMCC No: 66798. The cladosporidium sp. Ca38 disclosed by the invention has been preserved in the Guangdong Microbial Culture Collection Center on August 1, 2025. By inoculating cladosporium, wheat germination and growth can be effectively promoted, damage of salt stress to wheat can be relieved, the salt tolerance of plants is improved, and the key growth problem caused by soil salinization of wheat is solved. The method has a wide prospect in the cultivation application of wheat and other plants.

This application discloses a comprehensive treatment method for salinized soil in semi-arid region, comprises: stripping and collecting the topsoil; spreading sandy soil and / or loess soil as a imported soil layer; spreading an anti-seepage layer, a salt barrier layer and a membrane layer successively on the imported soil layer; mixing clay into the topsoil to obtain mixed soil; blending saline-alkali land conditioner with the mixed soil to obtain planted soil; spreading the planted soil on the membrane layer to obtain a planting layer. The method combines physical, hydraulic, chemical and biological remediation methods to comprehensively manage saline-alkali soil in semi-arid areas. It consumes less water resources, has a shorter treatment cycle, shows quick results, is conducive to plant growth, and can effectively inhibit the return of salt.