Compound ecological restoration method for coal gangue dump based on plant-microorganism synergy

Abstract

The invention discloses a compound ecological restoration method for a coal gangue mountain based on plant-microorganism synergy, and relates to the technical field of ecological restoration of the coal gangue mountain, the method comprises the following steps: obtaining a regional characteristic information set of a divided regional set of the coal gangue mountain; determining a regional microbial agent-field planting plant group set; planting the plants, preparing microbial root-irrigation liquid according to corresponding microbial agents, applying the microbial root-irrigation liquid to rhizosphere areas of the plants in a root-irrigation manner, and covering soil on the surfaces of the plants; obtaining an analysis result set; according to the analysis result set, directional adjustment is conducted on the microorganism root-irrigation liquid applied to the divided area set, and secondary root-irrigation ecological restoration is conducted on the corresponding divided areas according to the adjusted microorganism root-irrigation liquid. The technical problem that in the prior art, the restoration condition of the coal gangue mountain cannot be dynamically and comprehensively mastered, and consequently the ecological restoration effect is poor is solved. The technical effect of improving the ecological restoration quality is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological restoration of coal gangue mountains, and particularly to a composite ecological restoration method for coal gangue mountains based on the synergy of plants and microorganisms. Background Art

[0002] At present, due to the large amount of harmful substances (such as heavy metals and salts) and lack of organic matter in the soil of coal gangue mountains, they have become serious ecological pollution sources. Most traditional coal gangue mountain restoration methods rely on single plants or single microorganisms for restoration, but these methods often have difficulty in quickly and effectively improving soil quality and promoting vegetation growth, and the sustainability of the restoration effect is poor. Moreover, in the restoration process, a single-temporal restoration state analysis is adopted, lacking dynamic analysis of the restoration process, resulting in a large gap between the restoration plan and the actual situation of the coal gangue mountain. Summary of the Invention

[0003] The present application provides a composite ecological restoration method for coal gangue mountains based on the synergy of plants and microorganisms, which is used to solve the technical problem that the existing technology lacks a dynamic and comprehensive understanding of the restoration situation of coal gangue mountains, resulting in poor ecological restoration effects.

[0004] In view of the above problems, the present application provides a composite ecological restoration method for coal gangue mountains based on the synergy of plants and microorganisms. The method includes: obtaining a set of regional characteristic information of a set of divided regions of a coal gangue mountain; screening microbial inoculants and colonizing plants based on the set of regional characteristic information to determine a set of regional microbial inoculant-colonizing plant groups; according to the set of microbial inoculant-colonizing plant groups, respectively carrying out plant colonization on the set of divided regions, and configuring microbial irrigation solutions according to the corresponding microbial inoculants. After applying the microbial irrigation solutions to the rhizosphere regions of the plants by irrigation, surface soil covering is carried out; performing two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement on the set of divided regions at a preset monitoring window to obtain a set of analysis results; making directional adjustments to the microbial irrigation solutions applied to the set of divided regions according to the set of analysis results, and performing secondary irrigation ecological restoration on the corresponding divided regions according to the adjusted microbial irrigation solutions.

[0005] Preferably, the set of divided regions includes bare regions, weathered regions, waterlogged regions, shallow slope scouring regions, and regions with excessive heavy metals.

[0006] Preferably, a two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement is performed on the set of divided regions in a preset monitoring window to obtain a set of analysis results, including: extracting a first divided region from the set of divided regions; within the preset monitoring window, extracting plant root development indicators and soil environment improvement indicators for the first divided region respectively according to a preset monitoring frequency to obtain a first root length-root volume-root hair number sequence and a first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence; performing spatio-temporal interaction analysis on the first root length-root volume-root hair number sequence and the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence respectively to obtain a first updated root development temporal feature vector and a first updated soil environment improvement temporal feature vector; using an ecological restoration analyzer to identify the first updated root development temporal feature vector and the first updated soil environment improvement temporal feature vector to obtain a first analysis result; performing a two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement on the set of divided regions in the preset monitoring window respectively to obtain the set of analysis results.

[0007] Preferably, performing spatio-temporal interaction analysis on the first root length-root volume-root hair number sequence and the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence respectively to obtain a first updated root development temporal feature vector and a first updated soil environment improvement temporal feature vector includes: respectively using a temporal channel and a spatial channel to perform temporal feature analysis and spatial feature analysis on the first root length-root volume-root hair number sequence to obtain a first root development temporal feature vector and a first root development spatial feature vector; based on the first root development temporal feature vector and the first root development spatial feature vector, updating the attention weight of the temporal channel to obtain an updated temporal channel; using the updated temporal channel to perform feature analysis on the first root length-root volume-root hair number sequence to obtain a first updated root development temporal feature vector; performing spatio-temporal interaction analysis on the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence to obtain a first updated soil environment improvement temporal feature vector.

[0008] Preferably, based on the first root development temporal feature vector and the first root development spatial feature vector, updating the attention weight of the temporal channel to obtain an updated temporal channel includes: using a spatio-temporal feature interaction function to interact the first root development temporal feature vector and the first root development spatial feature vector to obtain a spatio-temporal interaction feature vector; based on the spatio-temporal interaction feature vector, the first root development temporal feature vector and the attention weight of the temporal channel, performing updated identification to obtain an updated attention weight; updating the temporal channel according to the updated attention weight to obtain the updated temporal channel.

[0009] Preferably, the spatio-temporal feature interaction function is: ; Among them, is the spatio-temporal interaction feature vector, is the first root system development timing feature vector, is the element mapping similarity normalization value according to the first root system development spatial feature vector and the first root system development timing feature vector, is the transpose of the first root system development spatial feature vector, is the dimension of the spatial feature vector, is used to introduce the prior position and is the bias term.

[0010] Preferably, the plant root system development indexes include root length, root system volume and root hair number; the soil environment improvement indexes include soil heavy metal concentration, nitrogen and phosphorus element content and pH value.

[0011] Preferably, the microbial irrigation solution applied to the divided area set is directionally adjusted according to the analysis result set, and the corresponding divided areas are respectively subjected to secondary irrigation ecological restoration with the adjusted microbial irrigation solution, including: obtaining the target ecological restoration result, comparing the target ecological restoration result with the analysis result set respectively to obtain a repair deviation set; taking reducing the repair deviation set as the adjustment direction, adjusting the microbial irrigation solution applied to the divided area set to obtain an adjusted microbial irrigation solution set; using the adjusted microbial irrigation solution set to perform secondary irrigation ecological restoration on the corresponding divided areas in the divided area set.

[0012] This application also provides an electronic device, including: A memory for storing executable instructions; a processor for implementing the coal gangue mountain composite ecological restoration method based on plant-microbe cooperation when executing the executable instructions stored in the memory.

[0013] This application also provides a computer-readable storage medium, including: A computer program is stored thereon, and when the program is executed by a processor, it implements the coal gangue mountain composite ecological restoration method based on plant-microbe cooperation.

[0014] One or more technical solutions provided in this application have at least the following technical effects or advantages: In this application, the regional characteristic information set of the divided area set of the coal gangue mountain is obtained, and then based on the regional characteristic information set, microbial inoculants and colonizing plants are screened to determine the regional microbial inoculant-colonizing plant group set. Furthermore, according to the microbial inoculant-colonizing plant group set, plants are respectively colonized in the divided area set, and microbial root irrigation solutions are configured according to the corresponding microbial inoculants. After applying the microbial root irrigation solutions to the rhizosphere area of the plants by means of root irrigation, surface soil covering is carried out. A two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement is performed on the divided area set in a preset monitoring window to obtain an analysis result set. Then, according to the analysis result set, the microbial root irrigation solutions applied to the divided area set are directionally adjusted, and secondary root irrigation ecological restoration is carried out on the corresponding divided areas according to the adjusted microbial root irrigation solutions. The technical effect of performing two-dimensional spatio-temporal interaction analysis on the restoration process and improving the quality of ecological restoration is achieved. Brief Description of the Drawings

[0015] Attached Figure 1 is a schematic flow chart of a coal gangue mountain composite ecological restoration method based on plant-microbe synergy provided by an embodiment of the present invention.

[0016] Attached Figure 2 is a schematic flow chart of obtaining an analysis result set in a coal gangue mountain composite ecological restoration method based on plant-microbe synergy provided by an embodiment of the present invention.

[0017] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0018] Reference Signs: Input device 301, Processor 302, Memory 303, Output device 304. Detailed Embodiments

[0019] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the present application.

[0020] It should be noted that the terms "include" and "have" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0021] Embodiment, as attached Figure 1As shown, the present application provides a composite ecological restoration method for coal gangue mountains based on plant-microbe collaboration. The method includes: S1: Obtain the set of regional characteristic information of the set of divided regions of the coal gangue mountain; Further, the set of divided regions includes bare areas, weathered areas, waterlogged areas, shallow slope erosion areas, and heavy metal exceeded areas.

[0022] In a possible embodiment, the coal gangue mountain is a mountain formed by piling up waste coal gangue. By using remote sensing monitoring and geological data retrieval methods, the coal gangue mountain is divided into regions, and each region has different soil characteristics, pollution levels, and restoration requirements. Among them, the set of divided regions includes bare areas, weathered areas, waterlogged areas, shallow slope erosion areas, and heavy metal exceeded areas. The set of regional characteristic information reflects the basic conditions of different divided regions and provides data support for the subsequent screening of microbial agents and colonized plants. Among them, each piece of regional characteristic information includes the soil characteristics, pollution level, and restoration requirements of the region.

[0023] Preferably, the situation of the regional characteristic information of different divided regions is shown in Table 1: Table 1 Regional Characteristic Information Table Area type Soil characteristics Pollution degree Remediation requirement Bare area No plant cover, soil surface directly exposed, vulnerable to water and wind erosion, soil is loose High heavy metal pollution, high salinity, lack of organic matter Increase organic matter, plant cover, reduce water and wind erosion, passivate heavy metals, control salinity Weathered area Soil is loose, mineral weathering, common lower soil density Heavy metal pollution, acidic environment, mineral loss Restore soil structure, adjust acidic soil, fix plant roots, promote plant growth by microorganisms Waterlogging area Soil is wet, oxygen-deficient, salinization tendency, poor soil air permeability Excessive salinity, excessive water, insufficient nitrogen and phosphorus Reduce salinity, drain water, improve soil air permeability, increase nitrogen and phosphorus fertilizers Shallow scouring area of slope Soil is weak, surface layer is often scoured, serious loss High soil erosion, possible heavy metal accumulation Restore soil structure, reduce scouring, promote vegetation growth, fix heavy metals by microorganisms Area with heavy metal exceeding standard Soil is seriously polluted, may be acidic or alkaline Pollution by high concentrations of heavy metals (such as Pb, As, Cd, etc.) Passivate heavy metals, microbial remediation, select heavy metal-tolerant plants, phytoremediation by hyperaccumulating plants S2: Based on the set of regional characteristic information, screen microbial agents and colonized plants to determine the set of regional microbial agent-colonized plant groups; In an embodiment, the microbial agent refers to a product containing specific microbial populations, including probiotics, soil remediation flora, nitrogen-fixing bacteria, phosphorus-solubilizing bacteria, salt-tolerant bacteria, etc., which can improve the soil environment through various mechanisms. The colonized plant refers to a plant selected and planted in a specific region during the restoration process. These plants need to have strong adaptability and pollution tolerance. Optionally, the colonized plants include hyperaccumulator plants, salt-tolerant plants, heavy metal-tolerant plants, etc.

[0024] Obtain a screening identifier, input the set of regional characteristic information into the screening identifier respectively for intelligent screening of microbial agents and colonized plants, and obtain the set of regional microbial agent-colonized plant groups. Among them, each regional microbial agent-colonized plant group in the set of regional microbial agent-colonized plant groups is a combination of microbial agents and colonized plants suitable for each region determined according to the analysis results of the set of regional characteristic information.

[0025] Preferably, multiple sample area characteristic information and multiple sample area microbial inoculant - colonized plant groups are obtained as training data, and the framework based on the feedforward neural network is supervised and trained using the training data to learn the mapping relationship between the area characteristic information and the area microbial inoculant - colonized plant group, and the network parameters of the framework are updated according to the output situation during training until a trained screening and recognition device is obtained. Among them, the screening and recognition device is used to intelligently determine the microbial inoculant and the colonized plant.

[0026] Exemplarily, the sets of area microbial inoculant - colonized plant groups corresponding to different areas are shown in Table 2.

[0027] Table 2 Area Microbial Inoculant - Colonized Plant Group Mapping Table Area type Microbial inoculant Established plants Bare area Nitrogen-fixing bacteria Switchgrass Weathered area Sulfate-reducing bacteria Amorpha fruticosa Waterlogging area Pseudomonas Phragmites australis Shallow scouring area of slope Organic matter-degrading bacteria Amorpha fruticosa Area with heavy metal exceeding standard Heavy metal-solidifying bacteria Commelina communis S3: According to the set of microbial inoculant - colonized plant groups, plant colonization is carried out on the divided area sets respectively, and microbial irrigation solutions are configured according to the corresponding microbial inoculants. After applying the microbial irrigation solutions to the rhizosphere area of the plants by irrigation, surface soil covering is carried out. In the embodiments of the present application, according to the set of microbial inoculant - colonized plant groups selected in the foregoing steps, plant colonization is carried out in different areas respectively. For example, in areas with heavy heavy metal pollution, plants capable of hyper - accumulating heavy metals are selected for colonization; in water - logged areas, water - tolerant plants are selected for colonization. The colonized plants will help restore the soil structure, improve the environmental conditions, and at the same time provide support for the microorganisms.

[0028] Preferably, according to the area characteristic information of the divided area, the position of the planting point is determined. For example, the selected planting point needs to have good drainage and appropriate soil depth, and avoid planting in areas with serious waterlogging or excessive infertility. For weathered areas and bare areas, usually the soil needs to be loosened first to break the soil compaction so that the roots can take root better. Manual or mechanical tools can be used to loosen the soil to ensure the looseness and air permeability of the soil at the planting position. Preferably, if the soil is infertile or seriously polluted, an appropriate amount of organic fertilizer, humus soil or other soil conditioners can be added before planting to improve the soil fertility and microbial activity and promote the growth of plant roots.

[0029] According to the size of the plant roots, planting holes with appropriate depth and width are dug to ensure that the plant roots can fully expand. Optionally, the depth of the planting hole is about 1.5 times the plant roots, and the width is set by those skilled in the art. The plant is placed in the planting hole to ensure that the roots are naturally stretched and the roots are not damaged. The roots are covered with soil and gently compacted to ensure that the plant stands firm. The soil is appropriately filled around the planting hole to avoid voids.

[0030] A microbial root irrigation solution is prepared by those skilled in the art according to the ratio requirements of the selected plants and microbial inoculants. Optionally, the microbial inoculant is propagated by liquid culture until the viable cell concentration is not less than 1×10 8 CFU / m, and then the microbial root irrigation solution is prepared. The microbial root irrigation solution is applied to the rhizosphere area of the plants by the root irrigation method. The irrigation amount is usually 200-500 milliliters per plant. After root irrigation, the plant roots are covered with soil to ensure that the roots are protected and the soil is kept moist. The thickness of the covered soil is usually 5-10 centimeters to avoid exposing the plant roots. The surface soil is gently compacted to reduce water evaporation.

[0031] S4: Perform a two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement on the set of divided regions in a preset monitoring window to obtain a set of analysis results; Further, as shown in the appendix Figure 2 shown, performing a two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement on the set of divided regions in a preset monitoring window to obtain a set of analysis results, step S4 of the embodiment of the present application further includes: Extract the first divided region from the set of divided regions; Within the preset monitoring window, extract the plant root development index and the soil environment improvement index for the first divided region respectively according to the preset monitoring frequency to obtain the first root length-root volume-root hair number sequence and the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence; Perform a spatio-temporal interaction analysis on the first root length-root volume-root hair number sequence and the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence respectively to obtain the first updated root development time series feature vector and the first updated soil environment improvement time series feature vector; Use an ecological restoration analyzer to identify the first updated root development time series feature vector and the first updated soil environment improvement time series feature vector to obtain the first analysis result; Perform a two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement on the set of divided regions within the preset monitoring window respectively to obtain the set of analysis results.

[0032] Further, the plant root development index includes root length, root volume, and root hair number; the soil environment improvement index includes soil heavy metal concentration, nitrogen and phosphorus element content, and pH value.

[0033] In a possible embodiment, the preset monitoring window is a monitoring time period preset by those skilled in the art, which can be 5 days, 7 days, etc. Spatiotemporal interaction analysis is performed on each divided area in two dimensions of plant growth and soil environment improvement to determine the ecological restoration situation of each divided area, and the hierarchical result set is obtained. Among them, the analysis result set reflects the ecological restoration degree of the divided area set after one root irrigation.

[0034] Preferably, a first divided area is extracted from the divided area set. Further, within the preset monitoring window, the plant root development index and the soil environment improvement index are respectively extracted from the first divided area according to the preset monitoring frequency, and a first root length-root volume-root hair number sequence and a first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence are obtained. Among them, the preset monitoring frequency is a monitoring time interval preset by those skilled in the art (such as 1 day, 2 days, etc.). The plant root development index includes root length, root volume, and root hair number; the soil environment improvement index includes soil heavy metal concentration, nitrogen and phosphorus element content, and pH value.

[0035] Preferably, the first root length-root volume-root hair number sequence reflects the plant change situation in the first divided area within the preset monitoring window, and further reflects whether the plant roots grow healthily during the restoration process and whether they can effectively absorb water and nutrients. The first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence reflects the soil environment improvement situation in the first divided area within the preset monitoring window, and further reflects the pollution degree of the soil and whether it tends to be an environment suitable for plant growth. Spatiotemporal interaction analysis refers to considering both the time and space dimensions simultaneously, analyzing the dynamic process of plant growth and soil environment improvement changing with time and their spatial distribution among different regions. This analysis can reveal the restoration effects of different restoration regions and different time points, providing support for further optimizing the restoration strategy.

[0036] The first updated root development time series feature vector is a feature vector extracted based on spatiotemporal interaction analysis of time series data related to root development (such as root length, root volume, etc.), which can reflect the growth state of plants in the first divided area. The first updated soil environment improvement time series feature vector is a feature vector extracted after spatiotemporal analysis of soil environment improvement indicators (such as heavy metal concentration, nitrogen and phosphorus content, etc.), representing the soil environment improvement situation within the preset monitoring window. The ecological restoration analyzer is a functional module for intelligently analyzing the ecological restoration degree. The input data are the updated root development time series feature vector and the updated soil environment improvement feature vector, and the output data are the analysis results.

[0037] In one embodiment, multiple sample-updated root system development time-series feature vectors and multiple sample-updated soil environment improvement feature vectors, as well as corresponding multiple analysis results, are obtained as the analyzer training dataset. According to the pre-set division ratio (such as 3:2) by those skilled in the art, the analyzer training dataset is divided into a training set and a validation set. The framework constructed based on the feedforward neural network is trained using the training set to learn the one-to-one mapping relationship between the sample-updated root system development time-series feature vectors, the sample-updated soil environment improvement feature vectors, and the analysis results. After the training is completed, the multiple sample-updated root system development time-series feature vectors and the multiple sample-updated soil environment improvement feature vectors in the validation set are input into the trained network to obtain multiple output analysis results. The similarity between the multiple output analysis results and the multiple sample analysis results in the validation set is compared, and the number of similarities that meet the similarity threshold pre-set by those skilled in the art is determined. If the number is greater than the preset number, the verification passes, and the trained ecological restoration analyzer is obtained.

[0038] The trained ecological restoration analyzer is used to identify the first sample-updated root system development time-series feature vector and the first sample-updated soil environment improvement time-series feature vector to obtain a first analysis result. Based on the same principle as obtaining the first analysis result, a two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement is respectively performed on the set of divided regions within a preset monitoring window to obtain the set of analysis results. The technical effect of analyzing the ecological restoration conditions of different divided regions and providing data support for the adjustment of the microbial irrigation solution during subsequent secondary root irrigation is achieved.

[0039] Further, a spatio-temporal interaction analysis is respectively performed on the first root length-root system volume-root hair number sequence and the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence to obtain the first sample-updated root system development time-series feature vector and the first sample-updated soil environment improvement time-series feature vector. Step S4 of the embodiment of the present application further includes: The time-series feature analysis and spatial feature analysis of the first root length-root system volume-root hair number sequence are respectively performed using the time-series channel and the spatial channel to obtain the first root system development time-series feature vector and the first root system development spatial feature vector; Based on the first root system development time-series feature vector and the first root system development spatial feature vector, the attention weight of the time-series channel is updated to obtain an updated time-series channel; The updated time-series channel is used to perform feature analysis on the first root length-root system volume-root hair number sequence to obtain the first sample-updated root system development time-series feature vector; A spatio-temporal interaction analysis is performed on the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence to obtain the first sample-updated soil environment improvement time-series feature vector.

[0040] Further, based on the first root system development timing feature vector and the first root system development spatial feature vector, the attention weight of the timing channel is updated to obtain an updated timing channel. Step S4 of the embodiment of the present application further includes: Use the spatio-temporal feature interaction function to interact the first root system development timing feature vector and the first root system development spatial feature vector to obtain a spatio-temporal interaction feature vector; Based on the spatio-temporal interaction feature vector, the first root system development timing feature vector, and the attention weight of the timing channel, perform updated recognition to obtain an updated attention weight; Update the timing channel according to the updated attention weight to obtain the updated timing channel.

[0041] Further, the spatio-temporal feature interaction function is: ; Wherein, is the spatio-temporal interaction feature vector, is the first root system development timing feature vector, is the element mapping similarity normalization value according to the first root system development spatial feature vector and the first root system development timing feature vector, is the transpose of the first root system development spatial feature vector, is the dimension of the spatial feature vector, is used to introduce a prior position and is a bias term.

[0042] In the embodiment of the present application, a sample root length-root system volume-root hair number sequence set, a sample root system development timing feature vector set, and a sample root system development spatial feature vector set are obtained. Use the sample root length-root system volume-root hair number sequence set and the sample root system development timing feature vector set to perform supervised training on the framework constructed based on the convolutional neural network until convergence to obtain the timing channel. Use the sample root length-root system volume-root hair number sequence set and the sample root system development spatial feature vector set to perform supervised training on the framework constructed based on the convolutional neural network until convergence to obtain the spatial channel. Among them, the timing channel is used to perform convolutional analysis on the information with obvious changes in the timing dimension of the root length-root system volume-root hair number sequence, and the spatial channel is used to perform convolutional analysis on the relatively static information in the spatial dimension of the root length-root system volume-root hair number sequence. The timing channel has a higher analysis frame rate than the spatial channel.

[0043] Preferably, perform spatio-temporal interaction on the first root system development timing feature vector and the first root system development spatial feature vector, perform fusion analysis on the features obtained under different convolutional scales, and update the attention weight of the timing channel according to the fusion analysis result to obtain the attention weight of the timing channel that conforms to the spatio-temporal two-dimensional situation.

[0044] Perform feature analysis on the first root length - root system volume - root hair number sequence using the updated temporal channel after updating the attention weights to obtain the first updated root system development temporal feature vector. Among them, the first updated root system development temporal feature vector is a feature vector obtained by analyzing static information in space and dynamic information in time. Based on the same principle as obtaining the first updated root system development temporal feature vector, perform spatio - temporal interaction analysis on the first soil heavy metal concentration - nitrogen and phosphorus element content - pH value sequence to obtain the first updated soil environment improvement temporal feature vector.

[0045] Preferably, the spatio - temporal feature interaction function is a mathematical model used to combine the temporal feature vector and the spatial feature vector to generate a fused spatio - temporal interaction feature vector. This function reveals the relationship between them through the interaction of temporal data and spatial data, and can more accurately capture the comprehensive characteristics of plant growth or soil improvement. The spatio - temporal interaction feature vector is a feature representation obtained through the spatio - temporal feature interaction function, which integrates information from both time and space. Through this feature vector, the model can consider the changes in plant growth over time.

[0046] Identify the similarity of the elements in the spatio - temporal interaction feature vector and the elements in the first root system development temporal feature vector respectively to obtain a set of element similarities. Divide any one element similarity by the sum of the set of element similarities, and use the difference between the calculation result and 1 as the weight of this element to obtain the updated attention weights. Use the updated attention weights to update the temporal channel to obtain the updated temporal channel. In the updated temporal channel, the model will give priority to processing those features with high weights during a specific period. This weighted feature analysis can further improve the repair effect. For example, if the analysis result shows that the growth of plant roots is very slow during a certain period, the temporal channel will increase the attention to this feature through the updated weights, thereby dynamically adjusting the repair strategy (such as increasing the application amount of the root - watering solution, improving the formula of the microbial inoculant, etc.).

[0047] S5: Directionally adjust the microbial root - watering solution applied to the set of divided regions according to the analysis result set, and perform secondary root - watering ecological restoration on the corresponding divided regions according to the adjusted microbial root - watering solution.

[0048] Furthermore, when directionally adjusting the microbial root - watering solution applied to the set of divided regions according to the analysis result set and performing secondary root - watering ecological restoration on the corresponding divided regions according to the adjusted microbial root - watering solution, step S5 of the embodiment of the present application further includes: Obtain the target ecological restoration result, compare the target ecological restoration result and the analysis result set respectively to obtain a set of repair deviations; Taking the reduction of the set of repair deviations as the adjustment direction, adjust the microbial root irrigation solution applied to the set of divided areas to obtain a set of adjusted microbial root irrigation solutions; Use the set of adjusted microbial root irrigation solutions to perform secondary root irrigation ecological restoration on the corresponding divided areas in the set of divided areas.

[0049] In a possible embodiment, the target ecological restoration result is the restoration target set by those skilled in the art, including indicators such as the improvement of soil quality and the promotion of plant growth. The target ecological restoration result provides a reference for the adjustment of subsequent restoration plans. By comparing the target ecological restoration result with the set of analysis results, a set of repair deviations is obtained. The set of repair deviations reflects the problems existing in the restoration process. For example, the plant growth in some areas is slow, or the improvement of the soil environment does not meet the expectations. These deviations will guide the adjustment of the restoration plan to ensure the refinement of the restoration process. By reducing the set of repair deviations, a precise direction can be provided for subsequent restoration.

[0050] According to the set of repair deviations, by optimizing the formula and application method of the microbial root irrigation solution, adjust the concentration, application frequency, etc. of the microbial agent. This adjustment can supplement the short board in the restoration process, such as enhancing the activity of certain microorganisms and improving the speed of soil improvement. After the adjustment of the microbial root irrigation solution, secondary root irrigation restoration is carried out on each area. Secondary root irrigation can further enhance the effect of microorganisms, make up for the deficiencies after the first restoration, ensure that the plants grow healthier, and optimize the soil quality. This step ensures the continuity and long-term effect of the restoration process. By comparing the target with the actual restoration result, the deviations in the restoration process can be accurately identified and adjusted accordingly. This process improves the flexibility and adaptability of the restoration plan.

[0051] In summary, the embodiments of the present application at least have the following technical effects: According to the specific requirements of the area, the present application accurately selects appropriate microbial agents and colonized plants, and forms a set of regional microbial agent - colonized plant groups. During the restoration process, through two-dimensional spatio-temporal interaction analysis of plant growth and soil environment improvement in the preset monitoring window for the divided areas, the restoration progress and effect of the area are obtained. This spatio-temporal interaction analysis can not only monitor the plant growth situation in real time, but also monitor the soil improvement process, provide timely feedback for subsequent restoration, ensure the dynamic optimization of the restoration plan, and achieve the technical effects of improving the restoration efficiency and durability.

[0052] Based on the foregoing embodiments, the embodiments of the present application also provide an electronic device and a computer-readable storage medium. A computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor of the electronic device, the method described in any previous embodiment can be implemented.

[0053] Figure 3 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing the embodiments of the present invention. Figure 3 The displayed electronic device is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present invention. The electronic device is presented in the form of a general computing device, and its components may include, but are not limited to, an input device 301, a processor 302, a memory 303, and an output device 304. Among them, the processor 302 may be one or more; the memory 303 may include a computer-readable medium and at least one program product, and this program product has a set (at least one) of program modules, and these program modules are configured to execute the functions of the embodiments of the present application.

[0054] The memory 303 shown in the embodiments of the present invention may adopt any combination of one or more computer-readable media; the computer-readable storage medium may be, but is not limited to, infrared rays, semiconductor systems, devices or components, or any combination of the above, for storing software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the method for composite ecological restoration of coal gangue mountains based on plant-microorganism cooperation in the embodiments of the present invention. The processor 302 executes various functional applications and data processing of the computer device by running the software programs, instructions, and modules stored in the memory 303, that is, implements the above-mentioned method for composite ecological restoration of coal gangue mountains based on plant-microorganism cooperation.

[0055] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above describes specific embodiments of this specification. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0056] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included within the protection scope of the present application.

[0057] This specification and the drawings are only exemplary descriptions of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A method for composite ecological restoration of coal gangue piles based on plant-microorganism cooperation, characterized in that, The method includes: Obtaining a set of regional characteristic information of the set of divided areas of the coal gangue mountain; Based on the set of regional characteristic information, screening microbial inoculants and colonizing plants to determine a set of regional microbial inoculant-colonizing plant groups; According to the set of microbial inoculant-colonizing plant groups, respectively carrying out plant colonization on the set of divided areas, and configuring microbial root irrigation solutions according to the corresponding microbial inoculants. After applying the microbial root irrigation solutions to the rhizosphere areas of the plants by the root irrigation method, surface soil covering is carried out; Performing two-dimensional spatio-temporal interaction analysis on the set of divided areas for plant growth and soil environment improvement in a preset monitoring window to obtain a set of analysis results; According to the set of analysis results, directionally adjust the microbial root irrigation solutions applied to the set of divided areas, and perform secondary root irrigation ecological restoration on the corresponding divided areas according to the adjusted microbial root irrigation solutions.

2. The method for composite ecological restoration of coal gangue mountain based on plant-microorganism cooperation according to claim 1, wherein The set of divided areas includes bare areas, weathered areas, water accumulation areas, shallow slope scouring areas, and heavy metal exceeding standard areas.

3. The method for composite ecological restoration of coal gangue mountain based on plant-microorganism cooperation according to claim 2, characterized in that, Performing two-dimensional spatio-temporal interaction analysis on the set of divided areas for plant growth and soil environment improvement in a preset monitoring window to obtain a set of analysis results, including: Extracting a first divided area from the set of divided areas; Within the preset monitoring window, extracting plant root development indexes and soil environment improvement indexes for the first divided area respectively according to a preset monitoring frequency to obtain a first root length-root volume-root hair number sequence and a first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence; Performing spatio-temporal interaction analysis on the first root length-root volume-root hair number sequence and the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence respectively to obtain a first updated root development time series feature vector and a first updated soil environment improvement time series feature vector; Using an ecological restoration analyzer to identify the first updated root development time series feature vector and the first updated soil environment improvement time series feature vector to obtain a first analysis result; Performing two-dimensional spatio-temporal interaction analysis on the set of divided areas for plant growth and soil environment improvement within the preset monitoring window to obtain the set of analysis results.

4. The method for composite ecological restoration of coal gangue mountain based on plant-microorganism cooperation according to claim 3, wherein Performing spatio-temporal interaction analysis on the first root length-root volume-root hair number sequence and the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence respectively to obtain a first updated root development time series feature vector and a first updated soil environment improvement time series feature vector, including: Respectively using a time series channel and a space channel to perform time series feature analysis and space feature analysis on the first root length-root volume-root hair number sequence to obtain a first root development time series feature vector and a first root development space feature vector; Based on the first root development time series feature vector and the first root development space feature vector, updating the attention weight of the time series channel to obtain an updated time series channel; Using the updated time series channel to perform feature analysis on the first root length-root volume-root hair number sequence to obtain a first updated root development time series feature vector; Performing spatio-temporal interaction analysis on the first soil heavy metal concentration-nitrogen and phosphorus element content-pH value sequence to obtain a first updated soil environment improvement time series feature vector.

5. The method for composite ecological restoration of coal gangue mountain based on plant-microorganism cooperation according to claim 4, wherein, Updating the attention weights of the temporal channels based on the first root system development temporal feature vector and the first root system development spatial feature vector to obtain updated temporal channels, including: Using a spatio-temporal feature interaction function to interact the first root system development temporal feature vector and the first root system development spatial feature vector to obtain a spatio-temporal interaction feature vector; Based on the spatio-temporal interaction feature vector, the first root system development temporal feature vector, and the attention weights of the temporal channels, performing update recognition to obtain updated attention weights; Updating the temporal channels according to the updated attention weights to obtain the updated temporal channels.

6. The method for composite ecological restoration of coal gangue mountain based on plant-microorganism cooperation according to claim 5, characterized in that, The spatio-temporal feature interaction function is: ； Among them, is the spatio-temporal interaction feature vector, is the first root system development timing feature vector, is the element mapping similarity normalization value based on the first root system development spatial feature vector and the first root system development timing feature vector, is the transpose of the first root system development spatial feature vector, is the dimension of the spatial feature vector, is used to introduce the prior position and is the bias term.

7. The method for composite ecological restoration of coal gangue mountain based on plant-microorganism cooperation according to claim 3, characterized in that, The plant root system development indicators include root length, root system volume, and root hair number; the soil environment improvement indicators include soil heavy metal concentration, nitrogen and phosphorus element content, and pH value.

8. The method for composite ecological restoration of coal gangue mountain based on plant-microorganism cooperation according to claim 1, wherein Performing directional adjustment on the microbial irrigation solution applied to the divided area set according to the analysis result set, and performing secondary irrigation ecological restoration on the corresponding divided areas according to the adjusted microbial irrigation solution, including: Obtaining a target ecological restoration result, comparing the target ecological restoration result with the analysis result set respectively to obtain a restoration deviation set; Taking reducing the restoration deviation set as the adjustment direction, adjusting the microbial irrigation solution applied to the divided area set to obtain an adjusted microbial irrigation solution set; Using the adjusted microbial irrigation solution set to perform secondary irrigation ecological restoration on the corresponding divided areas in the divided area set.

9. An electronic device, characterized in that, The electronic device includes: A memory for storing executable instructions; A processor for implementing the plant-microbe collaborative coal gangue mountain composite ecological restoration method according to any one of claims 1 to 8 when executing the executable instructions stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the plant-microbe collaborative coal gangue mountain composite ecological restoration method according to any one of claims 1-8.

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