CN117172996B - Microbial activity identification monitoring method and system for ecological environment restoration - Google Patents
Microbial activity identification monitoring method and system for ecological environment restoration Download PDFInfo
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Abstract
The invention discloses a microbial activity identification monitoring method and system for ecological environment restoration, comprising the following steps: acquiring pollution characteristics of a target pollution site, recommending a microbial agent for the target pollution site, and acquiring expected repairing effects of different repairing periods according to the pollution characteristics; screening the indicative microorganisms, and acquiring microscopic image information of the soil sample to identify the indicative microorganisms; acquiring an actual restoration effect of a target polluted site according to a soil sample, acquiring deviation of the actual restoration effect and an expected restoration effect, and evaluating microbial activity according to the deviation and an indicative microbial identification result; and judging the fitness of the recommended microbial agent and the target polluted site according to the microbial activity. According to the invention, the microbial activity in the pollution repair process is identified and evaluated, the adaptation degree of the microbial agent and the pollution is judged, a data basis is provided for the adjustment and optimization of the microbial pollution repair, the repair period is shortened by utilizing activity regulation and control, and the repair efficiency is improved.
Description
Technical Field
The invention relates to the technical field of microbial remediation, in particular to a microbial activity identification monitoring method and system for ecological environment remediation.
Background
With the urban, industrialized development and industrial layout adjustment, urban industrial factory building movement has become a development trend, and industrial waste sites are seriously polluted. The chemical degradation of soil and groundwater caused by site pollution seriously threatens the basic environment for human survival, and becomes one of the serious global problems currently faced. In the pollution in-situ remediation process, the biodegradation method is an effective method for removing organic matters, and compared with the traditional chemical method and physical method, the microorganism has the characteristics of strong culture property, simple operation, environmental friendliness and the like, and the microorganism remediation strategy is considered to be the most potential technology in the remediation process of the heavy metal pollution site at present.
The microbial remediation technology is a remediation technology for reducing the activity of harmful pollutants in a polluted site or degrading the harmful pollutants into harmless substances by utilizing indigenous microorganisms or artificially domesticated microorganisms with specific functions under proper environmental conditions, wherein in-situ microbial remediation does not need to remove polluted soil or water from the site, nutrient substances and oxygen are directly put into the polluted site, the metabolic activity of indigenous microorganisms or microorganisms with specific functions is promoted, and the pollutants are degraded. Because of various uncertainties in the pollution conditions of the polluted sites, corresponding microbial remediation schemes are prone to inapplicability. Therefore, in the microbial remediation, how to identify and monitor the microbial activity of soil in a polluted site and determine the microbial remediation effect is a problem to be solved urgently.
Disclosure of Invention
In order to solve the technical problems, the invention provides a microbial activity identification monitoring method and system for ecological environment restoration.
The first aspect of the invention provides a microbial activity identification monitoring method for ecological environment restoration, comprising the following steps:
acquiring pollution characteristics of a target pollution site, acquiring recommended microbial agents of the target pollution site according to the pollution characteristics and physicochemical properties of polluted soil of the site, and acquiring expected repairing effects of different repairing periods according to the pollution characteristics;
performing environment restoration on the target polluted site by using the recommended microbial agent, screening the indicative microorganisms according to the microbial agent and pollution characteristics, acquiring microscopic image information of a soil sample of the target polluted site, and identifying the indicative microorganisms based on the microscopic image information;
acquiring the actual restoration effect of the target polluted site according to the soil sample, acquiring the deviation of the actual restoration effect and the expected restoration effect, and evaluating the microbial activity according to the deviation and the indicative microbial identification result;
and judging the adaptation degree of the recommended microbial agent and the target pollution site according to the microbial activity, and optimizing the existing microbial agent to form a composite microbial agent to improve the microbial community structure when the adaptation degree does not meet the preset standard.
In the scheme, the pollution characteristics of the target pollution site are obtained, and the recommended microbial agent of the target pollution site is obtained according to the pollution characteristics and the physicochemical properties of the polluted soil of the site, and specifically comprises the following steps:
the method comprises the steps of obtaining a pollution type and a pollution concentration of a target pollution site in a current preset time step, carrying out principal component analysis based on the pollution type to obtain a main pollutant type of the target pollution site, and obtaining a pollution concentration sequence corresponding to the main pollutant type;
the pollution concentration sequence containing the main pollutant type label is imported into a Bi-GRU network, a forward characteristic information sequence and a reverse characteristic information sequence are obtained through learning from the forward direction and the reverse direction, and the obtained two characteristic information sequences are spliced to obtain an output vector;
importing the output vector into an encoder network, replacing an encoder structure in the encoder network by using a GRU network, and performing feature coding by using a linear transformation and activation function to obtain a reconstruction vector of the output vector;
the error of the reconstruction vector is obtained, parameters are continuously optimized through back propagation, the reconstruction vector and the output vector are fused to obtain a fusion vector, the fusion vector is led into an attention module to obtain weight information, and the fusion vector is weighted by the weight information to obtain a final feature vector;
And combining the final characteristic vector with the physical and chemical properties of soil of the place where the target pollution site is located to serve as a characteristic image of the target pollution site, and acquiring a recommended microbial agent of the target pollution site based on a related microbial remediation knowledge graph according to the characteristic image.
In this scheme, obtain the expected repair effect of different repair cycles according to pollution characteristic, specifically:
acquiring an ecological environment restoration example by utilizing data retrieval according to recommended microbial agents of the target polluted site, and screening similar ecological environment restoration examples by utilizing characteristic images of the target polluted site for marking;
acquiring pollution concentration changes of marked ecological environment restoration examples in different restoration periods, preprocessing data of the pollution concentration changes, removing outlier examples in different restoration periods, and acquiring restoration effects according to deviation of pollution concentration in the ecological environment restoration examples left after preprocessing and original pollution concentration;
and carrying out average obtaining on the repairing effects in the repairing examples of different ecological environments to obtain the average repairing effects of different repairing periods, correcting the average repairing effects according to the meteorological information of the target polluted site, and taking the corrected average repairing effects as expected repairing effects of different repairing periods.
In the scheme, the method comprises the steps of screening indicative microorganisms according to microbial agents and pollution characteristics, acquiring microscopic image information of soil samples of target pollution sites, and identifying the indicative microorganisms based on the microscopic image information, wherein the method specifically comprises the following steps:
acquiring main pollutant types and environmental factors of a target pollution site, and acquiring a microbial community with obvious correlation with pollution concentration in the current pollution environment according to the main pollutant types and the environmental factors;
obtaining microbial communities with obviously changed relative abundance through an ecological environment restoration example corresponding to the recommended microbial agent, and carrying out union treatment on the obtained two microbial communities to screen the target pollution sites for the indicator microorganisms corresponding to different pollution concentrations after the recommended microbial agent is applied;
collecting a soil sample in a target contaminated site, acquiring microscopic image information of the soil sample, preprocessing the microscopic image information to acquire morphological characteristics of indicative microorganisms, and calculating pearson correlation coefficients of the morphological characteristics and microorganism identification;
acquiring a feature subset according to the pearson correlation coefficient, constructing a microorganism identification model by generating an countermeasure network, performing model training by using the feature subset, and performing background segmentation on the preprocessed microscopic image to acquire an interested region of the microscopic image;
Introducing the region of interest into a generation network for generating an countermeasure network, and using a Unet network as a generation network of a microorganism identification model, introducing channel attention and space attention in the generation network for feature extraction;
and reconstructing the extracted features through upsampling, importing the reconstructed feature images into a discrimination network, fusing the feature images with different scales when the reconstructed features meet preset standards, and connecting the fused features with a Softmax classifier in series to identify and classify indicative microorganisms.
In the scheme, the deviation of the actual repair effect and the expected repair effect is obtained, and the microbial activity is evaluated through the deviation and the indicative microbial identification result, specifically:
performing pollution investigation by using a soil sample to obtain the pollution concentration change of a target pollution site to generate an actual repair effect, obtaining a current corresponding repair period, and extracting a corresponding expected repair effect according to the repair period;
judging whether the actual repairing effect accords with the expected repairing effect, if not, acquiring the deviation of the actual repairing effect and the expected repairing effect;
acquiring the relative abundance of the indicative microorganisms in a preset area of the target contaminated site according to the number of the indicative microorganisms of each type in the soil sample, and evaluating the microbial activity of the target contaminated site based on a preset evaluation system through the deviation and the relative abundance of the indicative microorganisms.
In this scheme, judge the degree of adaptation of recommended microorganism bacterial agent and target contaminated site according to microorganism activity, specifically do:
judging whether the microbial activity of the target polluted site meets a preset microbial activity level threshold, and if not, proving that the adaptation degree of the current recommended microbial agent and the target polluted site does not meet a preset standard;
acquiring the environmental deviation between the environmental characteristics of the target polluted site and the standard environmental characteristics corresponding to the indicative microorganisms, and improving the living environment of the microorganisms through the environmental deviation;
acquiring a multiplexing scheme of the current recommended microbial agent according to the pollution characteristics of the target pollution site, the current recommended microbial agent and the environmental characteristics, acquiring an action mechanism of the current recommended microbial agent, and eliminating a scheme identical to the action mechanism from the multiplexing scheme;
and obtaining plant characteristics of the target polluted site, obtaining a microbial community which is closely developed by utilizing the plant characteristics, and obtaining a multiplexing scheme with highest correlation degree with the microbial community in a multiplexing scheme after screening so as to improve the structure of the microbial community in soil.
The second aspect of the present invention also provides a microbial activity identification monitoring system for ecological environment restoration, the system comprising: the device comprises a memory and a processor, wherein the memory comprises a microbial activity identification monitoring method program for ecological environment restoration, and the microbial activity identification monitoring method program for ecological environment restoration realizes the following steps when being executed by the processor:
Acquiring pollution characteristics of a target pollution site, acquiring recommended microbial agents of the target pollution site according to the pollution characteristics and physicochemical properties of polluted soil of the site, and acquiring expected repairing effects of different repairing periods according to the pollution characteristics;
performing environment restoration on the target polluted site by using the recommended microbial agent, screening the indicative microorganisms according to the microbial agent and pollution characteristics, acquiring microscopic image information of a soil sample of the target polluted site, and identifying the indicative microorganisms based on the microscopic image information;
acquiring the actual restoration effect of the target polluted site according to the soil sample, acquiring the deviation of the actual restoration effect and the expected restoration effect, and evaluating the microbial activity according to the deviation and the indicative microbial identification result;
and judging the adaptation degree of the recommended microbial agent and the target pollution site according to the microbial activity, and optimizing the existing microbial agent to form a composite microbial agent to improve the microbial community structure when the adaptation degree does not meet the preset standard.
The invention discloses a microbial activity identification monitoring method and system for ecological environment restoration, comprising the following steps: acquiring pollution characteristics of a target pollution site, recommending a microbial agent for the target pollution site, and acquiring expected repairing effects of different repairing periods according to the pollution characteristics; screening the indicative microorganisms, and acquiring microscopic image information of the soil sample to identify the indicative microorganisms; acquiring an actual restoration effect of a target polluted site according to a soil sample, acquiring deviation of the actual restoration effect and an expected restoration effect, and evaluating microbial activity according to the deviation and an indicative microbial identification result; and judging the fitness of the recommended microbial agent and the target polluted site according to the microbial activity. According to the invention, the microbial activity in the pollution repair process is identified and evaluated, the adaptation degree of the microbial agent and the pollution is judged, a data basis is provided for the adjustment and optimization of the microbial pollution repair, the repair period is shortened by utilizing activity regulation and control, and the repair efficiency is improved.
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In order to more clearly illustrate the technical solutions of embodiments or examples of the present invention, the drawings that are required to be used in the embodiments or examples of the present invention will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the drawings without inventive efforts for those skilled in the art.
FIG. 1 shows a flow chart of a method of identifying and monitoring microbial activity for ecological restoration according to the present invention;
FIG. 2 shows a flow chart of the invention for identifying an indicative microorganism;
FIG. 3 shows a flow chart of the invention for assessing microbial activity of a target contaminated site;
FIG. 4 shows a block diagram of a microbial activity recognition monitoring system for ecological restoration according to the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, in the case of no conflict, the embodiments of the present application and the features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those described herein, and therefore the scope of the present invention is not limited to the specific embodiments disclosed below.
FIG. 1 shows a flow chart of a method for identifying and monitoring microbial activity for ecological restoration according to the present invention.
As shown in fig. 1, the first aspect of the present invention provides a method for identifying and monitoring microbial activity for ecological environment restoration, comprising:
s102, obtaining pollution characteristics of a target pollution site, obtaining recommended microbial agents of the target pollution site according to the pollution characteristics and physical and chemical properties of polluted soil of the site, and obtaining expected repairing effects of different repairing periods according to the pollution characteristics;
s104, performing environment restoration on the target polluted site by using the recommended microbial agent, screening the indicative microorganisms according to the microbial agent and pollution characteristics, acquiring microscopic image information of a soil sample of the target polluted site, and identifying the indicative microorganisms based on the microscopic image information;
s106, acquiring the actual restoration effect of the target polluted site according to the soil sample, acquiring the deviation of the actual restoration effect and the expected restoration effect, and evaluating the microbial activity according to the deviation and the indicative microbial identification result;
S108, judging the adaptation degree of the recommended microbial agent and the target pollution site according to the microbial activity, and optimizing the existing microbial agent to form a composite microbial agent to improve the microbial community structure when the adaptation degree does not meet the preset standard.
The method comprises the steps of sampling soil samples and measuring pollution to obtain the pollution type and the pollution concentration of a target pollution site in a current preset time step, and analyzing main components based on the pollution type to obtain the main pollutant type of the target pollution site and obtain a pollution concentration sequence corresponding to the main pollutant type; the pollution concentration sequence containing the main pollutant type label is imported into a Bi-GRU network, and a layer of GRU network is added on the basis of the GRU network to reversely process data. The state calculation of the GRU network comprises an update gate, a reset gate, a candidate value and a hidden state, wherein the update gate and the reset gate control the flow of information, the candidate value and the hidden state control node output, a forward characteristic information sequence and a reverse characteristic information sequence are learned from the forward direction and the reverse direction, and the two obtained characteristic information sequences are spliced to obtain an output vector; the output vector is imported into an encoder network, a GRU network is used for replacing an encoder structure in the encoder network, linear transformation and an activation function are used for carrying out feature encoding, a reconstruction vector of the output vector is obtained, the GRU network is used for replacing the encoder structure, the context characteristics of regional pollution can be obtained, and the consistency of the characteristics is ensured; the error of the reconstruction vector is obtained, parameters are continuously optimized through back propagation, the reconstruction vector and the output vector are fused to obtain a fusion vector, the fusion vector is led into an attention module to obtain weight information, and the fusion vector is weighted by the weight information to obtain a final feature vector; and combining the final characteristic vector with the physical and chemical properties of soil of the place where the target pollution site is located to serve as a characteristic image of the target pollution site, and acquiring a recommended microbial agent of the target pollution site based on a related microbial remediation knowledge graph according to the characteristic image.
The method is characterized in that an ecological environment restoration example is obtained by utilizing data retrieval according to recommended microbial agents of a target polluted site, and similar ecological environment restoration examples are screened and marked by utilizing characteristic images of the target polluted site; acquiring pollution concentration changes of marked ecological environment restoration examples in different restoration periods, preprocessing data of the pollution concentration changes, removing outlier examples in different restoration periods, and acquiring restoration effects according to deviation of pollution concentration in the ecological environment restoration examples left after preprocessing and original pollution concentration; and the repairing effects in the repairing examples of different ecological environments are averaged to obtain the average repairing effects of different repairing periods, and as the microbial repairing is greatly influenced by factors such as environmental temperature and humidity, the average repairing effects are corrected according to the meteorological information of the place where the target polluted place is located, and the corrected average repairing effects are used as expected repairing effects of different repairing periods.
FIG. 2 shows a flow chart of the present invention for identifying an indicative microorganism.
According to the embodiment of the invention, the indicative microorganisms are screened according to microbial agents and pollution characteristics, the microscopic image information of soil samples of a target polluted site is obtained, and the indicative microorganisms are identified based on the microscopic image information, specifically:
S202, acquiring main pollutant types and environmental factors of a target pollution site, and acquiring a microbial community with obvious correlation with pollution concentration in the current pollution environment according to the main pollutant types and the environmental factors;
s204, obtaining microbial communities with significantly changed relative abundance through an ecological environment restoration example corresponding to the recommended microbial agent, and carrying out union treatment on the obtained two microbial communities to screen the target pollution sites for the indicator microorganisms corresponding to different pollution concentrations after the recommended microbial agent is applied;
s206, collecting a soil sample in a target polluted site, acquiring microscopic image information of the soil sample, preprocessing the microscopic image information, acquiring morphological characteristics of indicative microorganisms, and calculating pearson correlation coefficients of the morphological characteristics and microorganism identification;
s208, acquiring a feature subset according to the Pearson correlation coefficient, constructing a microorganism identification model by generating an antagonism network, performing model training by using the feature subset, and performing background segmentation on the preprocessed microscopic image to acquire an interested region of the microscopic image;
s210, importing the region of interest into a generation network for generating an countermeasure network, and utilizing a Unet network as a generation network of a microorganism recognition model to introduce channel attention and space attention in the generation network for feature extraction;
S212, reconstructing the extracted features through up-sampling, importing the reconstructed feature images into a discrimination network, fusing the feature images with different scales when the reconstructed features meet preset standards, and connecting the fused features with a Softmax classifier in series to identify and classify indicative microorganisms.
The method is characterized in that environmental factors are screened through environmental characteristics such as soil temperature and humidity, pH value and organic content in a target polluted site, different microorganisms such as pollution concentration and degrading bacteria are subjected to LEfSe analysis and correlation analysis according to an ecological environment restoration example, a microbial community with obvious correlation is obtained according to a correlation coefficient, a microbial community with large relative abundance change is obtained in a recommended microbial agent, and indicating microorganisms are obtained according to the obtained microbial community so as to characterize microbial activity of a target polluted area.
The generation network of the microorganism identification model is improved through the Unet network, the segmentation effect of the model is improved, the Unet network can basically carry out convolution operation on pictures of any shape and size, and the problems that the quantity of microscopic image information of a soil sample is small, the boundary of a target area is unclear and the like are solved. Introducing a spatial attention mechanism and a channel attention mechanism into the Unet network, distributing weight information for different scale feature graphs to update feature distribution, recalibrating the feature graphs, focusing the model on important feature graphs, and generating optimized feature expression. In the training of the microorganism recognition model, freezing the network weight parameters of the generated network, performing the training of distinguishing and judging, and then freezing the network weight parameters of the distinguished network, performing the training of the generated network; after the alternate training, the value of the loss function of the generated countermeasure network reaches a preset threshold range, and then the microorganism identification model is output. And acquiring the current pollution concentration of the target pollution site, extracting an indicative microorganism community corresponding to the current pollution concentration, and setting a Softmax classifier according to the indicative microorganism community to perform identification classification.
FIG. 3 shows a flow chart of the invention for assessing microbial activity in a contaminated site of interest.
According to the embodiment of the invention, the deviation of the actual repair effect and the expected repair effect is obtained, and the microbial activity is evaluated according to the deviation and the indicative microbial identification result, specifically:
s302, performing pollution investigation by using a soil sample to obtain pollution concentration change of a target pollution site to generate an actual repair effect, obtaining a current corresponding repair period, and extracting a corresponding expected repair effect according to the repair period;
s304, judging whether the actual repair effect accords with the expected repair effect, and if not, acquiring the deviation of the actual repair effect and the expected repair effect;
s306, acquiring the relative abundance of the indicative microorganisms in the preset area of the target contaminated site according to the number of the indicative microorganisms of each type in the soil sample, and evaluating the microbial activity of the target contaminated site based on a preset evaluation system through the deviation and the relative abundance of the indicative microorganisms.
The method comprises the steps of carrying out correlation analysis according to the deviation of the repairing effect, the relative abundance of the indicating pollutant and the microbial activity, setting attention weight according to the correlation analysis result, obtaining a score threshold interval corresponding to the preset microbial activity level, constructing a preset evaluation system, and judging the corresponding microbial activity level according to the deviation and the relative abundance of the indicating microorganism and the attention weight.
The method includes the steps that whether the microbial activity of a target polluted site meets a preset microbial activity level threshold is judged, and when the microbial activity of the target polluted site does not meet the preset microbial activity level threshold, the fact that the adaptation degree of a current recommended microbial agent and the target polluted site does not meet a preset standard is proved; acquiring the environmental deviation between the environmental characteristics of the target polluted site and the standard environmental characteristics corresponding to the indicative microorganisms, and improving the living environment of the microorganisms through the environmental deviation; acquiring a multiplexing scheme of the current recommended microbial agent according to the pollution characteristics of the target pollution site, the current recommended microbial agent and the environmental characteristics, acquiring an action mechanism of the current recommended microbial agent, and eliminating a scheme identical to the action mechanism from the multiplexing scheme; and obtaining plant characteristics of the target polluted site, obtaining a microbial community which is closely developed by utilizing the plant characteristics, and obtaining a multiplexing scheme with highest correlation degree with the microbial community in a multiplexing scheme after screening so as to improve the structure of the microbial community in soil. When the target pollution site has no complete plant characteristics, obtaining a suitable plant according to the environmental characteristics and the relative abundance of microorganisms, generating a microorganism-plant combined restoration scheme, and restoring soil pollution according to the plant rhizosphere microenvironment.
According to the embodiment of the invention, a microbial remediation database is established, the pollution types, the environmental characteristics, the microbial agents, the indicative microorganisms corresponding to different pollution levels and microbial activity data corresponding to different pollution levels corresponding to each historical microbial remediation example are stored in the microbial remediation database, and the data in the database are subjected to clustering analysis to obtain microbial activity grade standards of the same pollution types and different pollution levels under the condition of using different microbial agents; according to the pollution characteristics of the current pollution site and the similarity comparison of the microbial agents in the database, acquiring a historical microbial restoration example meeting the requirement of a preset value in the microbial restoration database, and extracting a corresponding microbial activity grade standard; and obtaining the pollution characteristics of the pollution site to obtain the pollution degree, and optimizing the microbial agent if the microbial activity of the current pollution site does not meet the microbial activity grade standard corresponding to the pollution degree.
FIG. 4 shows a block diagram of a microbial activity recognition monitoring system for ecological restoration according to the present invention.
The second aspect of the present invention also provides a microbial activity recognition monitoring system 4 for ecological restoration, the system comprising: a memory 41, a processor 42, wherein the memory contains a microbial activity identification monitoring method program for ecological environment restoration, and the microbial activity identification monitoring method program for ecological environment restoration realizes the following steps when being executed by the processor:
Acquiring pollution characteristics of a target pollution site, acquiring recommended microbial agents of the target pollution site according to the pollution characteristics and physicochemical properties of polluted soil of the site, and acquiring expected repairing effects of different repairing periods according to the pollution characteristics;
performing environment restoration on the target polluted site by using the recommended microbial agent, screening the indicative microorganisms according to the microbial agent and pollution characteristics, acquiring microscopic image information of a soil sample of the target polluted site, and identifying the indicative microorganisms based on the microscopic image information;
acquiring the actual restoration effect of the target polluted site according to the soil sample, acquiring the deviation of the actual restoration effect and the expected restoration effect, and evaluating the microbial activity according to the deviation and the indicative microbial identification result;
and judging the adaptation degree of the recommended microbial agent and the target pollution site according to the microbial activity, and optimizing the existing microbial agent to form a composite microbial agent to improve the microbial community structure when the adaptation degree does not meet the preset standard.
The method is characterized in that an ecological environment restoration example is obtained by utilizing data retrieval according to recommended microbial agents of a target polluted site, and similar ecological environment restoration examples are screened and marked by utilizing characteristic images of the target polluted site; acquiring pollution concentration changes of marked ecological environment restoration examples in different restoration periods, preprocessing data of the pollution concentration changes, removing outlier examples in different restoration periods, and acquiring restoration effects according to deviation of pollution concentration in the ecological environment restoration examples left after preprocessing and original pollution concentration; and carrying out average obtaining on the repairing effects in the repairing examples of different ecological environments to obtain the average repairing effects of different repairing periods, correcting the average repairing effects according to the meteorological information of the target polluted site, and taking the corrected average repairing effects as expected repairing effects of different repairing periods.
The method comprises the steps of obtaining main pollutant types and environmental factors of a target pollution site, and obtaining a microbial community which has obvious correlation with pollution concentration in the current pollution environment according to the main pollutant types and the environmental factors; obtaining microbial communities with obviously changed relative abundance through an ecological environment restoration example corresponding to the recommended microbial agent, and carrying out union treatment on the obtained two microbial communities to screen the target pollution sites for the indicator microorganisms corresponding to different pollution concentrations after the recommended microbial agent is applied; collecting a soil sample in a target contaminated site, acquiring microscopic image information of the soil sample, preprocessing the microscopic image information to acquire morphological characteristics of indicative microorganisms, and calculating pearson correlation coefficients of the morphological characteristics and microorganism identification; acquiring a feature subset according to the pearson correlation coefficient, constructing a microorganism identification model by generating an countermeasure network, performing model training by using the feature subset, and performing background segmentation on the preprocessed microscopic image to acquire an interested region of the microscopic image; introducing the region of interest into a generation network for generating an countermeasure network, and using a Unet network as a generation network of a microorganism identification model, introducing channel attention and space attention in the generation network for feature extraction; and reconstructing the extracted features through upsampling, importing the reconstructed feature images into a discrimination network, fusing the feature images with different scales when the reconstructed features meet preset standards, and connecting the fused features with a Softmax classifier in series to identify and classify indicative microorganisms.
The method comprises the steps of carrying out pollution investigation by using a soil sample to obtain the pollution concentration change of a target pollution site to generate an actual repair effect, obtaining a current corresponding repair period, and extracting a corresponding expected repair effect according to the repair period; judging whether the actual repairing effect accords with the expected repairing effect, if not, acquiring the deviation of the actual repairing effect and the expected repairing effect; acquiring the relative abundance of the indicative microorganisms in a preset area of the target contaminated site according to the number of the indicative microorganisms of each type in the soil sample, and evaluating the microbial activity of the target contaminated site based on a preset evaluation system through the deviation and the relative abundance of the indicative microorganisms.
The third aspect of the present invention also provides a computer-readable storage medium having embodied therein a microbial activity recognition monitoring method program for ecological environment restoration, which when executed by a processor, implements the steps of the microbial activity recognition monitoring method for ecological environment restoration as described in any one of the above.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of the units is only one logical function division, and there may be other divisions in practice, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a computer readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a computer-readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solutions of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. The microbial activity identification monitoring method for ecological environment restoration is characterized by comprising the following steps of:
acquiring pollution characteristics of a target pollution site, acquiring recommended microbial agents of the target pollution site according to the pollution characteristics and physicochemical properties of polluted soil of the site, and acquiring expected repairing effects of different repairing periods according to the pollution characteristics;
performing environment restoration on the target polluted site by using the recommended microbial agent, screening the indicative microorganisms according to the microbial agent and pollution characteristics, acquiring microscopic image information of a soil sample of the target polluted site, and identifying the indicative microorganisms based on the microscopic image information;
acquiring the actual restoration effect of the target polluted site according to the soil sample, acquiring the deviation of the actual restoration effect and the expected restoration effect, and evaluating the microbial activity according to the deviation and the indicative microbial identification result;
judging the adaptation degree of the recommended microbial agent and the target pollution site according to the microbial activity, and optimizing the existing microbial agent to form a composite microbial agent to improve a microbial community structure when the adaptation degree does not meet a preset standard;
Screening indicative microorganisms according to microbial agents and pollution characteristics, acquiring microscopic image information of soil samples of target polluted sites, and identifying the indicative microorganisms based on the microscopic image information, wherein the method specifically comprises the following steps:
acquiring main pollutant types and environmental factors of a target pollution site, and acquiring a microbial community with obvious correlation with pollution concentration in the current pollution environment according to the main pollutant types and the environmental factors;
obtaining microbial communities with obviously changed relative abundance through an ecological environment restoration example corresponding to the recommended microbial agent, and carrying out union treatment on the obtained two microbial communities to screen the target pollution sites for the indicator microorganisms corresponding to different pollution concentrations after the recommended microbial agent is applied;
collecting a soil sample in a target contaminated site, acquiring microscopic image information of the soil sample, preprocessing the microscopic image information to acquire morphological characteristics of indicative microorganisms, and calculating pearson correlation coefficients of the morphological characteristics and microorganism identification;
acquiring a feature subset according to the pearson correlation coefficient, constructing a microorganism identification model by generating an countermeasure network, performing model training by using the feature subset, and performing background segmentation on the preprocessed microscopic image to acquire an interested region of the microscopic image;
Introducing the region of interest into a generation network for generating an countermeasure network, and using a Unet network as a generation network of a microorganism identification model, introducing channel attention and space attention in the generation network for feature extraction;
and reconstructing the extracted features through upsampling, importing the reconstructed feature images into a discrimination network, fusing the feature images with different scales when the reconstructed features meet preset standards, and connecting the fused features with a Softmax classifier in series to identify and classify indicative microorganisms.
2. The method for identifying and monitoring microbial activity for ecological environment restoration according to claim 1, wherein the method is characterized in that the pollution characteristics of the target pollution site are obtained, and the recommended microbial agent of the target pollution site is obtained according to the pollution characteristics and the physicochemical properties of the polluted soil of the site, and specifically comprises the following steps:
the method comprises the steps of obtaining a pollution type and a pollution concentration of a target pollution site in a current preset time step, carrying out principal component analysis based on the pollution type to obtain a main pollutant type of the target pollution site, and obtaining a pollution concentration sequence corresponding to the main pollutant type;
the pollution concentration sequence containing the main pollutant type label is imported into a Bi-GRU network, a forward characteristic information sequence and a reverse characteristic information sequence are obtained through learning from the forward direction and the reverse direction, and the obtained two characteristic information sequences are spliced to obtain an output vector;
Importing the output vector into an encoder network, replacing an encoder structure in the encoder network by using a GRU network, and performing feature coding by using a linear transformation and activation function to obtain a reconstruction vector of the output vector;
the error of the reconstruction vector is obtained, parameters are continuously optimized through back propagation, the reconstruction vector and the output vector are fused to obtain a fusion vector, the fusion vector is led into an attention module to obtain weight information, and the fusion vector is weighted by the weight information to obtain a final feature vector;
and combining the final characteristic vector with the physical and chemical properties of soil of the place where the target pollution site is located to serve as a characteristic image of the target pollution site, and acquiring a recommended microbial agent of the target pollution site based on a related microbial remediation knowledge graph according to the characteristic image.
3. The method for identifying and monitoring microbial activity for ecological environment restoration according to claim 1, wherein the method is characterized in that expected restoration effects of different restoration periods are obtained according to pollution characteristics, and specifically comprises the following steps:
acquiring an ecological environment restoration example by utilizing data retrieval according to recommended microbial agents of the target polluted site, and screening similar ecological environment restoration examples by utilizing characteristic images of the target polluted site for marking;
Acquiring pollution concentration changes of marked ecological environment restoration examples in different restoration periods, preprocessing data of the pollution concentration changes, removing outlier examples in different restoration periods, and acquiring restoration effects according to deviation of pollution concentration in the ecological environment restoration examples left after preprocessing and original pollution concentration;
and carrying out average obtaining on the repairing effects in the repairing examples of different ecological environments to obtain the average repairing effects of different repairing periods, correcting the average repairing effects according to the meteorological information of the target polluted site, and taking the corrected average repairing effects as expected repairing effects of different repairing periods.
4. The method for identifying and monitoring microbial activity for ecological restoration according to claim 1, wherein a deviation of an actual restoration effect from an expected restoration effect is obtained, and the microbial activity is evaluated by the deviation and an indicative microbial identification result, specifically:
performing pollution investigation by using a soil sample to obtain the pollution concentration change of a target pollution site to generate an actual repair effect, obtaining a current corresponding repair period, and extracting a corresponding expected repair effect according to the repair period;
Judging whether the actual repairing effect accords with the expected repairing effect, if not, acquiring the deviation of the actual repairing effect and the expected repairing effect;
acquiring the relative abundance of the indicative microorganisms in a preset area of the target contaminated site according to the number of the indicative microorganisms of each type in the soil sample, and evaluating the microbial activity of the target contaminated site based on a preset evaluation system through the deviation and the relative abundance of the indicative microorganisms.
5. The method for identifying and monitoring microbial activity for ecological environment restoration according to claim 1, wherein the method is characterized in that the suitability of recommended microbial agents and target polluted sites is judged according to the microbial activity, and specifically comprises the following steps:
judging whether the microbial activity of the target polluted site meets a preset microbial activity level threshold, and if not, proving that the adaptation degree of the current recommended microbial agent and the target polluted site does not meet a preset standard;
acquiring the environmental deviation between the environmental characteristics of the target polluted site and the standard environmental characteristics corresponding to the indicative microorganisms, and improving the living environment of the microorganisms through the environmental deviation;
acquiring a multiplexing scheme of the current recommended microbial agent according to the pollution characteristics of the target pollution site, the current recommended microbial agent and the environmental characteristics, acquiring an action mechanism of the current recommended microbial agent, and eliminating a scheme identical to the action mechanism from the multiplexing scheme;
And obtaining plant characteristics of the target polluted site, obtaining a microbial community which is closely developed by utilizing the plant characteristics, and obtaining a multiplexing scheme with highest correlation degree with the microbial community in a multiplexing scheme after screening so as to improve the structure of the microbial community in soil.
6. A microbial activity identification monitoring system for ecological restoration, the system comprising: the device comprises a memory and a processor, wherein the memory comprises a microbial activity identification monitoring method program for ecological environment restoration, and the microbial activity identification monitoring method program for ecological environment restoration realizes the following steps when being executed by the processor:
acquiring pollution characteristics of a target pollution site, acquiring recommended microbial agents of the target pollution site according to the pollution characteristics and physicochemical properties of polluted soil of the site, and acquiring expected repairing effects of different repairing periods according to the pollution characteristics;
performing environment restoration on the target polluted site by using the recommended microbial agent, screening the indicative microorganisms according to the microbial agent and pollution characteristics, acquiring microscopic image information of a soil sample of the target polluted site, and identifying the indicative microorganisms based on the microscopic image information;
Acquiring the actual restoration effect of the target polluted site according to the soil sample, acquiring the deviation of the actual restoration effect and the expected restoration effect, and evaluating the microbial activity according to the deviation and the indicative microbial identification result;
judging the adaptation degree of the recommended microbial agent and the target pollution site according to the microbial activity, and optimizing the existing microbial agent to form a composite microbial agent to improve a microbial community structure when the adaptation degree does not meet a preset standard;
screening indicative microorganisms according to microbial agents and pollution characteristics, acquiring microscopic image information of soil samples of target polluted sites, and identifying the indicative microorganisms based on the microscopic image information, wherein the method specifically comprises the following steps:
acquiring main pollutant types and environmental factors of a target pollution site, and acquiring a microbial community with obvious correlation with pollution concentration in the current pollution environment according to the main pollutant types and the environmental factors;
obtaining microbial communities with obviously changed relative abundance through an ecological environment restoration example corresponding to the recommended microbial agent, and carrying out union treatment on the obtained two microbial communities to screen the target pollution sites for the indicator microorganisms corresponding to different pollution concentrations after the recommended microbial agent is applied;
Collecting a soil sample in a target contaminated site, acquiring microscopic image information of the soil sample, preprocessing the microscopic image information to acquire morphological characteristics of indicative microorganisms, and calculating pearson correlation coefficients of the morphological characteristics and microorganism identification;
acquiring a feature subset according to the pearson correlation coefficient, constructing a microorganism identification model by generating an countermeasure network, performing model training by using the feature subset, and performing background segmentation on the preprocessed microscopic image to acquire an interested region of the microscopic image;
introducing the region of interest into a generation network for generating an countermeasure network, and using a Unet network as a generation network of a microorganism identification model, introducing channel attention and space attention in the generation network for feature extraction;
and reconstructing the extracted features through upsampling, importing the reconstructed feature images into a discrimination network, fusing the feature images with different scales when the reconstructed features meet preset standards, and connecting the fused features with a Softmax classifier in series to identify and classify indicative microorganisms.
7. The microbial activity recognition monitoring system for ecological restoration according to claim 6, wherein the expected restoration effect of different restoration cycles is obtained according to pollution characteristics, specifically:
Acquiring an ecological environment restoration example by utilizing data retrieval according to recommended microbial agents of the target polluted site, and screening similar ecological environment restoration examples by utilizing characteristic images of the target polluted site for marking;
acquiring pollution concentration changes of marked ecological environment restoration examples in different restoration periods, preprocessing data of the pollution concentration changes, removing outlier examples in different restoration periods, and acquiring restoration effects according to deviation of pollution concentration in the ecological environment restoration examples left after preprocessing and original pollution concentration;
and carrying out average obtaining on the repairing effects in the repairing examples of different ecological environments to obtain the average repairing effects of different repairing periods, correcting the average repairing effects according to the meteorological information of the target polluted site, and taking the corrected average repairing effects as expected repairing effects of different repairing periods.
8. The microbial activity recognition monitoring system for ecological restoration according to claim 6, wherein a deviation of an actual restoration effect from an expected restoration effect is obtained, and the microbial activity is evaluated by the deviation and an indicative microbial recognition result, specifically:
Performing pollution investigation by using a soil sample to obtain the pollution concentration change of a target pollution site to generate an actual repair effect, obtaining a current corresponding repair period, and extracting a corresponding expected repair effect according to the repair period;
judging whether the actual repairing effect accords with the expected repairing effect, if not, acquiring the deviation of the actual repairing effect and the expected repairing effect;
acquiring the relative abundance of the indicative microorganisms in a preset area of the target contaminated site according to the number of the indicative microorganisms of each type in the soil sample, and evaluating the microbial activity of the target contaminated site based on a preset evaluation system through the deviation and the relative abundance of the indicative microorganisms.
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