A method and system for selecting microbial communities

Abstract

The present invention relates to the field of computer processing technology, and in particular to a method and system for selecting a microbial community for placement. The method comprises the following steps: collecting and processing environmental parameters of an environmental area to be placed, and obtaining environmental parameter data of the environmental area to be placed; performing statistical analysis of microbial composition in the environmental area to be placed, and obtaining microbial composition information data of the environmental area to be placed; performing microbial environment association analysis and microbial community association simulation composition on the microbial composition information data of the environmental area to be placed, and obtaining microbial simulation composition communities of each environmental area to be placed; performing gene sequencing processing and gene function evaluation analysis on microbial simulation composition communities of each environmental area to be placed, and obtaining potential influencing factors of gene function; and simultaneously performing community advantage placement selection and generating a microbial community placement plan for the environmental area to be placed, so as to execute the microbial community placement work. The present invention can realize the accurate selection of microbial communities.

Description

Technical Field

[0001] The present invention relates to the field of computer processing technology, and in particular to a method and system for selecting a microbial community for placement. Background Art

[0002] Microbial community release is a technology used to improve the microbial composition of soil, water or organisms. It is often used in environmental remediation, agricultural production and other fields. However, traditional microbial community release selection methods are limited by manual experience or based on the analysis of a small number of biological characteristics. There are problems of inaccurate selection and unstable effects, making it difficult to achieve accurate selection and efficient release of microbial communities. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide a method and system for selecting a microbial community to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for selecting a microbial community for placement comprises the following steps:

[0005] Step S1: Collect and process environmental parameters of the environment area to be placed, and obtain environmental parameter data of the environment area to be placed; perform statistical analysis on the microbial composition of the environment area to be placed, and obtain information data on the microbial composition of the environment area to be placed;

[0006] Step S2: Based on the environmental parameter data of the environmental area to be released, the microbial composition information data of the environmental area to be released is subjected to microbial environmental association analysis to obtain the association matrix between the microorganisms and the environmental parameters of the area to be released; according to the environmental parameter data of the environmental area to be released and the association matrix between the microorganisms and the environmental parameters of the area to be released, the microbial community association simulation composition is performed to obtain the microbial simulation composition community of each environmental area to be released;

[0007] Step S3: performing gene sequencing processing on the microbial simulated community in each environmental area to be released, and obtaining the genome sequence data of the microbial simulated community in each environmental area to be released; performing gene function evaluation and analysis on the genome sequence data of the microbial simulated community in each environmental area to be released, and obtaining the potential influencing factors of the gene function of the microbial simulated community in each environmental area to be released;

[0008] Step S4: Based on the potential influencing factors of gene function, the microbial simulated community composition in each environmental area to be released is selected for community advantage release to obtain the recommended results of the microbial community advantage release selection; according to the recommended results of the microbial community advantage release selection, a microbial community release plan for the environmental area to be released is generated to perform the corresponding microbial community release work.

[0009] The present invention first collects and processes environmental parameters in the environmental area to be put in order to obtain key environmental parameter data, including but not limited to temperature, humidity, soil pH value, organic matter content, etc. The collection of these parameter data can help understand the overall environmental conditions of the environmental area to be put in, thereby providing necessary reference basis for subsequent microbial monitoring and analysis. By comprehensively analyzing these environmental parameter data, the characteristics and changing laws of the environment can be better understood, providing a scientific basis for subsequent processing. At the same time, by conducting a statistical analysis of microbial composition in the environmental area to be put in, the diversity and relative abundance of the original microorganisms in the environmental area to be put in can be measured to help further understand the type composition and quantity distribution of microorganisms in the environment to be put in, so as to understand the basic composition of microorganisms in the environmental area to be put in, and lay the foundation for subsequent analysis. Secondly, by conducting a microbial environment association analysis on the microbial composition information data of the environmental area to be put in based on the environmental parameter data of the environmental area to be put in, through this analysis process, the correlation between microorganisms and environmental parameters can be explored, and a correlation matrix between microorganisms and environmental parameters can be established. Subsequently, the association simulation composition of the microbial community is performed based on the environmental parameter data of the environmental area to be released and the association matrix between the microorganisms and environmental parameters of the area to be released, that is, the composition of the microbial community that may exist in each environmental area to be released under specific environmental parameter conditions is simulated. This step helps to understand the interaction between microorganisms and the environment, so that the structure and dynamic changes of the microbial community under different environmental parameter conditions can be predicted, thereby providing basic data guarantee for the subsequent genome sequencing and microbial community recommendation release process. Then, by performing gene sequencing on the simulated microbial community composition in each environmental area to be released, their genome sequence data can be obtained. The key to this step is that it can provide a comprehensive understanding of the genetic composition of the microbial community in the environment to be released, laying the foundation for subsequent analysis and research. The application of gene sequencing technology enables an in-depth understanding of the genetic information of the microbial community, so as to better understand its function and role in the environment to be released. In addition, the gene function evaluation and analysis of the genome sequence data of the microbial simulation communities in each environmental area to be released is also carried out to determine the potential influencing factors of the gene function of each microbial simulation community. This analysis and processing process helps to understand the functional impact characteristics of the microbial community at the genetic level, thereby providing a basis for the subsequent microbial release selection and improving the stability of the subsequent microbial community release selection effect. Finally, based on the potential influencing factors of gene function, the community advantage release selection of the microbial simulation communities in each environmental area to be released is carried out. In this way, by comprehensively considering the gene function impact characteristics of microorganisms, it is possible to determine which microbial communities may have advantages under specific environmental conditions, and put forward corresponding release selection recommendations, which can improve the accuracy of microbial community selection.Based on these recommended results, a release plan for the microbial communities in the corresponding environmental areas to be released is generated to guide subsequent microbial release work and achieve the purpose of environmental governance or ecological restoration, thereby realizing the accurate selection and efficient release of microbial communities.

[0010] Preferably, the present invention also provides a microbial community placement selection system for executing the microbial community placement selection method as described above, the microbial community placement selection system comprising:

[0011] The data analysis module for the environment area to be placed is used to collect and process environmental parameters of the environment area to be placed, and obtain environmental parameter data of the environment area to be placed; perform statistical analysis on the microbial composition of the environment area to be placed, and obtain information data on the microbial composition of the environment area to be placed;

[0012] The microbial community association processing module of the area to be released is used to perform microbial environmental association analysis on the microbial composition information data of the area to be released based on the environmental parameter data of the area to be released, so as to obtain the association matrix between the microorganisms and the environmental parameters of the area to be released; the microbial community association simulation composition is performed according to the environmental parameter data of the area to be released and the association matrix between the microorganisms and the environmental parameters of the area to be released, so as to obtain the microbial simulation composition community of each area to be released;

[0013] The microbial simulation community gene sequencing evaluation module is used to perform gene sequencing processing on the microbial simulation community components in each environmental area to be released, and obtain the genome sequence data of the microbial simulation community components in each environmental area to be released; the gene function evaluation and analysis is performed on the genome sequence data of the microbial simulation community components in each environmental area to be released, so as to obtain the potential influencing factors of the gene function of the microbial simulation community components in each environmental area to be released;

[0014] The microbial community gene function advantage release module is used to select the community advantage release of microbial simulated communities in each environmental area to be released based on the potential influencing factors of gene function, so as to obtain the recommended results of the microbial community advantage release selection; according to the recommended results of the microbial community advantage release selection, a microbial community release plan for the environmental area to be released is generated to carry out the corresponding microbial community release work.

[0015] In summary, the present invention provides a microbial community placement selection system, which consists of a data analysis module for the environmental area to be placed, a microbial community association processing module for the area to be placed, a microbial simulation community gene sequencing evaluation module, and a microbial community gene function advantage placement module. It can realize any microbial community placement selection method described in the present invention, and is used to combine the operations between computer programs running on each module to realize any microbial community placement selection method. The internal structures of the system cooperate with each other, which can greatly reduce duplication of work and manpower investment, and can quickly and effectively provide a more accurate and efficient microbial community placement selection process, thereby simplifying the operation process of the microbial community placement selection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0017] Figure 1 A schematic diagram of the steps of the method for selecting a microbial community for delivery of the present invention;

[0018] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0019] Figure 3 for Figure 2 Detailed step flow chart of step S14 in FIG. DETAILED DESCRIPTION

[0020] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0021] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0022] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0023] To achieve this, please refer to Figures 1 to 3 The present invention provides a method for selecting a microbial community, the method comprising the following steps:

[0024] Step S1: Collect and process environmental parameters of the environment area to be placed, and obtain environmental parameter data of the environment area to be placed; perform statistical analysis on the microbial composition of the environment area to be placed, and obtain information data on the microbial composition of the environment area to be placed;

[0025] Step S2: Based on the environmental parameter data of the environmental area to be released, the microbial composition information data of the environmental area to be released is subjected to microbial environmental association analysis to obtain the association matrix between the microorganisms and the environmental parameters of the area to be released; according to the environmental parameter data of the environmental area to be released and the association matrix between the microorganisms and the environmental parameters of the area to be released, the microbial community association simulation composition is performed to obtain the microbial simulation composition community of each environmental area to be released;

[0026] Step S3: performing gene sequencing processing on the microbial simulated community in each environmental area to be released, and obtaining the genome sequence data of the microbial simulated community in each environmental area to be released; performing gene function evaluation and analysis on the genome sequence data of the microbial simulated community in each environmental area to be released, and obtaining the potential influencing factors of the gene function of the microbial simulated community in each environmental area to be released;

[0027] Step S4: Based on the potential influencing factors of gene function, the microbial simulated community composition in each environmental area to be released is selected for community advantage release to obtain the recommended results of the microbial community advantage release selection; according to the recommended results of the microbial community advantage release selection, a microbial community release plan for the environmental area to be released is generated to perform the corresponding microbial community release work.

[0028] In the embodiment of the present invention, please refer to Figure 1 As shown, it is a schematic diagram of the steps of the microbial community delivery selection method of the present invention. In this example, the steps of the microbial community delivery selection method include:

[0029] Step S1: Collect and process environmental parameters of the environment area to be placed, and obtain environmental parameter data of the environment area to be placed; perform statistical analysis on the microbial composition of the environment area to be placed, and obtain information data on the microbial composition of the environment area to be placed;

[0030] The embodiment of the present invention first determines the sampling points and sampling time of the environmental area to be deployed, and uses appropriate tools and equipment (such as sensors, collection instruments, etc.) according to a pre-designed collection plan to collect environmental parameters (such as temperature, humidity, air pressure, soil pH value and other parameters) in the environmental area to be deployed, so as to help understand the overall environmental conditions of the environmental area to be deployed, thereby obtaining environmental parameter data of the environmental area to be deployed. Secondly, the types of microorganisms in the environmental area to be placed are monitored and processed by using the PCR method, so as to monitor and determine the types of microorganisms originally existing in the environmental area to be placed and their distribution in real time, and the number of microorganisms in the environmental area to be placed is monitored and processed by using a microscope observation method or a microbial sampling tool, so as to monitor the number level of microorganisms in the environmental area to be placed in real time. Then, the types and number data of microorganisms in the environmental area to be placed are analyzed to analyze the number distribution of each microorganism in the environmental area to be placed, and the composition of microorganisms in the environmental area to be placed is statistically analyzed by combining the microbial distribution differences obtained by the analysis of the number distribution of each microorganism in the environmental area to be placed, so as to identify the main types of microorganisms in the environmental area to be placed and their distribution patterns, and at the same time, the relative distribution of different microbial species in the environmental area to be placed is statistically calculated, including the relative abundance and distribution of each microbial species, so as to finally obtain the microbial composition information data of the environmental area to be placed.

[0031] Step S2: Based on the environmental parameter data of the environmental area to be released, the microbial composition information data of the environmental area to be released is subjected to microbial environmental association analysis to obtain the association matrix between the microorganisms and the environmental parameters of the area to be released; according to the environmental parameter data of the environmental area to be released and the association matrix between the microorganisms and the environmental parameters of the area to be released, the microbial community association simulation composition is performed to obtain the microbial simulation composition community of each environmental area to be released;

[0032] The embodiment of the present invention combines the environmental parameter data of the environment area to be released (including temperature, humidity, soil pH value, light intensity, etc.) with the corresponding machine learning or statistical analysis method (including regression analysis, support vector machine, random forest, etc.) to process the microbial composition information data of the environment area to be released (including the types, quantities, abundances, diversity, etc. of different microorganisms in the environment area to be released), so as to use the environmental parameter data as the independent variable and the microbial composition information data as the dependent variable for predictive analysis, thereby predicting the adaptability of different microorganisms under specific environmental conditions (including the growth rate, metabolic activity, etc. of the microorganisms), and combining the predicted data (including the growth rate, metabolic activity, etc. of the microorganisms under the corresponding environmental parameter conditions) with a linear analysis model (such as linear regression, Pearson correlation analysis, etc.) and a nonlinear analysis model (such as polynomial regression, logistic regression, Spea Rman rank correlation analysis, Kendall rank correlation analysis, etc.) are used to analyze the corresponding microorganisms in the microbial composition information data of the environmental area to be released, so as to evaluate and analyze the linear and nonlinear correlations between the corresponding microbial composition and the environmental parameters, so as to comprehensively evaluate the correlations between the microorganisms and the environmental parameters in the environmental area to be released. Secondly, the Pearson correlation coefficient calculation method is used to calculate the correlation between the microorganisms and the environmental parameters in the environmental area to be released, so as to quantify the degree of mutual correlation between the microorganisms and the environmental parameters. The correlation coefficient matrix between the microorganisms and the environmental parameters is constructed by arranging the calculated correlation coefficients between the microorganisms and the environmental parameters in the environmental area to be released in the form of microorganisms as horizontal columns and environmental parameters as vertical columns, so as to clearly show the correlation between the microorganisms and the environmental parameters, so as to obtain the correlation matrix between the microorganisms and the environmental parameters in the area to be released. Then, by simulating and creating corresponding multiple environmental parameter conditions according to the actual situation, such as inconsistent temperature ranges, inconsistent humidity ranges, inconsistent soil pH ranges, etc., the specific environmental parameter conditions of the environment to be released are simulated. At the same time, the correlation matrix between the microorganisms and the environmental parameters in the area to be released is screened according to the simulated limited environmental parameter conditions generated by the simulation, so as to screen out the correlation coefficient relationship matrix between the microorganisms and the environmental parameters under the corresponding limited environmental parameter conditions, and compare and judge according to the preset correlation coefficient threshold value, so as to screen out the microorganisms that meet the judgment conditions (whose correlation coefficient is greater than or equal to the preset correlation coefficient threshold value) under each limited environmental parameter condition and perform composition processing to determine the microbial composition under the corresponding limited environmental parameter conditions, and finally obtain the simulated composition community of microorganisms in each environmental area to be released.

[0033] Step S3: performing gene sequencing processing on the microbial simulated community in each environmental area to be released, and obtaining the genome sequence data of the microbial simulated community in each environmental area to be released; performing gene function evaluation and analysis on the genome sequence data of the microbial simulated community in each environmental area to be released, and obtaining the potential influencing factors of the gene function of the microbial simulated community in each environmental area to be released;

[0034] The embodiment of the present invention processes the simulated microbial communities in each environmental area to be released by using gene sequencing technology (such as Illumina sequencing, etc.) to deeply understand the genetic information of the simulated microbial communities in the corresponding environmental area to be released, and comprehensively understand the genetic composition of the microbial communities in the environmental area to be released, thereby obtaining the genome sequence data of the simulated microbial communities in each environmental area to be released. At the same time, the genome sequence data of the simulated microbial communities in each environmental area to be released obtained by sequencing are processed by using corresponding computer quality control processing technology (including removal of low-quality sequences, removal of linker sequences, removal of PCR repeat sequences, etc.) to control and adjust the corresponding genome sequence data and eliminate potential errors and noise. Secondly, the genome quality control sequence data obtained after quality control processing is processed by using pre-set and known genome sequence databases (such as NCBI, KEGG, MetaCyc, etc.) and genome annotation tools and databases (such as BLAST, GO, etc.) to predict and annotate the functional characteristics of homologous genes, and by using differential impact analysis methods The annotated genome quality control sequence data are analyzed to analyze and compare the functional differences and influence relationships between different gene sequences, and to reveal the ecological functions and mutual influence relationships of the corresponding microbial communities in the environmental areas to be released. Then, based on the ecological functions and mutual influence relationships of the microbial communities in the environmental areas to be released, the genome sequence data of the microbial simulation communities in each environmental area to be released are analyzed using an impact assessment analysis method to evaluate and analyze the potential influencing factors of the microbial communities in the environment to be released, such as the abundance and expression levels of specific microbial genes, and the influence correlation relationship between the microbial communities and environmental factors, etc., and finally the potential influencing factors of the gene functions of the microbial simulation communities in each environmental area to be released are obtained.

[0035] Step S4: Based on the potential influencing factors of gene function, the microbial simulated community composition in each environmental area to be released is selected for community advantage release to obtain the recommended results of the microbial community advantage release selection; according to the recommended results of the microbial community advantage release selection, a microbial community release plan for the environmental area to be released is generated to perform the corresponding microbial community release work.

[0036] The embodiment of the present invention uses bioinformatics analysis methods (such as PICRUSt technology) in combination with potential influencing factors of gene function to predict and analyze the gene functions of microbial simulation communities in each environmental area to be released, so as to deeply study the functional composition of the microbial genome, and analyzes the predicted results of the gene function composition of each microbial simulation community by using metabolic pathway analysis tools and databases (such as KEGG, etc.) and ecological analysis methods, so as to evaluate and analyze the activity of metabolic pathways and the ecological function correlation performance of the microbial simulation community under different environmental parameter conditions. At the same time, mathematical statistical analysis methods are used to statistically calculate the corresponding evaluation scores of the metabolic pathway activity evaluation results and the ecological function correlation evaluation results, and the corresponding evaluation scores are weighted and integrated to comprehensively consider the metabolic activity and ecological function of the microorganisms to quantify and calculate each The corresponding release recommendation index of each microbial simulation community is determined by comparison. According to the corresponding gene function prediction release recommendation index under specific environmental parameter conditions, it is determined which microbial simulation communities are more suitable for the specific environmental parameter conditions. The microbial simulation community in the environmental area to be released corresponding to the highest gene function prediction release recommendation index is recommended as the community release selection for the specific environmental parameter conditions, thereby obtaining the recommendation result of the advantageous release selection of the microbial community. At the same time, the characteristics of the release environmental parameter conditions, the characteristics of the microbial simulation community and the purpose of release are comprehensively considered to formulate a suitable microbial community release plan, thereby generating a microbial community release plan for the environmental area to be released, and finally executing the corresponding microbial community release work, including effectively arranging the time, place and quantity of microbial release.

[0037] The present invention first collects and processes environmental parameters in the environmental area to be put in order to obtain key environmental parameter data, including but not limited to temperature, humidity, soil pH value, organic matter content, etc. The collection of these parameter data can help understand the overall environmental conditions of the environmental area to be put in, thereby providing necessary reference basis for subsequent microbial monitoring and analysis. By comprehensively analyzing these environmental parameter data, the characteristics and changing laws of the environment can be better understood, providing a scientific basis for subsequent processing. At the same time, by conducting a statistical analysis of microbial composition in the environmental area to be put in, the diversity and relative abundance of the original microorganisms in the environmental area to be put in can be measured to help further understand the type composition and quantity distribution of microorganisms in the environment to be put in, so as to understand the basic composition of microorganisms in the environmental area to be put in, and lay the foundation for subsequent analysis. Secondly, by conducting a microbial environment association analysis on the microbial composition information data of the environmental area to be put in based on the environmental parameter data of the environmental area to be put in, through this analysis process, the correlation between microorganisms and environmental parameters can be explored, and a correlation matrix between microorganisms and environmental parameters can be established. Subsequently, the association simulation composition of the microbial community is performed based on the environmental parameter data of the environmental area to be released and the association matrix between the microorganisms and environmental parameters of the area to be released, that is, the composition of the microbial community that may exist in each environmental area to be released under specific environmental parameter conditions is simulated. This step helps to understand the interaction between microorganisms and the environment, so that the structure and dynamic changes of the microbial community under different environmental parameter conditions can be predicted, thereby providing basic data guarantee for the subsequent genome sequencing and microbial community recommendation release process. Then, by performing gene sequencing on the simulated microbial community composition in each environmental area to be released, their genome sequence data can be obtained. The key to this step is that it can provide a comprehensive understanding of the genetic composition of the microbial community in the environment to be released, laying the foundation for subsequent analysis and research. The application of gene sequencing technology enables an in-depth understanding of the genetic information of the microbial community, so as to better understand its function and role in the environment to be released. In addition, the gene function evaluation and analysis of the genome sequence data of the microbial simulation communities in each environmental area to be released is also carried out to determine the potential influencing factors of the gene function of each microbial simulation community. This analysis and processing process helps to understand the functional impact characteristics of the microbial community at the genetic level, thereby providing a basis for the subsequent microbial release selection and improving the stability of the subsequent microbial community release selection effect. Finally, based on the potential influencing factors of gene function, the community advantage release selection of the microbial simulation communities in each environmental area to be released is carried out. In this way, by comprehensively considering the gene function impact characteristics of microorganisms, it is possible to determine which microbial communities may have advantages under specific environmental conditions, and put forward corresponding release selection recommendations, which can improve the accuracy of microbial community selection.Based on these recommended results, a release plan for the microbial communities in the corresponding environmental areas to be released is generated to guide subsequent microbial release work and achieve the purpose of environmental governance or ecological restoration, thereby realizing the accurate selection and efficient release of microbial communities.

[0038] Preferably, step S1 comprises the following steps:

[0039] Step S11: collecting and processing environmental parameters of the environment area to be placed, and obtaining environmental parameter data of the environment area to be placed;

[0040] Step S12: monitoring and processing the microorganism species in the environmental area to be placed, and obtaining information data on the microorganism species in the environmental area to be placed;

[0041] Step S13: monitoring the number of microorganisms in the environmental area to be placed, and obtaining information data on the number of microorganisms in the environmental area to be placed;

[0042] Step S14: Based on the microbial species information data and the microbial quantity information data of the environmental area to be placed, a statistical analysis of the microbial composition of the environmental area to be placed is performed to obtain the microbial composition information data of the environmental area to be placed.

[0043] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps:

[0044] Step S11: collecting and processing environmental parameters of the environment area to be placed, and obtaining environmental parameter data of the environment area to be placed;

[0045] The embodiment of the present invention first determines the sampling points and sampling time of the environmental area to be deployed, and uses appropriate tools and equipment (such as sensors, collection instruments, etc.) according to a pre-designed collection plan to collect environmental parameters (such as temperature, humidity, air pressure, soil pH value and other parameters) in the environmental area to be deployed, so as to help understand the overall environmental conditions of the environmental area to be deployed, and finally obtain environmental parameter data of the environmental area to be deployed.

[0046] Step S12: monitoring and processing the microorganism species in the environmental area to be placed, and obtaining information data on the microorganism species in the environmental area to be placed;

[0047] The embodiment of the present invention uses the PCR method to monitor and process the types of microorganisms in the environmental area to be released, so as to monitor and determine in real time the types of microorganisms originally existing in the environmental area to be released and their distribution, and finally obtain information data on the types of microorganisms in the environmental area to be released.

[0048] Step S13: monitoring the number of microorganisms in the environmental area to be placed, and obtaining information data on the number of microorganisms in the environmental area to be placed;

[0049] The embodiment of the present invention monitors and processes the number of microorganisms in the environmental area to be placed by using a microscope observation method or a microbial sampling tool to monitor the number level of microorganisms in the environmental area to be placed in real time, and further understands the number composition of original microorganisms in the environmental area to be placed, and finally obtains information data on the number of microorganisms in the environmental area to be placed.

[0050] Step S14: Based on the microbial species information data and the microbial quantity information data of the environmental area to be placed, a statistical analysis of the microbial composition of the environmental area to be placed is performed to obtain the microbial composition information data of the environmental area to be placed.

[0051] The embodiment of the present invention first analyzes the microbial species information data and the microbial quantity information data of the environmental area to be placed to analyze the quantity distribution of each microorganism in the environmental area to be placed, and then, by combining the microbial distribution difference obtained by the analysis of the quantity distribution of each microorganism in the environmental area to be placed, the composition of the microorganisms in the environmental area to be placed is statistically analyzed to identify the main microbial species and their distribution patterns in the environmental area to be placed, and the relative distribution of different microbial species in the environmental area to be placed is statistically calculated, including the relative abundance and distribution of each microbial species, and finally the microbial composition information data of the environmental area to be placed is obtained.

[0052] The present invention first collects and processes environmental parameters in the environment area to be placed, so that various environmental parameter data in the environment area to be placed can be collected, such as parameters such as temperature, humidity, air pressure, soil pH value, etc. The collection of these data can help understand the overall environmental conditions of the environment area to be placed, thereby providing necessary reference basis for subsequent microbial monitoring and analysis. Through comprehensive analysis of these environmental parameter data, the characteristics and changing laws of the environment can be better understood, providing a scientific basis for subsequent processing procedures. Secondly, by monitoring and processing the microbial species in the environment area to be placed, the type information data of the microorganisms can be obtained. These data can help determine the types of microorganisms and their distribution in the environment to be placed, thereby providing basic data guarantee for subsequent microbial composition analysis. Then, by monitoring and processing the number of microorganisms in the environment area to be placed, the number information data of the microorganisms can be obtained. These data can help evaluate the number level of microorganisms in the environment to be placed, and further understand the number composition of original microorganisms in the environment area to be placed, thereby providing data support for subsequent processing procedures. Finally, by combining the microbial species information data and microbial quantity information data of the environmental area to be released, a statistical analysis of the microbial composition of the environmental area to be released is performed, thereby obtaining the microbial composition information data of the environmental area to be released. These data can help further understand the species composition and quantity distribution of microorganisms in the environment to be released, and provide basic data support for the subsequent environmental correlation analysis process.

[0053] Preferably, step S14 comprises the following steps:

[0054] Step S141: performing distribution statistics analysis on the microorganism species information data and the microorganism quantity information data of the environmental area to be placed, and obtaining the microorganism species quantity distribution status data of the environmental area to be placed;

[0055] Step S142: performing a microbial abundance conversion analysis on the environment area to be deployed based on the data on the number and distribution of microbial species in the environment area to be deployed, and obtaining a relative abundance of microorganisms in the environment area to be deployed;

[0056] Step S143: performing microbial diversity assessment and analysis on the environmental area to be deployed according to the relative abundance of microorganisms in the environmental area to be deployed, and obtaining microbial diversity level data of the environmental area to be deployed;

[0057] Step S144: performing microbial uniformity measurement calculation on the data of the number of microbial species and distribution in the environment area to be placed, so as to obtain a microbial uniformity measurement index for the environment area to be placed; performing microbial difference analysis on the microbial diversity level data in the environment area to be placed based on the microbial uniformity measurement index for the environment area to be placed, so as to obtain microbial distribution difference level data for the environment area to be placed;

[0058] Step S145: Performing a statistical analysis of the microbial composition of the environment to be deployed based on the microbial distribution difference level data of the environment to be deployed, and obtaining microbial composition information data of the environment to be deployed.

[0059] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 2 Detailed step flow diagram of step S14 in the embodiment, step S14 includes the following steps:

[0060] Step S141: performing distribution statistics analysis on the microorganism species information data and the microorganism quantity information data of the environmental area to be placed, and obtaining the microorganism species quantity distribution status data of the environmental area to be placed;

[0061] The embodiment of the present invention uses a distribution statistical analysis method to analyze the microbial species information data and the microbial quantity information data of the environment area to be placed, so as to analyze the quantity distribution of each microorganism in the environment area to be placed, thereby revealing the structure and composition characteristics of the original microbial community in the environment to be placed, and finally obtaining the microbial species quantity distribution status data of the environment area to be placed.

[0062] Step S142: performing a microbial abundance conversion analysis on the environment area to be deployed based on the data on the number and distribution of microbial species in the environment area to be deployed, and obtaining a relative abundance of microorganisms in the environment area to be deployed;

[0063] The embodiment of the present invention uses a microbial abundance calculation method (that is, the number of each microorganism divided by the total number of microorganisms in the environment to be released) to perform abundance conversion calculation by combining the number distribution of each microorganism in the environment to be released in the data on the number distribution of microbial species in the environment to be released, so as to convert the number distribution of microorganisms into a relative abundance measure and eliminate the difference in the number of microbial species, thereby reflecting the relative importance of different microbial species in the environment to be released, and finally obtaining the relative abundance measure of the microorganisms in the environment to be released.

[0064] Step S143: performing microbial diversity assessment and analysis on the environmental area to be deployed according to the relative abundance of microorganisms in the environmental area to be deployed, and obtaining microbial diversity level data of the environmental area to be deployed;

[0065] The embodiment of the present invention calculates the diversity index of the microorganisms in the environment area to be deployed by combining the calculated relative abundance of microorganisms in the environment area to be deployed with a diversity index calculation method (such as the Shannon diversity index, the Simpson diversity index, etc.), and evaluates and analyzes the environment area to be deployed based on the calculated microbial diversity index to evaluate and understand the richness and diversity level of the microorganisms in the environment area to be deployed, and finally obtains the microbial diversity level data of the environment area to be deployed.

[0066] Step S144: performing microbial uniformity measurement calculation on the data of the number of microbial species and distribution in the environment area to be placed, so as to obtain a microbial uniformity measurement index for the environment area to be placed; performing microbial difference analysis on the microbial diversity level data in the environment area to be placed based on the microbial uniformity measurement index for the environment area to be placed, so as to obtain microbial distribution difference level data for the environment area to be placed;

[0067] The embodiment of the present invention calculates the quantity distribution of each microorganism in the environment area to be placed in the data of the quantity distribution of microorganism species in the environment area to be placed by using various uniformity index calculation methods (such as Pielou uniformity index, Berger-Parker uniformity index, etc.), so as to statistically calculate the uniformity of the distribution of microorganisms in the environment area to be placed, thereby obtaining the uniformity measurement index of microorganisms in the environment area to be placed. Then, by combining the uniformity measurement index of microorganisms in the environment area to be placed, the distribution difference analysis method is used to analyze the data of the microbial diversity level in the environment area to be placed, so as to evaluate the distribution difference level of microorganisms in the environment by comparing the uniformity index between different microorganisms in the environment area to be placed, and further reveal the ecological balance state of the environment to be placed and the structural characteristics of microbial diversity, and finally obtain the data of the difference level of microbial distribution in the environment area to be placed.

[0068] Step S145: Performing a statistical analysis of the microbial composition of the environment to be deployed based on the microbial distribution difference level data of the environment to be deployed, and obtaining microbial composition information data of the environment to be deployed.

[0069] The embodiment of the present invention performs statistical analysis on the composition of microorganisms in the environment area to be placed by combining the distribution differences of microorganisms in the microbial distribution difference level data of the environment area to be placed, so as to identify the main microbial species and their distribution patterns in the environment area to be placed, and statistically calculate the relative distribution of different microbial species in the environment area to be placed, including the relative abundance and distribution of each microbial species, and finally obtain the microbial composition information data of the environment area to be placed.

[0070] The present invention firstly performs distribution statistics analysis on the information data of microorganism species in the environment area to be put in and the information data of the number of microorganisms in the environment area to be put in, so as to comprehensively consider the number distribution of different microorganism species. The key to this step is that the relative number of different microorganisms in the environment can be understood by analyzing the distribution of the number of microorganism species, thereby revealing the structure and composition characteristics of the original microbial community in the environment to be put in, so as to provide basic data support for subsequent microbial abundance conversion and diversity assessment. Secondly, by performing microbial abundance conversion analysis on the environment area to be put in according to the distribution data of the number of microorganism species in the environment area to be put in, the number of microorganisms can be converted into a relative abundance amount, so that the difference in the number of microorganism species can be eliminated, and the relative importance of different microorganism species in the environment to be put in can be more accurately reflected, thereby providing a more reliable data basis for microbial diversity assessment. Then, by performing microbial diversity assessment analysis on the environment area to be put in according to the relative abundance amount of microorganisms in the environment area to be put in, the key to this step is that the richness and diversity structure of microorganisms in the environment to be put in can be understood, which provides an important reference basis for the subsequent processing process. Next, the microbial uniformity measurement is calculated by using the corresponding computer statistical analysis method to calculate the distribution status of the number of microbial species in the environment to be released, so as to obtain the microbial uniformity measurement index, and the difference analysis of the microbial diversity level is performed based on the index. The key to this step is to be able to evaluate the uniformity of the distribution of microorganisms in the environment to be released by analyzing the uniformity of microorganisms, and further reveal the ecological balance state and structural characteristics of microbial diversity in the environment to be released. Finally, by performing a statistical analysis of the microbial composition of the environment to be released based on the data on the difference level of microbial distribution in the environment to be released, this step can identify the main microbial species and their distribution patterns in the environment to be released by analyzing the differences in microbial distribution, thereby providing basic data support for the subsequent environmental association analysis process.

[0071] Preferably, step S2 comprises the following steps:

[0072] Step S21: performing microbial environmental adaptability prediction analysis on the microbial composition information data of the environmental area to be deployed based on the environmental parameter data of the environmental area to be deployed, and obtaining microbial environmental adaptability prediction data of the environmental area to be deployed under the corresponding environmental parameter conditions;

[0073] The embodiment of the present invention uses corresponding machine learning or statistical analysis methods (including regression analysis, support vector machine, random forest, etc.) to process the microbial composition information data of the environmental area to be released (including the types, quantities, abundances, diversity, etc. of different microorganisms in the environmental area to be released) in combination with the environmental parameter data of the environmental area to be released (including temperature, humidity, soil pH value, light intensity, etc.), so as to use the environmental parameter data as the independent variable and the microbial composition information data as the dependent variable for predictive analysis, thereby predicting the adaptability of different microorganisms under specific environmental conditions (including the adaptability of the growth rate, metabolic activity, etc. of the microorganisms), and finally obtaining the predicted data of the environmental adaptability of the microorganisms in the environmental area to be released under the corresponding environmental parameter conditions.

[0074] Step S22: performing correlation evaluation and analysis on the microbial composition information data of the environment area to be deployed according to the prediction data of the environmental adaptability of the microorganisms in the environment area to be deployed under the corresponding environmental parameter conditions, and obtaining correlation relationship data between the microorganisms in the environment area to be deployed and the environmental parameters;

[0075] The embodiment of the present invention analyzes the corresponding microorganisms in the microbial composition information data of the environment area to be released by combining the predicted data of environmental adaptability of microorganisms in the environment area to be released under corresponding environmental parameter conditions (including the growth rate, metabolic activity, etc. of microorganisms under corresponding environmental parameter conditions) using linear analysis models (such as linear regression, Pearson correlation analysis, etc.) and nonlinear analysis models (such as polynomial regression, logistic regression, Spearman rank correlation analysis, Kendall rank correlation analysis, etc.), so as to evaluate and analyze the linear and nonlinear correlation between the corresponding microbial composition and the environmental parameters, thereby comprehensively evaluating the correlation between the microorganisms in the environment area to be released and the environmental parameters, and finally obtaining the correlation data between the microorganisms in the environment area to be released and the environmental parameters.

[0076] Step S23: Based on the correlation relationship data between the microorganisms in the environment area to be placed and the environmental parameters, the correlation coefficient is statistically calculated for the environmental parameter data of the environment area to be placed and the microorganism composition information data of the environment area to be placed, so as to obtain the correlation coefficient between the microorganisms in the environment area to be placed and the environmental parameters;

[0077] The embodiment of the present invention uses the Pearson correlation coefficient calculation method to calculate the environmental parameters corresponding to the environmental parameter data of the environmental area to be placed and the microorganisms corresponding to the microbial composition information data of the environmental area to be placed, by combining the correlation relationship data between the microorganisms in the environmental area to be placed and the environmental parameters, so as to quantify the degree of mutual correlation between the microorganisms and the environmental parameters, and finally obtain the correlation coefficient between the microorganisms in the environmental area to be placed and the environmental parameters.

[0078] Step S24: constructing a correlation matrix of correlation coefficients between microorganisms and environmental parameters in the area to be placed in the environment in which the microorganisms are arranged in horizontal columns and the environmental parameters are arranged in vertical columns, so as to obtain a correlation matrix between the microorganisms and environmental parameters in the area to be placed in the environment;

[0079] The embodiment of the present invention constructs a correlation coefficient matrix between microorganisms and environmental parameters by arranging the calculated correlation coefficients between the microorganisms in the environmental area to be released and the environmental parameters in the form of microorganisms as horizontal columns and environmental parameters as vertical columns, so as to clearly show the correlation relationship between the microorganisms and the environmental parameters, and finally obtains the correlation matrix between the microorganisms in the area to be released and the environmental parameters.

[0080] Step S25: Perform microbial community association simulation based on the environmental parameter data of the area to be released and the association matrix between the microorganisms and the environmental parameters in the area to be released, and obtain the microbial simulation community composition of each area to be released.

[0081] The embodiment of the present invention first collects environmental parameter data of the environmental area to be released, including temperature, humidity, soil pH value, light intensity, etc., and simulates and creates corresponding multiple environmental parameter conditions according to actual conditions, such as inconsistent temperature ranges, inconsistent humidity ranges, inconsistent soil pH value ranges, etc., so as to simulate the specific environmental parameter conditions of the environment to be released. At the same time, the correlation matrix between the microorganisms and the environmental parameters in the area to be released is screened according to the simulated limited environmental parameter conditions generated by the simulation, so as to screen out the correlation coefficient relationship matrix between the microorganisms and the environmental parameters under the corresponding limited environmental parameter conditions, and compares and judges the correlation coefficients in the microorganism correlation sub-matrix of the area to be released under the limited environmental parameter conditions according to the preset correlation coefficient threshold. If the first correlation coefficient in the microorganism correlation sub-matrix of the area to be released is greater than or equal to the preset correlation coefficient threshold, it is said that If it is clear that the microorganism corresponding to the correlation coefficient may prefer the corresponding limited environmental parameter conditions, the microorganisms in the microbial correlation sub-matrix of the area to be released corresponding to the correlation coefficient are screened out; if the first correlation coefficient in the microbial correlation sub-matrix of the area to be released is less than the preset correlation coefficient threshold, it means that the microorganism corresponding to the correlation coefficient does not prefer the corresponding limited environmental parameter conditions and the effect of the microorganism will be affected by the corresponding limited environmental parameter conditions, then the microorganism corresponding to the correlation coefficient is discarded, and the next correlation coefficient in the microbial correlation sub-matrix of the area to be released is compared and judged, and so on, until all the correlation coefficients in the correlation sub-matrix are traversed, and then, the microorganisms screened out under each limited environmental parameter condition are subjected to composition processing by using the community composition method to determine the microbial composition under the corresponding limited environmental parameter conditions, and finally obtain the microbial simulation composition community of each environmental area to be released.

[0082] The present invention firstly performs microbial environmental adaptation prediction analysis on the microbial composition information data of the environmental area to be put in combination with the environmental parameter data of the environmental area to be put in, and can predict the adaptability of different microorganisms under specific environmental conditions. The key of this step is to predict the survival and reproduction of microorganisms under different environmental parameter conditions, which can provide important references for subsequent processing processes, thereby helping to analyze the correlation between microbial composition and environmental parameters. Secondly, by performing correlation evaluation analysis on the microbial composition information of the environmental area to be put in according to the microbial environmental adaptability prediction data, the correlation between microorganisms and environmental parameters can be revealed. The key of this step is to analyze the correlation between microorganisms and environmental parameters by analyzing the environmental suitability of microorganisms under specific environmental parameter conditions. In this way, the response mechanism of microorganisms to environmental changes can be deeply understood, and a scientific basis is provided for the subsequent association matrix construction process. Then, by combining the correlation relationship data between the environmental area microorganisms and environmental parameters to be put in combination with the correlation relationship data between the environmental area microorganisms and environmental parameters to be put in, the correlation coefficient statistical calculation is performed to obtain the correlation coefficient between microorganisms and environmental parameters, so that the degree of interaction between microorganisms and environmental parameters can be quantified, and the correlation and influencing factors between them can be further understood. Next, the correlation coefficients between the microorganisms and environmental parameters in the environmental area to be released are processed in the form of microorganisms as horizontal columns and environmental parameters as vertical columns to construct a correlation matrix between microorganisms and environmental parameters. This can clearly show the correlation between microorganisms and environmental parameters. The key to this step is that it can intuitively display the correlation between microorganisms and environmental parameters, providing visualization support for further data analysis and community composition simulation. Finally, by performing microbial community association simulation based on the environmental parameter data of the environmental area to be released and the correlation matrix between the microorganisms and environmental parameters in the area to be released, the microbial composition community in the environmental area to be released under the corresponding environmental parameter conditions can be simulated. The key to this step is to simulate the original microbial community composition in the environmental area to be released under specific environmental parameter conditions by combining the correlation between microorganisms and environmental parameters. This can predict the structure and dynamic changes of microbial communities under different environmental conditions, thereby providing basic data support for subsequent genome sequencing and microbial community recommendation release processing.

[0083] Preferably, step S22 includes the following steps:

[0084] Step S221: performing linear correlation evaluation analysis on the microbial composition information data of the environment area to be deployed according to the environmental adaptability prediction data of the microorganisms in the environment area to be deployed under the corresponding environmental parameter conditions, and obtaining linear correlation relationship data between the microorganisms in the environment area to be deployed and the environmental parameters;

[0085] The embodiment of the present invention analyzes the corresponding microorganisms in the microbial composition information data of the environment area to be released by combining the predicted data of the environmental adaptability of the microorganisms in the environment area to be released under the corresponding environmental parameter conditions (including the growth rate, metabolic activity, etc. of the microorganisms under the corresponding environmental parameter conditions) using a linear analysis model (such as linear regression, Pearson correlation analysis, etc.), so as to evaluate and analyze the direct linear correlation relationship between the corresponding microbial composition and the environmental parameters, and finally obtain the linear correlation relationship data between the microorganisms in the environment area to be released and the environmental parameters.

[0086] Step S222: performing nonlinear correlation evaluation analysis on the microbial composition information data of the environment area to be deployed according to the environmental adaptability prediction data of the microorganisms in the environment area to be deployed under the corresponding environmental parameter conditions, and obtaining nonlinear correlation relationship data between the microorganisms in the environment area to be deployed and the environmental parameters;

[0087] The embodiment of the present invention analyzes the corresponding microorganisms in the microbial composition information data of the environment area to be released by combining the predicted data of the environmental adaptability of microorganisms in the environment area to be released under the corresponding environmental parameter conditions (including the growth rate, metabolic activity, etc. of the microorganisms under the corresponding environmental parameter conditions) using a nonlinear analysis model (such as polynomial regression, logistic regression, Spearman rank correlation analysis, Kendall rank correlation analysis, etc.), so as to evaluate and analyze the complex and diverse nonlinear correlation relationship between the microbial composition and the environmental parameters, and finally obtain the nonlinear correlation relationship data between the microorganisms in the environment area to be released and the environmental parameters.

[0088] Step S223: merging the linear correlation data and the nonlinear correlation data between the microorganisms in the environmental area to be released and the environmental parameters to obtain the correlation data between the microorganisms in the environmental area to be released and the environmental parameters.

[0089] The embodiment of the present invention combines the linear correlation data and nonlinear correlation data between the microorganisms in the environmental area to be released and the environmental parameters by using a weighted average method, so as to comprehensively consider the linear and nonlinear relationships between the microorganisms and the environmental parameters, and better understand the overall correlation response characteristics of the microbial community to different environmental parameter conditions, and finally obtain the correlation data between the microorganisms in the environmental area to be released and the environmental parameters.

[0090] The present invention firstly carries out linear correlation evaluation analysis on the microorganism composition information data of the environment area to be put in according to the prediction data of the environmental adaptability of the microorganisms in the environment area to be put in under the corresponding environmental parameter conditions, aiming to deeply understand the direct linear correlation relationship that may exist between microorganisms and environmental parameters. Through this analysis method, the linear trend and correlation that may exist between microorganisms and environmental parameters can be identified, and the linear correlation response of microbial communities to specific environmental conditions can also be understood, so as to provide data support for subsequent processing processes. Then, nonlinear correlation evaluation analysis is carried out on the microorganism composition information data of the environment area to be put in according to the prediction data of the environmental adaptability of the microorganisms in the environment area to be put in under the corresponding environmental parameter conditions, aiming to explore the more complex and diversified correlation relationship between microorganisms and environmental parameters. The acquisition of nonlinear correlation relationship data is crucial for understanding the more detailed and comprehensive interaction between microorganisms and the environment. Through nonlinear correlation evaluation analysis, the nonlinear response of microbial communities to environmental changes can be revealed, and the complex dynamic change law of microbial communities under different environmental conditions can be captured, so as to provide further basic data guarantee for subsequent processing processes. Finally, by merging the linear correlation data and the nonlinear correlation data, we can obtain the overall correlation data between the microorganisms and environmental parameters in the environmental area to be released. This comprehensive correlation data will contain more comprehensive and comprehensive information, and can simultaneously consider the linear and nonlinear relationships between microorganisms and environmental parameters. Through such data merging, we can better understand the overall response characteristics of the microbial community to different environmental conditions, thereby providing a more comprehensive and accurate data basis for the subsequent correlation coefficient calculation process.

[0091] Preferably, step S25 comprises the following steps:

[0092] Step S251: Performing environmental condition simulation and limitation processing on the environmental parameter data of the environment area to be placed, and obtaining simulated and limited environmental parameter conditions of the environment area to be placed;

[0093] The embodiment of the present invention first collects environmental parameter data of the environmental area to be deployed, including temperature, humidity, soil pH value, light intensity, etc., and then simulates and creates corresponding multiple environmental parameter conditions according to actual conditions, such as inconsistent temperature ranges, inconsistent humidity ranges, inconsistent soil pH value ranges, etc., to simulate the specific environmental parameter conditions of the environment to be deployed, and finally obtains the simulated limited environmental parameter conditions of the environmental area to be deployed.

[0094] Step S252: performing conditional screening on the correlation matrix between microorganisms in the area to be released and environmental parameters according to the limited environmental parameter conditions of the simulated environmental area to be released, so as to obtain a correlation matrix of microorganisms in the area to be released under the limited environmental parameter conditions;

[0095] The embodiment of the present invention screens the correlation matrix between the microorganisms in the area to be released and the environmental parameters according to the simulated limited environmental parameter conditions of the environmental area to be released generated by simulation, so as to screen out the correlation coefficient relationship matrix between the microorganisms and the environmental parameters under the corresponding limited environmental parameter conditions, and finally obtain the microorganism correlation sub-matrix of the area to be released under the limited environmental parameter conditions.

[0096] Step S253: comparing and judging the microbial association sub-matrix of the area to be deployed under the limited environmental parameter conditions according to the preset association coefficient threshold value; when the first association coefficient in the microbial association sub-matrix of the area to be deployed is greater than or equal to the preset association coefficient threshold value, the microorganisms in the microbial association sub-matrix of the area to be deployed corresponding to the association coefficient are screened out; when the first association coefficient in the microbial association sub-matrix of the area to be deployed is less than the preset association coefficient threshold value, comparing and judging the next association coefficient in the microbial association sub-matrix of the area to be deployed, and so on, so as to obtain the microbial composition set of the area to be deployed under the limited environmental parameter conditions;

[0097] In the embodiment of the present invention, the correlation coefficients in the microorganism correlation sub-matrix of the area to be deployed under the limited environmental parameter conditions are compared and judged according to a preset correlation coefficient threshold value. If the first correlation coefficient in the microorganism correlation sub-matrix of the area to be deployed is greater than or equal to the preset correlation coefficient threshold value, it means that the microorganism corresponding to the correlation coefficient may prefer the corresponding limited environmental parameter conditions, and the microorganisms in the microorganism correlation sub-matrix of the area to be deployed corresponding to the correlation coefficient are screened out; and if the first correlation coefficient in the microorganism correlation sub-matrix of the area to be deployed is less than the preset correlation coefficient threshold value, it means that the microorganism corresponding to the correlation coefficient does not prefer the corresponding limited environmental parameter conditions and the effect of the microorganism will be affected by the corresponding limited environmental parameter conditions, then the microorganism corresponding to the correlation coefficient is discarded, and the next correlation coefficient in the microorganism correlation sub-matrix of the area to be deployed is compared and judged, and so on, until all the correlation coefficients in the correlation sub-matrix are traversed, and finally the microorganism composition set of the area to be deployed under the limited environmental parameter conditions is screened out.

[0098] Step S254: Process the microbial community composition of the microbial composition set in the area to be released under the limited environmental parameter conditions to obtain the simulated microbial community composition of each environmental area to be released.

[0099] In the embodiment of the present invention, a community composition method is used to process the corresponding microorganisms in the microbial composition set of the area to be released screened under various limited environmental parameter conditions to determine the microbial composition under the corresponding limited environmental parameter conditions, and finally obtain the simulated microbial composition community of each environmental area to be released.

[0100] The present invention first simulates and limits the environmental parameters of the environmental area to be put into use, and can simulate the environmental parameters under specific conditions. The purpose of this simulation and limitation is to create multiple specific environmental parameter conditions so as to better understand the correlation between microorganisms and environmental parameters. By simulating and limiting the environmental parameters, microbial association analysis can be performed under specific environmental parameter control conditions, so as to more accurately understand the changes of microbial communities under different environmental conditions. Secondly, the association matrix between the microorganisms and environmental parameters in the area to be put into use is subjected to a limited condition screening process according to the simulated and limited environmental parameter conditions of the environmental area to be put into use, so as to obtain the microbial association sub-matrix of the area to be put into use under specific limited environmental parameter conditions. Through this screening process, the correlation between microorganisms and environmental parameters under specific environmental conditions can be focused on, so as to more accurately study the response of the microbial community to environmental conditions. Then, by comparing and judging the microbial association sub-matrix of the area to be put into use under limited environmental parameter conditions according to a preset correlation coefficient threshold, the microbial composition highly correlated with environmental parameters under specific environmental conditions can be screened out by gradually comparing the correlation coefficients. This method can help determine which microorganisms are closely related to specific environmental conditions, so as to better understand the composition of the microbial community and its adaptability to the environment. Finally, by processing the microbial community composition of the microbial composition set in the area to be released under limited environmental parameters, the composition of the microbial community under specific environmental conditions can be obtained, which is of great significance for predicting and simulating the dynamic changes of microbial communities under specific environmental conditions, thereby providing strong support for subsequent genome sequencing and microbial community recommendation release treatment process.

[0101] Preferably, step S3 comprises the following steps:

[0102] Step S31: performing gene sequencing on the simulated microbial communities in each environmental area to be released, to obtain genome sequence data of the simulated microbial communities in each environmental area to be released;

[0103] The embodiment of the present invention uses gene sequencing technology (such as Illumina sequencing, etc.) to process the simulated microbial communities in each environmental area to be released, so as to deeply understand the genetic information of the simulated microbial communities in the corresponding environmental area to be released, and comprehensively understand the genetic composition of the microbial communities in the environmental area to be released, and finally obtain the genome sequence data of the simulated microbial communities in each environmental area to be released.

[0104] Step S32: performing gene sequence quality control on the genome sequence data of the microbial simulation communities in each environmental area to be released, to obtain genome quality control sequence data;

[0105] The embodiment of the present invention processes the genome sequence data of each microbial simulation community in the environmental area to be released obtained through sequencing by using corresponding computer quality control processing technology (including removal of low-quality sequences, removal of linker sequences, removal of PCR duplicate sequences, etc.) to control and adjust the corresponding genome sequence data, eliminate potential errors and noise, and improve the credibility and accuracy of the genome sequence data of each microbial community, and finally obtain genome quality control sequence data.

[0106] Step S33: performing sequence comparison analysis on the genome quality control sequence data according to a preset genome sequence database to obtain homologous genome sequence data;

[0107] The embodiment of the present invention uses a pre-set and known genome sequence database (such as NCBI, KEGG, MetaCyc, etc.) to compare the genome quality control sequence data obtained after quality control processing to find and determine its homologous genes, so as to deeply understand the genetic information and evolutionary relationships of the microbial communities in the environment to be released, and finally obtain homologous genome sequence data.

[0108] Step S34: annotating homologous gene functions on homologous genome sequence data to obtain homologous gene sequence function annotation data; performing gene difference impact analysis on homologous gene sequence function annotation data to obtain gene sequence function difference impact relationship data;

[0109] The embodiment of the present invention predicts and annotates the gene functions of homologous genome sequence data by using genome annotation tools and databases (such as BLAST, GO, etc.) to predict and annotate the functional characteristics of homologous genes, thereby obtaining homologous gene sequence function annotation data. Then, the annotated homologous gene sequence function annotation data is analyzed by using a differential impact analysis method to analyze and compare the functional differences and impact relationships between different homologous gene sequences, and reveal the ecological functions and mutual impact relationships of the corresponding microbial communities in the environmental area to be released, and finally obtain the gene sequence function difference impact relationship data.

[0110] Step S35: Based on the gene sequence function difference influence relationship data, the gene function evaluation and analysis are performed on the genome sequence data of the microbial simulation community in each environmental area to be released, so as to obtain the potential influencing factors of the gene function of the microbial simulation community in each environmental area to be released.

[0111] The embodiment of the present invention uses an impact assessment analysis method to analyze the genome sequence data of the microbial simulation community in each environmental area to be released by combining the gene sequence function difference influence relationship data obtained by analysis, so as to evaluate and analyze the potential influencing factors of the microbial community in the environment to be released, such as the abundance and expression level of specific microbial genes and the influence correlation relationship between the microbial community and environmental factors, and finally obtain the potential influencing factors of the gene function of the microbial simulation community in each environmental area to be released.

[0112] The present invention firstly performs gene sequencing on the microorganism simulation composition community in each environmental area to be put into use, and can obtain their genome sequence data. The key of this step is that it can provide a comprehensive understanding of the gene composition of the microbial community in the environment to be put into use, which lays the foundation for subsequent analysis and research. The application of gene sequencing technology enables a deep understanding of the genetic information of the microbial community, so as to better understand its function and role in the environment to be put into use. Secondly, by performing gene sequence quality control on the genome sequence data of the microbial simulation composition community in each environmental area to be put into use, the gene sequence quality control process is an important step to ensure the accuracy and reliability of the subsequent analysis results. By controlling and adjusting the quality of the sequence data, potential errors and noise can be eliminated, thereby improving the credibility and accuracy of the genome sequence data of each microbial composition community. Then, by performing sequence comparison analysis on the genome quality control sequence data according to the preset genome sequence database, the main purpose of this step is to compare the genome sequence of the microorganism in the environment to be put into use with the known genome database to determine its homologous genes. Through the identification of homologous genes, the genetic information and evolutionary relationship of the microorganism in the environment to be put into use can be more deeply understood. Next, homologous gene functions are annotated for homologous genome sequence data, and gene difference impact analysis is performed on homologous gene sequence function annotation data obtained after functional annotation. The purpose of this series of analyses is to understand the functional characteristics of microbial genes and the differences in gene functions between different microorganisms, thereby revealing the ecological functions and interactions of microbial communities in the environment. Finally, gene function evaluation and analysis is performed on the genome sequence data of microbial simulation communities in each environmental area to be released based on the gene sequence function difference impact relationship data. The key to this step is to use the gene sequence function difference impact relationship of each microbial community to evaluate the potential influencing factors of the microbial community in the environment to be released, thereby providing a scientific basis and decision-making support for the subsequent microbial advantage recommendation release process.

[0113] Preferably, step S4 comprises the following steps:

[0114] Step S41: performing function prediction and recommendation calculations on the microbial simulation community components of each environmental area to be released based on the potential influencing factors of gene function, and obtaining the gene function prediction and release recommendation index of the microbial simulation community components of each environmental area to be released;

[0115] In the embodiment of the present invention, a bioinformatics analysis method (such as PICRUSt technology) is used in combination with potential influencing factors of gene function to predict and analyze the gene function of the microbial simulation community in each environmental area to be released, so as to deeply study the functional composition of the microbial genome and understand the possible role of different microbial simulation communities in the environmental area to be released, and the gene function composition prediction results of each microbial simulation community are analyzed by using metabolic pathway analysis tools and databases (such as KEGG, etc.) and ecological analysis methods, so as to evaluate and analyze the activity of the metabolic pathway of the microbial simulation community under different environmental parameter conditions and the performance of ecological function correlation. Then, the corresponding evaluation scores of the metabolic pathway activity evaluation results and the ecological function correlation evaluation results are statistically calculated by using mathematical statistical analysis methods, and the corresponding evaluation scores are weighted and integrated to comprehensively consider the metabolic activity and ecological function of the microorganisms to quantitatively calculate the corresponding release recommendation index of each microbial simulation community, and determine its adaptability and recommendation degree under different environmental parameter conditions, and finally obtain the gene function prediction release recommendation index of the microbial simulation community in each environmental area to be released.

[0116] Step S42: performing a community advantage release selection on the microbial simulation composition community in each environmental area to be released according to the gene function prediction release recommendation index, so as to obtain a microbial community advantage release selection recommendation result;

[0117] The embodiment of the present invention compares and determines the gene function prediction release recommendation index of each microbial simulation community in the environmental area to be released, so as to determine which microbial simulation communities are more suitable for the specific environmental parameter conditions according to the corresponding gene function prediction release recommendation index under the specific environmental parameter conditions, thereby recommending the microbial simulation community in the environmental area to be released corresponding to the highest gene function prediction release recommendation index as the community release selection for the specific environmental parameter conditions, and finally obtaining the recommendation result of the microbial community advantage release selection.

[0118] Step S43: generating a microbial community placement plan for the environmental area to be placed based on the microbial community advantage placement selection recommendation result to perform the corresponding microbial community placement work.

[0119] The embodiment of the present invention determines the most advantageous microbial community selection result under specific environmental parameter conditions in the environmental area to be released according to the selected microbial community advantage release selection recommendation result, and at the same time comprehensively considers the characteristics of the release environmental parameter conditions, the characteristics of the microbial simulation community composition and the release purpose to formulate a suitable microbial community release plan, thereby generating a microbial community release plan for the environmental area to be released, and finally executing the corresponding microbial community release work, including effectively arranging the time, place and quantity of microbial release.

[0120] The present invention firstly performs function prediction and recommendation calculation on each microorganism simulation composition community in the environmental area to be put in by combining the potential influencing factors of gene function, and can deeply analyze the gene functions of each microorganism simulation composition community in the environmental area to be put in, and recommend the most suitable microorganism release strategy based on these functional characteristics. Through this calculation method, the role and effect of the microorganism community in the environment can be accurately predicted for different environmental conditions and needs, and scientific basis and guidance are provided for subsequent microorganism release work. Then, the community advantage release selection is performed on each microorganism simulation composition community in the environmental area to be put in by predicting the release recommendation index according to the gene function. The key of this step is to determine which microorganism communities have more advantageous release effects under specific environmental conditions according to the release recommendation index, thereby optimizing the microorganism release scheme and improving the release effect and effectiveness. By selecting a microorganism community with a higher release recommendation index, the role of microorganisms in environmental restoration, biological control, etc. in the environmental area to be put in can be maximized, thereby achieving better ecological benefits in the environmental area to be put in. Finally, a release plan for the microbial community in the environmental area to be released is generated based on the recommended results of the dominant release selection of the microbial community, so as to carry out the corresponding microbial community release work. This step is the key link to transform the analysis and recommendations of the first two steps into actual operations. By formulating a release plan based on the results of the dominant release selection, the time, place and quantity of microbial release can be effectively arranged to ensure the maximization of the release effect, and verify the previous predictions and plans in practice. Such a systematic process can effectively improve the success rate and effect of microbial release, thereby providing a feasible solution for environmental governance and ecological restoration in the environmental area to be released.

[0121] Preferably, step S41 includes the following steps:

[0122] Step S411: performing gene function prediction analysis on the simulated microbial communities in each environmental area to be released based on the potential influencing factors of gene function, and obtaining the predicted results of gene function composition of the simulated microbial communities in each environmental area to be released;

[0123] The embodiment of the present invention uses bioinformatics analysis methods (such as PICRUSt technology) in combination with potential influencing factors of gene function to predict and analyze the gene functions of the simulated microbial communities in each environmental area to be released, so as to deeply study the functional composition of the microbial genome and understand the possible roles of different microbial communities in the environmental area to be released, and finally obtain the prediction results of the gene function composition of the simulated microbial communities in each environmental area to be released.

[0124] Step S412: performing metabolic pathway activity evaluation analysis on the gene function composition prediction results of the microbial simulation community in each environmental area to be released, and obtaining metabolic pathway activity evaluation results of the microbial simulation community in each environmental area to be released;

[0125] The embodiment of the present invention uses metabolic pathway analysis tools and databases (such as KEGG, etc.) to analyze the predicted results of gene function composition of microbial simulation communities in each environmental area to be released, so as to evaluate the activity of metabolic pathways of microbial simulation communities under different environmental parameter conditions, and determine which microbial simulation communities may be more active and have competitive advantages under specific environmental conditions, and finally obtain the metabolic pathway activity evaluation results of microbial simulation communities in each environmental area to be released.

[0126] Step S413: performing ecological function correlation evaluation and analysis on the gene function composition prediction results of the microbial simulation community in each environmental area to be released, and obtaining ecological function correlation evaluation results of the microbial simulation community in each environmental area to be released;

[0127] The embodiment of the present invention uses an ecological analysis method to analyze the predicted results of the gene function composition of the microbial simulation communities in each environmental area to be released, so as to consider the ecological function performance of each microbial simulation community under different environmental parameter conditions, and evaluate and analyze the ecological function correlation of each microbial simulation community, while understanding their roles and relationships in the ecosystem, and finally obtain the ecological function correlation evaluation results of the microbial simulation communities in each environmental area to be released.

[0128] Step S414: Based on the metabolic pathway activity evaluation results and the ecological function correlation evaluation results, the release recommendation index of the microbial simulation community in each environmental area to be released is calculated to obtain the gene function prediction release recommendation index of the microbial simulation community in each environmental area to be released.

[0129] The embodiment of the present invention uses a release recommendation index statistical calculation method in combination with the metabolic pathway activity evaluation results and the ecological function correlation evaluation results (i.e., by statistically calculating the corresponding evaluation scores of the metabolic pathway activity evaluation results and the ecological function correlation evaluation results, and weighting and integrating the corresponding evaluation scores) to perform statistical calculations on the microbial simulation community components in each environmental area to be released, so as to quantitatively calculate the corresponding release recommendation index of each microbial simulation community component by comprehensively considering the metabolic activity and ecological function of the microorganisms, and determine its adaptability and recommendation degree under different environmental parameter conditions, and finally obtain the gene function predicted release recommendation index of the microbial simulation community component in each environmental area to be released.

[0130] The present invention firstly predicts and analyzes the gene function of the simulated microbial communities in the environment to be released by combining the potential influencing factors of gene function. This can deeply study the functional composition of the microbial genome and understand the possible role of different microorganisms in the environment to be released, thereby providing an important reference for the formulation of subsequent microbial release plans. This analysis process can help determine which microbial communities may have advantages under specific environmental conditions and how their functional characteristics affect the stability and function of the ecosystem. Secondly, by evaluating and analyzing the metabolic pathway activity of the predicted results of the gene function composition of the simulated microbial communities in each area of ​​the environment to be released, it can help understand the metabolic activity of the microbial communities under different environmental parameter conditions, thereby predicting their adaptability and degree of influence on the environment. This evaluation process helps to determine which microbial communities may be more active and competitive under specific environmental conditions, thereby providing guidance for the selection of microbial release. Then, by conducting ecological function-related evaluation and analysis on the predicted results of gene function composition of microbial simulation communities in each environmental area to be released, the ecological function relevance of each microbial community can be evaluated and analyzed, and their roles and relationships in the ecosystem can be understood, so as to better predict their impact on the structure and function of the ecosystem. This evaluation process helps to determine which microbial communities are important for the ecological functions of the environment, as well as their status and role in the ecosystem. Finally, by combining the results of metabolic pathway activity evaluation and ecological function relevance evaluation, the release recommendation index of the microbial simulation community in each environmental area to be released is calculated. In this way, the metabolic activity and ecological function of the microorganisms can be comprehensively considered, and the corresponding release recommendation index can be determined for each microbial community, thereby guiding the optimization and implementation of the microbial release plan. This calculation process can provide a scientific basis for microbial release, ensure the maximum release effect, and maximize the role of microbial communities in environmental restoration and ecological protection.

[0131] Preferably, the present invention also provides a microbial community placement selection system for executing the microbial community placement selection method as described above, the microbial community placement selection system comprising:

[0132] The data analysis module for the environment area to be placed is used to collect and process environmental parameters of the environment area to be placed, and obtain environmental parameter data of the environment area to be placed; perform statistical analysis on the microbial composition of the environment area to be placed, and obtain information data on the microbial composition of the environment area to be placed;

[0133] The microbial community association processing module of the area to be released is used to perform microbial environmental association analysis on the microbial composition information data of the area to be released based on the environmental parameter data of the area to be released, so as to obtain the association matrix between the microorganisms and the environmental parameters of the area to be released; the microbial community association simulation composition is performed according to the environmental parameter data of the area to be released and the association matrix between the microorganisms and the environmental parameters of the area to be released, so as to obtain the microbial simulation composition community of each area to be released;

[0134] The microbial simulation community gene sequencing evaluation module is used to perform gene sequencing processing on the microbial simulation community components in each environmental area to be released, and obtain the genome sequence data of the microbial simulation community components in each environmental area to be released; the gene function evaluation and analysis is performed on the genome sequence data of the microbial simulation community components in each environmental area to be released, so as to obtain the potential influencing factors of the gene function of the microbial simulation community components in each environmental area to be released;

[0135] The microbial community gene function advantage release module is used to select the community advantage release of microbial simulated communities in each environmental area to be released based on the potential influencing factors of gene function, so as to obtain the recommended results of the microbial community advantage release selection; according to the recommended results of the microbial community advantage release selection, a microbial community release plan for the environmental area to be released is generated to carry out the corresponding microbial community release work.

[0136] In summary, the present invention provides a microbial community placement selection system, which consists of a data analysis module for the environmental area to be placed, a microbial community association processing module for the area to be placed, a microbial simulation community gene sequencing evaluation module, and a microbial community gene function advantage placement module. It can realize any microbial community placement selection method described in the present invention, and is used to combine the operations between computer programs running on each module to realize any microbial community placement selection method. The internal structures of the system cooperate with each other, which can greatly reduce duplication of work and manpower investment, and can quickly and effectively provide a more accurate and efficient microbial community placement selection process, thereby simplifying the operation process of the microbial community placement selection system.

[0137] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0138] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for selecting a microbial community, characterized in that: The following steps are involved: Step S1: Collect and process environmental parameters of the environment area to be placed, and obtain environmental parameter data of the environment area to be placed; perform statistical analysis on the microbial composition of the environment area to be placed, and obtain information data on the microbial composition of the environment area to be placed; Step S2: Based on the environmental parameter data of the environmental area to be deployed, the microbial composition information data of the environmental area to be deployed is subjected to microbial environmental association analysis to obtain the association matrix between the microorganisms and the environmental parameters of the area to be deployed; according to the environmental parameter data of the environmental area to be deployed and the association matrix between the microorganisms and the environmental parameters of the area to be deployed, the microbial community association simulation composition is performed to obtain the microbial simulation composition community of each environmental area to be deployed; wherein, step S2 includes the following steps: Step S21: performing microbial environmental adaptability prediction analysis on the microbial composition information data of the environmental area to be deployed based on the environmental parameter data of the environmental area to be deployed, and obtaining microbial environmental adaptability prediction data of the environmental area to be deployed under the corresponding environmental parameter conditions; Step S22: performing correlation evaluation and analysis on the microbial composition information data of the environment area to be deployed according to the prediction data of the environmental adaptability of the microorganisms in the environment area to be deployed under the corresponding environmental parameter conditions, and obtaining the correlation relationship data between the microorganisms in the environment area to be deployed and the environmental parameters; wherein step S22 includes the following steps: Step S221: performing linear correlation evaluation analysis on the microbial composition information data of the environment area to be deployed according to the environmental adaptability prediction data of the microorganisms in the environment area to be deployed under the corresponding environmental parameter conditions, and obtaining linear correlation relationship data between the microorganisms in the environment area to be deployed and the environmental parameters; Step S222: performing nonlinear correlation evaluation analysis on the microbial composition information data of the environment area to be deployed according to the environmental adaptability prediction data of the microorganisms in the environment area to be deployed under the corresponding environmental parameter conditions, and obtaining nonlinear correlation relationship data between the microorganisms in the environment area to be deployed and the environmental parameters; Step S223: merging the linear correlation data and the nonlinear correlation data between the microorganisms in the environmental area to be released and the environmental parameters to obtain the correlation data between the microorganisms in the environmental area to be released and the environmental parameters; Step S23: Based on the correlation relationship data between the microorganisms in the environment area to be placed and the environmental parameters, the correlation coefficient is statistically calculated for the environmental parameter data of the environment area to be placed and the microorganism composition information data of the environment area to be placed, so as to obtain the correlation coefficient between the microorganisms in the environment area to be placed and the environmental parameters; Step S24: constructing a correlation matrix of correlation coefficients between microorganisms and environmental parameters in the area to be placed in the environment in which the microorganisms are arranged in horizontal columns and the environmental parameters are arranged in vertical columns, so as to obtain a correlation matrix between the microorganisms and environmental parameters in the area to be placed in the environment; Step S25: performing microbial community association simulation composition according to the environmental parameter data of the environmental area to be released and the association matrix between the microorganisms and the environmental parameters of the area to be released, and obtaining the microbial simulation composition community of each environmental area to be released; wherein step S25 includes the following steps: Step S251: Performing environmental condition simulation and limitation processing on the environmental parameter data of the environment area to be placed, and obtaining simulated and limited environmental parameter conditions of the environment area to be placed; Step S252: performing conditional screening on the correlation matrix between microorganisms in the area to be released and environmental parameters according to the limited environmental parameter conditions of the simulated environmental area to be released, so as to obtain a correlation matrix of microorganisms in the area to be released under the limited environmental parameter conditions; Step S253: comparing and judging the microbial association sub-matrix of the area to be deployed under the limited environmental parameter conditions according to the preset association coefficient threshold value; when the first association coefficient in the microbial association sub-matrix of the area to be deployed is greater than or equal to the preset association coefficient threshold value, the microorganisms in the microbial association sub-matrix of the area to be deployed corresponding to the association coefficient are screened out; when the first association coefficient in the microbial association sub-matrix of the area to be deployed is less than the preset association coefficient threshold value, comparing and judging the next association coefficient in the microbial association sub-matrix of the area to be deployed, and so on, so as to obtain the microbial composition set of the area to be deployed under the limited environmental parameter conditions; Step S254: performing microbial community composition processing on the microbial composition set of the area to be released under the limited environmental parameter conditions to obtain the simulated microbial composition community of each environmental area to be released; Step S3: performing gene sequencing processing on the microbial simulated community in each environmental area to be released, and obtaining the genome sequence data of the microbial simulated community in each environmental area to be released; performing gene function evaluation and analysis on the genome sequence data of the microbial simulated community in each environmental area to be released, and obtaining the potential influencing factors of the gene function of the microbial simulated community in each environmental area to be released; Step S4: Based on the potential influencing factors of gene function, the microbial simulated community composition in each environmental area to be released is selected for community advantage release to obtain the recommended results of the microbial community advantage release selection; according to the recommended results of the microbial community advantage release selection, a microbial community release plan for the environmental area to be released is generated to perform the corresponding microbial community release work.

2. The method for selecting a microbial community according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: collecting and processing environmental parameters of the environment area to be placed, and obtaining environmental parameter data of the environment area to be placed; Step S12: monitoring and processing the microorganism species in the environmental area to be placed, and obtaining information data on the microorganism species in the environmental area to be placed; Step S13: monitoring the number of microorganisms in the environmental area to be placed, and obtaining information data on the number of microorganisms in the environmental area to be placed; Step S14: Based on the microbial species information data and the microbial quantity information data of the environmental area to be placed, a statistical analysis of the microbial composition of the environmental area to be placed is performed to obtain the microbial composition information data of the environmental area to be placed.

3. The method for selecting a microbial community according to claim 2, characterized in that: Step S14 includes the following steps: Step S141: performing distribution statistics analysis on the microorganism species information data and the microorganism quantity information data of the environmental area to be placed, and obtaining the microorganism species quantity distribution status data of the environmental area to be placed; Step S142: performing a microbial abundance conversion analysis on the environment area to be deployed based on the data on the number and distribution of microbial species in the environment area to be deployed, and obtaining a relative abundance of microorganisms in the environment area to be deployed; Step S143: performing microbial diversity assessment and analysis on the environmental area to be deployed according to the relative abundance of microorganisms in the environmental area to be deployed, and obtaining microbial diversity level data of the environmental area to be deployed; Step S144: performing microbial uniformity measurement calculation on the data of the number of microbial species and distribution in the environment area to be placed, so as to obtain a microbial uniformity measurement index for the environment area to be placed; performing microbial difference analysis on the microbial diversity level data in the environment area to be placed based on the microbial uniformity measurement index for the environment area to be placed, so as to obtain microbial distribution difference level data for the environment area to be placed; Step S145: Performing a statistical analysis of the microbial composition of the environment to be deployed based on the microbial distribution difference level data of the environment to be deployed, and obtaining microbial composition information data of the environment to be deployed.

4. The method for selecting a microbial community according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: performing gene sequencing on the simulated microbial communities in each environmental area to be released, to obtain genome sequence data of the simulated microbial communities in each environmental area to be released; Step S32: performing gene sequence quality control on the genome sequence data of the microbial simulation communities in each environmental area to be released, to obtain genome quality control sequence data; Step S33: performing sequence comparison analysis on the genome quality control sequence data according to a preset genome sequence database to obtain homologous genome sequence data; Step S34: annotating homologous gene functions on homologous genome sequence data to obtain homologous gene sequence function annotation data; performing gene difference impact analysis on homologous gene sequence function annotation data to obtain gene sequence function difference impact relationship data; Step S35: Based on the gene sequence function difference influence relationship data, the gene function evaluation and analysis are performed on the genome sequence data of the microbial simulation community in each environmental area to be released, so as to obtain the potential influencing factors of the gene function of the microbial simulation community in each environmental area to be released.

5. The method for selecting microbial communities according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing function prediction and recommendation calculations on the microbial simulation community components of each environmental area to be released based on the potential influencing factors of gene function, and obtaining the gene function prediction and release recommendation index of the microbial simulation community components of each environmental area to be released; Step S42: performing a community advantage release selection on the microbial simulation composition community in each environmental area to be released according to the gene function prediction release recommendation index, so as to obtain a microbial community advantage release selection recommendation result; Step S43: generating a microbial community placement plan for the environmental area to be placed based on the microbial community advantage placement selection recommendation result to perform the corresponding microbial community placement work.

6. The method for selecting microbial communities according to claim 5, characterized in that: Step S41 includes the following steps: Step S411: performing gene function prediction analysis on the simulated microbial communities in each environmental area to be released based on the potential influencing factors of gene function, and obtaining the gene function composition prediction results of the simulated microbial communities in each environmental area to be released; Step S412: performing metabolic pathway activity evaluation analysis on the gene function composition prediction results of the microbial simulation community in each environmental area to be released, and obtaining metabolic pathway activity evaluation results of the microbial simulation community in each environmental area to be released; Step S413: performing ecological function correlation evaluation and analysis on the gene function composition prediction results of the microbial simulation community in each environmental area to be released, and obtaining ecological function correlation evaluation results of the microbial simulation community in each environmental area to be released; Step S414: Based on the metabolic pathway activity evaluation results and the ecological function correlation evaluation results, the release recommendation index of the microbial simulation community in each environmental area to be released is calculated to obtain the gene function prediction release recommendation index of the microbial simulation community in each environmental area to be released.

7. A microbial community placement and selection system, characterized in that: Used to implement the microbial community selection method as described in claim 1.

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