Reclamation land soilless culture and green manure intercropping culture system

Abstract

The invention relates to the technical field of agricultural engineering, in particular to a reclamation land soilless culture and green manure intercropping culture system which comprises a reclamation land matrix preparation module, a soilless culture module, a green manure planting module and a microorganism bionic regulation and control module. The reclamation land matrix preparation module is used for preparing a matrix for soilless culture of a reclamation land; the soilless culture module comprises a culture bed, a nutrient solution supply unit and an environment control unit; the green manure planting module is provided with a special area for planting green manure crops, and the improvement of a soil structure and the optimization of nutrient circulation are realized by alternately or simultaneously planting the green manure and the crops; and the microbial bionic regulation and control module monitors and regulates and controls a microbial community structure in the matrix of the reclamation land in real time. According to the invention, not only are the ecological balance and stability of microbial communities improved, but also the nutrient absorption and disease resistance of crops are enhanced, and the growth conditions and yield of the crops are optimized.

Description

Technical Field

[0001] The invention relates to the technical field of agricultural engineering, and in particular to a reclaimed land soilless cultivation and green manure intercropping cultivation system. Background Art

[0002] Reclaimed land usually refers to degraded or abandoned land whose production capacity has been restored through artificial measures. This type of land often faces problems such as soil poverty, structural damage and nutrient loss. Agricultural planting on reclaimed land, especially soilless cultivation, can avoid soil problems directly affecting crop growth and achieve healthy growth and high yield of crops through scientific management strategies. At the same time, green manure intercropping, as a sustainable agricultural practice, can not only improve soil quality through biological nitrogen fixation and increase of organic matter, but also reduce dependence on chemical fertilizers and enhance the ecological benefits of farmland.

[0003] However, the existing soilless cultivation and green manure intercropping technologies in reclaimed land have many shortcomings. First, the traditional substrate preparation and management methods are relatively extensive, lacking precise control over the microbial community in the substrate, resulting in poor soil ecological functions and affecting the growth of crops. Secondly, in the soilless cultivation system, nutrient solution supply and environmental control often rely on fixed parameter settings, which are difficult to adapt to the special environmental changes in reclaimed land, resulting in an unstable crop growth environment. Furthermore, the existing green manure intercropping strategies often only focus on the simple planting and tillage of green manure, lack in-depth research and application of the dynamic ecological relationship between green manure and crops, and fail to give full play to the ecological function of green manure. Overall, the application of existing technologies in the reclaimed land environment has not yet achieved refined control and dynamic optimization of microbial communities, nutrient solutions and crop growth environments.

[0004] The purpose of the present invention is to provide a soilless cultivation and green manure intercropping cultivation system for reclaimed land, so as to improve the soil fertility and crop yield of the reclaimed land and ensure the efficient operation and sustainability of the system under complex environmental conditions. Summary of the invention

[0005] The invention provides a reclaimed land soilless culture and green manure intercropping culture system.

[0006] A reclaimed land soilless cultivation and green manure intercropping cultivation system, comprising a reclaimed land substrate preparation module, a soilless cultivation module, a green manure planting module and a microbial bionic regulation module, wherein;

[0007] The reclaimed land substrate preparation module prepares a substrate for soilless cultivation of the reclaimed land, wherein the substrate is a mixture of multiple inorganic and organic materials;

[0008] The soilless cultivation module includes a cultivation bed, a nutrient solution supply unit and an environmental control unit. The cultivation bed is connected to the nutrient solution supply unit to adjust the concentration, pH value and supply amount of the nutrient solution in real time.

[0009] The green manure planting module is provided with a special area for planting green manure crops, and the improvement of soil structure and optimization of nutrient circulation are achieved by alternately or simultaneously planting green manure and crops;

[0010] The microbial bionic regulation module monitors and regulates the microbial community structure in the reclaimed land matrix in real time, dynamically adjusts the types and quantities of microorganisms, and optimizes the ecological balance of the microbial community, specifically including:

[0011] Microbial community monitoring: real-time monitoring of microbial community data in the matrix of reclaimed land, including microbial species, quantity and activity status;

[0012] Bionic simulation and optimization: Based on the microbial community data, the bionic simulation model is used to simulate the ecological dynamics of the microbial community in the reclaimed land, identify and optimize the microbial combination of the current environment;

[0013] Microbial injection and regulation: Inject or adjust the type and quantity of microorganisms according to the results of bionic simulation and optimization;

[0014] Feedback learning and adaptive regulation: Continuously analyze the changing trends of microbial communities and crop growth responses, optimize bionic simulation models, and adjust microbial injection and regulation strategies to achieve adaptive optimization.

[0015] Optionally, the reclaimed land substrate preparation module includes:

[0016] Selection and treatment of inorganic materials: Select inorganic materials, including vermiculite, perlite, sand and gravel, and screen, clean and disinfect the inorganic materials;

[0017] Selection and pretreatment of organic materials: Select organic materials, including coconut bran, peat, and compost, and crush, ferment, and disinfect the organic materials;

[0018] Mixing process: Mix the treated inorganic materials with organic materials in a predetermined ratio.

[0019] Optionally, the soilless cultivation module includes:

[0020] Cultivation bed design: The cultivation bed is made of corrosion-resistant materials, filled with reclaimed land matrix, and has a porous structure;

[0021] Nutrient solution supply unit: The nutrient solution supply unit is connected to the cultivation bed. The sensor monitors the nutrient solution concentration and pH value in the cultivation bed in real time to dynamically adjust the supply amount and composition of the nutrient solution, which is expressed as:

[0022]

[0023] Among them, Q(t) is the amount of nutrient solution that needs to be replenished at time t, V(t) is the current volume of nutrient solution in the cultivation bed, and C opt is the target nutrient solution concentration, C(t) is the current nutrient solution concentration, and Δt is the time interval;

[0024] Environmental control unit: monitors the environmental parameters of the cultivation environment in real time through a sensor network, and adjusts relevant environmental parameters through control algorithms.

[0025] Optionally, the environmental control unit includes:

[0026] Sensor network monitoring: Using sensor networks to collect environmental parameters in the cultivation bed in real time, including temperature, humidity and light intensity;

[0027] Control algorithm calculation: Based on the real-time monitored environmental parameters, the environmental parameters adjusted by the control algorithm are calculated and expressed as:

[0028]

[0029] Among them, ΔP(t) is the change in the environmental parameter (temperature, humidity or light intensity) that needs to be adjusted at time t, S opt is the target setting value, S(t) is the current monitoring value, K p ,K i ,K d are proportional, integral and differential control coefficients respectively;

[0030] Environmental parameter adjustment: Based on the ΔP(t) calculated by the control algorithm, related equipment, including heaters, humidifiers, ventilation devices or lighting facilities, are automatically adjusted to achieve a dynamic balance of temperature, humidity and light intensity.

[0031] Optionally, the green manure planting module includes:

[0032] Alternate planting: Green manure and crops are planted alternately according to a predetermined cycle. After each planting cycle, the green manure crops are turned into the substrate and decomposed as organic fertilizer, improving the soil structure and increasing the organic matter content in the substrate;

[0033] Simultaneous planting: Green manure is planted with crops in a dedicated area at the same time. Green manure improves the soil microenvironment through symbiotic effects, increases the aeration and water retention capacity of the substrate, and increases the nutrient content in the substrate through nitrogen fixation and root secretions;

[0034] Optimization of nutrient recycling: After the green manure is harvested or naturally withers, its residue is processed into organic fertilizer and reapplied to the substrate.

[0035] Optionally, the microbial community monitoring includes:

[0036] Microbial sensor network: Arrange microbial sensors in the matrix to detect microbial biomarkers in the matrix, including metabolites and enzyme activities, to identify the types and quantities of microorganisms;

[0037] Real-time data collection: Continuously collect activity data of microorganisms in the matrix, including metabolite concentrations, enzyme activity indicators, redox potential, and pH changes;

[0038] Activity status analysis: Based on the collected microbial activity data, the activity status of the microbial community is evaluated in real time to determine its growth dynamics and ecological functions.

[0039] Optionally, the activity status analysis includes:

[0040] Data standardization: standardize the microbial activity data collected by the sensor network (including metabolite concentrations, enzyme activity indicators, redox potential, and pH changes);

[0041] Activity status assessment: Calculate the comprehensive activity status index I of the microbial community using a weighted index model a (t), expressed as:

[0042]

[0043] Among them, I a (t) is the microbial activity index at time t, D i (t) is the standardized value of the ith activity data indicator (such as metabolite concentration, enzyme activity, etc.), w i is the weight coefficient of the indicator, and n is the total number of data indicators;

[0044] Dynamic change analysis: by calculating the microbial activity state index I a The time derivative of (t) Evaluate the changing trend of microbial community activity to determine the growth dynamics and ecological functions of the microbial community, expressed as:

[0045] Indicates that microbial activity is enhanced. Indicates that microbial activity is reduced;

[0046] Ecological function judgment: based on activity status index I a (t) and its changing trend, combined with the ecological function threshold, determine whether the microbial community is in the optimal ecological function state, expressed as:

[0047]

[0048] Among them, I threshold is the ecological function threshold.

[0049] Optionally, the bionic simulation and optimization includes:

[0050] Data input: input the real-time collected microbial community data (including microbial species, quantity and activity status) into the bionic simulation model;

[0051] Bionic simulation algorithm: A bionic simulation algorithm based on population dynamics is used to simulate the ecological dynamic process of microbial communities, which can be expressed as:

[0052]

[0053] Among them, N i (t) represents the number of the i-th microorganism at time t, r i is the intrinsic growth rate of the microorganism, K i Its environmental carrying capacity, α ij is the competition coefficient between microbial populations i and j, N j (t) represents the number of the jth microorganism at time t;

[0054] Optimization strategy identification: Through bionic simulation, the dynamic equilibrium state of each microbial population under the current environmental conditions is calculated, and the microbial combination that is most conducive to maintaining ecological balance and promoting crop growth is identified, expressed as:

[0055]

[0056] Among them, β i is the contribution coefficient of microbial population i to the overall ecological function, F i is the performance of its ecological functions (such as ammonia fixation, phosphate mineralization, etc.) under current environmental conditions, and n is the total number of microbial species involved in the optimization calculation;

[0057] Optimization and adjustment of microbial combinations: According to the results of bionic simulation, the types and proportions of microbial communities are adjusted to optimize the microbial combination in the current environment.

[0058] Optionally, the microbial injection and regulation include:

[0059] Selection of injected microorganisms: Based on the identified optimal microbial combination, determine the types of microorganisms that need to be injected or adjusted. For each microorganism i, calculate the required injection volume Q i (t), expressed as:

[0060] Q i (t) = N target,i -N i (t);

[0061] Among them, Q i(t) is the number of microorganisms i that need to be injected at time t, N target,i The target number of this microorganism recommended for biomimetic simulation, N i (t) is the number of microorganisms actually present in the current matrix;

[0062] Quantity adjustment: According to the calculation results O i (t) Inject the required number of microorganisms, or promote or inhibit the reproduction of microorganisms by adjusting the growth conditions (such as nutrient solution composition, pH value, temperature, etc.) to achieve the target number recommended by the bionic simulation and optimization results.

[0063] Optionally, the feedback learning and adaptive adjustment include:

[0064] Real-time data collection: Continuously collect data on changes in microbial communities, including the rate of change of microbial populations, through a sensor network and crop growth response data G(t), Reflects the changing trend of the number of the i-th microorganism over time, G(t) includes the growth rate, chlorophyll content and yield of the crop;

[0065] Trend analysis: The collected change data were analyzed using the Autoregressive Integrated Moving Average (ARIMA) model to identify the changing trends of microbial communities and crop growth responses, expressed as:

[0066]

[0067] Among them, T i (t) represents the trend index of the i-th microorganism at time t, α 1 and α 2 is the weight coefficient, ∈ is the error term;

[0068] Model optimization: Based on the results of trend analysis, dynamically adjust the parameters in the bionic simulation model (microorganism growth rate r i , competition coefficient α ij ), expressed as:

[0069]

[0070] in, is the adjusted microbial growth rate, is the original growth rate, γ is the adjustment coefficient, T target is the target trend index;

[0071]

[0072] in, represents the adjusted competition coefficient, represents the original competition coefficient, Ti (t) and T j (t) are the trend indexes of the i-th and j-th microorganisms, respectively, and δ is the adjustment coefficient;

[0073] Strategy adjustment: According to the optimized bionic simulation model, the strategy of microbial injection and regulation is adjusted in real time, including microbial species selection, microbial quantity adjustment, nutrient solution and growth condition regulation, and microbial timing injection.

[0074] Beneficial effects of the present invention:

[0075] The present invention, through the combination of the reclaimed land substrate preparation module, the soilless cultivation module and the green manure planting module, can effectively support the growth of crops on barren or degraded land. At the same time, through the alternating and simultaneous planting strategies of green manure, the fertility and stability of the substrate are significantly improved, the dependence on external fertilizers is reduced, and the ecological sustainability of the system is enhanced.

[0076] The present invention, through real-time monitoring of the types, quantity and activity status of microbial communities, and combined with the optimization calculation of the bionic simulation model, the system can accurately regulate the types and quantities of microorganisms, thereby realizing dynamic optimization of the ecological functions of microorganisms. This bionic regulation not only improves the ecological balance and stability of the microbial community, but also enhances the nutrient absorption and disease resistance of crops, further optimizing the growth conditions and yield of crops.

[0077] The present invention, through real-time data collection and trend analysis, the system can dynamically adjust the bionic simulation model and microbial regulation strategy to ensure that the microbial community is always in the best state. This adaptive regulation mechanism improves the overall operating efficiency and stability of the system, so that the soilless cultivation system of reclaimed land can still maintain high-yield and high-quality crop growth effects in the face of changing environments, showing extremely high adaptability and long-term sustainability. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0079] Figure 1 A schematic diagram of system function modules according to an embodiment of the present invention;

[0080] Figure 2 Schematic diagram of a microbial bionic regulation module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0081] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0082] It should be noted that the references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0083] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0084] like Figure 1-Figure 2 As shown, a reclaimed land soilless cultivation and green manure intercropping cultivation system includes a reclaimed land substrate preparation module, a soilless cultivation module, a green manure planting module and a microbial bionic regulation module, wherein;

[0085] The reclaimed land substrate preparation module prepares the substrate for soilless cultivation in the reclaimed land. The substrate is a mixture of various inorganic and organic materials, has good air permeability and water retention capacity, and can provide the necessary support and nutrients for crops;

[0086] The soilless cultivation module includes a cultivation bed, a nutrient solution supply unit and an environmental control unit. The cultivation bed is connected to the nutrient solution supply unit to regulate the concentration, pH value and supply of the nutrient solution in real time to ensure the best growth environment for crops and adapt to the special soil conditions of the reclaimed land.

[0087] The green manure planting module has a dedicated area for planting green manure crops. By planting green manure and crops alternately or simultaneously, the soil structure is improved and the nutrient cycle is optimized, thereby improving the overall fertility of the reclaimed land.

[0088] The microbial bionic regulation module monitors and regulates the microbial community structure in the reclaimed land matrix in real time, dynamically adjusts the types and quantities of microorganisms, optimizes the ecological balance of the microbial community, and enhances the nutrient absorption and disease resistance of crop roots. Specifically, it includes:

[0089] Microbial community monitoring: real-time monitoring of microbial community data in the matrix of reclaimed land, including microbial species, quantity and activity status;

[0090] Bionic simulation and optimization: Based on the microbial community data, the bionic simulation model is used to simulate the ecological dynamic process of the microbial community in the reclaimed land, identify and optimize the microbial combination of the current environment, and adjust the microbial population according to the bionic simulation results to maintain ecological balance and promote crop growth;

[0091] Microbial injection and regulation: Based on the results of bionic simulation and optimization, inject or adjust the type and quantity of microorganisms to ensure that the microbial community can play the maximum role in the reclaimed land environment;

[0092] Feedback learning and adaptive regulation: Continuously analyze the changing trends of microbial communities and crop growth responses, optimize bionic simulation models and adjust microbial injection and regulation strategies to achieve adaptive optimization and improve the long-term stability and effectiveness of microbial communities;

[0093] Through the above contents, the efficient integration and dynamic optimization of soilless cultivation and green manure intercropping system in reclaimed land have been achieved, ensuring the stable operation and sustainability of the system under complex environmental conditions. Through real-time monitoring, bionic regulation and adaptive optimization, the system can accurately regulate microbial communities and environmental parameters, thereby improving crop growth efficiency, soil fertility and overall ecological benefits, reflecting significant innovation and practicality.

[0094] The module for preparing the substrate for land reclamation includes:

[0095] Selection and treatment of inorganic materials: Select inorganic materials, including vermiculite, perlite, sand and gravel, and screen, clean and disinfect the inorganic materials to ensure that they have good air permeability and physical stability;

[0096] Selection and pretreatment of organic materials: Select organic materials, including coconut bran, peat, and compost, and crush, ferment, and sterilize the organic materials to improve their water retention capacity and nutrient content;

[0097] Mixing process: The treated inorganic material is mixed with the organic material in a predetermined ratio, and a special mixing device is used to ensure the uniformity of the mixture, ultimately forming a matrix with good air permeability and moisture retention capacity;

[0098] Through the above content, a substrate with good air permeability and water retention capacity can be prepared, which effectively supports the healthy growth of crops in the reclaimed land, while improving the stability and adaptability of the substrate, ensuring the efficient operation of the soilless cultivation system.

[0099] The soilless cultivation module includes:

[0100] Cultivation bed design: The cultivation bed is made of corrosion-resistant materials, filled with reclaimed land matrix, and has a porous structure to ensure the aeration of the matrix and the uniform distribution of the nutrient solution;

[0101] Nutrient solution supply unit: The nutrient solution supply unit is connected to the cultivation bed. The sensor monitors the nutrient solution concentration and pH value in the cultivation bed in real time to dynamically adjust the supply amount and composition of the nutrient solution, which is expressed as:

[0102]

[0103] Among them, Q(t) is the amount of nutrient solution that needs to be replenished at time t, V(t) is the current volume of nutrient solution in the cultivation bed, and C opt is the target nutrient solution concentration, C(t) is the current nutrient solution concentration, and Δt is the time interval;

[0104] Environmental control unit: monitors the environmental parameters of the cultivation environment in real time through a sensor network, and adjusts the relevant environmental parameters through control algorithms to ensure that crops grow under optimal growth conditions;

[0105] Through the above content, real-time monitoring and dynamic adjustment of the cultivation environment are realized to ensure that crops obtain the best growth conditions in the complex environment of reclaimed land. It not only improves the precise supply of nutrient solution and the efficiency of environmental control, but also reduces the need for human intervention through intelligent management, greatly improves crop yield and the overall stability of the system, and has high adaptability and reliability.

[0106] The environmental control unit includes:

[0107] Sensor network monitoring: Using sensor networks to collect environmental parameters in the cultivation bed in real time, including temperature, humidity and light intensity;

[0108] Control algorithm calculation: Based on the real-time monitored environmental parameters, the environmental parameters adjusted by the control algorithm are calculated and expressed as:

[0109]

[0110] Among them, ΔP(t) is the change in the environmental parameter (temperature, humidity or light intensity) that needs to be adjusted at time t, S opt is the target setting value, S(t) is the current monitoring value, K p ,Ki ,K d are proportional, integral and differential control coefficients respectively;

[0111] Environmental parameter adjustment: Based on the ΔP(t) calculated by the control algorithm, relevant equipment, including heaters, humidifiers, ventilation devices or lighting facilities, are automatically adjusted to achieve a dynamic balance of temperature, humidity and light intensity, ensuring that the cultivation environment is always in the best state for crop growth;

[0112] Through the above content, the temperature, humidity and light intensity in the cultivation environment are accurately adjusted to ensure that crops obtain the best growth conditions in the complex environment of reclaimed land. Its control algorithm can not only dynamically respond to environmental changes, but also has adaptive optimization functions, continuously improving the adaptability and response speed of the system, thereby increasing crop yields and the overall operation efficiency of the system, reducing human intervention and improving the level of automation.

[0113] The green manure planting module includes:

[0114] Alternate planting: Green manure and crops are planted alternately according to a predetermined cycle. After each planting cycle, the green manure crops are turned into the substrate and decomposed as organic fertilizer, improving the soil structure and increasing the organic matter content in the substrate, providing nutrients for the crops in the next planting cycle;

[0115] Simultaneous planting: Green manure is planted with crops in a dedicated area at the same time. Green manure improves the soil microenvironment through symbiotic effect, increases the aeration and water retention capacity of the substrate, and increases the nutrient content in the substrate through nitrogen fixation and root secretions, promoting the healthy growth of the main crop.

[0116] Optimization of nutrient cycle: After the green manure is harvested or naturally withered, its residue is processed into organic fertilizer and reapplied to the substrate, ensuring the nutrient cycle between green manure planting and crop cultivation, thereby reducing the use of external chemical fertilizers and improving the ecological benefits of the system;

[0117] Through the above content, not only can the matrix structure of the reclaimed land be effectively improved, but also the recycling of nutrients can be achieved through scientific planting strategies, which enhances the growth environment of crops and improves the sustainability of the system.

[0118] Microbiome monitoring includes:

[0119] Microbial sensor network: Arrange microbial sensors in the matrix to detect microbial biomarkers in the matrix, including metabolites and enzyme activities, to identify the types and quantities of microorganisms;

[0120] Real-time data collection: Continuously collect activity data of microorganisms in the matrix, including metabolite concentrations, enzyme activity indicators, redox potential, and pH changes;

[0121] Activity status analysis: Based on the collected microbial activity data, the activity status of the microbial community is evaluated in real time to determine its growth dynamics and ecological functions;

[0122] Through the above content, the types, quantity and activity status of microbial communities in the reclaimed land matrix can be comprehensively and dynamically grasped. Through real-time evaluation of key indicators such as metabolites and enzyme activity, the structure of microbial communities can be adjusted in time to ensure the optimization of their ecological functions, improve the stability of the crop growth environment and the overall operating efficiency of the system.

[0123] Activity status analysis includes:

[0124] Data standardization: standardize the microbial activity data collected by the sensor network (including metabolite concentrations, enzyme activity indicators, redox potential, and pH changes) to convert different types of data into a comparable unified scale;

[0125] Activity status assessment: Calculate the comprehensive activity status index I of the microbial community using a weighted index model a (t), expressed as:

[0126]

[0127] Among them, I a (t) is the microbial activity index at time t, D i (t) is the standardized value of the ith activity data indicator (such as metabolite concentration, enzyme activity, etc.), w i is the weight coefficient of the indicator, and n is the total number of data indicators;

[0128] Dynamic change analysis: by calculating the microbial activity state index I a The time derivative of (t) Evaluate the changing trend of microbial community activity to determine the growth dynamics and ecological functions of the microbial community, expressed as:

[0129] Indicates that microbial activity is enhanced. Indicates that microbial activity is reduced;

[0130] Ecological function judgment: based on activity status index I a (t) and its changing trend, combined with the ecological function threshold, determine whether the microbial community is in the optimal ecological function state, expressed as:

[0131]

[0132] Among them, I threshold is the ecological function threshold;

[0133] Ecological Function Threshold I threshold Based on historical data and experimental results, determined through statistical analysis, including:

[0134] Data collection: Under experimental conditions, collect data on microbial activity at different growth stages, environmental conditions, and crop types. i (t) and the corresponding activity state index I a (ta), while recording the crop growth effects and soil improvement under these conditions;

[0135] Regression analysis: Using multivariate regression analysis, the activity status index I a (t) Conduct regression analysis with crop growth effects and soil improvement indicators (such as yield, root system development, soil fertility, etc.) to find the activity state index value that best reflects the optimal ecological function;

[0136] Threshold determination: Determine a critical value I through regression analysis results threshold , that is, when the value is above this value, the crop growth and soil improvement effect are the best. This value can be set as the optimal point or a value close to the optimal point in the regression curve according to the experimental results, expressed as:

[0137]

[0138] Where n is the number of experiments, I a (t j ) is the activity state index of the jth experiment, Optimal(t j ) is the identifier of the optimal ecological function condition corresponding to the jth experiment (e.g., the point with the highest yield is set to 1, and the rest are set to 0), and the activity state index of the optimal point is determined by weighted average;

[0139] Through the above content, it is possible to accurately judge whether the microbial community is in the best state and adjust the system parameters in time, thereby improving the growth effect of crops and soil improvement efficiency, enhancing the adaptability and accuracy of the system, and ensuring the efficient and sustainable operation of the soilless cultivation system in the reclaimed land.

[0140] Bionic simulation and optimization include:

[0141] Data input: input the real-time collected microbial community data (including microbial species, quantity and activity status) into the bionic simulation model;

[0142] Bionic simulation algorithm: A bionic simulation algorithm based on population dynamics is used to simulate the ecological dynamic process of microbial communities, which can be expressed as:

[0143]

[0144] Among them, N i(t) represents the number of the i-th microorganism at time t, r i is the intrinsic growth rate of the microorganism, K i Its environmental carrying capacity, α ij is the competition coefficient between microbial populations i and j, N j (k) represents the number of the jth microorganism at time t;

[0145] Optimization strategy identification: Through bionic simulation, the dynamic equilibrium state of each microbial population under the current environmental conditions is calculated, and the microbial combination that is most conducive to maintaining ecological balance and promoting crop growth is identified, expressed as:

[0146]

[0147] Among them, β i is the contribution coefficient of microbial population i to the overall ecological function, F i is the performance of its ecological functions (such as ammonia fixation, phosphate mineralization, etc.) under current environmental conditions, and n is the total number of microbial species involved in the optimization calculation;

[0148] Optimization and adjustment of microbial composition: According to the results of bionic simulation, the types and proportions of microbial communities are adjusted to optimize the microbial composition in the current environment to achieve a dynamic balance of the ecosystem and optimal crop growth conditions;

[0149] Through the above contents, it is possible to dynamically adapt to environmental changes, ensure the continuous optimization of microbial communities and the stability of the ecosystem, improve the adaptability and optimization level of crop growth conditions, and enhance the overall efficiency and sustainability of the soilless cultivation system in reclaimed land.

[0150] Microbial injection and regulation include:

[0151] Selection of injected microorganisms: Based on the identified optimal microbial combination, determine the types of microorganisms that need to be injected or adjusted. For each microorganism i, calculate the required injection volume Q i (t), expressed as:

[0152] Q i (t) = N target,i -N i (t);

[0153] Among them, Q i (t) is the number of microorganisms i that need to be injected at time t, N target,i The target number of this microorganism recommended for biomimetic simulation, N i (t) is the number of microorganisms actually present in the current matrix;

[0154] Quantity adjustment: According to the calculation result Q i(t) Injecting the required number of microorganisms, or promoting or inhibiting the reproduction of specific microorganisms by adjusting growth conditions (such as nutrient solution composition, pH value, temperature, etc.) to achieve the target number recommended by the bionic simulation and optimization results;

[0155] Through the above, it is ensured that the microbial community can quickly reach the optimal combination and adapt to the special environment of the reclaimed land, thereby optimizing the ecological balance and crop growth conditions.

[0156] Feedback learning and adaptive adjustment include:

[0157] Real-time data collection: Continuously collect data on changes in microbial communities, including the rate of change of microbial populations, through a sensor network and crop growth response data G(t), Reflects the changing trend of the number of the i-th microorganism over time, G(t) includes the growth rate, chlorophyll content and yield of the crop;

[0158] Trend analysis: The collected change data were analyzed using the Autoregressive Integrated Moving Average (ARIMA) model to identify the changing trends of microbial communities and crop growth responses, expressed as:

[0159]

[0160] Among them, T i (t) represents the trend index of the i-th microorganism at time t, α 1 and α 2 is the weight coefficient, ∈ is the error term;

[0161] Model optimization: Based on the results of trend analysis, dynamically adjust the parameters in the bionic simulation model (microorganism growth rate r i , competition coefficient α ij ), so that the bionic simulation model can more accurately reflect the dynamics of microbial communities in actual environments, expressed as:

[0162]

[0163] in, is the adjusted microbial growth rate, is the original growth rate, γ is the adjustment coefficient, T target is the target trend index;

[0164]

[0165] in, represents the adjusted competition coefficient, reflecting the interaction intensity between the i-th microorganism and the j-th microorganism. represents the original competition coefficient, T i(t) and T j (t) are the trend indexes of the i-th and j-th microorganisms, respectively, reflecting their growth dynamics. i (t) grows faster than T j (t), then α ij It may need to be increased to reflect the stronger competition of the i-th microorganism on the j-th microorganism. δ is the adjustment coefficient, which is used to control the adjustment range and ensure the stability of the model;

[0166] Strategy adjustment: According to the optimized bionic simulation model, the strategy of microbial injection and regulation is adjusted in real time, including microbial species selection, microbial quantity adjustment, nutrient solution and growth condition adjustment, and microbial timing injection, to ensure that the species and quantity of the microbial community are consistent with the optimization results, and to respond to the changing needs of crop growth in a timely manner to achieve adaptive optimization of the system;

[0167] Through the above, it is possible to respond quickly to changes in the environment and crop needs, continuously optimize the system's operating parameters, ensure that the microbial community and crop growth conditions are always in the best state, improve the system's stability and efficiency, and make the reclaimed land soilless cultivation system more adaptable and sustainable, thereby achieving higher crop yields and quality.

[0168] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0169] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A soilless cultivation and green manure intercropping cultivation system for reclaimed land, characterized in that: It includes the reclamation land substrate preparation module, soilless cultivation module, green manure planting module and microbial bionic regulation module, among which; The reclaimed land substrate preparation module prepares a substrate for soilless cultivation of the reclaimed land, wherein the substrate is a mixture of multiple inorganic and organic materials; The soilless cultivation module includes a cultivation bed, a nutrient solution supply unit and an environmental control unit. The cultivation bed is connected to the nutrient solution supply unit to adjust the concentration, pH value and supply amount of the nutrient solution in real time. The green manure planting module is provided with a special area for planting green manure crops, and the improvement of soil structure and optimization of nutrient circulation are achieved by alternately or simultaneously planting green manure and crops; The microbial bionic regulation module monitors and regulates the microbial community structure in the reclaimed land matrix in real time, dynamically adjusts the types and quantities of microorganisms, and optimizes the ecological balance of the microbial community, specifically including: Microbial community monitoring: real-time monitoring of microbial community data in the matrix of reclaimed land, including microbial species, quantity and activity status; Bionic simulation and optimization: Based on the microbial community data, the bionic simulation model is used to simulate the ecological dynamics of the microbial community in the reclaimed land, identify and optimize the microbial combination of the current environment; Microbial injection and regulation: Inject or adjust the type and quantity of microorganisms according to the results of bionic simulation and optimization; Feedback learning and adaptive regulation: Continuously analyze the changing trends of microbial communities and crop growth responses, optimize bionic simulation models, and adjust microbial injection and regulation strategies to achieve adaptive optimization.

2. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 1, characterized in that: The reclaimed land substrate preparation module comprises: Selection and treatment of inorganic materials: Select inorganic materials, including vermiculite, perlite, sand and gravel, and screen, clean and disinfect the inorganic materials; Selection and pretreatment of organic materials: Select organic materials, including coconut bran, peat, and compost, and crush, ferment, and disinfect the organic materials; Mixing process: Mix the treated inorganic materials with organic materials in a predetermined ratio.

3. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 2, characterized in that: The soilless cultivation module comprises: Cultivation bed design: The cultivation bed is made of corrosion-resistant materials, filled with reclaimed land matrix, and has a porous structure; Nutrient solution supply unit: The nutrient solution supply unit is connected to the cultivation bed. The sensor monitors the concentration and pH value of the nutrient solution in the cultivation bed in real time to dynamically adjust the supply amount and composition of the nutrient solution, which is expressed as: Among them, Q(t) is the amount of nutrient solution that needs to be replenished at time t, V(t) is the current volume of nutrient solution in the cultivation bed, and C opt is the target nutrient solution concentration, C(t) is the current nutrient solution concentration, and Δt is the time interval; Environmental control unit: monitors the environmental parameters of the cultivation environment in real time through a sensor network, and adjusts relevant environmental parameters through control algorithms.

4. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 3, characterized in that: The environmental control unit comprises: Sensor network monitoring: Using sensor networks to collect environmental parameters in the cultivation bed in real time, including temperature, humidity and light intensity; Control algorithm calculation: Based on the real-time monitored environmental parameters, the environmental parameters adjusted by the control algorithm are calculated and expressed as: Among them, ΔP(t) is the change in the environmental parameters that need to be adjusted at time t, S opt is the target setting value, S(t) is the current monitoring value, K p ,K i ,K d are proportional, integral and differential control coefficients respectively; Environmental parameter adjustment: Based on the ΔP(t) calculated by the control algorithm, related equipment, including heaters, humidifiers, ventilation devices or lighting facilities, are automatically adjusted to achieve a dynamic balance of temperature, humidity and light intensity.

5. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 1, characterized in that: The green manure planting module includes: Alternate planting: Green manure and crops are planted alternately according to a predetermined cycle. After each planting cycle, the green manure crops are turned into the substrate and decomposed as organic fertilizer, improving the soil structure and increasing the organic matter content in the substrate; Simultaneous planting: Green manure is planted with crops in a dedicated area at the same time. Green manure improves the soil microenvironment through symbiotic effects, increases the aeration and water retention capacity of the substrate, and increases the nutrient content in the substrate through nitrogen fixation and root secretions; Optimization of nutrient recycling: After the green manure is harvested or naturally withers, its residue is processed into organic fertilizer and reapplied to the substrate.

6. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 1, characterized in that: The microbial community monitoring includes: Microbial sensor network: Arrange microbial sensors in the matrix to detect microbial biomarkers in the matrix, including metabolites and enzyme activities, to identify the types and quantities of microorganisms; Real-time data collection: Continuously collect activity data of microorganisms in the matrix, including metabolite concentrations, enzyme activity indicators, redox potential, and pH changes; Activity status analysis: Based on the collected microbial activity data, the activity status of the microbial community is evaluated in real time to determine its growth dynamics and ecological functions.

7. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 6, characterized in that: The activity status analysis includes: Data standardization: standardize the microbial activity data collected by the sensor network; Activity status assessment: Calculate the comprehensive activity status index I of the microbial community using a weighted index model a (t), expressed as: Among them, I a (t) is the microbial activity index at time t, D i (t) is the standardized value of the i-th activity data indicator, w i is the weight coefficient of the indicator, and n is the total number of data indicators; Dynamic change analysis: by calculating the microbial activity state index I a The time derivative of (t) Evaluate the changing trend of microbial community activity to determine the growth dynamics and ecological functions of the microbial community, expressed as: Indicates that microbial activity is enhanced. Indicates that microbial activity is reduced; Ecological function judgment: based on activity status index I a (t) and its changing trend, combined with the ecological function threshold, determine whether the microbial community is in the optimal ecological function state, expressed as: Among them, I threshold is the ecological function threshold.

8. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 7, characterized in that: The bionic simulation and optimization include: Data input: Input the microbial community data collected in real time into the bionic simulation model; Bionic simulation algorithm: A bionic simulation algorithm based on population dynamics is used to simulate the ecological dynamic process of microbial communities, which can be expressed as: Among them, N i (t) represents the number of the i-th microorganism at time t, r i is the intrinsic growth rate of the microorganism, K i Its environmental carrying capacity, α ij is the competition coefficient between microbial populations i and j, N j (t) represents the number of the jth microorganism at time t; Optimization strategy identification: Through bionic simulation, the dynamic equilibrium state of each microbial population under the current environmental conditions is calculated, and the microbial combination that is most conducive to maintaining ecological balance and promoting crop growth is identified, expressed as: Among them, β i is the contribution coefficient of microbial population i to the overall ecological function, F i is the performance of its ecological function under current environmental conditions, and n is the total number of microbial species involved in the optimization calculation; Optimization and adjustment of microbial combinations: According to the results of bionic simulation, the types and proportions of microbial communities are adjusted to optimize the microbial combination in the current environment.

9. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 8, characterized in that: The microbial injection and regulation include: Selection of injected microorganisms: Based on the identified optimal microbial combination, determine the types of microorganisms that need to be injected or adjusted. For each microorganism i, calculate the required injection amount Qi(t), expressed as: Q i (t)=N target,i -N i (t); Among them, Q i (t) is the number of microorganisms i that need to be injected at time t, N target,i The target number of this microorganism recommended for biomimetic simulation, N i (t) is the number of microorganisms actually present in the current matrix; Quantity adjustment: According to the calculation result Q i (t) Injecting the required number of microorganisms, or promoting or inhibiting the reproduction of microorganisms by adjusting the growth conditions, so as to achieve the target number recommended by the bionic simulation and optimization results.

10. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 9, characterized in that: The feedback learning and adaptive adjustment include: Real-time data collection: Continuously collect data on changes in microbial communities, including the rate of change of microbial populations, through a sensor network and crop growth response data G(t), Reflects the changing trend of the number of the i-th microorganism over time, G(t) includes the growth rate, chlorophyll content and yield of the crop; Trend analysis: The collected change data were analyzed using an autoregressive integrated moving average model to identify the changing trends of microbial communities and crop growth responses, expressed as: Among them, T i (t) represents the trend index of the i-th microorganism at time t, α1 and α2 are weight coefficients, and ∈ is the error term; Model optimization: Based on the results of trend analysis, the parameters in the bionic simulation model are dynamically adjusted, expressed as: in, is the adjusted microbial growth rate, is the original growth rate, γ is the adjustment coefficient, T target is the target trend index; in, represents the adjusted competition coefficient, represents the original competition coefficient, T i (t) and T j (t) are the trend indexes of the i-th and j-th microorganisms, respectively, and δ is the adjustment coefficient; Strategy adjustment: According to the optimized bionic simulation model, the strategy of microbial injection and regulation is adjusted in real time, including the selection of microbial species, adjustment of microbial quantity, regulation of nutrient solution and growth conditions, and timing of microbial injection.

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