Soilless cultivation and green manure intercropping cultivation system for reclaimed land

Abstract

The present invention relates to the technical field of agricultural engineering, and particularly relates to a soilless cultivation and green manure intercropping cultivation system for reclaimed land, including a reclaimed land substrate preparation module, a soilless cultivation module, a green manure planting module, and a microbial bionic regulation module, wherein; the reclaimed land substrate preparation module prepares the substrate for soilless cultivation of reclaimed land; the soilless cultivation module includes a cultivation 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 by alternately or simultaneously planting green manure and crops, the improvement of soil structure and the optimization of nutrient cycling are realized; the microbial bionic regulation module monitors and regulates the microbial community structure in the reclaimed land substrate in real time. The present invention not only improves the ecological balance and stability of the microbial community, but also enhances the nutrient absorption and disease resistance of crops, and optimizes the growth conditions and yield of crops.

Description

Technical Field

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

[0002] Reclaimed land usually refers to degraded or abandoned land whose productivity is restored through artificial measures. Such land often faces problems such as poor soil fertility, damaged structure, and nutrient loss. Conducting agricultural planting, especially soilless cultivation, on reclaimed land can avoid the direct impact of soil problems on crop growth and achieve the 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 the increase of organic matter, but also reduce the dependence on chemical fertilizers and enhance the ecological benefits of farmland.

[0003] However, there are many deficiencies in the existing soilless cultivation and green manure intercropping technologies for reclaimed land. First, the traditional matrix preparation and management methods are relatively extensive, lacking precise control of the microbial community in the matrix, resulting in poor soil ecological functions and affecting the growth effect of crops. Second, in the soilless cultivation system, the nutrient solution supply and environmental control often rely on fixed parameter settings and are difficult to adapt to the special environmental changes in reclaimed land, leading to the instability of the crop growth environment. Third, the existing green manure intercropping strategies often only focus on the simple planting and ploughing of green manure, lacking in-depth research and application of the dynamic ecological relationship between green manure and crops, and failing to fully exert the ecological functions of green manure. Generally speaking, the application of existing technologies in the reclaimed land environment has not been able to achieve refined control and dynamic optimization of the microbial community, nutrient solution, and crop growth environment.

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

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

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

[0007] The reclaimed land matrix preparation module prepares the matrix for soilless cultivation of reclaimed land, and the matrix is composed of a variety of 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. By alternately or simultaneously planting green manure and crops, the improvement of soil structure and the optimization of nutrient cycling are achieved.

[0010] The microbial bionic regulation module monitors and regulates the microbial community structure in the reclaimed substrate in real time, dynamically adjusts the types and quantities of microorganisms, and optimizes the ecological balance of the microbial community. Specifically, it includes:

[0011] Microbial community monitoring: Real-time monitoring of microbial community data in the reclaimed substrate, including the types, quantities, and active states of microorganisms.

[0012] Bionic simulation and optimization: Based on the microbial community data, through a bionic simulation model, simulate the ecological dynamic process of the microbial community in the reclaimed land, and identify and optimize the microbial combination in the current environment.

[0013] Microbial injection and regulation: According to the results of bionic simulation and optimization, inject or adjust the types and quantities of microorganisms.

[0014] Feedback learning and adaptive regulation: Continuously analyze the change trends of the microbial community and the growth responses of crops, optimize the bionic simulation model, and adjust the strategies of microbial injection and regulation to achieve adaptive optimization.

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

[0016] Selection and treatment of inorganic materials: Select inorganic materials, including vermiculite, perlite, and sandstone, and screen, wash, and disinfect the inorganic materials.

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

[0018] Mixing process: Mix the treated inorganic materials and 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 substrate inside, and provided with a porous structure.

[0021] Nutrient solution supply unit: The nutrient solution supply unit is connected to the cultivation bed, and the nutrient solution concentration and pH value in the cultivation bed are monitored in real time through sensors to achieve dynamic adjustment of the supply quantity and composition of the nutrient solution, expressed as:

[0022]

[0023] Among them, Q(t) is the amount of nutrient solution to be supplemented at time t, V(t) is the current volume of nutrient solution in the cultivation bed, 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: Real-time monitor the environmental parameters of the cultivation environment through the sensor network, and adjust the relevant environmental parameters through the control algorithm.

[0025] Optionally, the environmental control unit includes:

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

[0027] Control algorithm calculation: According to the real-time monitored environmental parameters, calculate the adjusted environmental parameters through the control algorithm, expressed as:

[0028]

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

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

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

[0032] Alternate planting: Alternately plant green manure and crops according to a predetermined cycle. After each planting cycle ends, the green manure crops are turned into the substrate and decomposed as organic fertilizers to improve the soil structure and increase the organic matter content in the substrate;

[0033] Simultaneous planting: Plant green manure and crops in a dedicated area at the same time. The green manure improves the soil microenvironment through symbiotic effects, increases the air permeability and water retention capacity of the substrate, and at the same time increases the nutrient content in the substrate through nitrogen fixation and root exudates;

[0034] Nutrient cycle optimization: After the green manure is harvested or naturally withered, its residues are processed into organic fertilizers and reapplied to the substrate.

[0035] Optionally, the microbial community monitoring includes:

[0036] Microbial Sensor Network: Microbial sensors are arranged in the substrate to detect microbial biomarkers in the substrate, including metabolites and enzyme activities, to identify the types and quantities of microorganisms;

[0037] Real-time Data Acquisition: Continuously collect the activity data of microorganisms in the substrate, including metabolite concentrations, enzyme activity indicators, redox potentials, and pH value changes;

[0038] Activity State Analysis: Based on the collected activity data of microorganisms, evaluate the activity state of the microbial community in real time, and judge its growth dynamics and ecological functions.

[0039] Optionally, the activity state analysis includes:

[0040] Data Standardization: Standardize the microbial activity data (including metabolite concentrations, enzyme activity indicators, redox potentials, pH value changes) collected by the sensor network;

[0041] Activity State Evaluation: Use a weighted index model to calculate the comprehensive activity state index I a (t) of the microbial community, expressed as:

[0042]

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

[0044] Dynamic Change Analysis: Evaluate the change trend of the microbial community activity by calculating the time derivative a of the microbial activity state index I (t), expressed as:

[0045] Indicates an increase in microbial activity, Indicates a decrease in microbial activity;

[0046] Ecological Function Judgment: Based on the activity state index I a (t) and its change trend, combined with the ecological function threshold, judge whether the microbial community is in the optimal ecological function state, expressed as:

[0047]

[0048] where I threshold is the ecological function threshold.

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

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

[0051] Bionic simulation algorithm: Adopt a bionic simulation algorithm based on population dynamics to simulate the ecological dynamic process of the microbial community, expressed as:

[0052]

[0053] where N i (t) represents the quantity of the i-th type of microorganism at time t, r i is the intrinsic growth rate of this microorganism, K i is its environmental carrying capacity, α ij is the competition coefficient between microbial populations i and j, and N j (t) represents the quantity of the j-th type of microorganism at time t;

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

[0055]

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

[0057] Microbial combination optimization and adjustment: According to the bionic simulation results, adjust the types and proportions of the microbial community to optimize the microbial combination in the current environment.

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

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

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

[0061] where Q iN(i)(t) is the quantity of microorganism i to be injected at time t. target,i N(i) i is the target quantity of this microorganism recommended by the bionic simulation. i N(i)(t) is the quantity of this microorganism actually present in the current substrate;

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

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

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

[0065] Trend analysis: Use the autoregressive integrated moving average (ARIMA) model to analyze the collected change data and identify the change trends of the microbial community and crop growth response, expressed as:

[0066]

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

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

[0069]

[0070] where, is the adjusted microorganism growth rate, is the original growth rate, γ is the adjustment coefficient, and T target is the target trend index;

[0071]

[0072] where, represents the adjusted competition coefficient, represents the original competition coefficient, and Ti (t) and T j (t) are the trend indices 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 strategies for microorganism injection and regulation are adjusted in real time, including microorganism species selection, microorganism quantity adjustment, nutrient solution and growth condition regulation, and sequential microorganism injection.

[0074] Advantages of the present invention:

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

[0076] With the present invention, by real-time monitoring the species, quantity and active state of the microbial community and combining with the optimized calculation of the bionic simulation model, the system can accurately regulate the species and quantity of microorganisms, realizing the 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] With the present invention, through the collection and trend analysis of real-time data, the system can dynamically adjust the bionic simulation model and the microorganism regulation strategy to ensure that the microbial community is always in the best state. This adaptive regulation mechanism improves the overall operation efficiency and stability of the system, enabling the soilless cultivation system on the reclaimed land to still maintain high-yield and high-quality crop growth effects in the face of a changing environment, 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 following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only those of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0079] Figure 1 It is a schematic diagram of the system function module of the embodiment of the present invention;

[0080] Figure 2 It is a schematic diagram of the microbial bionic regulation module of the embodiment of the present invention. Detailed implementation manners

[0081] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments. For some well-known technologies, those skilled in the art can also adopt other alternative methods for implementation; moreover, 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 in the specification, references to "an embodiment", "embodiments", "exemplary embodiments", "some embodiments", etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not necessarily every embodiment includes such specific features, structures, or characteristics. Additionally, when combining embodiments to describe specific features, structures, or characteristics, implementing such features, structures, or characteristics in combination with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the relevant art.

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

[0084] As Figure 1 - Figure 2 shown, a soilless cultivation and green manure intercropping cultivation system for reclaimed land 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 of reclaimed land. The substrate is composed of a variety of inorganic and organic materials, has good air permeability and water retention capacity, and can provide necessary support and nutrients for crops;

[0086] The soilless cultivation module includes a cultivation bed, a nutrient solution supply unit, and an environment 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, ensuring the optimal growth environment for crops and adapting to the special soil conditions of reclaimed land;

[0087] The green manure planting module is provided with a special area for planting green manure crops. By alternately or simultaneously planting green manure and crops, the improvement of soil structure and the optimization of nutrient cycling are realized, thereby enhancing the overall fertility of reclaimed land;

[0088] The microbial bionic regulation module monitors and regulates the microbial community structure in the reclaimed substrate 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 reclaimed substrate, including the types, quantities, and active states of microorganisms;

[0090] Bionic simulation and optimization: Based on the microbial community data, through a bionic simulation model, 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: According to the results of bionic simulation and optimization, inject or adjust the types and quantities of microorganisms to ensure that the microbial community exerts the maximum efficiency in the reclaimed land environment;

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

[0093] Through the above content, the efficient integration and dynamic optimization of the soilless cultivation and green manure intercropping system in the reclaimed land are realized, 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 the microbial community and environmental parameters, thereby improving the growth efficiency of crops, soil fertility, and overall ecological benefits, demonstrating significant innovation and practicality.

[0094] The reclaimed substrate preparation module includes:

[0095] Selection and treatment of inorganic materials: Select inorganic materials, including vermiculite, perlite, and sand, and screen, wash, and disinfect the inorganic materials to ensure their good air permeability and physical stability;

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

[0097] Mixing process: Mix the treated inorganic materials and organic materials in a predetermined ratio, and use special mixing equipment to ensure the mixing uniformity, finally forming a substrate with good air permeability and water retention capacity;

[0098] Through the above, a substrate with good air permeability and water retention capacity can be prepared, effectively supporting the healthy growth of crops in the reclaimed land. At the same time, the stability and adaptability of the substrate are improved, 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 substrate inside, and a porous structure is set to ensure the air permeability of the substrate and the uniform distribution of nutrient solution.

[0101] Nutrient solution supply unit: The nutrient solution supply unit is connected to the cultivation bed, and the nutrient solution concentration and pH value in the cultivation bed are monitored in real time through sensors to dynamically adjust the supply volume and composition of the nutrient solution, expressed as:

[0102]

[0103] Among them, Q(t) is the amount of nutrient solution to be supplemented at time t, V(t) is the current volume of nutrient solution in the cultivation bed, 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: The environmental parameters of the cultivation environment are monitored in real time through a sensor network, and the relevant environmental parameters are adjusted through a control algorithm to ensure that the crops grow under the best growth conditions.

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

[0106] The environmental control unit includes:

[0107] Sensor network monitoring: Using a sensor network, the environmental parameters in the cultivation bed are collected in real time, including temperature, humidity and light intensity.

[0108] Control algorithm calculation: According to the real-time monitored environmental parameters, the adjusted environmental parameters are calculated through a control algorithm, expressed as:

[0109]

[0110] Among them, ΔP(t) is the change amount of the environmental parameter (temperature, humidity or light intensity) to be adjusted at time t, S opt is the target set value, S(t) is the current monitored value, K p ,Ki , K d are the proportional, integral, and derivative control coefficients respectively;

[0111] Environmental parameter adjustment: Based on ΔP(t) calculated by the control algorithm, relevant devices are automatically adjusted, including heaters, humidifiers, ventilation devices, or lighting facilities, to achieve 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 precisely adjusted to ensure that crops obtain the best growth conditions in the complex environment of the reclaimed land. Its control algorithm can not only dynamically respond to environmental changes but also has an adaptive optimization function, continuously improving the adaptability and response speed of the system, thereby increasing crop yields and the overall operating efficiency of the system, reducing human intervention, and improving the automation level.

[0113] The green manure planting module includes:

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

[0115] Simultaneous planting: Green manure and crops are planted in a dedicated area at the same time. The green manure improves the soil microenvironment through symbiotic effects, increases the aeration and water retention capacity of the substrate, and at the same time increases the nutrient content in the substrate through nitrogen fixation and root exudates, promoting the healthy growth of the main crops;

[0116] Nutrient cycle optimization: After the green manure is harvested or naturally withered, its residues are processed into organic fertilizers and reapplied to the substrate to ensure the nutrient cycle between green manure planting and crop cultivation, thereby reducing the use of external chemical fertilizers and enhancing the ecological benefits of the system;

[0117] Through the above content, it can not only effectively improve the substrate structure of the reclaimed land but also achieve the recycling of nutrients through scientific planting strategies, enhance the crop growth environment, and improve the sustainability of the system.

[0118] Microbial community monitoring includes:

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

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

[0121] Active state analysis: Based on the collected activity data of microorganisms, the active state of the microbial community is evaluated in real time to judge its growth dynamics and ecological functions;

[0122] Through the above content, it is possible to comprehensively and dynamically grasp the types, quantities, and active states of the microbial community in the reclaimed foundation substrate. By evaluating key indicators such as metabolites and enzyme activities in real time, the microbial community structure can be adjusted in a timely manner to ensure the optimization of its ecological functions and improve the stability of the crop growth environment and the overall operation efficiency of the system.

[0123] The active state analysis includes:

[0124] Data standardization: Standardize the microbial activity data collected by the sensor network (including metabolite concentration, enzyme activity index, redox potential, pH value change), and convert different types of data into a comparable unified scale;

[0125] Active state evaluation: Use the weighted index model to calculate the comprehensive active state index I a (t) of the microbial community, expressed as:

[0126]

[0127] where I a (t) is the microbial active state index at time t, D i (t) is the standardized value of the i-th active data index (such as metabolite concentration, enzyme activity, etc.), w i is the weight coefficient of this index, and n is the total number of data indexes;

[0128] Dynamic change analysis: By calculating the time derivative of the microbial active state index I a (t) evaluate the change trend of the microbial community activity to judge the growth dynamics and ecological functions of the microbial community, expressed as:

[0129] indicates an increase in microbial activity, indicates a decrease in microbial activity;

[0130] Ecological function judgment: Based on the active state index I a (t) and its change trend, combined with the ecological function threshold, judge whether the microbial community is in the optimal ecological function state, expressed as:

[0131]

[0132] where I threshold is the ecological function threshold;

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

[0134] Data collection: Under experimental conditions, collect microbial activity data D i (t) and the corresponding activity status index I a (ta), and simultaneously record the growth effect of crops and soil improvement under these conditions;

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

[0136] Threshold determination: Determine a critical value I threshold through the regression analysis results, that is, when the value is at or above this value, the crop growth and soil improvement effects 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] Among them, n is the number of experiments, I a (t j ) is the activity status index of the jth experiment, and Optimal(t j ) is the identifier (such as setting the point with the highest yield as 1 and the rest as 0) under the optimal ecological function conditions corresponding to the jth experiment. Determine the activity status index of the optimal point through weighted average;

[0139] Through the above content, it is possible to accurately judge whether the microbial community is in the best state, and timely adjust the system parameters, thereby improving the growth effect of crops and the soil improvement efficiency, enhancing the adaptability and accuracy of the system, and ensuring the efficient and sustainable operation of the soilless cultivation system in 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: Adopt a bionic simulation algorithm based on population dynamics to simulate the ecological dynamic process of the microbial community, expressed as:

[0143]

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

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

[0146]

[0147] where β i is the contribution coefficient of microorganism population i to the overall ecological function, and F i is the performance of its ecological function (such as nitrogen fixation, phosphorus mineralization, etc.) under the current environmental conditions, and n is the total number of microorganism species participating in the optimization calculation;

[0148] Microorganism combination optimization and adjustment: According to the bionic simulation results, adjust the types and proportions of the microorganism community to optimize the microorganism combination in the current environment to achieve the dynamic balance of the ecosystem and the best crop growth conditions;

[0149] Through the above content, it can dynamically adapt to environmental changes, ensure the continuous optimization of the microorganism community 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 the reclaimed land.

[0150] Microorganism injection and regulation include:

[0151] Selection of injected microorganisms: According to the identified best microorganism combination, determine the types of microorganisms that need to be injected or adjusted. For each microorganism i, calculate its required injection quantity Q i (t), expressed as:

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

[0153] where Q i (t) is the quantity of microorganism i that needs to be injected at time t, and N target,i is the target quantity of this microorganism recommended by the bionic simulation, and N i (t) is the quantity of this microorganism actually present in the current substrate;

[0154] Quantity adjustment: According to the calculation result Q i(t) Inject the required number of microorganisms, or promote or inhibit 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, adapt to the special environment of the reclaimed land, and then optimize the ecological balance and crop growth conditions.

[0156] Feedback learning and adaptive regulation include:

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

[0158] Trend analysis: Use the autoregressive integrated moving average (ARIMA) model to analyze the collected change data and identify the change trends of the microbial community and crop growth response, expressed as:

[0159]

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

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

[0162]

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

[0164]

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

[0166] Strategy adjustment: According to the optimized bionic simulation model, the strategies for microorganism injection and regulation are adjusted in real time, including microorganism species selection, microorganism quantity adjustment, nutrient solution and growth condition regulation, and microorganism sequential injection, to ensure that the types and quantities of the microorganism community are consistent with the optimization results and to promptly respond to the changing needs of crop growth, realizing the adaptive optimization of the system;

[0167] Through the above, it can quickly respond to changes in the environment and crop requirements, continuously optimize the operating parameters of the system, ensure that the microorganism community and crop growth conditions are always in the best state, improve the stability and efficiency of the system, make the soilless cultivation system in the reclaimed land more adaptable and sustainable, and thus achieve higher crop yields and quality.

[0168] This invention covers any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. For the public to have a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments of this invention. However, those skilled in the art can fully understand this invention without the description of these details. Additionally, well-known methods, processes, procedures, components, and circuits are not described in detail to avoid unnecessary confusion to the essence of this invention.

[0169] The above are only the preferred embodiments of this invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of this invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of this 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, including: 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: Q i (t) = N target,i -N i (t); where Q i (t) is the number of microorganisms i that need to be injected at time t, N target,i The target number of the i-th microorganism recommended for biomimetic simulation, N i (t) represents the number of the i-th microorganism at time t; 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 to achieve the target number recommended by the bionic simulation and optimization results; Feedback learning and adaptive regulation: Continuously analyze the changing trends of microbial communities and crop growth responses, optimize bionic simulation models, and adjust strategies for microbial injection and regulation to achieve adaptive optimization; 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.

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, and 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 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.

7. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 6, 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.

8. The reclaimed land soilless cultivation and green manure intercropping cultivation system according to claim 1, 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 microbial species selection, microbial quantity adjustment, nutrient solution and growth condition regulation, and microbial timing injection.

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