Carbon reduction effect evaluation method and system for healthy agricultural product production process

Abstract

The invention provides a carbon reduction effect evaluation method and system for a healthy agricultural product production process. According to the method, by tracking carbon migration paths of chemical fertilizer application, organic fertilizer degradation and soil respiration and combining matching analysis of chemical reaction chain data and an agricultural carbon emission database, a carbon retention area and methane generation and distribution characteristics in the production process are accurately identified. Modeling is carried out on the concentration of an intermediate product by applying a dynamic compensation engine, a soil pore optimization scheme and an organic fertilizer gradient feeding strategy are generated, and conversion of degradation residues to a stable carbon form is accelerated by regulating and controlling a micro-aerobic environment. Finally, a carbon cycle equilibrium map is constructed, greenhouse gas emission reduction monitoring and effect quantitative evaluation in the whole production period are achieved, and the soil carbon sequestration capacity is synchronously improved. According to the technical scheme provided by the invention, the agricultural production carbon cycle efficiency can be optimized.

Description

Technical Field

[0001] This application relates to the technical field of ecological carbon cycle assessment, and particularly to a method and system for evaluating the carbon reduction effect in the production process of healthy agricultural products. Background Art

[0002] In the production process of healthy agricultural products, it is necessary to accurately trace and quantitatively analyze the carbon footprint of the entire life cycle of agricultural inputs such as chemical fertilizers and pesticides, covering links such as production, transportation, application, and waste treatment, in order to scientifically evaluate the carbon reduction effects of different production management modes. The technical requirements focus on the following aspects: the dynamic collection and cross-linkage ability of the entire life cycle data, the carbon emission modeling and accounting methods based on multi-source heterogeneous data, and the decision-making support function for optimizing the carbon reduction path.

[0003] Currently, the mainstream solution is a digital carbon footprint tracing system based on the Internet of Things sensor network and the life cycle assessment model. This system realizes the automatic collection of the entire chain of data on the production, transportation, application, and waste treatment of chemical fertilizers and pesticides by deploying farmland environment sensors, intelligent agricultural machinery terminals, and supply chain blockchain technology. The dynamic life cycle assessment model is embedded in the regional emission factor library, and the emission accounting results are corrected by combining machine learning algorithms.

[0004] However, this solution still has significant bottlenecks. The contradiction between data coverage and cost is prominent. The deployment cost of high-precision sensors is high, making it difficult for small and medium-sized farms to bear, and there are blind spots in data collection for marginal links such as the recycling of pesticide packaging waste. The dynamic adaptability of the model is insufficient. The existing life cycle assessment parameter library mostly relies on static experimental data and is difficult to respond to the fluctuations of farmland carbon sinks. The decision feedback loop is missing, and there is a lack of interaction ability with the agricultural machinery control system and variable fertilization prescription maps, making it impossible to form a monitoring, evaluation, and regulation closed loop, resulting in the disconnection between carbon reduction suggestions and actual farming operations. Summary of the Invention

[0005] This application provides a method and system for evaluating the carbon reduction effect in the production process of healthy agricultural products to solve the problem of the disconnection between carbon reduction suggestions and actual farming operations in the prior art.

[0006] In a first aspect, this application provides a method for evaluating the carbon reduction effect in the production process of healthy agricultural products, including: Tracking the migration path of carbon elements in chemical fertilizer application, organic fertilizer degradation, and soil respiration, and simultaneously collecting chemical reaction chain data at each stage of the production process; Determining the carbon emission concentration area according to the carbon element migration path, matching the by-product generation amount in the chemical reaction chain data with the pre-stored agricultural carbon emission path database, and analyzing the carbon retention amount caused by incomplete degradation of organic fertilizers and the distribution of residual methane products in the production process; Input the carbon retention amount, methane product distribution, and the concentration of intermediate products in the chemical reaction chain data into the carbon emission dynamic compensation engine, and generate an optimization plan for the soil pore structure and a compensation strategy for the organic fertilizer feeding gradient based on the carbon reduction effect evaluation index in the healthy agricultural product production standard; Adjust the soil ventilation parameters according to the micro-oxygen environment control instruction in the compensation strategy, optimize the soil micro-oxygen environment in combination with the soil pore structure optimization plan, and at the same time control the degradation rate of organic fertilizer through the methane product conversion plan, so that the remaining intermediate products are converted into stable carbon forms to reduce the greenhouse gas emission; Dynamically monitor the migration path corresponding to the stable carbon form, and generate a carbon cycle balance map for evaluating the carbon reduction effect in combination with the adjusted soil ventilation parameters and chemical reaction chain data.

[0007] Optionally, input the carbon retention amount, methane product distribution, and the concentration of intermediate products in the chemical reaction chain data into the carbon emission dynamic compensation engine, and generate an optimization plan for the soil pore structure and an organic fertilizer feeding gradient compensation strategy based on the carbon reduction effect evaluation index in the healthy agricultural product production standard, including: Input the carbon retention amount, methane product distribution, and the concentration of intermediate products in the chemical reaction chain data caused by incomplete degradation of organic fertilizer during the production process into the carbon emission dynamic compensation engine, so as to dynamically determine the optimization range of pore structure parameters according to the obtained soil type and carbon retention amount through the carbon emission dynamic compensation engine, and generate an optimized interval for soil pore diameter classification; Based on the optimized interval for soil pore diameter classification, generate an optimization plan for the soil pore structure in combination with the distribution density of methane-oxidizing bacteria in different soil tillage layers; Through the carbon emission dynamic compensation engine, based on the methane product distribution and intermediate product concentration, analyze the degradation and chain-breaking threshold of plant structural organic matter in organic fertilizer, and generate the correlation rule between the staged feeding gradient and the regulation of the activity of degradation flora in combination with the environmental temperature fluctuation range during the production process; Integrate the optimized interval for soil pore diameter classification and the correlation rule to generate a compensation strategy for the organic fertilizer feeding gradient.

[0008] Optionally, integrate the optimized interval for soil pore diameter classification and the correlation rule to generate an organic fertilizer feeding gradient compensation strategy including a micro-oxygen flux threshold, a feeding time window offset, and a degradation rate compensation factor, including: According to the pore connectivity parameters of different soil types in the optimized interval for soil pore diameter classification, match the attenuation coefficient of the organic fertilizer degradation rate corresponding to the environmental temperature fluctuation in the correlation rule, and generate a dynamic constraint relationship table between the soil pore diameter and the degradation rate; Based on the dynamic constraint relation table, analyze the maximum methane diffusion flux allowed within the optimized interval of soil pore diameter classification, and combine the response delay time between the activity of the degrading bacterial community and the feeding gradient in the association rules to generate a micro-oxygen flux threshold interval and a feeding time window offset compensation range based on the depth of the soil tillage layer; According to the micro-oxygen flux threshold interval, inversely constrain the optimized interval of soil pore diameter classification, screen the pore diameter distribution patterns that meet the metabolic energy level requirements of methane-oxidizing bacteria, and at the same time, dynamically weight the compensation coefficient of the activity of the degrading bacterial community based on the feeding time window offset compensation range to generate an organic fertilizer feeding gradient compensation strategy including pore reconstruction priority, feeding interval hot zone division, and bacterial community activation trigger conditions.

[0009] Optionally, adjust the soil ventilation parameters according to the micro-oxygen environment control instructions in the compensation strategy, optimize the soil micro-oxygen environment in combination with the soil pore structure optimization plan, and at the same time control the degradation rate of organic fertilizer through the methane product conversion plan, including: Based on the compensation strategy, extract the target value range of soil oxygen concentration in the micro-oxygen environment control instructions, and obtain the soil ventilation adjustment parameters according to the soil pore structure optimization plan; According to the micro-oxygen environment control instructions, calculate the deviation between the current soil oxygen concentration and the target value range, and dynamically adjust the working mode of the soil ventilation equipment in combination with the soil ventilation adjustment parameters to generate optimized soil micro-oxygen environment data; According to the methane product conversion plan, determine the target rate range of organic fertilizer degradation, and dynamically adjust the feeding amount and distribution mode of organic fertilizer based on the soil micro-oxygen environment data to control the degradation rate of organic fertilizer.

[0010] Optionally, based on the methane product distribution and intermediate product concentration, analyze the degradation chain-breaking threshold of plant structural organic matter in organic fertilizer, and combine the environmental temperature fluctuation range during the production process to generate the association rules between the staged feeding gradient and the regulation of the activity of the degrading bacterial community, including: Based on the methane product distribution and intermediate product concentration, analyze the degradation chain-breaking threshold of plant structural organic matter in organic fertilizer. According to the degradation chain-breaking threshold, divide the degradation process of organic fertilizer into multiple stages, and determine the feeding gradient range for each stage; According to the environmental temperature fluctuation range during the production process, identify the influence law of temperature change on the degradation chain-breaking threshold, and establish the mapping relationship between temperature and the degradation chain-breaking threshold. Combine the mapping relationship to analyze the change trend of the activity of the degrading bacterial community under different temperature conditions, and determine the influence law of temperature on the activity of the degrading bacterial community; Generate the association rules for the staged feeding gradient and the regulation of the activity of the degrading microbial community based on the degradation breakage threshold and the feeding gradient range, and in combination with the influence law.

[0011] Optionally, determine the target rate range for the degradation of organic fertilizers according to the methane product conversion scheme, and dynamically adjust the feeding amount and distribution mode of organic fertilizers based on the soil micro-oxic environment data to control the degradation rate of organic fertilizers, including: According to the methane product conversion scheme, extract the target rate range for the degradation of organic fertilizers, including the upper limit value and the lower limit value of the degradation rate, and based on the soil micro-oxic environment data, analyze the influence of the current soil oxygen concentration on the degradation rate, and determine the applicable conditions for the target rate range; According to the target rate range, calculate the deviation amount between the current degradation rate of organic fertilizers and the target rate range, and determine the adjustment amount of the feeding amount based on the deviation amount; Based on the applicable conditions of the target rate range, and dynamically adjust the feeding amount and distribution mode of organic fertilizers according to the adjustment amount to ensure that the degradation rate is stable within the target rate range; Optionally, dynamically monitor the migration path of the stable carbon form, and generate a carbon cycle balance map for evaluating the carbon reduction effect in combination with the adjusted chemical reaction chain data, including: Set monitoring points along the geographical distribution of the field irrigation channels during the production process, and collect the retention amount and lateral diffusion rate of the stable carbon form at different soil tillage layer depths, and integrate the collected retention amount and diffusion rate data to generate dynamic monitoring data corresponding to the migration path with the field irrigation channel as the geographical reference; According to the dynamic monitoring data, analyze the migration time delay amount of the stable carbon form under the soil pore connectivity gradient, and combine the change rate of the concentration of the intermediate product of organic fertilizer degradation in the adjusted chemical reaction chain data to generate a dynamic mapping relationship table between the conversion efficiency of the stable carbon form and the degradation rate; Based on the dynamic mapping relationship table, match the constraints of the tillage layer depth and the migration rate of the stable carbon form of different soil textures in the open farmland to generate a set of carbon cycle dynamic parameters including the boundary of the humus retention hot zone, the lateral diffusion gradient of biochar, and the priority of methane oxidation inhibition; Perform spatial superposition of the set of carbon cycle dynamic parameters and the adjusted chemical reaction chain data to generate a carbon cycle balance map with the tillage layer depth as the vertical axis and the field irrigation channel as the horizontal axis.

[0012] In a second aspect, the present application provides a method for evaluating the carbon reduction effect in the production process of healthy agricultural products, including: A collection module that tracks the migration path of carbon elements in chemical fertilizer application, organic fertilizer degradation, and soil respiration, and simultaneously collects chemical reaction chain data at each stage during the production process; A matching module determines carbon emission concentration regions based on the carbon element migration paths, matches the by-product generation amounts in the chemical reaction chain data with a pre-stored agricultural carbon emission path database, and analyzes the carbon retention amount caused by incomplete degradation of organic fertilizers and the distribution of residual methane products during the production process; A compensation module inputs the carbon retention amount, methane product distribution, and intermediate product concentration in the chemical reaction chain data into a carbon emission dynamic compensation engine, and generates an optimization plan for the soil pore structure and a compensation strategy for the organic fertilizer feeding gradient based on the carbon reduction effect evaluation index in the healthy agricultural product production standard; An adjustment module adjusts the soil ventilation parameters according to the micro-oxygen environment control instruction in the compensation strategy, optimizes the soil micro-oxygen environment in combination with the soil pore structure optimization plan, and simultaneously controls the degradation rate of organic fertilizers through the methane product conversion plan, so that the residual intermediate products are converted into stable carbon forms to reduce greenhouse gas emissions; A generation module dynamically monitors the migration path corresponding to the stable carbon form, and generates a carbon cycle balance map for evaluating the carbon reduction effect in combination with the adjusted soil ventilation parameters and chemical reaction chain data.

[0013] In a third aspect, an embodiment of the present application provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a carbon reduction effect evaluation method for the production process of healthy agricultural products as described in the first aspect above.

[0014] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, and when the computer program is executed by a computer, it implements a carbon reduction effect evaluation method for the production process of healthy agricultural products as described in the first aspect.

[0015] In the embodiments of the present application, the migration path of carbon elements in chemical fertilizer application, organic fertilizer degradation, and soil respiration is traced, and chemical reaction chain data at each stage of the production process is collected; the carbon emission concentration area is determined according to the carbon element migration path, and the by-product generation amount in the chemical reaction chain data is matched with the pre-stored agricultural carbon emission path database to analyze the carbon retention amount caused by incomplete degradation of organic fertilizer and the distribution of residual methane products in the production process; the carbon retention amount, methane product distribution, and the concentration of intermediate products in the chemical reaction chain data are input into the carbon emission dynamic compensation engine, and an optimization plan for the soil pore structure and a compensation strategy for the organic fertilizer feeding gradient are generated based on the carbon reduction effect evaluation index in the healthy agricultural product production standard; the soil ventilation parameters are adjusted according to the micro-oxygen environment control instruction in the compensation strategy, and the soil micro-oxygen environment is optimized in combination with the soil pore structure optimization plan. At the same time, the degradation rate of organic fertilizer is controlled through the methane product conversion plan, so that the residual intermediate products are converted into stable carbon forms to reduce the greenhouse gas release amount; the migration path corresponding to the stable carbon form is dynamically monitored, and a carbon cycle balance map for evaluating the carbon reduction effect is generated in combination with the adjusted soil ventilation parameters and chemical reaction chain data.

[0016] The technical solution of the present application has the following beneficial effects: By tracing the migration path of carbon elements in chemical fertilizer application, organic fertilizer degradation, and soil respiration and combining with the collection of chemical reaction chain data, the present application realizes the accurate monitoring and quantitative analysis of the carbon footprint in the agricultural production process; by matching the agricultural carbon emission path database, the carbon emission concentration area is accurately identified, and the carbon retention amount and methane product distribution caused by incomplete degradation of organic fertilizer are analyzed, providing data support for carbon emission reduction; based on the dynamic compensation engine, an optimization plan for the soil pore structure and a compensation strategy for the organic fertilizer feeding gradient are generated, effectively improving the soil carbon sequestration capacity and optimizing the fertilizer utilization efficiency; by adjusting the soil ventilation parameters through the micro-oxygen environment control instruction and combining with the methane product conversion plan, the intermediate products are promoted to be converted into stable carbon forms, significantly reducing the greenhouse gas release amount; finally, by dynamically monitoring the migration path of the stable carbon form and combining with the adjusted chemical reaction chain data, a carbon cycle balance map is generated, providing a scientific evaluation basis for the carbon reduction effect in the production process of healthy agricultural products, and realizing the low-carbon and sustainable optimization of the entire agricultural production cycle.

[0017] Furthermore, by inputting the carbon retention amount, methane product distribution, and intermediate product concentration into the carbon emission dynamic compensation engine, and dynamically matching the pore structure parameter constraints in combination with the soil type, an optimized interval for soil pore diameter grading adapted to the organic matter decomposition rate is generated; based on the distribution density of methanotrophic bacteria, a soil pore structure optimization scheme with pore connectivity and gas diffusion resistance as constraints is constructed; finally, by integrating soil pore optimization and feeding rules, an organic fertilizer feeding gradient compensation strategy including micro-oxygen flux threshold, feeding time window offset, and degradation rate compensation factor is generated to achieve the collaborative optimization of soil structure and fertilizer degradation. Based on the degradation chain-breaking threshold and temperature fluctuation, a phased feeding gradient is generated to maximize fertilizer degradation efficiency and minimize carbon emissions, providing an efficient and low-carbon soil management and fertilizer application solution for the production of healthy agricultural products.

[0018] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application 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 some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 The flowchart of a carbon emission reduction effect evaluation method for the production process of healthy agricultural products provided by the present application is shown; Figure 2 The structural schematic diagram of a carbon emission reduction effect evaluation system for the production process of healthy agricultural products provided by the present application is shown; Figure 3 The structural schematic diagram of a computing device provided by the present application is shown. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0022] In some of the processes described in the specification, claims, and above-mentioned drawings of this application, a plurality of operations appear in a specific order. However, it should be clearly understood that these operations can be executed not in the order in which they appear herein or in parallel. The operation numbers such as 101, 102, etc. are only used to distinguish different operations, and the numbers themselves do not represent any execution order. Additionally, these processes may include more or fewer operations, and these operations can be executed sequentially or in parallel. It should be noted that the descriptions such as "first", "second", etc. in this text are used to distinguish different messages, devices, modules, etc., do not represent a sequence, and do not limit that "first" and "second" are of different types.

[0023] This application aims to develop a carbon reduction effect evaluation and optimization system for the production process of healthy agricultural products. By tracking the carbon element migration path, collecting chemical reaction chain data, and matching the agricultural carbon emission database, it accurately analyzes the carbon retention amount and the distribution of methane products. Combining with a dynamic compensation engine, it generates an optimized soil pore scheme and an organic fertilizer feeding gradient compensation strategy to regulate the micro-oxygen environment and promote the conversion of intermediate products into stable carbon forms. Finally, through dynamic monitoring and the construction of a carbon cycle balance map, it realizes the accurate monitoring of the carbon footprint throughout the agricultural production cycle, the optimization of greenhouse gas emissions reduction, and the scientific evaluation of the carbon reduction effect, providing low-carbon and sustainable technical support for the production of healthy agricultural products.

[0024] Next, the technical solutions in the embodiments of this application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of this application.

[0025] Figure 1 The following is a flowchart of a method for evaluating the carbon reduction effect in the production process of healthy agricultural products provided for the embodiments of this application, as Figure 1 shown, the method includes: 101. Track the carbon element migration path in chemical fertilizer application, organic fertilizer degradation, and soil respiration, and at the same time collect chemical reaction chain data at each stage of the production process; In this step, the carbon element migration path refers to the dynamic flow trajectory of carbon elements in the processes of chemical fertilizer application, organic fertilizer degradation, and soil respiration, including the process of carbon from organic fertilizer to soil and then to the atmosphere.

[0026] The chemical reaction chain data refers to the chemical reaction data at each stage of the production process, including reactants, intermediate products, by-products, and their concentration changes.

[0027] In the embodiments of the present application, first, a sensor network is deployed to monitor the flow of carbon elements in the soil. Combining with gas chromatography - mass spectrometry technology, the carbon form changes during the degradation of organic fertilizers are analyzed to determine the migration path of carbon elements. Then, a reactor experiment is used to simulate the chemical reactions in the production process, and chemical reaction chain data is collected, including the concentration changes of reactants, intermediate products, and by - products. Finally, by integrating the carbon element migration path and the chemical reaction chain data, a complete carbon flow model is formed to provide basic data support for subsequent analysis.

[0028] In a certain farmland, high - precision soil carbon sensors and gas collection equipment are deployed to monitor the carbon release during the degradation of organic fertilizers. At the same time, a reactor experiment device is set up in the laboratory to simulate the production process of organic fertilizers, and the by - product generation amounts at each stage in the reaction chain are recorded. Through the analysis by gas chromatography - mass spectrometry technology, it is found that a large amount of carbon dioxide and a small amount of methane are generated during the degradation of organic fertilizers. After data integration, the migration path of carbon elements and the key nodes in the reaction chain are initially determined. For example, it is found that the carbon emission in a certain area is significantly higher than that in other areas.

[0029] 102. Determine the carbon emission concentration area according to the carbon element migration path, combine the by - product generation amounts in the chemical reaction chain data with the pre - stored agricultural carbon emission path database for matching, and analyze the carbon retention amount and the distribution of residual methane products caused by incomplete degradation of organic fertilizers during the production process; In this step, the carbon emission concentration area refers to the area where the carbon emission in the carbon element migration path is significantly higher than that in other areas.

[0030] The carbon retention amount refers to the amount of carbon elements retained in the soil due to incomplete degradation of organic fertilizers. The distribution of methane products refers to the spatial distribution of methane generated during the degradation of organic fertilizers in the soil.

[0031] The agricultural carbon emission path database is a pre - stored data set for matching carbon emission paths. The random forest algorithm is a machine learning algorithm used to predict hot spots of methane generation.

[0032] In the embodiments of the present application, first, based on the carbon migration path, spatial data analysis technology is used to determine the carbon emission concentration area, and it is found that the carbon emission in a certain farmland is significantly higher than that in other areas. Then, combining the by - product generation amounts in the chemical reaction chain data, it is matched with the pre - stored agricultural carbon emission path database to analyze the carbon retention amount and the distribution of methane products. Then, the hot spots of methane generation are predicted through the random forest algorithm. Finally, it is found that the retained carbon is converted into methane under specific conditions, forming hot spots in the distribution of methane products. This analysis result provides an important basis for subsequent carbon emission compensation.

[0033] Based on the previous process, spatial analysis of the carbon emission data of farmland was carried out using GIS tools, and it was found that the carbon emissions in a certain area were significantly higher than those in other areas. By matching the agricultural carbon emission path database, it was found that the degradation of organic fertilizers in this area was incomplete, resulting in a large amount of carbon retention. Further analysis found that the retained carbon was converted into methane under anaerobic conditions, forming a hot spot for methane production distribution. Through prediction by the random forest algorithm, the hot spots for methane production were mainly concentrated in the deep soil area, providing a target area for subsequent methane conversion schemes.

[0034] 103. Input the carbon retention amount, methane production distribution, and the concentration of intermediate products in the chemical reaction chain data into the carbon emission dynamic compensation engine, and generate an optimization plan for soil pore structure and a compensation strategy for the feeding gradient of organic fertilizers based on the carbon reduction effect evaluation index in the healthy agricultural product production standard; In this step, the carbon emission dynamic compensation engine is a system based on an algorithm model, which is used to dynamically adjust the carbon retention amount and methane production distribution to reduce carbon emissions.

[0035] The optimization plan for soil pore structure refers to improving the migration and conversion efficiency of carbon elements by adjusting the soil pore structure.

[0036] The compensation strategy for the feeding gradient of organic fertilizers refers to dynamically adjusting the feeding amount and frequency of organic fertilizers according to the carbon retention amount. The genetic algorithm is an algorithm used to generate optimization plans.

[0037] The healthy agricultural product production standard is a standard system used to evaluate the carbon reduction effect.

[0038] In the example of this application, first, input the carbon retention amount, methane production distribution, and chemical reaction chain data into the carbon emission dynamic compensation engine, and based on the carbon reduction effect evaluation index in the healthy agricultural product production standard. Then, use the genetic algorithm to generate an optimization plan for soil pore structure and a compensation strategy for the feeding gradient of organic fertilizers. Then, by optimizing the soil pore structure, increasing the oxygen supply, and promoting the stable conversion of carbon elements; finally, dynamically adjust the feeding amount of organic fertilizers according to the carbon retention amount to reduce carbon emissions. This plan provides specific guidance for subsequent micro-oxygen environment control.

[0039] Based on the previous process, input the data into the carbon emission dynamic compensation engine, and the system generates an optimization plan: by increasing soil ventilation equipment, adjusting the soil pore structure to increase oxygen supply, and at the same time dynamically reducing the feeding amount of organic fertilizers according to the carbon retention amount. After implementing this plan, the carbon emissions of the farmland are significantly reduced, the conversion efficiency of carbon elements in the soil is improved, and the methane production is reduced.

[0040] 104. Adjust soil aeration parameters according to the micro-aerobic environment control instructions in the compensation strategy, optimize the soil micro-aerobic environment in combination with the soil pore structure optimization scheme, and control the degradation rate of organic fertilizers through the methane product conversion scheme to convert the residual intermediate products into stable carbon forms, so as to reduce greenhouse gas release; In this step, the micro-aerobic environment control instruction refers to creating a micro-aerobic environment suitable for the stable conversion of carbon elements by adjusting soil ventilation parameters.

[0041] The methane conversion program refers to converting methane into a stable carbon form by controlling the degradation rate of organic fertilizers.

[0042] The soil pore structure optimization program refers to a program that improves the migration and conversion efficiency of carbon elements by optimizing the soil pore structure (such as pore diameter, connectivity, etc.).

[0043] In the present application example, according to the micro-oxygen environment control instructions in the compensation strategy, the soil ventilation parameters are dynamically adjusted to ensure the stability of the soil micro-oxygen environment. At the same time, in combination with the soil pore structure optimization scheme, the soil micro-oxygen environment is further optimized by adjusting the soil pore diameter and connectivity, and the migration and conversion efficiency of carbon elements are improved. In addition, the degradation rate of organic fertilizers is controlled by the methane product conversion scheme, and the degradation process is accelerated by bio-enzyme technology, and the residual intermediate products are converted into stable carbon forms to reduce the release of greenhouse gases such as methane. Ultimately, by optimizing the soil micro-oxygen environment and controlling the degradation rate of organic fertilizers, efficient conversion of carbon elements and significant reduction in greenhouse gas emissions are achieved.

[0044] On the basis of the previous process, soil aeration equipment was installed and aeration parameters were adjusted to create a micro-oxygen environment. At the same time, bio-enzyme preparations were sprayed to accelerate the degradation of organic fertilizers and convert methane into a stable carbon form. Through monitoring, it was found that greenhouse gas emissions were significantly reduced, and the carbon elements in the soil were mainly converted into stable organic carbon, further reducing carbon emissions.

[0045] 105. Dynamically monitor the migration path corresponding to the stable carbon form, and generate a carbon cycle balance map for evaluating the carbon reduction effect by combining the adjusted soil aeration parameters and chemical reaction chain data.

[0046] In this step, the stable carbon form migration path refers to the dynamic flow trajectory of carbon elements after they are converted into a stable form.

[0047] The carbon cycle balance map is a comprehensive map used to evaluate the carbon reduction effect, including the input, output and retention of carbon elements.

[0048] Data visualization is a technique used to generate carbon cycle balance maps.

[0049] The adjusted soil aeration parameters refer to the soil aeration parameters optimized according to the micro-oxygen environment control instructions.

[0050] In the example of this application, first, the migration path data of stable carbon forms are collected through the sensor network, and its flow law in the soil is analyzed. Then, combined with the adjusted soil aeration parameters and chemical reaction chain data, the data are integrated using spatial overlay technology to generate a carbon cycle balance map. Through map analysis, the carbon reduction effect is evaluated, and the soil micro-oxygen environment and the degradation rate of organic fertilizers are further optimized to ensure the continuous reduction of carbon emissions in the agricultural production process.

[0051] On the basis of the previous process, continue to monitor the migration path of stable carbon forms, and it is found that carbon elements mainly remain in the deep soil layer. Combined with the adjusted chemical reaction chain data, a carbon cycle balance map is generated, and it is found that the carbon cycle in the farmland tends to be balanced, and the carbon reduction effect is significant. Through further optimization of the plan, the carbon emissions in the farmland are further reduced, achieving the goal of low-carbon agricultural production.

[0052] In summary, through steps 101 to 105, the carbon emissions in the agricultural production process are effectively reduced by tracking the migration path of carbon elements, analyzing the concentrated areas of carbon emissions, dynamically compensating for carbon emissions, optimizing the soil pore structure, and controlling the micro-oxygen environment. At the same time, by monitoring the migration path of stable carbon forms and generating a carbon cycle balance map, it provides a scientific basis for the sustainable development of agricultural production and achieves the goals of low-carbon and high-efficiency agricultural production.

[0053] The following is a carbon reduction production process for healthy agricultural products: First, select excellent crop varieties, preferably crop varieties with disease resistance, stress tolerance, and high carbon sequestration ability, and plant them in combination with high photosynthetic efficiency varieties such as leguminous plants to reduce pesticide dependence and reduce the application rate of chemical fertilizers. Strictly follow the non-GMO certification standards to avoid the risk of gene pollution and ensure that the varieties meet the production requirements of healthy agricultural products, reducing the use of chemical inputs from the source.

[0054] Secondly, construct a healthy production environment. Analyze the soil carbon retention amount and type through a dynamic compensation engine to generate an optimized plan for pore diameter grading (such as 0.1 - 0.3 mm) to improve the oxygen diffusion efficiency and inhibit methane generation; deploy soil aeration equipment to regulate the micro-oxygen environment (target oxygen concentration 0.5 - 1.2 mg / L) to accelerate the conversion of organic fertilizers into stable humus. Regularly take soil samples to monitor the heavy metal content, and adopt soil remediation technology according to the actual situation to provide a safe soil environment for crop growth. At the same time, the ambient air quality should meet the secondary standards in GB 3095 and the regulations in GB 9137, and the irrigation water quality should meet the regulations in GB 5084.

[0055] Then, green and efficient means of production are invested, combined with meteorological sensors, using GIS, remote sensing and other technologies, based on the degradation chain breaking threshold and the law of environmental temperature fluctuations, a phased organic fertilizer gradient feeding strategy is formulated (such as 3 days / time in high temperature period and 7 days / time in low temperature period), combined with biochar addition to improve soil pore connectivity and reduce lateral diffusion of methane. Microbial agents are used to replace chemical pesticides to inhibit diseases. The use of low-energy agricultural machinery and equipment is encouraged to promote energy conservation and utilization. The integrated intelligent irrigation system uses water-fertilizer integration technology to accurately control resource input, reduce nitrogen leaching and water resource waste, and achieve efficient utilization of means of production and minimize carbon emissions.

[0056] Then, precision agriculture management is implemented to monitor carbon migration paths (such as CO2 and CH4 release) and identify carbon emission hotspots. Data such as carbon retention and methane distribution are input into the compensation engine to generate soil aeration parameter optimization instructions (such as adjusting the rotary tillage depth to 15-20cm) and dynamic correction plans for feed amount. By integrating the stable carbon form migration path and chemical reaction chain data, a carbon cycle balance map with the tillage layer depth as the vertical axis and the field irrigation channel as the horizontal axis is constructed to quantify the carbon reduction effect, and optimize the distribution of organic fertilizers according to the boundaries of the humus retention hotspot to maximize the soil carbon sequestration efficiency.

[0057] Finally, the healthy agricultural product output and certification, detection of pesticide residues and heavy metal content, ensure that the product complies with the provisions of GB2763 and GB2762; simultaneous evaluation of fruit appearance such as size and color, determination of nutritional indicators such as vitamins and minerals and taste indicators such as volatile flavor substances, and evaluation of the health of agricultural products. Based on the carbon cycle map, the carbon emission intensity per unit output (kgCO2e / kg) is calculated, and the "low-carbon healthy agricultural product" certification mark is applied; blockchain technology is used to record the data of the entire life cycle (such as fertilizer source, degradation efficiency), and a transparent traceability system for planting is constructed to enhance consumer trust. Ultimately, through the synergy of environmental benefits and social benefits, a trinity of agricultural production models of "low carbon-high quality-high efficiency" is achieved.

[0058] In order to solve the problems of carbon retention, methane generation and greenhouse gas emissions caused by incomplete degradation of organic fertilizers in agricultural production, a soil pore structure and organic fertilizer feeding optimization system based on a carbon emission dynamic compensation engine has been developed to achieve soil structure optimization, fertilizer degradation efficiency improvement and effective control of greenhouse gas emissions, providing low-carbon and sustainable technical support for the production of healthy agricultural products. In some embodiments, the carbon retention amount, methane product distribution and intermediate product concentration in the chemical reaction chain data are input into the carbon emission dynamic compensation engine in step 103, and the soil pore structure optimization scheme and organic fertilizer feeding gradient compensation strategy are generated based on the carbon reduction effect evaluation index in the healthy agricultural product production standard, including: 201. Input the carbon retention amount, methane product distribution, and the concentration of intermediate products in the chemical reaction chain data caused by incomplete degradation of organic fertilizers during the production process into the carbon emission dynamic compensation engine, so as to dynamically determine the optimization range of pore structure parameters according to the obtained soil type and carbon retention amount through the carbon emission dynamic compensation engine, and generate an optimized interval for soil pore diameter grading; In step 201, the carbon retention amount refers to the amount of carbon elements retained in the soil due to incomplete degradation of organic fertilizers. The methane product distribution refers to the spatial distribution of methane generated during the degradation of organic fertilizers in the soil, which is usually closely related to the anaerobic environment and organic matter content of the soil. The concentration of intermediate products refers to the concentration value of intermediate products generated during the reaction in the chemical reaction chain data. The carbon emission dynamic compensation engine is a system based on an algorithm model used to dynamically adjust the carbon retention amount and methane product distribution to reduce carbon emissions. Its core function is to generate a carbon reduction strategy through data analysis and optimization algorithms. The soil type refers to the classification of the physical and chemical properties of farmland soil, including sandy soil, clay soil, etc. Different soil types have a significant impact on the migration and transformation efficiency of carbon elements. The pore structure parameters refer to the parameters affecting the soil pore structure, such as pore diameter, pore connectivity, etc. The optimized interval for soil pore diameter grading refers to the optimized range of pore diameter dynamically determined according to the carbon retention amount and soil type. By adjusting the pore diameter, the conversion efficiency of carbon elements can be improved.

[0059] In the embodiment of the present application, first, data on carbon retention amount, methane product distribution, and intermediate product concentration are obtained through a sensor network and laboratory analysis and input into the carbon emission dynamic compensation engine. Then, the engine dynamically determines the optimization range of pore structure parameters according to the soil type and carbon retention amount using an optimization algorithm and generates an optimized interval for soil pore diameter grading. Specifically, the engine determines the optimization range of pore diameter by analyzing the influence of different soil types on carbon retention amount, combined with the concentration of intermediate products and methane product distribution. Finally, this interval provides a scientific basis for the subsequent optimization of soil pore structure, ensuring the maximization of the migration and transformation efficiency of carbon elements and reducing greenhouse gas emissions.

[0060] 202. Based on the optimized interval for soil pore diameter grading, combine the distribution density of methane-oxidizing bacteria in different soil tillage layers to generate an optimized scheme for soil pore structure; In step 202, the optimized range of soil pore diameter classification refers to the optimized range of pore diameter determined dynamically according to the carbon retention amount and soil type. The soil tillage layer refers to the thickness of the tillage layer of farmland soil, which is usually divided into the surface layer, middle layer and deep layer. Different tillage layers have a significant impact on the migration and transformation efficiency of carbon elements. The distribution density of methane-oxidizing bacteria refers to the distribution of methane-oxidizing bacteria in the soil. Methane-oxidizing bacteria are microorganisms that can convert methane into carbon dioxide and water, and their distribution density directly affects the conversion efficiency of methane. The soil pore structure optimization scheme refers to the scheme for improving the migration and transformation efficiency of carbon elements by optimizing the soil pore structure, specifically including adjusting parameters such as pore diameter and pore connectivity.

[0061] In the embodiments of the present application, first, the optimized range of pore diameter is determined through the optimized range of soil pore diameter classification. Then, in combination with the distribution density of methane-oxidizing bacteria in different soil tillage layers, a soil pore structure optimization scheme is generated using spatial analysis technology. Specifically, by analyzing the distribution density of methane-oxidizing bacteria in different tillage layers and combining the optimized range of pore diameter, the optimization scheme of the pore structure is determined. Finally, by optimizing the soil pore structure, the activity of methane-oxidizing bacteria is improved, the conversion of methane is promoted, greenhouse gas emissions are reduced, and the efficient conversion of carbon elements is achieved.

[0062] 203. Based on the methane product distribution and intermediate product concentration, the carbon emission dynamic compensation engine analyzes the degradation and chain-breaking threshold of plant structural organic matter in organic fertilizers, and combines the environmental temperature fluctuation range during the production process to generate the correlation rule between the staged feeding gradient and the regulation of the activity of the degradation bacterial community; In step 203, the methane product distribution refers to the spatial distribution of methane generated during the degradation of organic fertilizers in the soil. The intermediate product concentration refers to the concentration value of the intermediate product generated during the reaction process in the chemical reaction chain data. The degradation and chain-breaking threshold of plant structural organic matter refers to the chain-breaking conditions of plant structural organic matter in organic fertilizers during degradation, including factors such as temperature, humidity and microbial activity. The environmental temperature fluctuation range refers to the change range of the environmental temperature during the production process, and the temperature fluctuation has a significant impact on the degradation rate of organic fertilizers. The staged feeding gradient refers to the feeding amount of organic fertilizers dynamically adjusted according to the degradation and chain-breaking threshold and the environmental temperature fluctuation range. By staged feeding, the degradation efficiency of organic fertilizers can be improved. The correlation rule for regulating the activity of the degradation bacterial community refers to the rule for dynamically adjusting the feeding gradient according to the activity of the degradation bacterial community. By regulating the activity of the degradation bacterial community, the degradation efficiency of organic fertilizers can be improved.

[0063] In the embodiments of the present application, first, the degradation and chain-breaking threshold of plant structural organic matter is analyzed through the distribution of methane products and the concentration of intermediate products to determine the key influencing factors during the degradation process. Then, in combination with the environmental temperature fluctuation range, data mining technology is used to generate the association rules between the staged feeding gradient and the regulation of the activity of the degradation flora. Specifically, by analyzing the influence of environmental temperature fluctuations on the degradation and chain-breaking threshold, and combining the distribution of methane products and the concentration of intermediate products, the association rules between the staged feeding gradient and the regulation of the activity of the degradation flora are generated. Finally, by dynamically adjusting the feeding gradient, the degradation efficiency of the organic fertilizer is maximized, carbon retention and methane generation are reduced, and the low-carbon goal of agricultural production is achieved.

[0064] 204. Integrate the optimized range of the soil pore diameter classification with the association rules to generate a compensation strategy for the organic fertilizer feeding gradient.

[0065] In step 204, the optimized range of the soil pore diameter classification refers to the optimized range of the pore diameter dynamically determined according to the carbon retention amount and the soil type. The association rules refer to the rules for the staged feeding gradient and the regulation of the activity of the degradation flora. The compensation strategy for the organic fertilizer feeding gradient refers to the organic fertilizer feeding strategy dynamically adjusted according to the optimized range of the soil pore diameter classification and the association rules. By dynamically adjusting the feeding gradient, the degradation efficiency of the organic fertilizer can be improved and carbon emissions can be reduced.

[0066] In the embodiments of the present application, first, the optimized range of the pore structure is determined according to the optimized range of the soil pore diameter classification. Then, in combination with the association rules, an optimization algorithm is used to generate a compensation strategy for the organic fertilizer feeding gradient. Specifically, by analyzing the influence of the optimized range of the pore structure on the degradation efficiency, and combining the association rules between the staged feeding gradient and the regulation of the activity of the degradation flora, a compensation strategy for the organic fertilizer feeding gradient is generated. Finally, by dynamically adjusting the organic fertilizer feeding gradient, the degradation efficiency of the organic fertilizer is maximized, carbon emissions are reduced, and the sustainable development of agricultural production is achieved.

[0067] The following is a specific example: In the practical application of carbon footprint tracing in the whole life cycle of agricultural inputs, taking a large-scale corn planting base as an example, first, the carbon retention amount caused by incomplete degradation of organic fertilizers, the distribution of methane products, and the concentration of intermediate products in the chemical reaction chain data during the production process are input into the carbon emission dynamic compensation engine. Based on the obtained soil types (such as loam and clay) and carbon retention amount, the engine dynamically determines the optimization range of pore structure parameters and generates an optimized interval for soil pore diameter grading (such as 0.1 - 0.3 mm). Based on this interval, combined with the distribution density of methane-oxidizing bacteria in different soil tillage layers (such as 0 - 20 cm), an optimized soil pore structure plan is generated to ensure that the pore connectivity and gas diffusion resistance meet the methane oxidation requirements. Subsequently, based on the distribution of methane products and the concentration of intermediate products, the engine analyzes the degradation breakage threshold of plant structural organic matter (such as cellulose and hemicellulose) in organic fertilizers, and combined with the environmental temperature fluctuation range during the production process (such as 15 - 35 °C), generates the association rules between the staged feeding gradient and the regulation of the activity of degradation bacteria groups. For example, when the temperature is higher than 25 °C, the feeding interval is shortened to 3 days, and the activity compensation coefficient of the degradation bacteria group is increased to 1.5. Finally, by integrating the optimized interval for soil pore diameter grading and the association rules, a compensation strategy for the organic fertilizer feeding gradient is generated, including the micro-oxygen flux threshold (0.5 - 1.2 mg / L), the offset of the feeding time window (±3 days), and the degradation rate compensation factor (1.2 - 1.5), realizing the dynamic optimization and precise control of carbon emissions during the corn planting process.

[0068] In summary, through steps 201 to 204, the dynamic analysis based on soil types and carbon retention amount is realized, the optimization range of pore structure parameters is accurately determined, and the optimized interval for soil pore diameter grading is generated, providing a scientific basis for the optimization of the soil microecological environment; effectively improving the soil gas diffusion efficiency and methane oxidation ability; further, by analyzing the degradation breakage threshold of plant structural organic matter in organic fertilizers, the efficiency and stability of the organic fertilizer degradation process are ensured; finally, a compensation strategy for the organic fertilizer feeding gradient is generated, significantly improving the organic matter degradation efficiency and soil carbon sink capacity, and providing a systematic and precise technical solution for greenhouse gas emission reduction and green and low-carbon transformation in the agricultural production process.

[0069] To address the issues of carbon retention and methane emissions caused by the mismatch between the soil pore structure and the degradation efficiency of organic fertilizers in agricultural production, a generation system for the organic fertilizer feeding gradient compensation strategy based on dynamic constraint relationships has been developed. It realizes the coordinated optimization of the soil pore structure and fertilizer degradation efficiency, significantly improves the degradation efficiency of organic fertilizers, and effectively reduces greenhouse gas emissions, providing precise technical support for the low-carbonization of agricultural production. In some embodiments, in step 204, the generation of the organic fertilizer feeding gradient compensation strategy by integrating the soil pore diameter grading optimization interval and the association rule, including the micro-oxygen flux threshold, the feeding time window offset, and the degradation rate compensation factor, includes: 301. According to the pore connectivity parameters of different soil types in the soil pore diameter grading optimization interval, match the attenuation coefficient of the organic fertilizer degradation rate corresponding to the environmental temperature fluctuation in the association rule, and generate a dynamic constraint relationship table between the soil pore diameter and the degradation rate; In step 301, the soil pore diameter grading optimization interval refers to the pore diameter optimization range adapted according to the organic matter decomposition rate. The pore connectivity parameter refers to the degree of connectivity between soil pores. The environmental temperature fluctuation refers to the change range of the environmental temperature during the production process. The attenuation coefficient of the organic fertilizer degradation rate refers to the influence coefficient of the environmental temperature fluctuation on the organic fertilizer degradation rate. The dynamic constraint relationship table refers to the dynamic relationship table between the soil pore diameter and the degradation rate, which is used to guide the optimization of the pore structure and the feeding strategy of organic fertilizers.

[0070] In the embodiments of the present application, first, by analyzing the pore connectivity parameters of different soil types, determine its influence on the organic fertilizer degradation rate. According to the pore connectivity parameters of different soil types in the soil pore diameter grading optimization interval, match the attenuation coefficient of the organic fertilizer degradation rate corresponding to the environmental temperature fluctuation in the association rule. Then, combined with the influence of the environmental temperature fluctuation on the degradation rate, use the data matching technology to generate a dynamic constraint relationship table. Generate a dynamic constraint relationship table between the soil pore diameter and the degradation rate. Finally, through the dynamic constraint relationship table, clarify the relationship between the soil pore diameter and the degradation rate, providing a basis for the subsequent generation of the micro-oxygen flux threshold interval and the feeding time window offset compensation range.

[0071] 302. Based on the dynamic constraint relationship table, analyze the maximum methane diffusion flux allowed within the soil pore diameter grading optimization interval, and combine the response delay time between the degradation flora activity and the feeding gradient in the association rule to generate a micro-oxygen flux threshold interval and a feeding time window offset compensation range based on the depth of the soil tillage layer; In step 302, the maximum methane diffusion flux refers to the maximum amount of methane diffusion allowed in the soil. The response delay time of the degradation flora activity to the feeding gradient refers to the response time of the degradation flora activity to the change in the feeding gradient. The depth of the soil tillage layer refers to the thickness of the tillage layer of farmland soil. The micro-oxygen flux threshold interval refers to the oxygen flux range in the micro-oxygen environment of the soil. The compensation range of the feeding time window offset refers to the feeding time offset range dynamically adjusted according to the degradation flora activity.

[0072] In the embodiment of the present application, first, the maximum methane diffusion flux is determined through the dynamic constraint relationship table to ensure the maximization of methane oxidation efficiency. Based on the dynamic constraint relationship table, the maximum methane diffusion flux allowed within the optimized interval of the soil pore diameter classification is analyzed. Then, in combination with the response delay time of the degradation flora activity to the feeding gradient, an optimization algorithm is used to generate the micro-oxygen flux threshold interval and the compensation range of the feeding time window offset. The micro-oxygen flux threshold interval and the compensation range of the feeding time window offset are generated based on the depth of the soil tillage layer. Finally, based on the depth of the soil tillage layer, the applicability and effectiveness of the micro-oxygen flux threshold interval and the compensation range of the feeding time window offset are ensured.

[0073] 303. Perform reverse constraint on the optimized interval of the soil pore diameter classification according to the micro-oxygen flux threshold interval, screen the pore diameter distribution pattern that meets the metabolic energy level requirements of methane-oxidizing bacteria, and at the same time perform dynamic weighting on the degradation flora activity compensation coefficient based on the compensation range of the feeding time window offset to generate an organic fertilizer feeding gradient compensation strategy including the pore reconstruction priority, the division of the feeding interval hot zone, and the triggering condition for flora activation.

[0074] In step 303, the metabolic energy level requirements of methane-oxidizing bacteria refer to the requirements for the pore diameter during the metabolism of methane-oxidizing bacteria. The pore diameter distribution pattern refers to the pore diameter distribution method that meets the metabolic energy level requirements of methane-oxidizing bacteria. The degradation flora activity compensation coefficient refers to the compensation coefficient dynamically adjusted according to the degradation flora activity. The pore reconstruction priority refers to the priority order of soil pore structure optimization. The division of the feeding interval hot zone refers to the feeding interval area divided according to the compensation range of the feeding time window offset. The triggering condition for flora activation refers to the triggering condition of the degradation flora activity compensation coefficient.

[0075] In the embodiments of the present application, first, the grading optimization interval of soil pore diameter is reversely constrained by the micro-oxygen flux threshold interval, and the pore diameter distribution pattern that meets the metabolic energy level requirements of methanotrophs is screened out. According to the micro-oxygen flux threshold interval, the grading optimization interval of soil pore diameter is reversely constrained to screen the pore diameter distribution pattern that meets the metabolic energy level requirements of methanotrophs. Then, based on the offset compensation range of the feeding time window, the dynamic weighting algorithm is used to adjust the activity compensation coefficient of the degradation flora, and an organic fertilizer feeding gradient compensation strategy including pore reconstruction priority, hot zone division of feeding intervals, and flora activation trigger conditions is generated. By dynamically adjusting these parameters, the degradation efficiency of organic fertilizer is maximized and carbon emissions are reduced.

[0076] The following is a specific example: In the traceability of the carbon footprint of agricultural inputs throughout their life cycle, taking a tomato planting base as an example, by analyzing the dynamic relationship between soil pore diameter and the degradation rate of organic fertilizer, combined with seasonal temperature fluctuations (15 - 25°C in spring, 25 - 35°C in summer), a constraint relationship table between soil pore diameter and degradation rate is generated, clarifying that the degradation rate reaches its peak at 25°C when the pore diameter is 0.2 - 0.3 mm. Based on this, the maximum methane diffusion flux allowed within the optimized interval of soil pore diameter is analyzed, and combined with the response delay time of the activity of the degradation flora and the feeding gradient (2 days in summer, 4 days in spring), the micro-oxygen flux threshold interval (0.8 - 1.2 mg / L in summer, 0.5 - 0.8 mg / L in spring) and the offset of the feeding time window (±2 days in summer, ±3 days in spring) based on a tillage layer depth of 20 cm are determined. Finally, the pore diameter distribution pattern that meets the metabolic energy level of methanotrophs is screened out (0.25 - 0.3 mm in summer, 0.2 - 0.25 mm in spring), and the activity compensation coefficient of the degradation flora is dynamically weighted (1.5 in summer, 1.2 in spring), generating an organic fertilizer feeding gradient compensation strategy including pore reconstruction priority, hot zone division of feeding intervals, and flora activation trigger conditions, achieving precise optimization of carbon emissions.

[0077] To sum up, through steps 301 to 303, by dynamically matching the grading optimization interval of soil pore diameter with the attenuation coefficient of the degradation rate of organic fertilizer, a precise constraint relationship between soil pore diameter and degradation rate is constructed, thereby optimizing the gas diffusion and methane oxidation efficiency of the soil microecological environment; finally, through reverse constraint, the pore diameter distribution pattern that meets the metabolic energy level of methanotrophs is screened out, and combined with the dynamically weighted activity compensation coefficient of the flora, an organic fertilizer feeding gradient compensation strategy including pore reconstruction priority, hot zone division of feeding intervals, and flora activation trigger conditions is formed, significantly improving the degradation efficiency of organic matter and the soil carbon sink capacity, providing scientific support for the green and low-carbon transformation of agricultural production.

[0078] In order to solve the greenhouse gas emission problem caused by the incoordination between soil aeration parameters and organic fertilizer degradation rate in agricultural production, a collaborative optimization system based on micro-aerobic environment control and methane product conversion has been developed, which realizes the efficient conversion of residual intermediate products to stable carbon forms under preset boundary conditions, effectively controls the degradation rate of organic fertilizers and significantly reduces the amount of greenhouse gas emissions, providing precise technical support for low-carbon agricultural production. In some embodiments, the soil aeration parameters are adjusted according to the micro-aerobic environment control instructions in the compensation strategy in step 104, the soil micro-aerobic environment is optimized in combination with the soil pore structure optimization scheme, and the degradation rate of organic fertilizers is controlled by the methane product conversion scheme, including: 401. Based on the compensation strategy, extract the target value range of soil oxygen concentration in the microaerobic environment control instruction, and obtain soil ventilation adjustment parameters according to the soil pore structure optimization scheme; In step 401, the compensation strategy refers to a strategy for reducing carbon emissions by dynamically adjusting soil ventilation parameters and organic fertilizer feeding gradients. Microaerobic environment control instructions refer to instructions for achieving microaerobic environment control by adjusting soil ventilation parameters, aiming to create a microaerobic environment suitable for stable conversion of carbon elements. The target value range of soil oxygen concentration refers to the ideal range of oxygen concentration in the soil under a microaerobic environment, which is usually determined by experimental data or model calculations. The soil pore structure optimization program refers to a program for improving the migration and conversion efficiency of carbon elements by optimizing the soil pore structure (such as pore diameter, connectivity, etc.). Soil ventilation adjustment parameters refer to ventilation parameters determined according to the soil pore structure optimization program, including ventilation volume, ventilation frequency, etc.

[0079] In the embodiments of the present application, firstly, based on the compensation strategy, the target value range for soil oxygen concentration in the microaerobic environment control instruction is extracted to clarify the oxygen concentration requirement under the microaerobic environment. Then, according to the soil pore structure optimization scheme, the soil ventilation adjustment parameters are obtained, including ventilation volume and ventilation frequency. Specifically, by analyzing the influence of soil pore structure on oxygen concentration and combining the microaerobic environment control instruction, the ventilation adjustment parameters are determined. Finally, by integrating the target value range and ventilation adjustment parameters, data support is provided for the subsequent optimization of the soil microaerobic environment to ensure that the migration and conversion efficiency of carbon elements are maximized.

[0080] 402. According to the microaerobic environment control instruction, the deviation between the current soil oxygen concentration and the target value range is calculated, and in combination with the soil ventilation adjustment parameter, the working mode of the soil ventilation device is dynamically adjusted to generate optimized soil microaerobic environment data; In step 402, the microaerobic environment control instruction refers to an instruction for achieving microaerobic environment control by adjusting soil ventilation parameters. The current soil oxygen concentration refers to the oxygen concentration value in the soil monitored by the sensor network. The target value range refers to the ideal range of oxygen concentration in the soil under a microaerobic environment. The soil ventilation adjustment parameter refers to the ventilation parameter determined according to the soil pore structure optimization scheme. The soil ventilation equipment refers to equipment used to adjust soil ventilation parameters, such as ventilation pipes, fans, etc. The optimized soil microaerobic environment data refers to the soil microaerobic environment data generated by dynamically adjusting the working mode of the soil ventilation equipment.

[0081] In the embodiment of the present application, first, according to the micro-aerobic environment control instruction, the deviation between the current soil oxygen concentration and the target value range is calculated to clarify the adjustment demand of the oxygen concentration. Then, in combination with the soil ventilation adjustment parameters, the optimization algorithm is used to dynamically adjust the working mode of the soil ventilation equipment, including the ventilation volume and ventilation frequency, etc. Specifically, the working mode of the ventilation equipment is determined by analyzing the relationship between the oxygen concentration deviation and the ventilation adjustment parameters. Finally, the optimized soil micro-aerobic environment data is generated to ensure that the oxygen concentration in the soil is stable within the target value range, providing a suitable micro-aerobic environment for the degradation of organic fertilizers.

[0082] 403. According to the methane product conversion scheme, determine the target rate range of organic fertilizer degradation, and based on the soil microaerobic environment data, dynamically adjust the amount and distribution of organic fertilizer to control the degradation rate of organic fertilizer.

[0083] In step 403, the methane product conversion scheme refers to a scheme for converting methane into a stable carbon form by controlling the degradation rate of organic fertilizer. The target rate range of organic fertilizer degradation refers to the ideal rate range of organic fertilizer degradation determined according to the methane product conversion scheme. Soil microaerobic environment data refers to soil microaerobic environment data generated by dynamically adjusting the working mode of the soil aeration equipment. The feeding amount of organic fertilizer refers to the feeding amount of organic fertilizer. The distribution mode of organic fertilizer refers to the distribution form of organic fertilizer in the soil, such as uniform distribution or layered distribution.

[0084] In the present application embodiment, first, according to the methane product conversion scheme, the target rate range of organic fertilizer degradation is determined, and the adjustment demand of degradation rate is clarified. Then, based on the soil microaerobic environment data, the feed amount and distribution mode of organic fertilizer are dynamically adjusted using an optimization algorithm to ensure that the degradation rate is stable within the target range. Specifically, by analyzing the impact of the soil microaerobic environment on the degradation rate, combined with the target rate range, the feed amount and distribution mode of organic fertilizer are determined. Finally, by controlling the degradation rate of organic fertilizer, the residual intermediate product is converted into a stable carbon form, reducing the release of greenhouse gases such as methane, and realizing efficient conversion of carbon elements.

[0085] The following is a specific example: In the practical application of tracing the carbon footprint of agricultural inputs throughout their life cycle, taking a large-scale vegetable planting base as an example, first, based on the compensation strategy, the target value range of soil oxygen concentration (0.5 - 1.2 mg / L) in the micro-oxygen environment control instruction is extracted, and the soil ventilation adjustment parameters are obtained according to the soil pore structure optimization plan (such as the optimized interval of pore diameter is 0.1 - 0.3 mm, and the rotary tillage depth is 15 - 20 cm). Subsequently, according to the micro-oxygen environment control instruction, the deviation between the current soil oxygen concentration and the target value range is calculated, and combined with the soil ventilation adjustment parameters, the working mode of the soil ventilation equipment is dynamically adjusted (such as increasing the rotary tillage frequency or adjusting the blade spacing) to generate optimized soil micro-oxygen environment data, ensuring that the soil oxygen concentration is stable within the target range. Then, according to the methane product conversion plan, the target rate range of organic fertilizer degradation is determined (such as degrading 0.1 - 0.15 kg / m² per day), and based on the optimized soil micro-oxygen environment data, the feeding amount and distribution method of the organic fertilizer are dynamically adjusted (such as reducing the feeding amount by 10% and adopting a uniform distribution method) to control the degradation rate of the organic fertilizer to meet the target rate range. Through the above steps, the precise regulation of the soil micro-oxygen environment and the optimization of the degradation rate of organic fertilizer in the vegetable planting process are achieved, effectively reducing carbon emissions.

[0086] In summary, through steps 401 to 403, the precise regulation of the soil micro-oxygen environment is achieved; the optimized soil micro-oxygen environment data is generated, significantly improving the soil ventilation performance and gas diffusion efficiency; according to the methane product conversion plan, the target rate range of organic fertilizer degradation is determined, and based on the optimized soil micro-oxygen environment data, the feeding amount and distribution method of the organic fertilizer are dynamically adjusted, achieving the precise control of the degradation rate of the organic fertilizer, effectively reducing greenhouse gas emissions, and providing scientific and efficient technical support for the optimization of the carbon cycle and the green and low-carbon transformation in the agricultural production process.

[0087] To solve the problems of methane generation and greenhouse gas emissions caused by insufficient degradation of plant structural organic matter in organic fertilizers during agricultural production, a phased feeding gradient and degradation flora activity regulation system based on temperature fluctuation and degradation breakage threshold is developed, achieving the efficient degradation of plant structural organic matter and the effective control of methane generation, significantly reducing greenhouse gas emissions, and providing precise technical support for low-carbon agricultural production. In some embodiments, in step 203, based on the methane product distribution and intermediate product concentration, the degradation breakage threshold of plant structural organic matter in the organic fertilizer is analyzed, and the degradation breakage threshold is combined with the environmental temperature fluctuation range during the production process to generate the correlation rules for phased feeding gradient and degradation flora activity regulation, including: 501. Analyze the degradation and chain-breaking threshold of plant structural organic matter in organic fertilizers based on the methane product distribution and intermediate product concentration. According to the degradation and chain-breaking threshold, divide the degradation process of organic fertilizers into multiple stages, and determine the feeding gradient range for each stage. In step 501, the methane product distribution refers to the spatial distribution of methane generated during the degradation process of organic fertilizers in the soil. The intermediate product concentration refers to the concentration value of intermediate products generated during the reaction process in the chemical reaction chain data. The degradation and chain-breaking threshold of plant structural organic matter refers to the chain-breaking conditions of plant structural organic matter in organic fertilizers during the degradation process, including factors such as temperature, humidity, and microbial activity. The degradation stage refers to the different stages into which the degradation process of organic fertilizers is divided according to the degradation and chain-breaking threshold. The feeding gradient range refers to the feeding amount range of organic fertilizers in each degradation stage.

[0088] In the embodiments of the present application, first, based on the methane product distribution and intermediate product concentration, analyze the degradation and chain-breaking threshold of plant structural organic matter in organic fertilizers to clarify the key influencing factors during the degradation process. Then, according to the degradation and chain-breaking threshold, divide the degradation process of organic fertilizers into multiple stages and determine the feeding gradient range for each stage. Specifically, by analyzing the influence of methane product distribution and intermediate product concentration on the degradation and chain-breaking threshold, combined with the degradation characteristics of organic fertilizers, divide the degradation process into multiple stages and determine the feeding gradient range for each stage. Finally, through this division and range determination, provide data support for the subsequent regulation of the activity of degradation bacteria groups to ensure the maximization of the degradation efficiency of organic fertilizers.

[0089] 502. According to the environmental temperature fluctuation range during the production process, identify the influence law of temperature change on the degradation and chain-breaking threshold, and establish the mapping relationship between temperature and the degradation and chain-breaking threshold. Combine the mapping relationship to analyze the change trend of the activity of degradation bacteria groups under different temperature conditions, and determine the influence law of temperature on the activity of degradation bacteria groups. In step 502, the environmental temperature fluctuation range refers to the change range of the environmental temperature during the production process. The influence law of temperature change on the degradation and chain-breaking threshold refers to the influence trend and law of temperature change on the degradation and chain-breaking threshold. The mapping relationship between temperature and the degradation and chain-breaking threshold refers to the quantitative relationship between temperature and the degradation and chain-breaking threshold. The activity of degradation bacteria groups refers to the activity level of degradation bacteria groups in the soil, which is usually affected by factors such as temperature, humidity, and nutrient supply. The influence law of temperature on the activity of degradation bacteria groups refers to the influence trend and law of temperature change on the activity of degradation bacteria groups.

[0090] In the embodiments of the present application, first, according to the environmental temperature fluctuation range during the production process, the influence law of temperature change on the degradation and chain-breaking threshold is identified, and the action mechanism of temperature on the degradation and chain-breaking threshold is clarified. Then, using data mining technology, the mapping relationship between temperature and the degradation and chain-breaking threshold is established to quantify the influence of temperature on the degradation and chain-breaking threshold. Next, combining the mapping relationship, the change trend of the activity of the degradation bacterial community under different temperature conditions is analyzed to determine the influence law of temperature on the activity of the degradation bacterial community. Specifically, by analyzing the influence of temperature fluctuation on the activity of the degradation bacterial community and combining the change trend of the degradation and chain-breaking threshold, the action mechanism of temperature on the activity of the degradation bacterial community is clarified. Finally, based on this law, a scientific basis is provided for the subsequent generation of association rules to ensure the effective regulation of the activity of the degradation bacterial community.

[0091] 503. Based on the degradation and chain-breaking threshold and the feeding gradient range, and in combination with the influence law, generate the association rules for the staged feeding gradient and the regulation of the activity of the degradation bacterial community.

[0092] In step 503, the degradation and chain-breaking threshold refers to the chain-breaking condition of the plant structural organic matter in the organic fertilizer during the degradation process. The feeding gradient range refers to the feeding amount range of the organic fertilizer in each degradation stage. The influence law refers to the influence law of temperature on the activity of the degradation bacterial community. The association rules for the staged feeding gradient and the regulation of the activity of the degradation bacterial community refer to the association rules generated according to the degradation and chain-breaking threshold and the feeding gradient range, in combination with the influence law of temperature on the activity of the degradation bacterial community, and are used to dynamically adjust the feeding gradient of the organic fertilizer and the activity of the degradation bacterial community.

[0093] In the embodiments of the present application, first, based on the degradation and chain-breaking threshold and the feeding gradient range, the feeding requirements for each stage during the degradation of the organic fertilizer are clarified. Then, in combination with the influence law of temperature on the activity of the degradation bacterial community, an optimization algorithm is used to generate the association rules for the staged feeding gradient and the regulation of the activity of the degradation bacterial community. Specifically, by analyzing the influence of the degradation and chain-breaking threshold and the feeding gradient range on the degradation efficiency and combining the action mechanism of temperature on the activity of the degradation bacterial community, the association rules are generated. Finally, through this association rule, the feeding gradient of the organic fertilizer and the activity of the degradation bacterial community are dynamically adjusted to ensure the maximization of the degradation efficiency of the organic fertilizer and reduce carbon retention and methane generation.

[0094] The following is a specific example: In the practical application of tracing the carbon footprint of agricultural inputs throughout their life cycle, taking a large-scale rice planting base as an example, first, based on the distribution of methane products and the concentration of intermediate products, the degradation and chain-breaking thresholds of plant structural organic matter (such as cellulose and hemicellulose) in organic fertilizers are analyzed. According to the degradation and chain-breaking thresholds, the degradation process of organic fertilizers is divided into multiple stages (such as the initial stage, the rapid degradation stage, and the stable stage), and the feeding gradient range for each stage is determined (such as feeding once every 3 days in the initial stage and once every 5 days in the rapid degradation stage). Subsequently, according to the range of environmental temperature fluctuations during the production process (such as 15 - 35 °C), the influence law of temperature changes on the degradation and chain-breaking thresholds is identified, and the mapping relationship between temperature and the degradation and chain-breaking thresholds is established (such as for every 5 °C increase in temperature, the degradation and chain-breaking threshold decreases by 10%). Combining this mapping relationship, the change trend of the activity of the degradation flora under different temperature conditions is analyzed (such as the activity of the flora decreases significantly when the temperature is below 20 °C), and the influence law of temperature on the activity of the degradation flora is determined. Finally, based on the degradation and chain-breaking thresholds and the feeding gradient range, and combining the influence law of temperature on the activity of the degradation flora, the association rules for the phased feeding gradient and the regulation of the activity of the degradation flora are generated (such as shortening the feeding interval to 3 days when the temperature is higher than 25 °C, extending the feeding interval to 7 days when the temperature is below 20 °C, and adjusting the flora activity compensation coefficient to 1.2 - 1.5). Through the above steps, the precise control of the degradation rate of organic fertilizers during the rice planting process is achieved, effectively optimizing carbon emission management.

[0095] In summary, through steps 501 to 503, a scientific basis is provided for the precise control of the organic fertilizer degradation process; at the same time, by identifying the influence law of environmental temperature fluctuations on the degradation and chain-breaking thresholds, establishing the mapping relationship between temperature and the degradation and chain-breaking thresholds, and combining the change trend of the activity of the degradation flora under different temperature conditions, the influence law of temperature on the activity of the degradation flora is determined, realizing the dynamic regulation of the degradation process; finally, based on the degradation and chain-breaking thresholds and the feeding gradient range, and combining the influence law of temperature on the activity of the degradation flora, the association rules for the phased feeding gradient and the regulation of the activity of the degradation flora are generated, significantly improving the degradation efficiency and stability of organic fertilizers, and providing a systematic and precise technical solution for greenhouse gas emission reduction and resource efficient utilization in the agricultural production process.

[0096] To address the problem of methane generation and greenhouse gas emissions caused by the lack of coordination between rotary tillage operations and inoculant spraying in agricultural production, a collaborative control system based on the coupling of tillage depth gradient and inoculant spraying path has been developed, achieving efficient coordination between rotary tillage operations and inoculant spraying, significantly reducing methane generation and greenhouse gas emissions, and providing precise technical support for the low-carbonization of agricultural production. In some embodiments, in step 403, according to the methane product conversion scheme, determining the target rate range for the degradation of organic fertilizers and dynamically adjusting the feeding amount and distribution method of organic fertilizers based on the soil micro-oxygen environment data to control the degradation rate of organic fertilizers includes: 601. According to the methane product conversion scheme, extract the target rate range for the degradation of organic fertilizers, including the upper limit value and the lower limit value of the degradation rate, and based on the soil micro-oxygen environment data, analyze the influence of the current soil oxygen concentration on the degradation rate, and determine the applicable conditions for the target rate range; In step 601, the methane product conversion scheme refers to a scheme for converting methane into a stable carbon form by controlling the degradation rate of organic fertilizers. The target rate range for the degradation of organic fertilizers refers to the ideal rate range for the degradation of organic fertilizers determined according to the methane product conversion scheme, including the upper limit value and the lower limit value of the degradation rate. The soil micro-oxygen environment data refers to the soil micro-oxygen environment data generated after dynamically adjusting the working mode of the soil ventilation equipment. The current soil oxygen concentration refers to the oxygen concentration value in the soil monitored by the sensor network. The applicable conditions for the target rate range refer to the applicable conditions of the target rate range in actual production, including factors such as soil oxygen concentration and temperature.

[0097] In the embodiments of the present application, first, according to the methane product conversion scheme, extract the target rate range for the degradation of organic fertilizers to clarify the ideal range of the degradation rate. Then, based on the soil micro-oxygen environment data, analyze the influence of the current soil oxygen concentration on the degradation rate, and determine the applicable conditions for the target rate range. Specifically, by analyzing the relationship between the soil oxygen concentration and the degradation rate and combining the target rate range, determine its applicable conditions in the current soil micro-oxygen environment. Finally, through this applicable condition, provide a scientific basis for the subsequent adjustment of the feeding amount to ensure that the degradation rate is stable within the target range.

[0098] 602. According to the target rate range, calculate the deviation amount between the current degradation rate of the organic fertilizer and the target rate range, and determine the adjustment amount of the feeding amount based on the deviation amount; In step 602, the target rate range refers to the ideal rate range for the degradation of organic fertilizers. The current degradation rate of the organic fertilizer refers to the value of the degradation rate of the organic fertilizer monitored by the sensor network. The deviation amount refers to the difference between the current degradation rate and the target rate range. The adjustment amount of the feeding amount refers to the adjusted value of the feeding amount of the organic fertilizer determined according to the deviation amount.

[0099] In the embodiments of the present application, first, according to the target rate range, the deviation amount between the current degradation rate of the organic fertilizer and the target rate range is calculated to clarify the adjustment requirement of the degradation rate. Then, based on the deviation amount, the adjustment amount of the feeding amount is determined using an optimization algorithm. Specifically, by analyzing the influence of the deviation amount on the degradation rate and combining with the target rate range, the adjustment amount of the feeding amount is determined. Finally, through this adjustment amount, data support is provided for the subsequent adjustment of the feeding amount and distribution method to ensure that the degradation rate is stable within the target range.

[0100] 603. Dynamically adjust the feeding amount and distribution method of the organic fertilizer based on the applicable conditions of the target rate range to ensure that the degradation rate is stable within the target rate range.

[0101] In step 603, the applicable conditions of the target rate range refer to the applicable conditions of the target rate range in actual production. The adjustment amount refers to the adjusted value of the feeding amount of the organic fertilizer determined according to the deviation amount. The feeding amount of the organic fertilizer refers to the feeding quantity of the organic fertilizer. The distribution method of the organic fertilizer refers to the distribution form of the organic fertilizer in the soil, such as uniform distribution or layered distribution.

[0102] In the embodiments of the present application, first, based on the applicable conditions of the target rate range, the environmental limitations for adjusting the degradation rate are clarified. Then, according to the adjustment amount, the feeding amount and distribution method of the organic fertilizer are dynamically adjusted using an optimization algorithm. Specifically, by analyzing the influence of the applicable conditions on the degradation rate and combining with the adjustment amount, the adjustment scheme for the feeding amount and distribution method is determined. Finally, by dynamically adjusting the feeding amount and distribution method of the organic fertilizer, it is ensured that the degradation rate is stable within the target rate range, reducing carbon retention and methane generation, and achieving efficient conversion of carbon elements.

[0103] The following is a specific example: In the practical application of carbon footprint traceability of agricultural inputs throughout their life cycle, taking a large-scale wheat planting base as an example, firstly, according to the methane product conversion scheme, the target rate range of organic fertilizer degradation is extracted, including the upper limit (such as 0.15kg / m² per day) and lower limit (such as 0.1kg / m² per day) of the degradation rate, and based on the soil micro-aerobic environment data, the influence of the current soil oxygen concentration (such as 0.8mg / L) on the degradation rate is analyzed to determine the applicable conditions of the target rate range (such as the soil oxygen concentration needs to be maintained between 0.5-1.2mg / L). Subsequently, according to the target rate range, the deviation between the current organic fertilizer degradation rate (such as 0.12kg / m² per day) and the target rate range is calculated (such as lower than the lower limit of 0.02kg / m²), and the adjustment amount of the feed amount is determined based on the deviation (such as increasing the feed amount by 5%). Finally, based on the applicable conditions of the target rate range, the amount and distribution of organic fertilizer are dynamically adjusted according to the adjustment amount (such as increasing the amount from 500kg per hectare to 525kg per hectare and using a uniform distribution method) to ensure that the degradation rate is stable within the target rate range (such as 0.1-0.15kg / m² per day). Through the above steps, the degradation rate of organic fertilizer during wheat planting is precisely controlled, effectively optimizing carbon emission management.

[0104] In summary, through steps 601 to 603, the applicable conditions for determining the target rate range are realized, which provides a scientific basis for the precise regulation of the degradation rate; at the same time, by calculating the deviation between the current organic fertilizer degradation rate and the target rate range, and determining the adjustment amount of the feed amount based on the deviation, the dynamic optimization of the organic fertilizer degradation process is realized; finally, based on the applicable conditions of the target rate range, the feed amount and distribution method of the organic fertilizer are dynamically adjusted according to the adjustment amount to ensure that the degradation rate is stable within the target rate range, which significantly improves the degradation efficiency and stability of the organic fertilizer, and provides a systematic and precise technical solution for greenhouse gas emission reduction and efficient resource utilization in agricultural production.

[0105] In order to solve the problem of incomplete evaluation of carbon reduction effects caused by inaccurate monitoring of stable carbon form migration paths in agricultural production, a carbon cycle balance map generation system based on dynamic monitoring of carbon migration paths and fusion of chemical reaction chain data has been developed, which realizes accurate monitoring of carbon migration paths and scientific evaluation of carbon reduction effects in agricultural production processes, and provides comprehensive data support for low-carbon agriculture. In some embodiments, the dynamic monitoring of the migration path of the stable carbon form in step 105, combined with the adjusted chemical reaction chain data to generate a carbon cycle balance map for evaluating carbon reduction effects, includes: 701. Set monitoring points along the geographical distribution of the field irrigation channels during the production process, and collect the retention amounts and lateral diffusion rates of stable carbon forms at different soil tillage layer depths. Integrate the collected retention amount and diffusion rate data to generate dynamic monitoring data corresponding to the migration paths based on the field irrigation channels as the geographical reference. In step 701, the production process refers to the application and degradation process of organic fertilizers during agricultural production. The field irrigation channels refer to the irrigation channels in farmland, which are usually used as the geographical reference for the spatial distribution of monitoring data. The monitoring points refer to the points set along the field irrigation channels for collecting data. The soil tillage layer depth refers to the thickness of the tillage layer of farmland soil, which is usually divided into the surface layer, middle layer, and deep layer. Different tillage layers have a significant impact on the migration and transformation efficiency of carbon elements. The retention amount of stable carbon forms refers to the retention amount of stable carbon forms in the soil, specifically manifested as the accumulation of incompletely decomposed organic carbon in the soil. The lateral diffusion rate refers to the lateral diffusion speed of stable carbon forms in the soil, which is usually affected by the soil pore structure and water content. The dynamic monitoring data refers to the retention amount of stable carbon forms and the lateral diffusion rate data collected through the monitoring points, and the dynamic monitoring data of the migration paths generated after integration based on the field irrigation channels as the geographical reference.

[0106] In the embodiments of the present application, first, set monitoring points along the geographical distribution of the field irrigation channels to ensure the spatial coverage and representativeness of the monitoring data. Then, collect the retention amounts and lateral diffusion rates of stable carbon forms at different soil tillage layer depths through the sensor network to obtain the migration and transformation data of stable carbon forms in the soil. Then, integrate the collected retention amount and diffusion rate data, and use spatial analysis technology to generate dynamic monitoring data of the migration paths based on the field irrigation channels as the geographical reference. Specifically, by analyzing the retention amounts and diffusion rates of stable carbon forms in different tillage layers, and combining the geographical information of the field irrigation channels, generate dynamic monitoring data of the migration paths. Finally, through this data, provide a scientific basis for the subsequent optimization of carbon migration paths and carbon emission control, and ensure the efficient conversion of carbon elements and a significant reduction in greenhouse gas emissions. 702. According to the dynamic monitoring data, analyze the migration time delay amount of stable carbon forms under the soil pore connectivity gradient, and combine the change rate of the concentration of intermediate products of organic fertilizer degradation in the adjusted chemical reaction chain data to generate a dynamic mapping relationship table of the conversion efficiency and degradation rate of stable carbon forms. In step 702, the dynamic monitoring data of the carbon migration path refers to the dynamic monitoring data of the carbon migration path with the irrigation channel of the field plot as the geographical reference. The soil pore connectivity gradient refers to the change gradient of the soil pore connectivity. The migration time delay amount refers to the migration time delay value of the stable carbon form under the soil pore connectivity gradient. The chemical reaction chain data refers to the chemical reaction data at each stage of the production process. The change rate of the concentration of the intermediate product of organic fertilizer degradation refers to the change speed of the concentration of the intermediate product during the degradation of organic fertilizer. The conversion efficiency of the stable carbon form refers to the conversion efficiency of the stable carbon form. The degradation rate refers to the degradation speed of the organic fertilizer. The dynamic mapping relationship table refers to the dynamic relationship table between the conversion efficiency of the stable carbon form and the degradation rate.

[0107] In the embodiment of the present application, first, the migration time delay amount of the stable carbon form under the soil pore connectivity gradient is determined through the dynamic monitoring data of the carbon migration path. According to the dynamic monitoring data of the carbon migration path, the migration time delay amount of the stable carbon form under the soil pore connectivity gradient is analyzed, and in combination with the change rate of the concentration of the intermediate product of organic fertilizer degradation in the adjusted chemical reaction chain data, a dynamic mapping relationship table between the conversion efficiency of the stable carbon form and the degradation rate is generated. Then, in combination with the change rate of the concentration of the intermediate product of organic fertilizer degradation, a dynamic mapping relationship table is generated by using data mining technology to clarify the relationship between the conversion efficiency of the stable carbon form and the degradation rate, providing a basis for the generation of the subsequent carbon cycle dynamic parameter set.

[0108] 703. Based on the dynamic mapping relationship table, match the constraint conditions between the tillage layer depth and the migration rate of the stable carbon form of different soil textures in the open farmland, and generate a carbon cycle dynamic parameter set including the boundary of the humus retention hot zone, the lateral diffusion gradient of biochar, and the priority of methane oxidation inhibition; In step 703, the open farmland refers to the open environment during the farmland production process. The soil texture refers to the physical properties of the farmland soil, such as sandy soil, clay soil, etc. The tillage layer depth refers to the thickness of the tillage layer of the farmland soil. The migration rate of the stable carbon form refers to the migration speed of the stable carbon form in the soil. The boundary of the humus retention hot zone refers to the boundary of the hot spot area where humus stays in the soil. The lateral diffusion gradient of biochar refers to the lateral diffusion gradient of biochar in the soil. The priority of methane oxidation inhibition refers to the priority order of controlling the activity of methane oxidizing bacteria. The carbon cycle dynamic parameter set refers to the carbon cycle dynamic parameter set including the boundary of the humus retention hot zone, the lateral diffusion gradient of biochar, and the priority of methane oxidation inhibition.

[0109] In the embodiments of the present application, first, the constraint conditions between the stable carbon form migration rate and the tillage layer depth are determined through the dynamic mapping relationship table. Based on the dynamic mapping relationship table, the constraint conditions between the tillage layer depth and the stable carbon form migration rate of different soil textures in open farmland are matched, and a set of carbon cycle dynamic parameters including the boundary of the humus retention hot zone, the lateral diffusion gradient of biochar, and the priority of methane oxidation inhibition is generated. Then, combined with different soil textures, an optimization algorithm is used to generate a set of carbon cycle dynamic parameters to ensure the applicability and effectiveness of the boundary of the humus retention hot zone, the lateral diffusion gradient of biochar, and the priority of methane oxidation inhibition.

[0110] 704. Superimpose the set of carbon cycle dynamic parameters and the adjusted chemical reaction chain data in space to generate a carbon cycle balance map with the tillage layer depth as the vertical axis and the field irrigation channel as the horizontal axis.

[0111] In step 704, the set of carbon cycle dynamic parameters refers to the set of carbon cycle dynamic parameters including the boundary of the humus retention hot zone, the lateral diffusion gradient of biochar, and the priority of methane oxidation inhibition. The chemical reaction chain data refers to the chemical reaction data at each stage in the production process. Spatial superposition refers to the operation of superimposing the set of carbon cycle dynamic parameters and the chemical reaction chain data in space. The tillage layer depth refers to the thickness of the tillage layer of farmland soil. The field irrigation channel refers to the irrigation channel in the farmland. The carbon cycle balance map refers to the carbon cycle balance map with the tillage layer depth as the vertical axis and the field irrigation channel as the horizontal axis.

[0112] In the embodiments of the present application, first, the set of carbon cycle dynamic parameters and the chemical reaction chain data are integrated through spatial superposition technology to determine the migration and transformation path of carbon elements in the soil. The set of carbon cycle dynamic parameters and the adjusted chemical reaction chain data are superimposed in space to generate a carbon cycle balance map with the tillage layer depth as the vertical axis and the field irrigation channel as the horizontal axis. Then, combined with the geographical information of the tillage layer depth and the field irrigation channel, a carbon cycle balance map is generated to provide a scientific basis for carbon emission control in the agricultural production process.

[0113] The following is a specific example: In the practical application of carbon footprint tracing of agricultural inputs, taking a large-scale rice planting base as an example, first, based on the chemical bond stability threshold of stable carbon forms, the retention amount and lateral diffusion rate of stable carbon forms at different soil tillage layer depths are synchronously collected during the production process to generate dynamic monitoring data of carbon migration paths with the irrigation channels of the field plot as the geographical reference. For example, within the tillage layer depth range of 10 - 20 cm, the retention amount of stable carbon forms is 0.8 kg per square meter, and the lateral diffusion rate is 0.2 m per hour. Subsequently, based on the dynamic monitoring data of carbon migration paths, the migration time delay of stable carbon forms under the soil pore connectivity gradient is analyzed, and combined with the change rate of the concentration of intermediate products of organic fertilizer degradation in the adjusted chemical reaction chain data, a dynamic mapping relationship table of the conversion efficiency and degradation rate of stable carbon forms is generated. For example, when the pore connectivity is 0.5, the conversion efficiency of stable carbon forms reaches 85%, and the degradation rate is 0.15 kg / m² per hour. Then, based on the dynamic mapping relationship table, the constraint conditions of the tillage layer depth and the stable carbon form migration rate of different soil textures in the open farmland are matched to generate a set of dynamic carbon cycle parameters including the boundary of the humus retention hot zone (within 2 m from the field ridge), the lateral diffusion gradient of biochar (diffusing 0.5 kg per 10 m), and the priority of methane oxidation inhibition. Finally, the set of dynamic carbon cycle parameters is spatially superimposed with the adjusted chemical reaction chain data to generate a carbon cycle balance map with the tillage layer depth as the vertical axis and the irrigation channels of the field plot as the horizontal axis, providing a scientific basis and precise guidance for carbon emission optimization during the rice planting process.

[0114] In summary, through steps 701 to 704, it is realized that by synchronously collecting the retention amount and lateral diffusion rate of stable carbon forms at different soil tillage layer depths, a dynamic mapping relationship table of the conversion efficiency and degradation rate of stable carbon forms is constructed, providing a scientific basis for the optimization of the carbon cycle process; at the same time, a set of dynamic carbon cycle parameters including the boundary of the humus retention hot zone, the lateral diffusion gradient of biochar, and the priority of methane oxidation inhibition is generated, significantly improving the soil carbon sequestration capacity and greenhouse gas emission reduction effect; finally, by spatially superimposing the set of dynamic carbon cycle parameters with the chemical reaction chain data, a carbon cycle balance map with the tillage layer depth as the vertical axis and the irrigation channels of the field plot as the horizontal axis is generated, providing efficient and reliable technical support for the carbon cycle balance management and sustainable development of the farmland ecosystem.

[0115] Figure 2 The present application embodiment provides a structural schematic diagram of a carbon emission reduction effect evaluation system for the production process of healthy agricultural products, as Figure 2 shown, the system includes: A collection module 21, which traces the carbon element migration paths in chemical fertilizer application, organic fertilizer degradation, and soil respiration, and simultaneously collects chemical reaction chain data at each stage during the production process; The matching module 22 determines the carbon emission concentration area according to the carbon element migration path, matches the by-product generation amount in the chemical reaction chain data with the pre-stored agricultural carbon emission path database, and analyzes the carbon retention amount and the distribution of residual methane products caused by incomplete degradation of organic fertilizers during the production process; The compensation module 23 inputs the carbon retention amount, the methane product distribution, and the intermediate product concentration in the chemical reaction chain data into the carbon emission dynamic compensation engine, and generates an optimization plan for the soil pore structure and a compensation strategy for the organic fertilizer feeding gradient based on the carbon reduction effect evaluation index in the healthy agricultural product production standard; The adjustment module 24 adjusts the soil ventilation parameters according to the micro-oxygen environment control instruction in the compensation strategy, optimizes the soil micro-oxygen environment in combination with the soil pore structure optimization plan, and simultaneously controls the degradation rate of organic fertilizers through the methane product conversion plan, so that the residual intermediate products are converted into stable carbon forms to reduce the greenhouse gas emission amount; The generation module 25 dynamically monitors the migration path corresponding to the stable carbon form, and generates a carbon cycle balance map for evaluating the carbon reduction effect in combination with the adjusted soil ventilation parameters and the chemical reaction chain data.

[0116] Figure 2 The described carbon reduction effect evaluation system for the production process of healthy agricultural products can execute Figure 1 The described carbon reduction effect evaluation method for the production process of healthy agricultural products in the illustrated embodiment, and its implementation principle and technical effects will not be elaborated. For the carbon reduction effect evaluation system for the production process of healthy agricultural products in the above embodiment, the specific ways in which each module and unit perform operations have been described in detail in the embodiment related to the method, and will not be elaborated here.

[0117] In a possible design, Figure 2 The carbon reduction effect evaluation system for the production process of healthy agricultural products in the illustrated embodiment can be implemented as a computing device, such as Figure 3 shown, and this computing device can include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, and among them, the one or more computer instructions are called and executed by the processing component 32.

[0118] The processing component 32 is used for the Figure 1 described carbon reduction effect evaluation method for the production process of healthy agricultural products in the illustrated embodiment.

[0119] Among them, the processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-mentioned method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components for executing the above-mentioned method.

[0120] The storage component 31 is configured to store various types of data to support the operation of the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disc.

[0121] Of course, the computing device may also necessarily include other components, such as input / output interfaces, display components, communication components, etc.

[0122] The input / output interface provides an interface between the processing component and the peripheral interface module, and the above-mentioned peripheral interface module may be an output device, an input device, etc.

[0123] The communication component is configured to facilitate communication between the computing device and other devices in a wired or wireless manner, etc.

[0124] Among them, the computing device may be a physical device or an elastic computing host provided by a cloud computing platform, etc. At this time, the computing device may refer to a cloud server, and the above-mentioned processing component, storage component, etc. may be basic server resources obtained from the cloud computing platform.

[0125] The embodiment of the present application also provides a computer storage medium storing a computer program, and when the computer program is executed by a computer, it can implement the above-mentioned Figure 1 A method for evaluating the carbon reduction effect in the production process of healthy agricultural products shown in the embodiment.

[0126] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0127] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative effort.

[0128] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or equivalently replace some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. A method for evaluating the carbon reduction effect in the production process of healthy agricultural products, characterized in that, Including: Tracking the carbon element migration path in chemical fertilizer application, organic fertilizer degradation and soil respiration, and collecting chemical reaction chain data at each stage of the production process; Determining the carbon emission concentration area according to the carbon element migration path, matching the by-product generation amount in the chemical reaction chain data with the pre-stored agricultural carbon emission path database, and analyzing the carbon retention amount caused by incomplete degradation of organic fertilizer and the distribution of residual methane products in the production process; Inputting the carbon retention amount, methane product distribution and intermediate product concentration in the chemical reaction chain data into the carbon emission dynamic compensation engine, and generating an optimization plan for soil pore structure and a compensation strategy for the organic fertilizer feeding gradient based on the carbon reduction effect evaluation index in the healthy agricultural product production standard; Adjusting the soil ventilation parameters according to the micro-oxygen environment control instruction in the compensation strategy, optimizing the soil micro-oxygen environment in combination with the soil pore structure optimization plan, and simultaneously controlling the organic fertilizer degradation rate through the methane product conversion plan to convert the residual intermediate products into stable carbon forms, so as to reduce the greenhouse gas release amount; Dynamically monitoring the migration path corresponding to the stable carbon form, and generating a carbon cycle balance map for evaluating the carbon reduction effect in combination with the adjusted soil ventilation parameters and chemical reaction chain data.

2. The method according to claim 1, wherein Inputting the carbon retention amount, methane product distribution and intermediate product concentration in the chemical reaction chain data into the carbon emission dynamic compensation engine, and generating an optimization plan for soil pore structure and an organic fertilizer feeding gradient compensation strategy based on the carbon reduction effect evaluation index in the healthy agricultural product production standard, including: Inputting the carbon retention amount caused by incomplete degradation of organic fertilizer, methane product distribution and intermediate product concentration in the chemical reaction chain data into the carbon emission dynamic compensation engine, so as to dynamically determine the optimization range of pore structure parameters according to the obtained soil type and carbon retention amount through the carbon emission dynamic compensation engine, and generate an optimized interval for soil pore diameter classification; Based on the optimized interval of soil pore diameter classification, combining the distribution density of methane-oxidizing bacteria in different soil tillage layers, generating an optimization plan for soil pore structure; Through the carbon emission dynamic compensation engine, based on the methane product distribution and intermediate product concentration, analyzing the degradation and chain-breaking threshold of plant structural organic matter in organic fertilizer, and combining the environmental temperature fluctuation range in the production process, generating the correlation rule between the staged feeding gradient and the regulation of degradation flora activity; Fusing the optimized interval of soil pore diameter classification and the correlation rule, generating a compensation strategy for the organic fertilizer feeding gradient.

3. The method according to claim 2, characterized in that, Fusing the optimized interval of soil pore diameter classification and the correlation rule, generating an organic fertilizer feeding gradient compensation strategy including micro-oxygen flux threshold, feeding time window offset and degradation rate compensation factor, including: According to the pore connectivity parameters of different soil types in the optimized interval of soil pore diameter classification, matching the organic fertilizer degradation rate attenuation coefficient corresponding to the environmental temperature fluctuation in the correlation rule, and generating a dynamic constraint relationship table between soil pore diameter and degradation rate; Based on the dynamic constraint relation table, analyze the maximum methane diffusion flux allowed within the optimized range of soil pore diameter classification, and combine the response delay time between the activity of the degrading microbial community and the feeding gradient in the association rules to generate a micro-oxygen flux threshold range and a feeding time window offset compensation range based on the depth of the soil tillage layer; According to the micro-oxygen flux threshold range, inversely constrain the optimized range of soil pore diameter classification, screen the pore diameter distribution patterns that meet the metabolic energy level requirements of methane-oxidizing bacteria, and at the same time, dynamically weight the compensation coefficient of the degrading microbial community activity based on the feeding time window offset compensation range to generate an organic fertilizer feeding gradient compensation strategy including pore reconstruction priority, feeding interval hot zone division, and microbial community activation trigger conditions.

4. The method according to claim 1, wherein Adjust the soil ventilation parameters according to the micro-oxygen environment control instructions in the compensation strategy, optimize the soil micro-oxygen environment in combination with the soil pore structure optimization plan, and at the same time control the degradation rate of organic fertilizer through the methane product conversion plan, including: Based on the compensation strategy, extract the target value range of soil oxygen concentration in the micro-oxygen environment control instructions, and obtain the soil ventilation adjustment parameters according to the soil pore structure optimization plan; According to the micro-oxygen environment control instructions, calculate the deviation between the current soil oxygen concentration and the target value range, and dynamically adjust the working mode of the soil ventilation equipment in combination with the soil ventilation adjustment parameters to generate optimized soil micro-oxygen environment data; According to the methane product conversion plan, determine the target rate range of organic fertilizer degradation, and dynamically adjust the feeding amount and distribution method of organic fertilizer based on the soil micro-oxygen environment data to control the degradation rate of organic fertilizer.

5. The method according to claim 2, wherein Based on the methane product distribution and intermediate product concentration, analyze the degradation and chain-breaking threshold of plant structural organic matter in organic fertilizer, and combine the environmental temperature fluctuation range during the production process to generate the association rules for staged feeding gradient and degrading microbial community activity regulation, including: Based on the methane product distribution and intermediate product concentration, analyze the degradation and chain-breaking threshold of plant structural organic matter in organic fertilizer, divide the degradation process of organic fertilizer into multiple stages according to the degradation and chain-breaking threshold, and determine the feeding gradient range for each stage; According to the environmental temperature fluctuation range during the production process, identify the influence law of temperature change on the degradation and chain-breaking threshold, and establish the mapping relationship between temperature and the degradation and chain-breaking threshold; Combine the mapping relationship, analyze the change trend of degrading microbial community activity under different temperature conditions, and determine the influence law of temperature on degrading microbial community activity; Based on the degradation and chain-breaking threshold and the feeding gradient range, and combine the influence law to generate the association rules for staged feeding gradient and degrading microbial community activity regulation.

6. The method according to claim 4, characterized in that, According to the methane product conversion plan, determine the target rate range of organic fertilizer degradation, and dynamically adjust the feeding amount and distribution method of organic fertilizer based on the soil micro-oxygen environment data to control the degradation rate of organic fertilizer, including: According to the methane product conversion scheme, extract the target rate range for the degradation of organic fertilizers, including the upper and lower limit values of the degradation rate, and based on the soil micro-oxygen environment data, analyze the impact of the current soil oxygen concentration on the degradation rate, and determine the applicable conditions for the target rate range; According to the target rate range, calculate the deviation amount between the current organic fertilizer degradation rate and the target rate range, and determine the adjustment amount of the feeding amount based on the deviation amount; Based on the applicable conditions of the target rate range, and according to the adjustment amount, dynamically adjust the feeding amount and distribution method of the organic fertilizer to ensure that the degradation rate is stable within the target rate range.

7. The method according to claim 1, characterized in that, Dynamically monitor the migration path of the stable carbon form, and generate a carbon cycle balance map for evaluating the carbon reduction effect by combining the adjusted chemical reaction chain data, including: Set monitoring points along the geographical distribution of the field irrigation channels during the production process, and collect the retention amount and lateral diffusion rate of the stable carbon form at different soil tillage layer depths. Integrate the collected retention amount and diffusion rate data to generate dynamic monitoring data corresponding to the migration path with the field irrigation channel as the geographical reference; According to the dynamic monitoring data, analyze the migration time delay amount of the stable carbon form under the soil pore connectivity gradient, and combine the change rate of the intermediate product concentration in the adjusted chemical reaction chain data to generate a dynamic mapping relationship table between the stable carbon form conversion efficiency and the degradation rate; Based on the dynamic mapping relationship table, match the constraint conditions between the tillage layer depth of different soil textures in the open farmland and the migration rate of the stable carbon form, and generate a set of carbon cycle dynamic parameters including the boundary of the humus retention hot zone, the lateral diffusion gradient of biochar, and the priority of methane oxidation inhibition; Overlay the set of carbon cycle dynamic parameters with the adjusted chemical reaction chain data spatially to generate a carbon cycle balance map with the tillage layer depth as the vertical axis and the field irrigation channel as the horizontal axis.

8. A carbon reduction effect evaluation system for the production process of healthy agricultural products, characterized in that, Including: A collection module that tracks the migration path of carbon elements in chemical fertilizer application, organic fertilizer degradation, and soil respiration, and simultaneously collects the chemical reaction chain data at each stage during the production process; A matching module that determines the carbon emission concentration area according to the carbon element migration path, combines the by-product generation amount in the chemical reaction chain data with the pre-stored agricultural carbon emission path database for matching, and analyzes the carbon retention amount and the distribution of residual methane products caused by incomplete degradation of organic fertilizers during the production process; A compensation module that inputs the carbon retention amount, methane product distribution, and the intermediate product concentration in the chemical reaction chain data into the carbon emission dynamic compensation engine, and generates an optimization plan for the soil pore structure and a compensation strategy for the organic fertilizer feeding gradient based on the carbon reduction effect evaluation index in the healthy agricultural product production standard; An adjustment module that adjusts the soil ventilation parameters according to the micro-oxygen environment control instruction in the compensation strategy, optimizes the soil micro-oxygen environment in combination with the soil pore structure optimization plan, and simultaneously controls the degradation rate of the organic fertilizer through the methane product conversion scheme to convert the residual intermediate product into a stable carbon form to reduce the greenhouse gas release amount; A generation module dynamically monitors the migration path corresponding to the stable carbon form, and generates a carbon cycle balance map for evaluating the carbon reduction effect by combining the adjusted soil aeration parameters and chemical reaction chain data.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for evaluating the carbon reduction effect in the production process of healthy agricultural products according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that, A computer program is stored, and when the computer program is executed by a computer, it implements a method for evaluating the carbon reduction effect in the production process of healthy agricultural products according to any one of claims 1 to 7.

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