A cultivation method for improving waterlogging resistance of sugarcane

Abstract

The present application relates to the field of agricultural engineering and crop cultivation, and discloses a cultivation method for improving the waterlogging resistance of sugarcane, comprising the following steps: S1, obtaining field data by three-dimensional terrain scanning and soil parameter analysis, and dividing high-risk areas, medium-risk areas and low-risk areas; S2, arranging aeration column devices in the high-risk areas, and dynamically distributing the gas injection rate according to the risk level of the areas; S3, filling porous materials and mechanically loosening the soil; S4, constructing an optimization model, and dynamically adjusting the aeration rate and the drainage rate; S5, dynamically regulating the aeration and drainage equipment in different areas according to the output results of the optimization model; and S6, reevaluating the soil porosity and water content after the waterlogging damage ends, and carrying out soil replacement and aeration supplement for the damaged areas. Through the combination of soil porosity optimization and dynamic control, the soil aeration and drainage capacity are improved, and the root zone environment is more suitable for waterlogging stress.

Description

Technical Field

[0001] The invention relates to the technical field of agricultural engineering and crop cultivation, and in particular to a cultivation method for improving the waterlogging resistance of sugarcane. Background Art

[0002] Sugarcane is a water-intensive crop, but its roots require high soil oxygen levels. Existing research indicates that the optimal soil oxygen content for sugarcane growth is 8% to 12%. However, excessive rainfall or irrigation rapidly depletes oxygen from the soil, leading to root hypoxia.

[0003] In major sugarcane-producing regions (such as tropical and subtropical regions), monsoon climates result in concentrated, heavy rainfall. Existing drainage technologies primarily rely on fixed ditch systems, which are slow to drain water and prone to failure during sudden rainfall increases. Studies have shown that when rainfall exceeds 50 mm per day, water often accumulates in low-lying areas, slowing water infiltration and directly affecting soil permeability and oxygen supply to the root zone.

[0004] Existing technologies primarily rely on fixed ditch drainage or single aeration systems to mitigate the impact of waterlogging. However, these measures lack dynamic control capabilities and are unable to adapt to the complex changes in field conditions. Especially in low-lying areas, where accumulated water is difficult to drain promptly, insufficient oxygen supply to the root zone further exacerbates secondary diseases such as root rot.

[0005] Furthermore, existing soil optimization methods primarily focus on the cultivated layer, neglecting to repair the pore structure of deeper soil layers. The lack of dynamic monitoring and real-time feedback control technologies also delays waterlogging management, making it difficult to implement effective measures in a timely manner. In the later stages of waterlogging, the lack of a systematic restoration plan results in inefficient soil structure reconstruction and oxygen recovery, leading to significant declines in sugarcane yield and quality. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the present invention provides a cultivation method for improving the waterlogging resistance of sugarcane, which solves the problems of root zone hypoxia, soil structure degradation and poor drainage caused by waterlogging in the existing sugarcane planting technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: A cultivation method for improving the waterlogging resistance of sugarcane, comprising the following steps:

[0008] S1. Through 3D terrain scanning and soil parameter analysis, obtain field topography distribution, soil porosity, saturation, and oxygen concentration data, and divide the field into high-risk, medium-risk, and low-risk areas;

[0009] S2. Deploy ventilation column devices in high-risk areas and dynamically allocate gas injection rates based on regional risk levels;

[0010] S3, filling with porous materials and mechanical loosening;

[0011] S4, using sensors to monitor soil oxygen concentration, moisture, and pore strain data, build an optimization model, and dynamically adjust ventilation and drainage rates;

[0012] S5. Based on the output of the optimization model, dynamically adjust the ventilation and drainage equipment in different areas to maintain the oxygen concentration in the root zone above the minimum oxygen concentration and the soil porosity within the target range;

[0013] S6. Reassess soil porosity and moisture content after waterlogging is over, and re-soil and supplement ventilation in damaged areas.

[0014] Preferably, in step S2, the ventilation device deployment includes arranging a distributed ventilation network in the high-risk area, and adjusting the gas injection rate to 1.5 to 2.0 cubic meters per hour through a pressure control device.

[0015] Preferably, in the step S3, the soil pore optimization includes filling the high-risk area with porous silicon-based granular material with a porosity of 35% to 45%.

[0016] Preferably, in step S4, the deployed sensors are used to collect soil oxygen concentration, moisture and pore strain data, and dynamically adjust the soil oxygen diffusion coefficient in combination with an oxygen diffusion model, and the oxygen diffusion model dynamically updates the diffusion rate according to the soil porosity and water saturation.

[0017] Preferably, the optimization model constructed in step S4 maximizes the soil oxygen transmission flux and maintains the oxygen concentration in the root zone not less than the minimum oxygen concentration of 0.02 kg per cubic meter, while dynamically adjusting the gas injection rate and drainage rate.

[0018] Preferably, in the step S5, by optimizing the objective function, the gas injection rate is maintained at 0.1 to 2.0 cubic meters per hour, the drainage rate is maintained at 1 to 3 centimeters per hour, and the soil porosity is maintained between 35% and 45%.

[0019] Preferably, in step S5, the gas injection rates of different regions are distributed according to the following ranges:

[0020] High-risk areas: gas injection rate is 1.5 to 2.0 cubic meters per hour;

[0021] Medium risk areas: gas injection rate is 0.5 to 1.0 cubic meters per hour;

[0022] Low-risk areas: Gas injection rate is 0.1 to 0.5 cubic meters per hour.

[0023] A cultivation system for improving waterlogging resistance of sugarcane, comprising:

[0024] Field data collection module, used to collect soil topography, porosity, saturation, oxygen concentration and humidity parameters;

[0025] A ventilation device module, including a ventilation column, a pressure control device and a distributed ventilation network;

[0026] Soil pore optimization module, including mechanical soil loosening device and porous granular material;

[0027] Real-time monitoring module, including oxygen concentration sensor, humidity sensor and pore strain sensor;

[0028] The dynamic optimization module runs soil oxygen diffusion, water flow and pore deformation models through computing units to dynamically control the ventilation rate, drainage rate and soil loosening frequency.

[0029] Preferably, the ventilation column of the ventilation device module is arranged vertically, with its bottom penetrating 40 to 50 cm into the root zone soil and its upper part connected to the atmosphere. The pressure control device dynamically adjusts the gas injection amount according to the optimization results to maintain a stable oxygen concentration gradient.

[0030] Preferably, the dynamic optimization module constructs a group of partial differential equations through real-time feedback data, and dynamically adjusts the operating parameters of the ventilation device and the loosening device in combination with the numerical solution method, so that the oxygen concentration and porosity of the root zone soil meet the target conditions required for plant growth.

[0031] The present invention provides a cultivation method for improving the waterlogging resistance of sugarcane. It has the following beneficial effects:

[0032] 1. This invention combines soil porosity optimization with dynamic control to improve soil aeration and drainage, making the root zone more resilient to waterlogging. Compared to traditional single-step mechanical soil scarification methods, this invention monitors and dynamically adjusts soil porosity in real time, addressing the limited aeration and rigid operation of traditional technologies.

[0033] 2. This invention utilizes a dynamic gas injection solution based on regional optimization. By combining a distributed ventilation network with real-time monitoring, it achieves precise control of oxygen concentrations in different risk areas. Compared to existing technologies that rely solely on fixed gas injection rates, this significantly addresses the issue of oxygen shortages in high-risk areas while also avoiding resource waste in low-risk areas.

[0034] 3. This invention utilizes real-time monitoring and optimization modeling technology to link soil oxygen diffusion and water flow patterns with control strategies, ensuring a stable root zone environment. Compared to existing solutions that rely on static management, this invention addresses the uncontrollable environmental changes under waterlogging conditions while also improving the adaptability of the solution.

[0035] 4. This invention combines post-flood recovery with a long-term optimization model, enabling rapid soil structure restoration and optimizing subsequent management strategies even after the disaster. Traditional post-flood treatment technologies often focus solely on drainage. This invention not only addresses the long recovery period after flooding but also provides a more scientific basis for predicting the next stage of cultivation management. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A diagram showing the steps of the method of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solution of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0038] Please see the attached Figure 1 The embodiment of the present invention provides a cultivation method for improving waterlogging resistance of sugarcane, comprising the following steps:

[0039] S1. Through 3D terrain scanning and soil parameter analysis, obtain field topography distribution, soil porosity, saturation, and oxygen concentration data, and divide the field into high-risk, medium-risk, and low-risk areas;

[0040] Specifically, when implementing the cultivation method of the present invention, accurate field data collection is fundamental to the entire technical process. To ensure scientific basis for subsequent steps such as aeration system deployment, soil porosity optimization, and dynamic regulation, a systematic analysis of the sugarcane field's topography and soil parameters is necessary.

[0041] In this example, a three-dimensional topographic scan of the sugarcane field was first performed to clearly identify the distribution of highlands, lowlands, and flat areas within the field. This topographic scan was performed using a drone-mounted LiDAR device. Typically, the scan resolution was set at 0.1 to 0.5 meters to ensure accurate topographic data. The results of the topographic scan were directly used for subsequent regional risk delineation.

[0042] In one possible implementation, field soil porosity, saturation, and initial oxygen concentration are collected to assess soil physical properties. Porosity can be measured using mercury intrusion or gas displacement methods, while saturation is measured using a TDR (time domain reflectometry) soil sensor. Furthermore, to ensure spatial data coverage, soil sampling points are placed in the field at intervals of 5 to 10 meters. These data can reflect the microenvironmental characteristics of the field soil.

[0043] Specifically, soil oxygen concentration is measured using multi-point gas diffusion sensors, which can monitor oxygen distribution at different soil depths in real time. Alternatively, oxygen sensors can be placed in the root zone (20 cm to 50 cm deep) to measure the average and gradient changes in oxygen concentration in the root zone.

[0044] In one embodiment, this step also analyzes the water distribution in the field in conjunction with meteorological data. For example, by inputting data on rainfall, evaporation, and soil drainage capacity into a hydrological simulation model, the distribution of accumulated water in the field can be determined. The hydrological simulation uses the following formula for calculation:

[0045]

[0046] Where: θ(t): soil moisture content, unit is m 3 / m 3 ; θ0: initial water content; P(t): rainfall, in mm; E(t): evaporation, in mm; q(t): drainage, in mm; φ: soil porosity (dimensionless).

[0047] In some embodiments, to improve data collection efficiency, drones can be combined with ground-based sampling equipment. The drones scan the terrain, while the ground-based equipment measures soil parameters. This collaborative approach enables data collection over large fields in a short period of time.

[0048] Specifically, sampling density was increased in high-risk areas to more accurately characterize soil properties in these areas. The sampling data was also directly input into subsequent optimization models to predict oxygen diffusion and water flow behavior.

[0049] S2. Deploy ventilation column devices in high-risk areas and dynamically allocate gas injection rates based on regional risk levels;

[0050] Specifically, after completing the field data collection and risk area demarcation in step S1, the core objective of step S2 is to rationally deploy ventilation devices based on regional risk levels to ensure that the oxygen supply to the root zone soil meets the actual needs of different areas. This step achieves precise management by designing ventilation column devices and distributed ventilation networks, dynamically adjusting the gas injection rate based on real-time monitoring data. Unlike traditional single ventilation methods, this method prioritizes deployment in high-risk areas, focusing on zoning optimization to ensure efficient resource utilization.

[0051] Generally, the design of aeration columns in this step should consider factors such as soil depth, gas diffusion patterns, and regional needs. In some embodiments, the depth and injection rate of aeration columns are adjusted to dynamically optimize the distribution of oxygen concentration in the root zone. Furthermore, the pipeline network is designed based on topographical characteristics to effectively align regional distribution with actual needs.

[0052] In this embodiment, the placement of the aeration column system is based on the field data analysis results from step S1. First, in high-risk areas, aeration columns are distributed according to the low-lying areas of the field. The bottoms of the columns are deep into the root zone of the soil, generally to a depth of 40 to 50 cm, to ensure that gas can directly reach the root zone. The tops of the columns are connected to the atmosphere, using atmospheric pressure differences as the primary driving force to inject gas into the soil.

[0053] In one possible implementation, the density of ventilation columns is dynamically adjusted based on the regional risk level. For example, in high-risk areas, the spacing between ventilation columns is generally 2 to 5 meters, while in medium-risk areas, this can be increased to 5 to 10 meters. In low-risk areas, only a small number of ventilation columns can be deployed, primarily to supplement oxygen supply.

[0054] Alternatively, this step can include designing a distributed aeration network, connecting the aeration columns to a ground piping system for more centralized and efficient gas injection. Specifically, the piping system can be made of corrosion-resistant PVC, with a diameter typically ranging from 50 mm to 100 mm to meet gas delivery requirements. In some embodiments, a pressure regulator is installed at the base of the aeration columns in high-risk areas to adjust the gas injection pressure to ensure that the oxygen diffusion rate matches the soil's requirements.

[0055] In order to further optimize the gas injection efficiency, this embodiment introduces an oxygen concentration diffusion model. The diffusion process of oxygen in soil follows Fick's first law, and its flux formula is:

[0056]

[0057] Where: J: oxygen flux, unit is kg / m 2 ·s; D: diffusion coefficient, unit is Determined by soil porosity and water saturation; Oxygen concentration gradient, in kg / m 3 / m.

[0058] In one possible implementation, the diffusion coefficient D is dynamically adjusted according to the soil porosity φ and water saturation θ. The specific expression is:

[0059]

[0060] Where: D0: oxygen diffusion coefficient in air, unit is m 2 / s; θ: soil water saturation (dimensionless); φ: soil porosity (dimensionless), generally between 0.35 and 0.45; n: empirical exponent, usually taken as 2.

[0061] By real-time monitoring of oxygen concentration and diffusion gradient changes, the injection rate of the ventilation column is dynamically adjusted to keep the oxygen concentration in the root zone of high-risk areas above 0.02 kilograms per cubic meter.

[0062] In general, the design of gas injection rate needs to be combined with regional division and soil properties. In the present invention, the gas injection rate of different risk areas is as follows:

[0063] The injection rate in high-risk areas was set at 1.5 to 2.0 cubic meters per hour;

[0064] Medium-risk areas are 0.5 to 1.0 cubic meters per hour;

[0065] In low-risk areas, it is 0.1 to 0.5 cubic meters per hour.

[0066] In another implementation, the aeration column injection system also incorporates a time-controlled mechanism. For example, high-intensity injection can be concentrated in the first three days after rainfall, running for more than eight hours per day, while the daily injection time can be reduced to two to four hours during normal periods.

[0067] This embodiment also enhances the focused management effectiveness of gas injection by optimizing the centralized deployment of gas in low-lying areas. For example, by increasing the density of aeration columns and injection pressure in low-lying areas of the field, gas can quickly cover the entire low-lying soil, reducing the stress of oxygen deficiency on the root system.

[0068] S3, filling with porous materials and mechanical loosening;

[0069] Specifically, in this embodiment, soil porosity optimization is primarily implemented through two steps: filling with porous materials and mechanical loosening. In high-risk areas, silicon-based porous granular materials are placed in low-lying areas of the field. These materials, made from lightweight silicates, typically have a porosity of 65% to 80%, significantly improving soil aeration. The particle size is typically between 0.5 mm and 2 mm to ensure adequate penetration into the root zone.

[0070] Specifically, porous granular materials can increase the effective porosity of the soil, thereby improving oxygen diffusion coefficient and water excretion capacity. Alternatively, these granules can be doped with materials with slow-release properties, such as zeolites or modified gypsum, to further enhance the material's functionality.

[0071] In this embodiment, the primary purpose of mechanical soil scarification is to further enhance the aeration and drainage capacity of the root zone soil. Generally, the scarification depth is 20 to 30 cm to ensure a uniform root zone environment. In high-risk areas, the scarification frequency can be increased appropriately, for example, every 10 to 15 days.

[0072] Alternatively, the mechanical scarification equipment can be equipped with a rotating rake mechanism that can simultaneously break up the soil's surface and mid-layer structure. In some embodiments, the scarification device is also equipped with sensors to monitor soil porosity and moisture content in real time, allowing for dynamic adjustment of operating depth.

[0073] In order to verify the effect of soil pore optimization, the present invention uses oxygen diffusion coefficient and water excretion rate as evaluation indicators.

[0074] The calculation of soil water excretion rate (q) is based on Darcy's law:

[0075]

[0076] Where: k h : hydraulic conductivity of soil in m / s, which depends on porosity and degree of saturation; Hydraulic gradient, in m / m.

[0077] Comparison of soil parameters before and after improvement confirmed the effectiveness of the porosity optimization. For example, in high-risk areas, the porosity increased from 0.30 to 0.40, the oxygen diffusion coefficient increased by over 30%, and the water excretion rate was significantly enhanced.

[0078] S4, using sensors to monitor soil oxygen concentration, moisture, and pore strain data, build an optimization model, and dynamically adjust ventilation and drainage rates;

[0079] Specifically, in this embodiment, the sensor network deployment is based on the field area division and soil optimization results from steps S1 and S3. Specifically, oxygen concentration sensors, moisture sensors, and pore strain sensors are prioritized in high-risk areas. These sensors monitor root zone oxygen concentration, soil moisture content, and soil deformation, respectively, ensuring comprehensive coverage of the target area.

[0080] As an option, oxygen concentration sensors are deployed within the root zone at a depth of 20 to 50 centimeters, with a monitoring frequency typically set every 10 minutes. These sensors can collect dynamic changes in soil oxygen concentration in real time and upload the data to a monitoring center via a wireless transmission module.

[0081] Humidity sensors are used to measure soil moisture content and saturation. Typically, humidity sensors use TDR (time domain reflectometry) technology, and their probe length can be flexibly adjusted based on soil depth, typically ranging from 10 to 30 centimeters. In some embodiments, to improve humidity monitoring accuracy, the density of measurement points can be increased, with sensors deployed every 5 to 10 meters.

[0082] Pore ​​strain sensors are used to monitor soil deformation and porosity changes. Installed in the surface and middle layers of the root zone, these sensors can capture dynamic changes in soil deformation in real time, providing data support for assessing soil structural stability.

[0083] In one possible implementation, a partial differential equation model is used in this example to analyze the monitoring data.

[0084] The dynamic changes of oxygen concentration follow the following diffusion model:

[0085] Where: C: soil oxygen concentration, unit is kg / m 3 ; t: time, unit is s; D: oxygen diffusion coefficient, unit is m 2 / s; Laplace operator, representing the spatial gradient of oxygen concentration; k: oxygen consumption rate, unit is s -1 , which is determined by the root oxygen absorption rate and microbial metabolic rate.

[0086] Specifically, the calculation formula of the diffusion coefficient D is: D = D0(1-θ)φ n

[0087] Where: D0: oxygen diffusion coefficient in air; θ: soil water saturation, dimensionless; φ: soil porosity, dimensionless; n: empirical exponent, generally taken as 2. The oxygen consumption rate k is calculated based on root metabolism and soil microbial activity.

[0088] Alternatively, oxygen consumption parameters can be determined experimentally for different soil types.

[0089] In order to evaluate the soil water drainage capacity, this example uses Darcy's law to describe the water flow behavior. The hydraulic conductivity k x The dynamic changes of are calculated by the following formula:

[0090] k x =k X0 (1-θ)^m

[0091] Where: k X0 : hydraulic conductivity of soil under saturated state; θ: soil saturation; m: empirical index, usually 3.

[0092] S5. Based on the output of the optimization model, dynamically adjust the ventilation and drainage equipment in different areas to maintain the oxygen concentration in the root zone above the minimum oxygen concentration and the soil porosity within the target range;

[0093] Specifically, in this embodiment, dynamic control is implemented based on the optimization model results from step S4. Specifically, the optimization model outputs control parameters for equipment operation based on monitoring data on regional oxygen concentration, soil moisture content, and porosity. For high-risk areas, the gas injection rate and drainage equipment operation frequency are prioritized to quickly alleviate environmental pressures.

[0094] Alternatively, the gas injection rate can be adjusted based on soil oxygen concentration. Generally, when the oxygen concentration falls below the minimum oxygen requirement (0.02 kg / m3), the injection rate of the aeration column needs to be increased.

[0095] The adjustment strategy can be described by the following formula:

[0096] Q 注入 =α·∫ Ω (C 目标 -C 实际 )dΩ

[0097] Where: Q 注入 : Gas injection rate, in m 3 / h; α: control gain factor, dynamically adjusted according to the field environment; C 目标 : Target oxygen concentration, generally set to 0.03 kg per cubic meter; C 实际 : Current oxygen concentration, obtained by monitoring the sensor; Ω: Area volume.

[0098] In one possible implementation, the control strategy of the drainage device uses soil moisture content and hydraulic gradient as main parameters.

[0099] hydraulic gradient Using Darcy's law, the drainage rate adjustment formula is:

[0100]

[0101] Where: q 排水 : The operating speed of the drainage equipment, in m 3 / s; β: control gain factor, used to adjust the response intensity of the drainage equipment; Hydraulic gradient, in m / m.

[0102] Specifically, when the soil saturation exceeds a threshold (e.g., 0.8), the system automatically increases the intensity of drainage equipment operation. Alternatively, drainage equipment in low-lying areas is activated first, while drainage equipment in high-lying areas is gradually operated according to water flow conditions.

[0103] In one possible implementation, the dynamic control strategy of the present invention also incorporates a regionalized priority adjustment mechanism. Specifically, the operating frequency and intensity of equipment in high-risk areas are prioritized to ensure that resources are concentrated in areas with the greatest environmental pressure. Equipment in medium-risk areas operates at normal frequencies, while equipment in low-risk areas is placed in standby mode and activated only when necessary.

[0104] In some embodiments, dynamic control strategies also incorporate predictions from historical data. For example, based on meteorological forecasts of rainfall and evaporation, equipment operating intensity can be adjusted in advance to prevent sudden increases in environmental pressure from impacting system operations.

[0105] This embodiment also achieves efficient dynamic control through multiple iterations of optimization. For example, within a single adjustment cycle, the system continuously updates the optimization model based on real-time monitoring data and generates new control parameters to ensure that the device's operating status always matches environmental requirements. The control cycle is typically set to every 10 to 30 minutes to balance the system's real-time performance with computational cost.

[0106] S6. Reassess soil porosity and moisture content after waterlogging is over, and re-soil and supplement ventilation in damaged areas.

[0107] Specifically, in this embodiment, post-flood recovery begins with a reassessment of soil conditions to determine the specific extent of damage in each area. Specifically, high-risk areas, due to prolonged waterlogging, may experience soil compaction and severe oxygen depletion. Therefore, these areas are prioritized for soil restoration and oxygen replenishment through aeration systems.

[0108] A cultivation system for improving waterlogging resistance of sugarcane, comprising:

[0109] Field data collection module, used to collect soil topography, porosity, saturation, oxygen concentration and humidity parameters;

[0110] A ventilation device module, including a ventilation column, a pressure control device and a distributed ventilation network;

[0111] Soil pore optimization module, including mechanical soil loosening device and porous granular material;

[0112] Real-time monitoring module, including oxygen concentration sensor, humidity sensor and pore strain sensor;

[0113] The dynamic optimization module runs soil oxygen diffusion, water flow and pore deformation models through computing units to dynamically control the ventilation rate, drainage rate and soil loosening frequency.

[0114] Specifically, the field data acquisition module combines sensing equipment with terrain scanning equipment to capture field soil topography, porosity, saturation, oxygen concentration, and humidity. This module utilizes drone-mounted LiDAR scanning equipment to obtain three-dimensional topographic maps, while a soil sensor array deployed in the field simultaneously collects microscopic data in real time. This data is wirelessly transmitted to the dynamic optimization module, providing real-time input for subsequent analysis. By acquiring precise data, this module avoids the limitations of relying on empirical judgment and provides a scientific foundation for the operation of the entire system.

[0115] The aeration module consists of an aeration column, a pressure control device, and a distributed aeration network, which is connected to different areas of the field via surface pipes. The bottom of the aeration column extends deep into the root zone, and the top is connected to the atmosphere or a pressure control device, which adjusts the air pressure to achieve precise oxygen injection. The distributed aeration network dynamically distributes oxygen flow according to field zones, prioritizing the needs of high-risk areas. By enhancing the oxygen concentration gradient in the root zone, the module improves the diffusion efficiency of oxygen in the soil and effectively alleviates the problem of root hypoxia in waterlogged environments.

[0116] The Soil Porosity Optimization Module combines a mechanical scarifier with porous granular materials to improve soil aeration and drainage. The mechanical scarifier uses rotating rakes to deeply scarify the root zone, enhancing soil air permeability and water mobility. The porous granular materials are then added to the soil to maintain the optimized pore structure over time. The module effectively improves soil structural degradation after waterlogging and provides a good physical pathway for oxygen diffusion and water drainage.

[0117] The real-time monitoring module, comprised of oxygen concentration sensors, humidity sensors, and pore strain sensors, collects key field soil parameters through a sensor network and transmits this data in real time to the dynamic optimization module. Through high-frequency monitoring, the module captures dynamic changes in the field environment, providing an accurate basis for subsequent adjustments to control strategies. The real-time monitoring module's advantage lies in its precise reflection of soil oxygen concentration, humidity, and deformation, avoiding the inherent lag and limited data collection inherent in traditional monitoring technologies.

[0118] The dynamic optimization module is the system's core computing unit. It runs soil oxygen diffusion, water flow, and pore deformation models, comprehensively analyzing input from the field data acquisition and real-time monitoring modules. Based on the optimization objectives, the module dynamically outputs control parameters such as aeration rate, drainage rate, and soil scarification frequency, adjusting the operating status of each execution module. The dynamic optimization module enables intelligent system management, making the operation of aeration, drainage, and soil scarification equipment more precise and efficient, effectively improving resource utilization and field management effectiveness.

[0119] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A cultivation method for improving waterlogging resistance of sugarcane, characterized in that: The following steps are involved: S1. Through 3D terrain scanning and soil parameter analysis, obtain field topography distribution, soil porosity, saturation, and oxygen concentration data, and divide the field into high-risk, medium-risk, and low-risk areas; S2. Deploy ventilation devices in high-risk areas and dynamically allocate gas injection rates based on regional risk levels; S3, filling with porous materials and mechanically loosening the soil; S4, using sensors to monitor soil oxygen concentration, moisture, and pore strain data, build an optimization model, and dynamically adjust ventilation and drainage rates; S5. Based on the output of the optimization model, dynamically adjust the ventilation and drainage equipment in different areas to maintain the oxygen concentration in the root zone above the minimum oxygen concentration and the soil porosity within the target range; S6. Reassess soil porosity and moisture content after waterlogging is over, and re-soil and supplement ventilation in damaged areas.

2. The method for improving the waterlogging resistance of sugarcane according to claim 1, wherein: In the step S2, the deployment of ventilation devices includes arranging a distributed ventilation network in the high-risk area, and adjusting the gas injection rate to 1.5 to 2.0 cubic meters per hour through a pressure control device.

3. The method for improving the waterlogging resistance of sugarcane according to claim 1, wherein: In step S4, the deployed sensors are used to collect soil oxygen concentration, moisture, and pore strain data, and dynamically adjust the soil oxygen diffusion coefficient in combination with an oxygen diffusion model. The oxygen diffusion model dynamically updates the diffusion rate based on soil porosity and water saturation.

4. A cultivation method for improving waterlogging resistance of sugarcane according to claim 3, characterized in that: The optimization model constructed in the S4 step maximizes the soil oxygen transmission flux and maintains the root zone oxygen concentration not lower than the minimum oxygen concentration of 0.02 kg / m3, while dynamically adjusting the gas injection rate and drainage rate.

5. The method for improving the waterlogging resistance of sugarcane according to claim 1, wherein: In the step S5, by optimizing the objective function, the gas injection rate is maintained at 0.1 to 2.0 cubic meters per hour, the drainage rate is maintained at 1 to 3 centimeters per hour, and the soil porosity is maintained between 35% and 45%.

6. The method for improving waterlogging resistance of sugarcane according to claim 1, wherein: In step S5, the gas injection rates of different regions are distributed according to the following ranges: High-risk areas: gas injection rate is 1.5 to 2.0 cubic meters per hour; Medium risk areas: gas injection rate is 0.5 to 1.0 cubic meters per hour; Low-risk areas: Gas injection rate is 0.1 to 0.5 cubic meters per hour.

7. A cultivation system for improving waterlogging resistance of sugarcane, according to a cultivation method for improving waterlogging resistance of sugarcane according to any one of claims 1 to 6, characterized in that: include: Field data collection module, used to collect soil topography, porosity, saturation, oxygen concentration and humidity parameters; A ventilation device module, including a ventilation column, a pressure control device and a distributed ventilation network; Soil pore optimization module, including mechanical soil loosening device and porous granular material; Real-time monitoring module, including oxygen concentration sensor, humidity sensor and pore strain sensor; The dynamic optimization module runs soil oxygen diffusion, water flow and pore deformation models through computing units to dynamically control the ventilation rate, drainage rate and soil loosening frequency.

8. The cultivation system for improving waterlogging resistance of sugarcane according to claim 7, characterized in that: The ventilation column of the ventilation device module is arranged vertically, with its bottom 40 to 50 cm deep into the root zone soil and the upper part connected to the atmosphere. The pressure control device dynamically adjusts the gas injection amount according to the optimization results to maintain a stable oxygen concentration gradient.

9. The cultivation system for improving waterlogging resistance of sugarcane according to claim 7, characterized in that: The dynamic optimization module constructs a set of partial differential equations through real-time feedback data, and combines numerical solution methods to dynamically adjust the operating parameters of the ventilation device and the loosening device so that the oxygen concentration and porosity of the root zone soil meet the target conditions required for plant growth.

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