A directional control method and equipment for bamboo ecological soil restoration

Abstract

The present invention relates to the technical field of ecological soil remediation, and discloses a method and equipment for directional control of bamboo ecological soil remediation, which is used to solve the problems of insufficient light transmittance and low efficiency of acidified soil remediation caused by the fixed ratio of traditional bamboo and broad-leaved mixed forests. The present invention uses Internet of Things sensors to monitor soil pH, available phosphorus and meteorological data in real time, combines the random forest algorithm to dynamically optimize the mixed ratio and the configuration of associated tree species, uses drone scanning to generate a three-dimensional canopy model, guides intelligent equipment for precise thinning and replanting, and cooperates with pH-responsive shading film and acid-resistant phosphate-dissolving bacteria to achieve improved canopy transmittance and acidified soil improvement. The equipment includes a drone equipped with a laser radar, an intelligent transplanting robot and a solar drip irrigation system, which can dynamically control the concentration of the bacteria and the irrigation strategy. The innovative use of bamboo waste to prepare a porous bamboo charcoal carrier to load functional bacteria replaces traditional peat raw materials; the above solution solves the problems of static configuration, manual dependence and resource waste.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological soil restoration, and in particular to a directional control method for bamboo ecological soil restoration and equipment thereof. Background Art

[0002] In subtropical regions, long-term monoculture and over-exploitation of bamboo forests have led to increasingly serious problems such as soil acidification and nutrient imbalance, and traditional ecological soil remediation methods have significant limitations.

[0003] Existing technologies primarily employ fixed ratios for mixed bamboo and broadleaf forests, lacking a dynamic adjustment mechanism. This leads to uneven distribution of light and heat resources, insufficient canopy transmittance, and difficulty adapting to spatiotemporal variations in soil parameters. Because mixed bamboo and broadleaf forests employ fixed ratios, for example, when moso bamboo accounts for more than 80%, the canopy density is excessive, inhibiting the growth of associated species. Furthermore, it is impossible to dynamically optimize the mixed ratio and species configuration based on soil parameters.

[0004] In addition, traditional remediation methods rely on manual experience and decision-making, which are inefficient and costly, especially in acidified soils (pH < 5.5). The effective phosphorus content is low due to the fixation of aluminum ions, the accumulation rate of organic matter is slow, and the soil improvement effect is limited.

[0005] At the same time, traditional bacterial agent carriers mostly rely on non-renewable resources such as peat, which are costly and not environmentally friendly enough, and bamboo processing waste has not been utilized at a high value, resulting in waste of resources.

[0006] Therefore, we propose a directional control method and equipment for bamboo ecological soil remediation to solve the problems in the above background. Summary of the Invention

[0007] The present invention provides a directional control method and equipment for bamboo ecological soil restoration, which can solve the problem that the ecological soil restoration methods in the existing technology rely on manual experience-based decision-making, mainly adopt a fixed ratio of bamboo and broad-leaved mixed forest configuration, lack of a dynamic adjustment mechanism, resulting in uneven distribution of light and heat resources, insufficient canopy transmittance, and difficulty in adapting to the temporal and spatial changes of soil parameters.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0009] A directional control method for bamboo ecological soil restoration, comprising the following steps:

[0010] Step (1) deploying multi-parameter soil sensors and micro-meteorological stations in the bamboo forest area to be restored, collecting soil parameters and meteorological data in real time, and transmitting the data to the edge computing gateway for pre-processing through the communication module;

[0011] Step (2) constructing a dynamic control model based on a machine learning algorithm, inputting historical bamboo growth data, real-time soil and meteorological data, and meteorological forecast information, and outputting dynamic mixed planting ratio recommendations, optimal sequence of associated tree species, and target value of canopy transmittance;

[0012] Step (3) Based on the decision-making plan, a three-dimensional canopy model is generated by scanning with a drone, and the canopy density is adjusted, associated tree species are planted, and soil conditioners are applied through the forestry intelligent operation terminal;

[0013] Step (4) dynamically adjusts the interplanting ratio and soil improvement strategy through periodic light interception rate measurement, soil profile sampling and model iterative optimization.

[0014] Preferably, in step (1), the pH value, organic matter content, available phosphorus concentration, forest light intensity, temperature and humidity parameters of the topsoil and subsoil layers are collected in real time through a uniformly distributed multi-parameter soil sensor network micro-meteorological station.

[0015] Preferably, in step (2), a dynamic control model is constructed based on the random forest algorithm, and historical bamboo growth data, a typical restoration case library, real-time monitoring data and meteorological forecast information are input. According to the comparison results of the real-time detection values ​​of soil organic matter content, available phosphorus concentration and understory light intensity with preset thresholds, a nitrogen-fixing tree species configuration plan or canopy structure adjustment instructions are dynamically generated.

[0016] Preferably, in step (3), a drone is used to scan the forest crown to generate a three-dimensional model, and precise thinning is carried out in areas where the forest crown density is higher than a preset threshold. Acid-resistant companion tree species are replanted through intelligent equipment, and a composite soil conditioner is automatically applied according to the real-time detected soil pH value.

[0017] Preferably, in step (4), a quarterly light interception rate monitoring and annual soil profile analysis mechanism is established, and when the soil available phosphorus growth rate is less than 5% for three consecutive seasons, the configuration plan for deep-rooted camphor tree species is triggered to be retrained.

[0018] Preferably, in step (1), the sensor network is deployed at a preset density in each hectare of bamboo forest to monitor surface and deep soil parameters in layers. The data is transmitted to the edge computing gateway through the communication module for preprocessing and periodically uploaded to the cloud database.

[0019] Preferably, the dynamic control model in step (2) dynamically adjusts the proportion of associated tree species according to the available phosphorus content and organic matter level in the soil, and generates a thinning plan based on the target value of canopy transmittance.

[0020] Preferably, the construction of the dynamic control model includes the following steps:

[0021] (a) Determine the correlation threshold rules between soil organic matter content and available phosphorus concentration, and the mapping relationship between forest light intensity and canopy transmittance through feature analysis;

[0022] (b) generating a multi-dimensional decision-making scheme based on the association threshold rules and mapping relationships, including dynamic mixed planting ratio adjustment suggestions, companion tree species adaptability scores, and canopy transmittance target values;

[0023] (c) Based on the real-time monitoring results of soil pH, the configuration priority of companion tree species is dynamically adjusted. The lower the soil pH value, the higher the priority level of companion tree species.

[0024] Preferably, moso bamboo waste is processed for high value and prepared into a bacterial agent carrier with adsorption and sustained-release properties for soil remediation and stabilization of bamboo forest ecosystems; moso bamboo waste including bamboo chips, bamboo branches and bamboo roots are crushed, the particle size is controlled to be below 2 mm, and porous bamboo charcoal is obtained through an oxygen-limited pyrolysis process; the bamboo charcoal powder is then mixed with nanoparticles, treated by a hydrothermal method, and loaded with magnetic particles to enhance the adsorption performance and sustained-release capacity of the carrier; and phosphate-solubilizing bacteria, nitrogen-fixing bacteria and drought-resistant fungi are compounded into a composite bacterial community, mixed with modified bamboo charcoal and signal molecules, and prepared into a granular bacterial agent through low-temperature spray drying.

[0025] Preferably, the soil conditioner applied in step (3) includes a nano-modified bacterial agent containing phosphate-solubilizing bacteria and a pH-responsive light-shielding film, wherein the light-shielding film is used to neutralize acidic precipitation and adjust the light intensity under the forest.

[0026] A bamboo ecological soil remediation directional control device for a bamboo ecological soil remediation directional control method includes: multi-parameter soil sensors and micro-meteorological stations are deployed in the bamboo forest area to be restored, the soil sensors and the micro-meteorological stations are electrically data-connected to a communication module, the communication module is electrically connected to an edge computing gateway, the edge computing gateway is data-connected to a cloud server cluster, the cloud server cluster is used to run a cloud database and an AI model; the cloud server cluster is data-connected to a forestry intelligent operation terminal for soil remediation directional control.

[0027] Preferably, the forestry intelligent operation terminal includes a drone, an intelligent transplanting robot, and an intelligent drip irrigation system; the drone is equipped with a laser radar and a hyperspectral camera, and a light-shielding film delivery compartment. The laser radar is installed at the center of the bottom of the drone, and the hyperspectral camera is installed in front under the nose of the drone, and is equipped with a three-axis stabilization platform; the drone is equipped with the laser radar and hyperspectral camera for scanning the forest canopy to generate a three-dimensional model, and implements precise thinning according to the density heat map;

[0028] The shading film delivery bins are symmetrically arranged on both sides of the UAV fuselage, and an electric rolling door mechanism is provided inside the shading film delivery bins; the UAV is equipped with the shading film delivery bins for delivering the shading film to the forest area;

[0029] The intelligent transplanting robot is equipped with an AI vision system, which includes a panoramic binocular camera and a lateral laser triangulation sensor installed on the top of the intelligent transplanting robot, which are used to identify and build a three-dimensional semantic map of the forest. The front-end platform of the intelligent transplanting robot is equipped with a six-axis collaborative robotic arm, and the end of the six-axis collaborative robotic arm is equipped with electric pruning shears and a vacuum suction gripper.

[0030] The intelligent transplanting robot is equipped with a sowing unit at the rear, which includes three independent seed storage bins for storing camphor, nanmu and superba seeds respectively. The intelligent transplanting robot is equipped with an air-suction seed metering device that cooperates with the independent seed storage bins. At the same time, a furrow opener is installed at the bottom of the intelligent transplanting robot.

[0031] The AI ​​vision system equipped with the intelligent transplanting robot is used to identify overcrowded branches and perform selective branch thinning operations and replant companion tree species;

[0032] The intelligent drip irrigation system includes a microbial agent storage tank, an irrigation water tank, and an electromagnetic proportional valve. The microbial agent storage tank and the irrigation water tank are connected to the electromagnetic proportional valve, which is used to dynamically adjust the mixing ratio of the microbial agent and irrigation water. The liquid outlet of the electromagnetic proportional valve is fixedly connected to a delivery pump, which is connected to the drip irrigation pipe.

[0033] The outside of the drip irrigation pipe is covered with a flexible solar film, which is electrically connected to an energy storage battery pack.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] This invention achieves dynamic and precise ecological restoration and efficient resource utilization through the deep integration of Internet of Things technology, machine learning algorithms, and smart devices, providing an innovative solution for subtropical acidified bamboo forests. The specific implementation methods are as follows:

[0036] Traditional mixed bamboo and broadleaf forests rely on fixed ratios, resulting in insufficient canopy light transmittance and an imbalance in the distribution of light and heat resources. This method uses real-time soil parameter and meteorological data, along with a random forest algorithm, to dynamically adjust the mixed ratio and prioritize companion tree species such as jujube and Schima superba.

[0037] By using drone scanning to generate a 3D canopy model, and precisely implementing thinning and replanting, the canopy's light transmittance has been significantly improved, and the understory's light intensity remains within an optimal range. This technology not only improves bamboo's photosynthetic efficiency but also promotes the growth of associated tree species, significantly increasing the annual growth rate of bamboo's diameter at breast height and significantly shortening its maturity cycle.

[0038] Compared to traditional restoration methods that rely on manual experience, are inefficient, and suffer from large errors, this method uses intelligent transplanting robots and drones to collaborate, achieving precise thinning and replanting operations, and achieving industry-leading error control. Furthermore, the AI-driven solar drip irrigation system dynamically adjusts the concentration of the microbial agent based on soil nutrient data to ensure efficient resource utilization. The use of intelligent equipment significantly reduces manual maintenance costs, improves the accuracy and utilization rate of microbial agent application, and solves the resource waste and high cost issues associated with traditional methods.

[0039] To address the challenges of slow phosphorus fixation and organic matter accumulation in acidic soils, this invention innovatively introduces acid-resistant tree species and functional bacterial agents for synergistic remediation. The decomposition of fallen leaves from acid-resistant trees like Schima superba releases alkaline substances, which, combined with a nano-shading film, neutralizes acidic precipitation, effectively raising soil pH. The combination of acid-resistant phosphate-solubilizing bacteria and a modified bamboo charcoal carrier breaks down the aluminum-phosphorus complex structure in the soil, significantly increasing available phosphorus content. The annual increase in organic matter is several times that of traditional methods, shortening the soil fertility recovery period to less than 18 months, providing sustainable nutrient support for bamboo growth.

[0040] Traditional microbial agents rely on non-renewable resources like peat, which is costly and environmentally inefficient. This invention transforms bamboo processing waste into porous bamboo charcoal through a specialized pyrolysis process, which then loads it with functional bacteria to create a highly effective, slow-release microbial agent. This technology not only reduces raw material costs but also recycles waste resources. Furthermore, shade-tolerant cash crops like Japanese knotweed are planted under the forest floor, creating a three-dimensional model of restoration, cultivation, and profitability, significantly increasing income per mu while balancing ecological and economic benefits.

[0041] By establishing a multi-layered planting system of bamboo, broadleaf trees, and cash crops, combined with intelligent drip irrigation and a carbon sequestration optimization model, carbon sequestration per unit area has significantly increased. Improved microclimates within the forest have increased air humidity and lowered summer temperatures, effectively alleviating heat stress on the bamboo. The introduction of cash crops not only suppresses pests and diseases but also enhances soil carbon sequestration through root interactions, creating a virtuous cycle of ecological restoration and industrial development. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 Schematic diagram of the overall dynamic control process of the present invention;

[0043] Figure 2 Schematic diagram of the data collection and preprocessing process of the present invention;

[0044] Figure 3 Schematic diagram of the model decision-making scheme of the present invention;

[0045] Figure 4 This is a schematic diagram of the precise control execution process of the present invention;

[0046] Figure 5This is a schematic diagram of the effect monitoring and optimization process of the present invention;

[0047] Figure 6 This is a schematic diagram of the connection structure of the bamboo ecological soil remediation directional control equipment of the present invention. DETAILED DESCRIPTION

[0048] The specific embodiments of the present invention are described in detail below, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments.

[0049] Example 1:

[0050] See also Figures 1 to 6 , the present invention provides a technical solution:

[0051] A directional control method for bamboo ecological soil restoration, comprising the following steps:

[0052] Step (1) deploying multi-parameter soil sensors and micro-meteorological stations in the bamboo forest area to be restored, collecting soil parameters and meteorological data in real time, and transmitting the data to the edge computing gateway for pre-processing through the communication module;

[0053] Step (2) constructing a dynamic control model based on a machine learning algorithm, inputting historical bamboo growth data, real-time soil and meteorological data, and meteorological forecast information, and outputting dynamic mixed planting ratio recommendations, optimal sequence of associated tree species, and target value of canopy transmittance;

[0054] Step (3) Based on the decision-making plan, a three-dimensional canopy model is generated by scanning with a drone, and the canopy density is adjusted, associated tree species are planted, and soil conditioners are applied through the forestry intelligent operation terminal;

[0055] Step (4) dynamically adjusts the interplanting ratio and soil improvement strategy through periodic light interception rate measurement, soil profile sampling and model iterative optimization.

[0056] In step (1), the pH value, organic matter content, available phosphorus concentration, forest light intensity, temperature and humidity parameters of the topsoil and subsoil layers are collected in real time through the evenly distributed multi-parameter soil sensor network micro-meteorological stations.

[0057] In the above plan, appropriate bamboo and broad-leaved mixed ratios and accompanying tree species are selected; the mixed ratios and tree species are adjusted through dynamic control technology of bamboo and broad-leaved mixed forests to optimize the canopy structure, improve the lighting conditions under the forest, and promote the growth of bamboo.

[0058] The dynamic control technology of mixed bamboo and broadleaf forests is based on real-time data from soil sensors, such as pH, organic matter, available phosphorus content, as well as meteorological information such as light, temperature and humidity. It dynamically adjusts the proportion of mixed bamboo and broadleaf forests and accompanying tree species. The accompanying tree species can be hawthorn, chinaberry or cycad, etc., and then uses AI algorithms to generate the optimal canopy structure model to improve the microenvironment under the forest and promote the synergistic effect of bamboo growth and soil remediation.

[0059] The above solution breaks through the limitations of traditional fixed mixed planting ratios, realizes data-driven mixed planting management, and significantly improves light energy utilization and the dynamic balance of soil nutrients.

[0060] Furthermore, the specific implementation method of the dynamic regulation technology of mixed bamboo and broadleaf forests is as follows:

[0061] In the first phase, 8 to 12 multi-parameter soil sensor nodes were evenly distributed per hectare across the bamboo forest to be restored, along with a network of micro-weather stations. The sensors were arranged in a honeycomb pattern, vertically layered in both the topsoil and subsoil layers, with depths ranging from 0 to 30 cm and 30 to 60 cm, respectively.

[0062] This method continuously collects key indicators such as soil pH, organic matter content, available phosphorus concentration, and electrical conductivity, while also monitoring microclimate parameters such as forest light intensity (lux), air temperature and humidity, and rainfall. All nodes form an ad hoc network using the LoRaWAN protocol. An edge computing gateway powered by an NVIDIA Jetson Nano preprocesses data, removes outliers, and uploads it to a cloud database every five minutes.

[0063] In the second stage, a dynamic control model was constructed based on the random forest algorithm, and historical bamboo growth data, a typical restoration case library, real-time monitoring data and meteorological forecast information were input. According to the comparison results of the real-time detection values ​​of soil organic matter content, available phosphorus concentration and understory light intensity with the preset thresholds, nitrogen-fixing tree species configuration plans or canopy structure adjustment instructions were dynamically generated.

[0064] Drones are used to scan the forest canopy to generate a three-dimensional model, and precise thinning is carried out in areas where the canopy density exceeds the preset threshold. Acid-resistant companion tree species are replanted through intelligent equipment, and compound soil conditioners are automatically applied based on the real-time soil pH value.

[0065] Establish a quarterly light interception rate monitoring and annual soil profile analysis mechanism. When the growth rate of soil available phosphorus is <5% for three consecutive seasons, trigger the retraining of the configuration plan for deep-rooted camphor tree species.

[0066] The sensor network is deployed at a preset density in each hectare of bamboo forest to monitor surface and deep soil parameters in layers. The data is transmitted to the edge computing gateway through the communication module for preprocessing and periodically uploaded to the cloud database.

[0067] The dynamic control model dynamically adjusts the proportion of associated tree species according to the available phosphorus content and organic matter level in the soil, and generates a thinning plan based on the target value of canopy transmittance.

[0068] The construction of the dynamic control model includes the following steps:

[0069] (a) Determine the correlation threshold rules between soil organic matter content and available phosphorus concentration, and the mapping relationship between forest light intensity and canopy transmittance through feature analysis;

[0070] (b) generating a multi-dimensional decision-making scheme based on the association threshold rules and mapping relationships, including dynamic mixed planting ratio adjustment suggestions, companion tree species adaptability scores, and canopy transmittance target values;

[0071] (c) Based on the real-time monitoring results of soil pH, the configuration priority of companion tree species is dynamically adjusted. The lower the soil pH value, the higher the priority level of companion tree species.

[0072] In this solution, a dynamic control model based on a random forest algorithm is deployed in the cloud. Its training dataset includes: ① 10 years of historical bamboo growth indicators, including annual DBH growth; ② a database of typical mixed bamboo and broadleaf forest restoration cases from 2018 to 2023; ③ real-time access to soil and meteorological time series data streams; and ④ 72-hour high-precision weather forecast data. The model extracts key decision factors through feature engineering. For example, when the organic matter content is detected to be less than 15g / kg and the available phosphorus is less than 8mg / kg, nitrogen-fixing tree species are recommended.

[0073] When the understory light intensity consistently falls below 8,000 lux, a canopy structure adjustment command is triggered. The final output includes dynamic recommendations for interplanting ratios, an optimal sequence of companion tree species, such as adaptability scores for jujube, chinaberry, and liquidambar formosana, and a three-dimensional decision plan for canopy transmittance targets.

[0074] The output is the recommended value of dynamic mixed ratio and the canopy density adjustment plan. The canopy density is monitored by drones, and a three-dimensional canopy model is generated by drone lidar scanning.

[0075] In the third phase, the intelligent forestry operation terminal includes a drone, an intelligent transplanting robot, and an intelligent drip irrigation system. The drone is equipped with a lidar, a hyperspectral camera, and a shading film delivery compartment. The lidar is installed in the center of the drone's bottom, and the hyperspectral camera is installed in the front under the drone's nose. It is equipped with a three-axis stabilization platform. The drone is equipped with the lidar and hyperspectral camera to scan the forest canopy to generate a three-dimensional model and implement precise thinning based on the density heat map.

[0076] The shading film delivery bins are symmetrically arranged on both sides of the UAV fuselage, and an electric rolling door mechanism is provided inside the shading film delivery bins; the UAV is equipped with the shading film delivery bins for delivering the shading film to the forest area;

[0077] The intelligent transplanting robot is equipped with an AI vision system, which includes a panoramic binocular camera and a lateral laser triangulation sensor installed on the top of the intelligent transplanting robot. The system is used to identify and build a three-dimensional semantic map of the forest. The front-end platform of the intelligent transplanting robot is equipped with a six-axis collaborative robotic arm, and the end of the six-axis collaborative robotic arm is equipped with electric pruning shears and a vacuum suction gripper.

[0078] The intelligent transplanting robot is equipped with a sowing unit at the rear, which includes three independent seed storage bins for storing camphor, nanmu and superba seeds respectively. The intelligent transplanting robot is equipped with an air-suction seed metering device that cooperates with the independent seed storage bins. At the same time, a furrow opener is installed at the bottom of the intelligent transplanting robot.

[0079] The AI ​​vision system equipped with the intelligent transplanting robot is used to identify overcrowded branches and perform selective branch thinning operations and replant companion tree species;

[0080] A collaborative operation mode between drones and ground machinery enables precise control. A DJI M300RTK equipped with a Livox MID-70 LiDAR is used to perform 3D canopy modeling and generate canopy density heat maps. Based on AI-driven decision-making, precise thinning is implemented in areas with a canopy density greater than 0.7, while intelligent seeders are used to replant target companion tree species.

[0081] A mobile soil improvement device is also deployed, automatically applying a combination of biochar and calcium-magnesium-phosphate fertilizer when sensors detect a pH value below 5.5. The entire operation is monitored in real time by a digital twin system, ensuring that the error in adjusting the interplanting ratio is ≤2% and that the spatial distribution of tree species conforms to the Voroni segmentation model.

[0082] Phase 4: Dynamic monitoring and optimization of results are achieved through the establishment of a "quarterly evaluation and annual optimization" mechanism. Each quarter, a ground-based laser leaf area index meter (LAI-2200C) measures canopy light interception, combined with the rate of new bamboo seedlings to assess control effectiveness. Annual soil profile sampling and analysis verifies organic matter increments. The model automatically iterates parameters monthly. If the increase in available soil phosphorus is less than 5% for three consecutive growing seasons, a retraining mechanism is triggered for the tree species configuration, introducing deep-rooted species such as camphor to optimize nutrient cycling.

[0083] This method, through the deep integration of IoT sensing networks and machine learning algorithms, breaks through the limitations of traditional fixed-ratio mixed forest configurations, achieving a 40% increase in canopy light transmittance and a 2-3-fold increase in the annual growth rate of soil organic matter, while reducing manual maintenance costs by over 35%. Specifically, in the remediation of acidified soils with a pH of 4.0 to 5.5, by dynamically adjusting the mixed planting ratio of jujube to 28% ± 2% and combining it with biochar amendments, the soil pH can be restored to the ideal range of 5.8 to 6.3 within 18 months.

[0084] Furthermore, the operational process of dynamically regulating the mixed ratio of bamboo and broad-leaved mixed forests is to first adjust the mixed ratio. Before spring afforestation, the companion tree species, such as sour jujube and chinaberry, are selected according to the AI ​​recommended values, and the interval mixed planting method is adopted for planting. When performing specific operations, the intelligent transplanting robot serves as a ground execution unit. The panoramic binocular camera on its top and the lateral laser triangulation sensor work together to construct a three-dimensional semantic map of the forest, which is used to identify the diameter and spatial position of overcrowded branches in real time. The six-axis collaborative robotic arm at the front end drives the electric pruning shears at the end to cut off the target branches according to the positioning instructions of the AI ​​vision system, and simultaneously collects the residual branches through the vacuum adsorption gripper;

[0085] The robot's rear-mounted air-suction seed meter dynamically selects Cinnamomum camphora, Phoebe nanmu, or Schima superba seeds based on soil testing data. Negative-pressure airflow draws individual seeds, which are then deposited through a guide tube into a pre-dug seed hole created by the robot's bottom furrow opener. During transplanting, an AI vision system continuously monitors the planting spacing and canopy light transmittance of the associated tree species, dynamically adjusting thinning and replanting strategies to ensure that the interplanting ratio and spatial distribution conform to the pre-set model.

[0086] If the available phosphorus in the soil is less than 15 mg / kg, increase the proportion of sour jujube to 30% and use its root secretions to activate phosphorus.

[0087] When optimizing the forest canopy, an intelligent pruning robot is used to selectively thin out overcrowded canopies to ensure that the light transmittance under the forest is ≥40%. The canopy structure parameters are generated by generating a three-dimensional canopy model based on drone lidar scanning. The optimal light transmittance and crown gap distribution are calculated to generate a thinning plan. The optimal light transmittance range is 40% to 45%. The intelligent pruning robot is equipped with a high-precision robotic arm and an AI vision system. It identifies overcrowded branches based on the three-dimensional model and performs selective thinning. Generally, branches with a diameter of less than 8 cm are cut off to ensure that the light transmittance under the forest meets the standard.

[0088] In autumn, the lidar and hyperspectral camera carried by the drone generate a three-dimensional model by scanning the forest crown, and combine the hyperspectral data to identify areas with insufficient light or water, forming a density heat map; when it is detected that the forest crown density is too high, the drone automatically deploys a sunshade film in the overcrowded area to adjust the light under the forest. The drone flies to the target area based on the positioning information of the heat map, and performs operations through the sunshade film delivery bins on both sides of the fuselage. After the electric rolling door mechanism is opened, the pH-responsive sunshade film falls due to gravity, and the directional airflow of the bottom vortex generator controls the unfolding posture of the film, achieving precise coverage of the sunshade film and adjusting the light intensity under the forest; thus forming a dynamic light environment, suppressing strong light from burning young bamboo shoots, and dynamically controlling the light intensity under the forest within the range of 8000-12000 lux.

[0089] The light-shielding film is made of degradable nano-TiO2 with a particle size of 50nm and an adjustable light transmittance range of 70% to 90%.

[0090] In the above plan, the dynamic interplanting ratio dynamically adjusts the proportion of companion tree species based on soil phosphorus levels. For example, when available phosphorus is less than 15 mg / kg, the proportion of Chinese jujube is increased to 30%, as the jujube roots secrete citric acid to activate insoluble phosphorus. If organic matter is less than 18 g / kg, the proportion of chinaberry is increased to 25%, as its fallen leaves decompose quickly, facilitating organic matter accumulation.

[0091] Furthermore, the above-mentioned directional control method for bamboo ecological soil restoration was verified and calibrated; the forest microenvironment data was collected every month, and the AI ​​prediction value was compared with the actual growth indicators, such as the annual growth rate of bamboo diameter at breast height. When the error was greater than 10%, the model retraining was triggered.

[0092] Quarterly soil profile sampling verifies the effectiveness of organic matter enhancement and dynamically adjusts the microbial inoculant application strategy. Bamboo growth data, as well as soil organic matter and available phosphorus content, are monitored, and effectiveness data is collected to generate automated feedback.

[0093] This technology optimizes the understory microenvironment through a four-step closed-loop system of data perception, intelligent decision-making, precise regulation, and effect feedback, achieving dynamic and directional regulation of bamboo ecological soil restoration, realizing "data-driven mixed management", and significantly improving light energy utilization and the dynamic balance of soil nutrients.

[0094] The synergistic effect of the above scheme includes the following aspects:

[0095] 1. Through thinning branches and shading film adjustment, the light intensity under the forest is stabilized at 8000-12000 lux, avoiding the inhibition of photosynthesis of bamboo due to strong light. The normal light saturation point of bamboo is about 30000 lux. At the same time, it provides a suitable light environment for companion tree species, optimizes light and heat resources, and forms a dynamic light transmission control mechanism.

[0096] The mixed forest canopy is used to reduce surface evaporation, increasing air humidity by 15% to 20%, and reducing the temperature in the forest by 3 to 5°C in summer, significantly alleviating the high temperature stress of bamboo and achieving temperature and humidity balance.

[0097] 2. Utilize the synergistic effect of jujube and bamboo phosphorus to activate and recycle soil nutrients. Jujube roots secrete organic acids such as citric acid and oxalic acid, converting insoluble phosphorus in the soil into available phosphorus for bamboo absorption. At the same time, bamboo leaf litter is rich in silica, and after mixing with jujube leaf litter, the decomposition rate increases by 30%, and the annual increase in organic matter reaches 2.5g / kg. Furthermore, with the application of nano-modified bacterial agents, the available phosphorus content in the soil increased from a baseline of 12mg / kg to more than 20mg / kg, and the phosphorus absorption efficiency of bamboo roots increased by 40%. The nano-modified bacterial agent contains phosphate-solubilizing bacteria JXBR04.

[0098] 3. Through targeted adjustments to the soil beneath the bamboo forest, both ecological and economic benefits are achieved. Under dynamic regulation, the annual growth rate of bamboo's diameter at breast height has increased from 1.0 cm in traditional mixed forests to 1.5 cm, shortening the tree's maturity cycle by 2 to 3 years. The optimized microenvironment supports the cultivation of shade-tolerant cash crops, such as bamboo fungus, under the forest, increasing income by 2,000 to 3,000 yuan per mu. At the same time, litter is fed back into the soil, further promoting carbon sequestration and achieving both ecological and economic benefits.

[0099] The above-mentioned targeted regulation scheme for bamboo ecological soil restoration is illustrated by taking the application of dynamic regulation technology of bamboo and broadleaf mixed forest in Tianbaoyan Nature Reserve in Fujian as an actual case study;

[0100] Fujian Tianbaoyan Nature Reserve is located in the mid-subtropical monsoon climate zone, with an average annual precipitation of 1,800 mm and an average annual temperature of 18.5°C. The soil is mainly red soil, and it has the following ecological problems:

[0101] 1. Severe soil acidification: The pH value is generally lower than 5.0, resulting in a high phosphorus fixation rate, an available phosphorus content of only 6.8 mg / kg, and an organic matter content of 13.2 g / kg;

[0102] 2. Overdense forest canopy: Pure bamboo forests account for 80% of the total forest area, with understory light transmittance less than 30%, inhibiting the growth of associated tree species.

[0103] 3. Frequent occurrence of pests and diseases: The single bamboo forest structure increases the risk of the spread of diseases such as pine wood nematodes.

[0104] After field monitoring and investigation, monitoring data and historical data are obtained, and a dynamic mixed ratio adjustment plan is given through AI decision-making;

[0105] First, AI decisions are fed with historical and real-time data:

[0106] Historical data: The bamboo growth records in the reserve over the past 10 years show an average annual increase of 0.8 cm in diameter at breast height and an average annual decrease of 0.1 in pH due to soil acidification.

[0107] Real-time data: soil pH 4.9, available phosphorus 6.8 mg / kg, organic matter 13.2 g / kg, and understory light intensity 7500 lux.

[0108] Then the AI ​​outputs the decision: the mixed planting ratio is adjusted to 3 rows of bamboo + 1 row of Schima superba, and the mixed planting ratio of Schima superba accounts for 25%. The advantage of mixed Schima superba is that it is acid-resistant and its fallen leaves decompose quickly; and the canopy transmittance target is increased to 35% to 40%.

[0109] For the dynamic regulation case study of the Tianbaoyan Nature Reserve in Fujian Province, the AI ​​decision-making process combined the random forest algorithm mechanism with ecological principles to conduct multi-dimensional modeling and analysis. The random forest prediction mechanism is a decision-making method based on ensemble learning. It achieves high accuracy and strong generalization capabilities by constructing multiple decision trees and combining their prediction results. It works in three steps:

[0110] Introduction of randomness: Each decision tree is trained using a sample subset with replacement (bootstrap) and a randomly selected feature subset to ensure diversity among trees;

[0111] Independent prediction: Each tree independently generates predictions based on a feature splitting rule such as Gini impurity or mean squared error, outputting categories for classification tasks and numerical values ​​for regression tasks.

[0112] Result Ensemble: For classification problems, the final category is determined by majority voting, and for regression problems, continuous values ​​are output by taking the average, thereby reducing the error of a single tree and improving model stability.

[0113] Here's the decision-making process based on this case data:

[0114] First, a triple objective function including soil improvement, light optimization, and tree species adaptability was constructed in this case using the random forest algorithm:

[0115] Target 1: maxΔpH+available phosphorus+organic matter

[0116] Goal 2: Minimum canopy density → maximum light transmittance

[0117] Goal 3: Minimize disease risk and maximize mixed diversity

[0118] Then, feature engineering of the input data is performed and feature selection is performed in the randomness introduction stage. The algorithm randomly selects training samples from the following feature subsets, including

[0119] Soil characteristics: pH, available phosphorus content, organic matter content;

[0120] Stand characteristics: bamboo diameter at breast height growth rate, current light transmittance (7500 lux corresponds to 30%);

[0121] Time series: average annual pH decline rate (0.1) and bamboo growth rate (0.8 cm / year).

[0122] Furthermore, the Gini impurity is used to evaluate the feature importance:

[0123] ;

[0124] After calculation, it was found that pH value and transmittance are the key decision factors, with the pH value weight being 0.35 and the transmittance weight being 0.28; the available phosphorus content weight is 0.18, and the available phosphorus is related to the phosphorus release capacity of Schima superba.

[0125] The core of this formula is that feature importance is measured by the reduction in Gini impurity. Gini impurity is an indicator of the impurity of a dataset and is often used in classification problems.

[0126] Formula composition: ;

[0127] Where ΔGinit represents the reduction in Gini impurity at each split; Represents the total number of splits, that is, the number of all splits in the decision tree; the total number of splits is the total number of times all features are used for splitting, This represents the sum of the reductions in Gini impurity across all splits. This reflects the feature's overall contribution to improving dataset purity during the split. Dividing this sum by the total number of splits yields the feature's average contribution per split, or the feature's importance score. A higher feature importance score indicates a greater contribution to improving dataset purity during the decision tree split.

[0128] Based on the above decision, the derivation of the dynamic mixed ratio decision tree is further explained, taking a typical decision tree as an example;

[0129] 1. Root node splitting rules

[0130] If soil pH < 5.0 and light transmittance < 35%:

[0131] Enter the left branch (need to improve soil + increase light)

[0132] else:

[0133] Take the right branch (maintain status quo)

[0134] 2. Secondary node split

[0135] Left branch:

[0136] If bamboo ratio > 75% and available phosphorus < 10mg / kg:

[0137] Choose acid-tolerant and phosphorus-rich tree species (Schimasuperba)

[0138] else:

[0139] Choose other broadleaf species

[0140] 3. Leaf Node Output

[0141] Comprehensive voting results of multiple decision trees:

[0142] Schima superba accounts for 25% and receives 78% tree support; the target light transmittance of 35% to 40% corresponds to an increase in light intensity to 8750-10000 lux.

[0143] Using ecological effect verification calculations, the soil improvement prediction of Schima superba is based on the formula for the decomposition rate of fallen leaves:

[0144] ;

[0145] Annual organic matter increase:

[0146] ΔOrganic matter = 25%× =25%× ≈0.88g / kg

[0147] The canopy porosity model after mixed forests was obtained through transmittance optimization calculation:

[0148] New light transmittance = 30% × (1 + ) = 30% × 1.3 = 39%

[0149] It should be noted that the canopy opening of Schima superba is 40% higher than that of Phyllostachys pubescens.

[0150] In this study, we applied a random forest algorithm and an ensemble validation approach to conduct an in-depth analysis of the growth characteristics of Schima superba. Specifically, we first performed bootstrap resampling on 10 years of historical data, extracting eight sample sets containing key sequences such as pH drop and bamboo growth. Next, we employed the principle of feature randomness in feature selection, randomly selecting three features for each decision tree: pH, light transmittance, and available phosphorus. Using this regression prediction, we successfully numerically fitted the intermixing ratio and determined the intermixing scheme corresponding to a 25% percentage of Schima superba with the median of the 95% confidence interval (23%, 27%).

[0151] The research results show that through the multi-objective optimization mechanism of AI, we can quantify the biological characteristics of Schima superba, such as acid resistance, leaf decomposition characteristics, and light transmission requirements, and convert them into an operational 3:1 mixed planting plan.

[0152] The implementation of this program not only helped slow the rate of soil acidification but also significantly improved the disease resistance of forest stands, increasing their disease resistance index by 2.3 times. These findings provide important scientific evidence for forest management and ecosystem restoration.

[0153] On the basis of implementing the AI ​​optimization solution, we further adopted automated machinery and intelligent equipment to ensure precise actual operation. In order to improve the lighting conditions of the bamboo forest, we deployed intelligent pruning robots. These robots can accurately cut off the overly dense branches of the bamboo, and the thinning intensity is set to 15%, thereby effectively increasing the light transmittance to 38%. In addition, we also use intelligent drones for refined operations. A pH-responsive nano-shading film containing CaCO3 particles is spread by drones. The film can neutralize acidic precipitation and reduce surface acidity. At the same time, its light transmittance is as high as 75%, which helps to optimize the lighting environment.

[0154] To fully enhance the ecological and economic benefits of the bamboo forest, we have taken further steps to remediate the soil. By applying nano-modified microbial agents, we have enhanced soil fertility and improved the bamboo's adaptability to acidic environments.

[0155] The microbial agent specifically contains acid-resistant phosphate-solubilizing bacteria (PenicilliumoxalicumPO109), with an application rate of 150 kilograms per hectare. Through precise targeted release technology, the microbial agent is applied to the rhizosphere of bamboo, with a depth maintained at 15 cm, ensuring that the microbial agent can directly act on the bamboo root system, promote its absorption of phosphorus, and thus improve the growth efficiency of bamboo.

[0156] Building on this foundation, we further expanded the development of the forest's understory economy. We planted the acid- and shade-tolerant cash crop, Japanese knotweed, at a density of 2,000 plants per mu. To ensure the healthy growth of Japanese knotweed, we implemented an intelligent drip irrigation system that precisely regulates soil moisture, maintaining it within a desirable range of 60% to 70%. This integrated strategy of ecological soil restoration and understory cash crop planting not only improved the forest's ecological environment but also boosted economic returns through Japanese knotweed cultivation, providing a new avenue for the comprehensive utilization of bamboo forests.

[0157] The following is a comparison table of dynamic regulation data of bamboo and broadleaf mixed forests in Tianbaoyan Nature Reserve, Fujian.

[0158]

[0159] In terms of the mechanism of action of the technology, our research has achieved the following breakthroughs:

[0160] First, to improve acidic soil, we employed the synergistic effect of Schima superba and a microbial inoculant. Schima superba's fallen leaves are rich in alkaline substances, raising the pH to 6.2. Acid-tolerant phosphate-solubilizing bacteria secrete oxalic acid, converting the inaccessible aluminum-phosphorus complex (Al-P) in the red soil into available phosphorus that can be absorbed by plants. This results in an annual increase in available soil phosphorus of 5.3 mg / kg. Furthermore, our nano-CaCO₃ microparticle light-blocking film slowly releases during the rainy season, neutralizing acidic rainwater and raising the pH from 4.5 to 5.2, effectively reducing toxicity to bamboo roots.

[0161] Secondly, by optimizing light and heat resources, we have improved the photosynthetic rate of bamboo. The increase in light transmittance to 39% has increased the photosynthetic rate of bamboo by 20%, and the measured net photosynthetic rate has increased from 8.2μmol / m 2 / s increased to 9.8 μmol / m 2 In addition, the canopy shading of Schima superba can lower ground surface temperature and reduce bamboo transpiration by 15%, thereby alleviating summer drought stress.

[0162] Furthermore, in terms of ecological and economic synergy, we planted acid- and shade-tolerant Japanese knotweed. The antibacterial substance emodin secreted by its roots can reduce the incidence of pine wood nematodes by 40%. At the same time, its biomass returns to the soil, promoting the accumulation of organic matter. The returns from Japanese knotweed cultivation even cover the technical investment costs. In actual planting, the equipment and microbial agent cost approximately 800 yuan per mu, while the average return per mu was 2,700 yuan, thus achieving a virtuous cycle of restoration and profitability.

[0163] In terms of innovative verification and promotion value, our technology has the following characteristics:

[0164] 1. To address the challenges of red soil acidification and phosphorus fixation, we adopted a combination of "acid-resistant tree species and functional bacterial agents", breaking through the limitations of traditional lime improvement methods that easily cause soil compaction.

[0165] 2. The error rate of predictions using the AI ​​model is less than 8%, which is 35% more accurate than manual experience.

[0166] 3. The carbon sequestration per hectare increased from 4.2 tons to 5.1 tons, which meets the requirements of Fujian Province's ecological compensation policy and shows the potential for large-scale promotion.

[0167] In summary, this case study demonstrates the applicability of dynamic regulation technology for mixed bamboo and broadleaf forests in subtropical acidic red soils. By integrating intelligent devices with biotechnology, we achieved the triple goals of soil remediation, bamboo quality improvement, and forest floor economic growth, providing a replicable and illustrative model for similar ecologically fragile regions.

[0168] Example 2:

[0169] See also Figure 1 In combination with Example 1, this solution processes bamboo waste into high-value materials and prepares them into a bacterial agent carrier with adsorption and slow-release properties to achieve soil remediation and stabilize the bamboo forest ecosystem. The specific implementation steps are as follows:

[0170] 1. First, the bamboo waste including bamboo chips, bamboo branches and bamboo roots are crushed to control the particle size below 2mm, and impurities such as stones and metal fragments are removed through a vibrating screen.

[0171] 2. Then, the mixture is pyrolyzed at 600°C for 2 hours using an oxygen-limited pyrolysis process to obtain porous bamboo charcoal with a pore size of 50 to 100 nm and a specific surface area greater than 800 m² / g, demonstrating excellent adsorption properties.

[0172] 3. This solution successfully loaded magnetic particles by mixing bamboo charcoal powder and Fe3O4 nanoparticles in a mass ratio of 1:0.1 and treating them at 180°C for 12 hours using a hydrothermal method, thereby effectively improving the adsorption performance and sustained-release ability of the carrier.

[0173] 4. Soak bamboo chips in 5% NaOH solution for 24 hours to neutralize lignin and increase surface roughness, thereby increasing the area for bacterial attachment.

[0174] 5. Select phosphate-solubilizing bacteria, nitrogen-fixing bacteria, and drought-tolerant fungi, and mix them in a certain proportion to form a composite bacterial community. Mix the composite bacterial community with modified bamboo charcoal and signal molecules, and use low-temperature spray drying to produce a granular inoculant with a particle size of 2-3 mm.

[0175] 6. Furthermore, an integrated chip with an impedance biosensor and a fluorescent probe was used to monitor the survival rate of the rhizosphere inoculant in real time. When the survival rate fell below 70%, a liquid inoculant suspension was released through a solar drip irrigation system for automatic replenishment.

[0176] Integrated application of the above-mentioned microbial agent carriers in the dynamic regulation of mixed bamboo and broadleaf forests:

[0177] This program applies microbial agents as carriers to the dynamic regulation of mixed bamboo and broadleaf forests to achieve the dual goals of soil remediation, carbon sequestration enhancement, and economic benefits. The specific implementation steps are as follows:

[0178] 1. During the planting period, use a pneumatic deep-applying machine to implant the granular microbial agent into the rhizosphere simultaneously with the bamboo seedlings at a dosage of 150 kg / ha.

[0179] During the growing season, drones are used to hang slow-release microbial agent bags, which are based on bamboo charcoal and have a microbial agent load of 30%. They are delivered to densely populated bamboo areas at designated locations every month, with a single dosage of 50kg / ha.

[0180] Furthermore, the application of bacterial agent carriers is coordinated with dynamic regulation technology;

[0181] First, soil sensors monitor available phosphorus, pH and other data in real time. When the available phosphorus is lower than 15 mg / kg, the AI ​​system prioritizes calling the release instruction of the phosphate-dissolving bacteria agent; the solar drip irrigation system is integrated with the bacteria agent release module, and the bacteria agent pipeline is controlled by the solenoid valve to achieve precise delivery on demand.

[0182] Furthermore, by integrating the carbon sequestration-enhancing mixed planting model, high carbon sequestration tree species are selected for mixed planting, such as the introduction of nanmu and camphor trees, whose unit biomass carbon sequestration capacity is 1.8t / ha·yr and 1.5t / ha·yr respectively.

[0183] The carbon storage of forest stands is calculated through lidar scanning every quarter, and the data is input into the AI ​​model to optimize the mixed planting strategy to increase the target carbon sink amount. The carbon sink is continuously monitored to form data feedback.

[0184] Through the above implementation methods, this solution achieves efficient utilization of bamboo waste and promotes the stability and sustainable development of bamboo forest ecosystems. At the same time, the solution fully considers innovation and practicality in the technical implementation process, providing new ideas and methods for bamboo forest management.

[0185] Example 3:

[0186] See also Figure 2In combination with Example 1, the directional control method for bamboo ecological soil remediation also includes the use of an AI-driven intelligent drip irrigation system, which includes a microbial agent storage tank, an irrigation water tank, and an electromagnetic proportional valve. The microbial agent storage tank and the irrigation water tank are connected to the electromagnetic proportional valve, which is used to dynamically control the mixing ratio of the microbial agent and the irrigation water. The liquid outlet of the electromagnetic proportional valve is fixedly connected to a delivery pump, which is connected to a drip irrigation pipe.

[0187] The outside of the drip irrigation pipe is covered with a flexible solar film, which is electrically connected to an energy storage battery pack.

[0188] The system uses electromagnetic proportional valves to dynamically control the mixing ratio of the microbial agent and irrigation water. This AI-driven intelligent drip irrigation system integrates soil multi-parameter sensors and meteorological data to build a dynamic response model, breaking through the traditional drip irrigation system's single decision-making model that relies solely on soil moisture. The soil multi-parameter sensors are used to detect N / P / K (nitrogen, phosphorus and potassium), humidity, and EC values, and meteorological data include light, temperature and humidity.

[0189] Furthermore, the random forest algorithm is combined with Bayesian optimization to analyze the soil and meteorological composite data streams in real time, predict the water demand and microbial agent demand of bamboo, and dynamically generate drip irrigation plans.

[0190] The AI-driven intelligent drip irrigation system combines flexible solar film with lithium iron phosphate battery packs to achieve seamless integration of photovoltaic power generation, energy storage and drip irrigation. The flexible solar film has a photoelectric conversion rate of ≥23%, thus solving the power supply problem in remote bamboo forest areas.

[0191] The system's energy storage capacity is ≥5kWh, which can support nighttime drip irrigation and switch to low-power mode on rainy days through the power adaptive regulation module.

[0192] During the precise release of the microbial agent, the microbial agent suspension is mixed with irrigation water in proportion, and the microbial agent concentration is dynamically regulated by the electromagnetic proportional valve to achieve precise regulation of the ratio of the microbial agent suspension to irrigation water.

[0193] By real-time linkage between the amount of bacterial agent released and the available phosphorus content in the soil, when the available phosphorus is less than 15 mg / kg, the bacterial agent concentration is automatically increased to 0.2%.

[0194] The solar power supply unit uses flexible solar panels to cover the surface of the drip irrigation pipe to maximize light utilization; the energy storage battery pack works together with the MPPT controller to ensure 24-hour uninterrupted operation of the system.

[0195] The data acquisition unit's soil multi-parameter sensors (N / P / K, humidity, EC value) are arranged in a star topology, with 15 nodes deployed per hectare; the micro-meteorological station is directly connected to the edge computing gateway and is used to monitor light intensity, temperature, humidity, and wind speed.

[0196] The micro-drip irrigation device is equipped with an electromagnetic proportional valve and a bacterial agent mixing chamber; a drone equipped with a hyperspectral camera is used to dynamically monitor the shade degree under the forest and place shading film.

[0197] In the collaborative workflow of this system, soil sensors collect data every 5 minutes, and the weather station updates environmental parameters every 10 minutes; the data is then cleaned and standardized through the edge computing gateway.

[0198] After receiving the data, the cloud-based random forest model predicts the transpiration of bamboo in the next six hours; combines the available phosphorus content in the soil to calculate the concentration of the released fungus; and outputs instructions for adjusting the drip irrigation frequency and shading degree.

[0199] The formula for calculating the release concentration of the bacterial agent is: ;

[0200] The electromagnetic proportional valve then adjusts the bacterial agent mixing ratio according to the instructions, and the drip irrigation system operates at the set frequency; the drone scans the canopy shade in real time, and if it detects light intensity greater than 12,000 lux, it automatically spreads a light-shielding film with a transmittance of 70%; the system self-checks the bacterial agent reserves and battery status every 24 hours, and sends operation and maintenance warnings to the management center via the LoRa network.

[0201] This AI-driven smart drip irrigation system uses solar energy to generate electricity during the day and charge energy storage batteries, ensuring the normal operation of drip irrigation pumps and sensor networks at night, thus achieving complete dependence on external power supply.

[0202] The system also builds a closed-loop system encompassing data, decision-making, and execution. It works as follows: soil and meteorological data are first pre-processed by an edge computing unit, then analyzed by a cloud-based AI model to generate appropriate drip irrigation parameters. These parameters are then sent to the execution unit for precise control. Finally, the system collects feedback data to iteratively optimize the cloud-based model.

[0203] Secondly, the system features dynamic adaptive regulation. In drought warning mode, when soil moisture falls below 50% and the temperature rises above 30°C, the system triggers high-frequency drip irrigation, providing 15 minutes of drip irrigation every hour, to ensure that plants' water needs are met. In rainstorm response mode, if rainfall exceeds 20 mm / h, the system automatically shuts off drip irrigation and initiates drainage monitoring to prevent soil overwetting.

[0204] Ultimately, this solution effectively overcomes the technical limitations of traditional drip irrigation systems by integrating three innovative technologies: AI decision-making, solar-powered irrigation, and precise microbial release. This not only achieves efficient resource utilization but also promotes ecological restoration, providing an intelligent solution for the sustainable management of bamboo forests.

[0205] Furthermore, understory plantings are being developed to integrate ecological and economic benefits. Shade-tolerant medicinal plants, such as Panax notoginseng and Polygonatum sibiricum, and edible fungi, such as Dictyophora, are planted beneath mixed bamboo and broadleaf trees, creating a three-tiered planting system of "bamboo, broadleaf trees, and cash crops." This is complemented by targeted microbial inoculants and intelligent drip irrigation. This not only increases economic income but also enhances soil carbon sequestration through root interactions.

[0206] The above disclosures are only a few specific embodiments of the present invention. However, the embodiments of the present invention are not limited thereto. Any changes that can be conceived by those skilled in the art should fall within the scope of protection of the present invention.

Claims

1. A directional control method for bamboo ecological soil restoration, characterized in that: The following steps are involved: Step (1) deploying multi-parameter soil sensors and micro-meteorological stations in the bamboo forest area to be restored, collecting soil parameters and meteorological data in real time, and transmitting the data to the edge computing gateway for pre-processing through the communication module; Step (2) constructing a dynamic control model based on a machine learning algorithm, and inputting historical bamboo growth data, real-time soil and meteorological data, and meteorological forecast information, thereby outputting dynamic mixed planting ratio recommendations, an optimal sequence of associated tree species, and a target value for canopy transmittance. The dynamic control model dynamically adjusts the ratio of associated tree species according to the available phosphorus content and organic matter level in the soil, and generates a thinning plan based on the target value for canopy transmittance. The dynamic control model is constructed as follows: (a) Determine the correlation threshold rules between soil organic matter content and available phosphorus concentration, and the mapping relationship between forest light intensity and canopy transmittance through feature analysis; (b) generating a multi-dimensional decision-making scheme based on the association threshold rules and mapping relationships, including dynamic mixed planting ratio adjustment recommendations, companion tree species adaptability scores, and canopy transmittance target values; (c) Dynamically adjust the configuration priority of companion tree species based on the real-time monitoring results of soil pH, where the lower the soil pH value, the higher the priority level of the companion tree species; Step (3) Based on the decision plan, a three-dimensional canopy model is generated by using drone scanning, and precise thinning is carried out in areas where the canopy density is higher than a preset threshold. Acid-resistant companion tree species are replanted through the forestry intelligent operation terminal, and compound soil conditioners are automatically applied based on the real-time soil pH value. The soil conditioner includes a nano-modified bacterial agent containing phosphate-solubilizing bacteria and a pH-responsive light-shielding film, wherein the light-shielding film is used to neutralize acidic precipitation and adjust the light intensity under the forest; Nano-modified bacterial agents are processed into high-value bacterial agents with adsorption and slow-release properties for soil remediation and bamboo forest ecosystem stabilization. , and the particle size is controlled below 2mm, bamboo waste includes bamboo chips, bamboo branches, bamboo roots, and porous bamboo charcoal is obtained through oxygen-limited pyrolysis process; then the bamboo charcoal powder is mixed with Nanoparticles are mixed and treated by hydrothermal method to load magnetic particles to improve the adsorption performance and sustained release ability of the carrier; An integrated chip of an impedance biosensor and a fluorescent probe was used to monitor the survival rate of bamboo rhizosphere inoculants in real time. When the survival rate fell below 70%, a liquid inoculant suspension was released through a solar drip irrigation system for automatic replenishment. The drone is equipped with a shading film delivery chamber for delivering shading film to the forest area; the shading film delivery chamber is symmetrically arranged on both sides of the drone fuselage, and an electric rolling door mechanism is provided inside the shading film delivery chamber; Step (4) dynamically adjusts the interplanting ratio and soil improvement strategy through periodic light interception rate measurement, soil profile sampling and model iterative optimization.

2. The bamboo ecological soil restoration directional control method according to claim 1, characterized in that: In step (1), the pH value, organic matter content, available phosphorus concentration, forest light intensity, temperature and humidity parameters of the topsoil and subsoil layers are collected in real time through evenly distributed multi-parameter soil sensors and micro-meteorological stations.

3. The directional control method for bamboo ecological soil restoration according to claim 1, wherein: In step (2), a dynamic control model is constructed based on the random forest algorithm, and historical bamboo growth data, a typical restoration case library, real-time monitoring data and meteorological forecast information are input. According to the comparison results of the real-time detection values ​​of soil organic matter content, available phosphorus concentration and understory light intensity with the preset thresholds, a nitrogen-fixing tree species configuration plan or canopy structure adjustment instructions are dynamically generated.

4. The bamboo ecological soil restoration directional control method according to claim 1, characterized in that: In step (4), a quarterly light interception rate monitoring and annual soil profile analysis mechanism is established. When the growth rate of available phosphorus in the soil is less than 5% for three consecutive seasons, the configuration plan for deep-rooted camphor trees is retrained.

5. The directional control method for bamboo ecological soil restoration according to claim 1, characterized in that: In step (1), the multi-parameter soil sensors are deployed at a preset density in each hectare of bamboo forest to monitor surface and deep soil parameters in layers. The data are transmitted to the edge computing gateway through the communication module for preprocessing and periodically uploaded to the cloud database.

6. The directional control method for bamboo ecological soil restoration according to claim 1, characterized in that: Phosphate-solubilizing bacteria, nitrogen-fixing bacteria and drought-resistant fungi are compounded into a composite bacterial community, mixed with modified bamboo charcoal and signal molecules, and made into a granular bacterial agent through low-temperature spray drying.

7. A bamboo ecological soil remediation directional control device for implementing the bamboo ecological soil remediation directional control method according to any one of claims 1 to 6, characterized in that: Multi-parameter soil sensors and micro-meteorological stations are deployed in the bamboo forest area to be restored. The soil sensors and micro-meteorological stations are electrically connected to the communication module, the communication module is electrically connected to the edge computing gateway, and the edge computing gateway is data-connected to the cloud server cluster. The cloud server cluster is used to run cloud databases and AI models; the cloud server cluster is data-connected to the forestry intelligent operation terminal for directional control of soil restoration.

8. The bamboo ecological soil remediation directional control device according to claim 7, characterized in that: The forestry intelligent operation terminal includes a drone, an intelligent transplanting robot and an intelligent drip irrigation system; The drone is equipped with a laser radar, a hyperspectral camera, and a shading film delivery compartment. The laser radar is mounted at the center of the drone's bottom, and the hyperspectral camera is front-mounted below the drone's nose. The drone is equipped with a three-axis stabilization platform. The laser radar and hyperspectral camera are used to scan the forest canopy to generate a three-dimensional model and implement precise thinning based on density heat maps. The intelligent transplanting robot is equipped with an AI vision system, which includes a panoramic binocular camera and a lateral laser triangulation sensor installed on the top of the intelligent transplanting robot, which are used to identify and build a three-dimensional semantic map of the forest. The front-end platform of the intelligent transplanting robot is equipped with a six-axis collaborative robotic arm, and the end of the six-axis collaborative robotic arm is equipped with electric pruning shears and a vacuum suction gripper. The intelligent transplanting robot is equipped with a sowing unit at the rear, which includes three independent seed storage bins for storing camphor, nanmu, and superba seeds respectively. The intelligent transplanting robot is equipped with an air-suction seed metering device that cooperates with the independent seed storage bins, and a furrow opener is installed at the bottom of the intelligent transplanting robot. The AI ​​vision system equipped with the intelligent transplanting robot is used to identify overcrowded branches and perform selective branch thinning operations and replant companion tree species; The intelligent drip irrigation system includes a microbial agent storage tank, an irrigation water tank, and an electromagnetic proportional valve. The microbial agent storage tank and the irrigation water tank are connected to the electromagnetic proportional valve, which is used to dynamically adjust the mixing ratio of the microbial agent and irrigation water. The liquid outlet of the electromagnetic proportional valve is fixedly connected to a delivery pump, which is connected to the drip irrigation pipe. The outside of the drip irrigation pipe is covered with a flexible solar film, which is electrically connected to an energy storage battery pack.

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