Directional regulation and control method and equipment for moso bamboo ecological soil remediation

Abstract

The invention relates to the technical field of ecological soil remediation, and discloses a moso bamboo ecological soil remediation directional regulation and control method and equipment which are used for solving the problems of insufficient light transmittance, low acidified soil remediation efficiency and the like caused by a fixed proportion of a traditional bamboo and broad-leaved mixed forest. A random forest algorithm is combined to dynamically optimize a mixing proportion and associated tree species configuration, an unmanned aerial vehicle is used for scanning to generate a three-dimensional crown model, intelligent equipment is guided to accurately intermediate cutting and complementary planting, and in cooperation with a pH response type shading film and an acid-resistant phosphate solubilizing bacterium agent, crown light transmittance improvement and acidified soil improvement are achieved. The equipment comprises an unmanned aerial vehicle carrying a laser radar, an intelligent transplanting robot and a solar drip irrigation system, and the concentration of a fungicide and an irrigation strategy can be dynamically regulated and controlled. The porous bamboo charcoal carrier is prepared by innovatively utilizing the moso bamboo waste, and the functional flora is loaded to replace the traditional peat raw material; according to the scheme, the problems of static configuration, manual dependence and resource waste are solved.

Description

Technical Field

[0001] The 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 mainly use a fixed ratio of bamboo and broadleaf mixed forest configuration, lacking a dynamic adjustment mechanism, resulting in uneven distribution of light and heat resources, insufficient canopy transmittance, and difficulty in adapting to the spatiotemporal changes in soil parameters. Since bamboo and broadleaf mixed forests use a fixed ratio, for example, when the proportion of bamboo is greater than 80%, the canopy density is too high, inhibiting the growth of associated tree species, and it is impossible to dynamically optimize the mixed ratio and tree species configuration according to 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 phosphorus content is low due to aluminum ion fixation, 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 the waste from bamboo processing has not been utilized at a high value, resulting in waste of resources.

[0006] Therefore, we propose a directional regulation 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 ecological soil restoration of bamboo, which can solve the problem that the ecological soil restoration method in the prior art relies on artificial experience decision-making, mainly adopts a fixed ratio of bamboo and broad-leaved mixed forest configuration, lacks a dynamic adjustment mechanism, leads to 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: A directional control method for bamboo ecological soil restoration, comprising the following steps: 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 a communication module; 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; Step (3) Based on the decision-making plan, a three-dimensional canopy model is generated by using drone scanning, and the canopy density is adjusted, associated tree species are planted, and soil conditioners are applied through the forestry intelligent operation terminal; Step (4) dynamically adjusts the interplanting ratio and soil improvement strategy through periodic light interception rate measurement, soil profile sampling and model iterative optimization.

[0009] 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.

[0010] 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, effective phosphorus concentration and understory light intensity with preset thresholds, a nitrogen-fixing tree species configuration plan or canopy structure adjustment instructions are dynamically generated.

[0011] 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 composite soil conditioners are automatically applied according to the real-time detected soil pH value.

[0012] 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 <5% for three consecutive seasons, the configuration plan for deep-rooted camphor tree species is retrained.

[0013] 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.

[0014] Preferably, the dynamic control model in step (2) dynamically adjusts the proportion of associated tree species according to the soil available phosphorus content and organic matter level, and generates a thinning plan based on the target value of canopy transmittance.

[0015] Preferably, the construction of the dynamic control model includes the following steps: (a) Determine the correlation threshold rules between soil organic matter content and available phosphorus concentration, as well as the mapping relationship between forest light intensity and canopy transmittance through feature analysis; (b) generating a multi-dimensional decision-making scheme for dynamic mixed planting ratio adjustment suggestions, companion tree species adaptability scores, and canopy transmittance target values ​​based on the association threshold rules and mapping relationships; (c) According to the real-time monitoring results of soil pH value, 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.

[0016] 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.

[0017] Preferably, the soil conditioner applied in step (3) comprises a nano-modified bacterial agent containing phosphate-solubilizing bacteria and a pH-responsive shading film, wherein the shading film is used to neutralize acidic precipitation and adjust the light intensity under the forest.

[0018] A bamboo ecological soil restoration directional control device for a bamboo ecological soil restoration directional control method, comprising: multi-parameter soil sensors and micro-meteorological stations are deployed in a 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 restoration directional control.

[0019] 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 shading film delivery bin, the laser radar is installed at the center of the bottom of the drone, the hyperspectral camera is front-mounted under the nose of the drone, and is equipped with a three-axis stabilization platform; the drone is equipped with a laser radar and a hyperspectral camera for scanning the forest canopy to generate a three-dimensional model, and implements precise thinning according to the density heat map; 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 shading film delivery bins for delivering shading film to the forest area; The intelligent transplanting robot is equipped with an AI vision system, which includes a panoramic binocular camera and a lateral laser triangulation ranging 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 adsorption gripper; The intelligent transplanting robot is equipped with a sowing unit at the rear, and the sowing unit includes three independent seed storage bins, which are used to store seeds of camphor, nanmu and superba respectively. The intelligent transplanting robot is equipped with an air suction seed metering device matched with the independent seed storage bins, and a furrow opener is installed at the bottom of the intelligent transplanting robot.

[0020] The AI ​​vision system equipped with the intelligent transplanting robot is used to identify overcrowded branches and perform selective thinning operations and replanting of companion tree species; The intelligent drip irrigation system includes a bacterial agent storage tank, an irrigation water tank and an electromagnetic proportional valve. The bacterial agent storage tank and the irrigation water tank are connected to an electromagnetic proportional valve, which is used to dynamically adjust the mixing ratio of the bacterial 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 pipeline. The outside of the drip irrigation pipe is covered with a flexible solar film, and the flexible solar film is electrically connected to an energy storage battery pack.

[0021] Compared with the prior art, the beneficial effects achieved by the present invention are: The present invention realizes the dynamic and precise ecological restoration process and efficient resource utilization through the deep integration of Internet of Things technology, machine learning algorithms and intelligent devices, and provides an innovative solution for subtropical acidified bamboo forests. The specific implementation methods are as follows: Traditional bamboo and broadleaf mixed forests rely on fixed ratio configuration, resulting in insufficient canopy light transmittance and unbalanced light and heat resource allocation. The present invention uses real-time collected soil parameters and meteorological data, and uses a random forest algorithm to dynamically adjust the mixed ratio, and selects companion tree species such as sour jujube and Schima superba; The three-dimensional canopy model was generated by drone scanning, and thinning and replanting were carried out accurately, which significantly improved the canopy light transmittance and stabilized the light intensity under the forest within an appropriate range. This technology not only improved the photosynthesis efficiency of bamboo, but also promoted the growth of associated tree species. The annual growth rate of bamboo breast diameter increased significantly, and the maturity period was greatly shortened.

[0022] Compared with traditional restoration methods that rely on manual experience, have low efficiency and large errors; the present invention uses intelligent transplanting robots and drones to work together to achieve precise operations of thinning and replanting, and the error control reaches the industry-leading level. At the same time, the AI-driven solar drip irrigation system dynamically adjusts the concentration of the microbial agent according to soil nutrient data to ensure efficient use of resources. The application of intelligent equipment has significantly reduced the cost of manual management and maintenance, and the accuracy and utilization rate of microbial agent delivery have been simultaneously improved, solving the problems of resource waste and high costs in traditional methods.

[0023] In order to solve the problem of phosphorus fixation and slow accumulation of organic matter in acidic soil, the present invention innovatively introduces acid-resistant tree species and functional bacterial agents for synergistic restoration; the fallen leaves of acid-resistant tree species such as Schima superba release alkaline substances after decomposition, and the combination of nano-shading film neutralizes acidic precipitation, effectively increasing the soil pH value. The combination of acid-resistant phosphate-dissolving bacteria and modified bamboo charcoal carriers breaks the aluminum-phosphorus complex structure in the soil and significantly increases the effective phosphorus content. The annual increase in organic matter is several times that of traditional methods, and the soil fertility recovery period is shortened to less than 18 months, providing sustainable nutrient support for the growth of bamboo.

[0024] Traditional bacterial agent carriers rely on non-renewable resources such as peat, which are costly and not environmentally friendly. The present invention converts bamboo processing waste into porous bamboo charcoal through a special pyrolysis process, and loads functional bacteria to make an efficient slow-release bacterial agent. This technology not only reduces the cost of raw materials, but also realizes the recycling of waste resources. At the same time, shade-tolerant economic crops such as knotweed are planted under the forest, forming a three-dimensional model of restoration, planting and income, with a significant increase in income per mu, taking into account both ecological and economic benefits.

[0025] By building a multi-layer planting system of bamboo, broad-leaved trees and cash crops, and coordinating with intelligent drip irrigation and carbon sink optimization models, the carbon sequestration per unit area has been significantly increased; after the microenvironment in the forest has improved, the air humidity has increased and the summer temperature has decreased, effectively alleviating the high temperature stress of bamboo. The introduction of cash crops not only suppresses pests and diseases, but also enhances the soil's carbon sequestration capacity through root interactions, forming a virtuous cycle of ecological restoration and industrial development. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the overall dynamic control process of the present invention; Figure 2 It is a schematic diagram of the data collection and preprocessing process of the present invention; Figure 3 It is a schematic diagram of the model decision-making scheme of the present invention; Figure 4 This is a schematic diagram of the precise control execution process of the present invention; Figure 5 It is a schematic diagram of the effect monitoring and optimization process of the present invention; Figure 6 This is a schematic diagram of the connection structure of the bamboo ecological soil restoration directional control equipment of the present invention. DETAILED DESCRIPTION

[0027] 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.

[0028] Embodiment 1:

[0029] See also Figures 1 to 6 , the present invention provides a technical solution: A directional control method for bamboo ecological soil restoration, comprising the following steps: 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 a communication module; 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; Step (3) Based on the decision-making plan, a three-dimensional canopy model is generated by using drone scanning, and the canopy density is adjusted, associated tree species are planted, and soil conditioners are applied through the forestry intelligent operation terminal; Step (4) dynamically adjusts the interplanting ratio and soil improvement strategy through periodic light interception rate measurement, soil profile sampling and model iterative optimization.

[0030] 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.

[0031] In the above plan, appropriate bamboo-broadleaf mixed ratio and accompanying tree species are selected; the mixed ratio and tree species are adjusted through dynamic control technology of bamboo-broadleaf mixed forests to optimize the canopy structure, improve the lighting conditions under the forest, and promote the growth of bamboo.

[0032] The dynamic control technology of mixed bamboo and broad-leaved forests is based on real-time data from soil sensors, such as pH, organic matter, available phosphorus content, and meteorological information such as light, temperature and humidity. It dynamically adjusts the proportion of mixed bamboo and broad-leaved forests and accompanying tree species. The accompanying tree species can be hawthorn, chinaberry or elm, etc., and then generates the optimal canopy structure model through AI algorithm to improve the microenvironment under the forest and promote the synergistic effect of bamboo growth and soil restoration.

[0033] 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.

[0034] Furthermore, the specific implementation method of the dynamic regulation technology of bamboo and broadleaf mixed forest is as follows; In the first phase, 8 to 12 groups of multi-parameter soil sensor nodes were evenly distributed per hectare in the bamboo forest area to be restored, and a network of micro-meteorological stations was installed simultaneously. The sensor groups were evenly arranged in a honeycomb pattern, with double-layer deployment in the topsoil and subsoil layers in the vertical direction, with a topsoil depth of 0 to 30 cm and a subsoil depth of 30 to 60 cm.

[0035] Through the above methods, key indicators such as soil pH, organic matter content, effective phosphorus concentration, and conductivity are continuously collected, and microclimate parameters such as forest light intensity (lux), air temperature and humidity, and rainfall are monitored. All nodes form an ad hoc network through the LoRaWAN protocol, and use the edge computing gateway equipped with NVIDIA Jetson Nano to pre-process the data. After removing abnormal values, the data is uploaded to the cloud database at a frequency of 5 minutes / time.

[0036] In the second stage, a dynamic control model was built 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, effective phosphorus concentration and understory light intensity with the preset thresholds, nitrogen-fixing tree species configuration plans or canopy structure adjustment instructions were dynamically generated.

[0037] 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 composite soil conditioners are automatically applied based on real-time soil pH values.

[0038] Establish a quarterly light interception rate monitoring and annual soil profile analysis mechanism. When the soil available phosphorus growth rate is <5% for three consecutive seasons, trigger the re-training of the configuration plan for deep-rooted camphor tree species.

[0039] 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.

[0040] The dynamic control model dynamically adjusts the proportion of associated tree species according to the soil available phosphorus content and organic matter level, and generates a thinning plan based on the target value of canopy transmittance.

[0041] The construction of the dynamic control model includes the following steps: (a) Determine the correlation threshold rules between soil organic matter content and available phosphorus concentration, as well as the mapping relationship between forest light intensity and canopy transmittance through feature analysis; (b) generating a multi-dimensional decision-making scheme for dynamic mixed planting ratio adjustment suggestions, companion tree species adaptability scores, and canopy transmittance target values ​​based on the association threshold rules and mapping relationships; (c) According to the real-time monitoring results of soil pH value, 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.

[0042] In the above scheme, a dynamic control model based on the random forest algorithm is deployed in the cloud, and its training data set includes: ① 10-year historical bamboo growth indicators, including the annual growth of DBH; ② 2018-2023 typical bamboo and broadleaved mixed forest restoration case library; ③ real-time access to soil and meteorological time series data streams; ④ 72-hour high-precision meteorological forecast data. The model extracts key decision factors through feature engineering. For example, when the organic matter content is detected to be <15g / kg and the available phosphorus is <8mg / kg, nitrogen-fixing tree species are recommended first; When the light intensity under the forest is continuously lower than 8000 lux, the canopy structure adjustment command is triggered. The final output includes: dynamic suggestions for mixed proportions, optimal sequences of companion tree species, such as the adaptability scores of Choerospondias / Azalea / Liquidambar formosana, and a three-dimensional decision-making plan for the target value of canopy light transmittance.

[0043] 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.

[0044] In the third stage, 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 bin. The laser radar is installed at the center of the bottom of the drone, and the hyperspectral camera is installed under the nose of the drone and equipped with a three-axis stabilization platform. The drone is equipped with a laser radar and a hyperspectral camera to scan the forest canopy to generate a three-dimensional model, and implement precise thinning according to the density heat map. 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 shading film delivery bins for delivering shading film to the forest area; The intelligent transplanting robot is equipped with an AI vision system, which includes a panoramic binocular camera and a lateral laser triangulation ranging 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 adsorption gripper; The intelligent transplanting robot is equipped with a sowing unit at the rear, and the sowing unit includes three independent seed storage bins, which are used to store seeds of camphor, nanmu and superba respectively. The intelligent transplanting robot is equipped with an air suction seed metering device matched with the independent seed storage bins, and a furrow opener is installed at the bottom of the intelligent transplanting robot.

[0045] The AI ​​vision system equipped with the intelligent transplanting robot is used to identify overcrowded branches and perform selective thinning operations and replanting of companion tree species; The collaborative operation mode of drones and ground machinery is used to achieve precise control. The DJI M300RTK equipped with LivoxMID-70 laser radar is used to perform three-dimensional canopy modeling and generate canopy density heat maps. According to AI decision instructions, precise thinning is carried out in areas with a canopy density > 0.7, and intelligent seeders are used to replant target companion tree species simultaneously. At the same time, a mobile soil improvement device is configured to automatically apply biochar and calcium magnesium phosphate compound conditioner when the sensor detects that the pH value is <5.5. The entire operation process is monitored in real time by the digital twin system to ensure that the adjustment error of the mixed planting ratio is ≤2% and the spatial distribution of tree species conforms to the Voroni segmentation model.

[0046] Phase 4: Dynamic effect monitoring and optimization are achieved by establishing a "quarterly evaluation and annual optimization" mechanism. The canopy light interception rate is measured by a ground-based laser leaf area index meter (LAI-2200C) every quarter, and the regulation effect is evaluated in combination with the new bamboo seedling rate of moso bamboo; the annual cycle uses soil profile sampling and analysis to verify the organic matter increment. The model automatically iterates parameters every month. When the soil available phosphorus growth rate is <5% for three consecutive growing seasons, the retraining mechanism of the tree species configuration plan is triggered, and deep-rooted tree species such as camphor are introduced to optimize nutrient circulation.

[0047] This method breaks through the limitations of the fixed ratio configuration of traditional mixed forests through the deep integration of IoT sensing networks and machine learning algorithms, achieving the technical effect of increasing canopy light transmittance by 40% and increasing the annual growth rate of soil organic matter by 2 to 3 times, while reducing the cost of manual management by more than 35%. Especially in the acidified soil restoration scenario with a pH of 4.0 to 5.5, the proportion of mixed planting of Solanum jujuba can be dynamically adjusted to 28% ± 2%, and biochar improvement measures can be used to restore the soil pH to the ideal range of 5.8 to 6.3 within 18 months.

[0048] Furthermore, the operational process of dynamically regulating the mixed proportion of bamboo and broad-leaved mixed forests is to first adjust the mixed proportion. 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 the 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; The air-suction seed meter of the rear sowing unit dynamically selects camphor, nanmu or Schima superba seeds according to soil test data, and absorbs single seeds through negative pressure airflow. The single seeds are then dropped into the seed holes pre-dug by the robot's bottom furrow opener through a guide tube. During the transplanting process, the AI ​​vision system continuously monitors the planting spacing and canopy light transmittance of the companion tree species, dynamically adjusts the thinning and replanting strategies, and ensures that the mixed proportion and spatial distribution conform to the preset model.

[0049] 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.

[0050] 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 based on a three-dimensional canopy model generated by drone lidar scanning. The thinning plan is generated by calculating the optimal light transmittance and crown gap distribution. The optimal light transmittance ranges from 40% to 45%. The intelligent pruning robot is equipped with a high-precision robotic arm and AI vision system, and the overcrowded branches are identified based on the three-dimensional model for 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.

[0051] In autumn, the laser radar 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 deficiency, forming a density heat map; when it is detected that the forest crown density is too high, the drone automatically deploys a shading 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 shading film delivery bins on both sides of the fuselage. After the electric rolling door mechanism is opened, the pH-responsive shading film falls due to gravity, and the directional airflow of the bottom vortex generator controls the unfolding posture of the film material, achieving precise coverage of the shading film and adjusting the light intensity under the forest; thus forming a dynamic light environment, inhibiting strong light from burning young bamboo shoots, and dynamically controlling the light intensity under the forest within the range of 8000 to 12000 lux.

[0052] The shading film is made of degradable nano-TiO 2 , the shading film has a particle size of 50nm and a light transmittance adjustable range of 70% to 90%; In the above scheme, the dynamic mixed planting ratio is to dynamically adjust the proportion of companion tree species according to the soil phosphorus level. For example, when the available phosphorus is less than 15mg / kg, the proportion of jujube is increased to 30%, and the citric acid secreted by the jujube root system activates the insoluble phosphorus; if the organic matter is less than 18g / kg, the proportion of neem is increased to 25%, and the fallen leaves of neem are decomposed quickly, which is conducive to the accumulation of organic matter.

[0053] Furthermore, the above-mentioned directional control method for bamboo ecological soil restoration was verified and calibrated; the understory microenvironment data was collected every month, and the AI ​​prediction values ​​were compared with the actual growth indicators, such as the annual growth rate of bamboo breast diameter. When the error was greater than 10%, the model retraining was triggered.

[0054] The organic matter improvement effect is verified through soil profile sampling every quarter, and the microbial agent application strategy is adjusted dynamically. The growth data of bamboo and the content of soil organic matter and available phosphorus are monitored, and the effect data is collected to further form automatic feedback.

[0055] This technology optimizes the understory microenvironment through a four-step closed-loop system of data perception, intelligent decision-making, precise regulation and effect feedback, achieves dynamic directional regulation of bamboo ecological soil restoration, realizes "data-driven mixed management", and significantly improves light energy utilization and dynamic balance of soil nutrients.

[0056] The above scheme can achieve synergistic effects in the following aspects: 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 regulation mechanism.

[0057] The mixed forest canopy is also used to reduce surface evaporation, increase air humidity by 15% to 20%, and reduce the temperature in the forest by 3 to 5°C in summer, significantly alleviating high temperature stress on bamboo and achieving temperature and humidity balance.

[0058] 2. The synergistic effect of the phosphorus of jujube and bamboo is used to activate and circulate soil nutrients. The roots of jujube secrete organic acids such as citric acid and oxalic acid, which convert soil insoluble phosphorus into effective phosphorus for bamboo to absorb. At the same time, bamboo leaves are rich in silicon. After mixing with jujube leaves, the decomposition rate increases by 30%, and the annual increase of organic matter reaches 2.5g / kg. Furthermore, with the application of nano-modified bacterial agents, the effective phosphorus content in the soil increases from the baseline of 12mg / kg to more than 20mg / kg, and the phosphorus absorption efficiency of bamboo roots increases by 40%. The nano-modified bacterial agent contains phosphate-solubilizing bacteria JXBR04.

[0059] 3. Through targeted adjustments to the soil under the bamboo forest, both ecological and economic benefits can be achieved. Under dynamic regulation, the annual growth rate of bamboo's breast diameter has increased from 1.0 cm in traditional mixed forests to 1.5 cm, and the period of maturity has been shortened by 2 to 3 years. The optimized microenvironment supports the planting of shade-tolerant economic crops under the forest, such as bamboo fungus, which can increase income by 2,000 to 3,000 yuan per mu. At the same time, litter is fed back to the soil, further promoting carbon sequestration and achieving both ecological and economic benefits.

[0060] The above-mentioned directional control scheme for bamboo ecological soil restoration is illustrated by taking the application of dynamic control technology of bamboo and broadleaf mixed forest in Tianbaoyan Nature Reserve in Fujian as an actual case; Fujian Tianbaoyan Nature Reserve is located in the mid-subtropical monsoon climate zone, with an average annual precipitation of 1800 mm and an average annual temperature of 18.5°C. The soil is mainly red soil, and it has the following ecological problems: 1. Severe soil acidification: pH values ​​are generally lower than 5.0, resulting in a high phosphorus fixation rate, an effective phosphorus content of only 6.8 mg / kg, and an organic matter content of 13.2 g / kg; 2. Too dense canopy: Pure bamboo forests account for 80%, and the light transmittance under the forest is less than 30%, which inhibits the growth of associated tree species; 3. Frequent occurrence of pests and diseases: The single bamboo forest structure leads to an increased risk of the spread of diseases such as pine wood nematodes.

[0061] 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; First, AI decisions are fed with historical and real-time data: Historical data: According to the bamboo growth records in the reserve over the past 10 years, its DBH increased by an average of 0.8 cm per year, and the soil acidification trend pH decreased by an average of 0.1 per year; Real-time data: soil pH 4.9, available phosphorus 6.8 mg / kg, organic matter 13.2 g / kg, and light intensity under the forest 7500 lux.

[0062] Then 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 is 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%.

[0063] For the dynamic regulation case of Tianbaoyan Nature Reserve in Fujian, the AI ​​decision-making process combines the random forest algorithm mechanism and ecological principles for multi-dimensional modeling and analysis. The prediction mechanism of random forest is a decision-making method based on ensemble learning. It achieves high accuracy and strong generalization ability by constructing multiple decision trees and combining their prediction results. Its working method is divided into three steps: Introduction of randomness: Each decision tree is trained using a sample subset with replacement sampling (bootstrap) and a randomly selected feature subset to ensure diversity among trees; Independent prediction: Each tree independently generates prediction results based on feature splitting rules such as Gini impurity or mean square error, outputs categories through classification tasks, and then outputs values ​​through regression tasks; Result integration: 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.

[0064] The following is the decision-making process based on the case data: First, a triple objective function including soil improvement, light optimization and tree species adaptability was constructed in this case through the random forest algorithm: Target 1: maxΔpH+available phosphorus+organic matter Goal 2: min canopy density → max light transmittance Goal 3: min disease risk + max hybrid diversity Then the 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 ‌Soil characteristics‌: pH value, available phosphorus content, organic matter content; Stand characteristics: growth rate of bamboo diameter at breast height, current light transmittance (7500 lux corresponds to 30%); ‌Time series‌: annual average pH decline rate (0.1) bamboo growth rate (0.8 cm / year); Furthermore, the Gini impurity is used to evaluate the feature importance: ;

[0065] 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 weight of available phosphorus content is 0.18, and available phosphorus is related to the phosphorus release capacity of Schima superba.

[0066] The core of this formula is that the importance of features is measured by the reduction of Gini impurity. Gini impurity is an indicator of the impurity of a data set and is often used in classification problems.

[0067] Formula composition: ;

[0068] Among them, ΔGinit represents the reduction of 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. It represents the sum of the reductions in Gini impurity during all splitting processes. This reflects the overall contribution of the feature to the improvement of the purity of the data set during the splitting process. Dividing this sum by the total number of splits gives the average contribution of the feature in each split, i.e., the importance score of the feature. The higher the feature importance score, the greater the contribution of the feature to the improvement of the purity of the data set during the decision tree splitting process.

[0069] Based on the above decision, the derivation of the dynamic hybrid ratio decision tree is further explained, taking a typical decision tree as an example; 1. Root node splitting rules If soil pH <5.0 and light transmittance <35%: Enter the left branch (need to improve soil + increase light) else: Enter the right branch (maintain the status quo) 2. Secondary node split Left branch: If bamboo proportion>75% and available phosphorus<10mg / kg: Choose acid-tolerant and phosphorus-rich tree species (Schimasuperba) else: Choose other broadleaf species 3. Leaf node output Comprehensive voting results of multiple decision trees: Schima superba accounts for 25% and receives 78% support from trees; the target light transmittance of 35% to 40% corresponds to an increase in light intensity to 8750-10000 lux.

[0070] Using ecological effect verification calculation, the soil improvement prediction of Schima superba is given by the formula of decomposition rate of fallen leaves: ;

[0071] Annual organic matter increase: ΔOrganic matter=25%× =25%× ≈0.88g / kg The canopy porosity model after mixed forests was obtained through optimization calculation of light transmittance: New light transmittance = 30% × (1 + ) = 30% × 1.3 = 39% It should be noted that the canopy opening of Schima superba is 40% higher than that of Phyllostachys pubescens.

[0072] In this study, we used the random forest algorithm and conducted an in-depth analysis of the growth characteristics of Schima superba through an integrated verification method. Specifically, we first performed Bootstrap resampling on 10 years of historical data, from which we extracted 8 sets of samples containing key sequences such as pH drop and bamboo growth. Then, in feature selection, we adopted the principle of feature randomness and randomly selected 3 features for each decision tree, such as pH, light transmittance, and available phosphorus. Through such regression prediction, we successfully performed numerical fitting on the mixed planting ratio and determined the mixed planting scheme corresponding to 25% of Schima superba and the median of the 95% confidence interval [23%, 27%] within the 95% confidence interval.

[0073] 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 transform them into an operational 3:1 mixed breeding plan.

[0074] The implementation of this program not only helps slow down the rate of soil acidification, but also significantly improves the disease resistance of forest stands, increasing the disease resistance index by 2.3 times. The above findings provide important scientific basis for forest management and ecosystem restoration.

[0075] On the basis of implementing the AI ​​optimization solution, we further adopted automated machinery and intelligent equipment to ensure precise practical operations. In order to improve the lighting conditions in the bamboo forest, we deployed intelligent pruning robots. These robots can accurately cut off the 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 used intelligent drones for refined operations. A pH-responsive nano-shading film containing CaCO is spread by drones. 3 The particles can neutralize acidic precipitation and reduce surface acidity. At the same time, their light transmittance is as high as 75%, which helps to optimize the lighting environment.

[0076] In order to comprehensively improve the ecological and economic benefits of bamboo forests, we have taken further measures in soil remediation. By applying nano-modified bacteria, we have enhanced soil fertility and improved the adaptability of bamboo to acidic environments.

[0077] The microbial agent specifically contains acid-resistant phosphate-solubilizing bacteria (PenicilliumoxalicumPO109), with an application rate of 150 kg per hectare. Through precise targeted release technology, the microbial agent is applied to the rhizosphere of bamboo, with a depth of 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.

[0078] On this basis, we further expanded the development of forest understory economy. We planted the acid-tolerant and shade-tolerant cash crop Polygonum cuspidatum under the forest, with a planting density of 2,000 plants per mu. In order to ensure the healthy growth of Polygonum cuspidatum, we equipped it with an intelligent drip irrigation system that can accurately control soil moisture and keep it within the appropriate range of 60% to 70%. This comprehensive ecological soil restoration and forest understory cash crop planting strategy not only improved the ecological environment of the forest, but also achieved economic benefits through the planting of Polygonum cuspidatum, providing a new way for the comprehensive utilization of bamboo forests.

[0079] The following is a comparison table of dynamic regulation data of bamboo and broadleaved mixed forests in Tianbaoyan Nature Reserve in Fujian.

[0080]

[0081] In terms of the mechanism of action of the technology, our research has achieved the following breakthroughs: First, we used the synergistic effect of Schima superba and bacterial agents to improve acidic soil. The fallen leaves of Schima superba are rich in alkaline substances, with a pH value of 6.2, and the acid-tolerant phosphate-solubilizing bacteria secrete oxalic acid, which converts the aluminum-phosphorus complex (Al-P) in the red soil that is difficult to use into effective phosphorus that can be absorbed by plants, thereby increasing the annual increase in soil effective phosphorus to 5.3 mg / kg. At the same time, the nano-CaCO 3 The micro-granular shading film will be slowly released during the rainy season to neutralize acidic rainwater, raising the pH value from 4.5 to 5.2, effectively reducing the toxicity to the bamboo roots.

[0082] Secondly, by optimizing light and heat resources, we increased the photosynthetic rate of bamboo. The increase in light transmittance to 39% increased the photosynthetic rate of bamboo by 20%, and the measured net photosynthetic rate increased from 8.2μmol / m 2 / s increased to 9.8 μmol / m 2 In addition, the canopy shading of Schima superba can also reduce the surface temperature and reduce bamboo transpiration by 15%, thereby alleviating drought stress in summer.

[0083] In terms of ecological and economic synergy, we planted acid-resistant and shade-tolerant Polygonum cuspidatum. The antibacterial substance rhein secreted by the root system of Polygonum cuspidatum 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 income from the planting of Polygonum cuspidatum can even cover the cost of technical investment. In actual planting, the cost of equipment and microbial agents per mu is about 800 yuan, and the income from Polygonum cuspidatum is 2,700 yuan per mu, thus realizing a virtuous cycle of restoration and income.

[0084] In terms of innovative verification and promotion value, our technology has the following characteristics: 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" to overcome the limitations of traditional lime improvement methods that easily cause soil compaction.

[0085] 2. The error rate of prediction through the AI ​​model is less than 8%, which is 35% higher than the manual experience method.

[0086] 3. The amount of carbon sequestered 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.

[0087] In summary, this case study verifies the applicability of dynamic regulation technology for mixed bamboo and broadleaf forests in subtropical acidic red soil areas. Through the integration of smart devices and biotechnology, we have achieved the triple goals of soil restoration, bamboo quality improvement, and forest economic value-added, providing a replicable and referenceable paradigm for similar ecologically fragile areas.

[0088] Embodiment 2:

[0089] See also Figure 1 In combination with Example 1, this solution processes bamboo waste into high-value materials and prepares them into bacterial agent carriers with adsorption and slow-release properties to achieve soil remediation and the stability of the bamboo forest ecosystem. The specific implementation steps are as follows: 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.

[0090] 2. Then, the porous bamboo charcoal is obtained by pyrolysis at 600°C for 2 hours using an oxygen-limited pyrolysis process. The porous bamboo charcoal has a pore size of 50 to 100 nm, a specific surface area of ​​more than 800 m² / g, and good adsorption performance.

[0091] 3. This scheme combines bamboo charcoal powder with Fe 3 O 4 The nanoparticles were mixed in a mass ratio of 1:0.1 and treated at 180°C for 12 hours using a hydrothermal method to successfully load the magnetic particles, thereby effectively improving the adsorption performance and sustained-release ability of the carrier.

[0092] 4. Soak bamboo chips in 5% NaOH solution for 24 hours to neutralize lignin and increase surface roughness, thereby increasing the area of ​​bacterial attachment.

[0093] 5. Select phosphate-solubilizing bacteria, nitrogen-fixing bacteria and drought-resistant fungi, and compound them into a composite bacterial community in a certain proportion. Mix the composite bacterial community with modified bamboo charcoal and signal molecules, and make a granular bacterial agent through low-temperature spray drying with a particle size of 2 to 3 mm.

[0094] 6. Furthermore, an impedance biosensor and a fluorescent probe integrated chip are used to monitor the survival rate of rhizosphere bacteria in real time. When the survival rate is lower than 70%, the liquid bacterial suspension is released through the solar drip irrigation system to achieve automatic bacterial replenishment.

[0095] Integrated application of the above-mentioned bacterial agent carriers in dynamic regulation of bamboo-broadleaved mixed forests: This plan applies the bacterial agent carrier to the dynamic regulation of bamboo and broadleaf mixed forests to achieve the dual goals of soil restoration, carbon sequestration enhancement and economic benefits. The specific implementation steps are as follows: 1. During the planting period, use a pneumatic deep application machine to implant the granular bacterial agent into the rhizosphere simultaneously with the bamboo seedlings, with a dosage of 150kg / ha.

[0096] During the growing season, drones are used to hang slow-release packages of microbial agents. The packages are based on bamboo charcoal and have a microbial loading of 30%. They are released to densely populated bamboo areas at designated locations every month, with a single dosage of 50kg / ha.

[0097] Furthermore, the application of bacterial agent carriers is coordinated with dynamic regulation technology; First, soil sensors monitor data such as available phosphorus and pH in real time. When the available phosphorus is lower than 15 mg / kg, the AI ​​system prioritizes calling the phosphate-dissolving bacteria release instruction; the solar drip irrigation system is integrated with the bacteria release module, and the bacteria pipeline is controlled by the solenoid valve to achieve precise delivery on demand.

[0098] Furthermore, by utilizing the integrated carbon sink-enhancing mixed planting model, we selected high carbon sink tree species for mixed planting, such as introducing Phoebe nanmu and Cinnamomum camphora, whose carbon fixation per unit biomass is 1.8 t / ha·yr and 1.5 t / ha·yr, respectively.

[0099] The carbon storage of the forest stand 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, and the carbon sink is continuously monitored to form data feedback.

[0100] Through the above implementation methods, this scheme has achieved efficient utilization of bamboo waste and promoted the stability and sustainable development of bamboo forest ecosystem. At the same time, the scheme has fully considered innovation and practicality in the process of technical implementation, providing new ideas and methods for bamboo forest management.

[0101] Embodiment three:

[0102] See also Figure 2, and in combination with Example 1, the directional control method for bamboo ecological soil restoration also includes an AI-driven intelligent drip irrigation system, the intelligent drip irrigation system includes a bacterial agent storage tank, an irrigation water tank and an electromagnetic proportional valve, the bacterial agent storage tank and the irrigation water tank are connected to an electromagnetic proportional valve, the electromagnetic proportional valve is used to dynamically control the mixing ratio of the bacterial agent and the irrigation water, the liquid outlet of the electromagnetic proportional valve is fixedly connected to a delivery pump, and the delivery pump is connected to a drip irrigation pipeline; The outside of the drip irrigation pipe is covered with a flexible solar film, and the flexible solar film is electrically connected to an energy storage battery pack.

[0103] The system uses an electromagnetic proportional valve to dynamically control the mixing ratio of the bacterial agent and irrigation water. The 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 mode that only relies on soil moisture. The soil multi-parameter sensor is used to detect N / P / K (nitrogen, phosphorus and potassium), humidity, and EC values. The meteorological data includes light, temperature and humidity.

[0104] 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 bacterial agent demand of bamboo, and dynamically generate drip irrigation plans.

[0105] The AI-driven intelligent drip irrigation system combines flexible solar film with lithium iron phosphate battery packs to achieve seamless connection between photovoltaic power generation, energy storage and drip irrigation. The photoelectric conversion rate of the flexible solar film is ≥23%, thus solving the power supply problem in remote bamboo forest areas.

[0106] The system's energy storage capacity is ≥5kWh, which can support nighttime drip irrigation, and through the power adaptive regulation module, it can switch to low-power mode on rainy days.

[0107] During the precise release of the bacterial agent, the bacterial agent suspension and irrigation water are mixed in proportion, and the concentration of the bacterial agent is dynamically controlled by an electromagnetic proportional valve to achieve precise control of the ratio of the bacterial agent suspension to irrigation water.

[0108] 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 concentration of the bacterial agent automatically increases to 0.2%.

[0109] 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 that the system runs uninterruptedly 24 hours a day.

[0110] The soil multi-parameter sensors (N / P / K, humidity, EC value) of the data acquisition unit 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 the micro-meteorological station is used to monitor light intensity, temperature, humidity, and wind speed.

[0111] The micro-drip irrigation device is equipped with an electromagnetic proportional valve and a bacterial agent mixing chamber; dynamic monitoring of the shade degree under the forest and the placement of shading film are carried out through a drone equipped with a hyperspectral camera.

[0112] 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.

[0113] After receiving the data, the cloud-based random forest model predicts the transpiration of bamboo in the next six hours; calculates the concentration of bacterial agent release based on the available phosphorus content in the soil; and outputs drip irrigation frequency and shading adjustment instructions.

[0114] The formula for calculating the release concentration of the bacterial agent is: ; Then the electromagnetic proportional valve adjusts the mixing ratio of the bacterial agent according to the instructions, and the drip irrigation system works at the set frequency; the drone scans the canopy shading in real time, and if it detects that the light intensity is greater than 12000lux, it automatically spreads a shading film with a light 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 through the LoRa network.

[0115] 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, thereby achieving complete reliance on external power supply.

[0116] The system has built a closed-loop system including data, decision-making and execution; its working method is that soil and meteorological data are first pre-processed by the edge computing unit, and then analyzed by the cloud AI model to generate corresponding drip irrigation parameters. These parameters are then sent to the execution unit for precise control. Finally, the system collects feedback effect data to iteratively optimize the cloud model.

[0117] Secondly, the system has a dynamic adaptive adjustment function; in drought warning mode, when the soil moisture is lower than 50% and the temperature is higher than 30°C, the system will trigger high-frequency drip irrigation, that is, drip irrigation for 15 minutes every hour to ensure that the water needs of plants are met. In rainstorm response mode, once the rainfall exceeds 20mm / h, the system will automatically shut down the drip irrigation and start drainage monitoring to prevent the soil from being too wet.

[0118] Ultimately, this solution effectively broke through the technical limitations of traditional drip irrigation systems by integrating three innovative technologies: AI decision-making, solar-powered driving, and precise release of microbial agents. This not only achieved efficient resource utilization, but also promoted ecological restoration, providing an intelligent solution for the sustainable management of bamboo forests.

[0119] Furthermore, we can add ecological and economic compound planting patterns under the forest, plant shade-tolerant medicinal plants such as Panax notoginseng or Polygonatum sibiricum, and edible fungi such as Dictyophora in mixed bamboo and broadleaf forests, forming a three-layer three-dimensional planting system of "bamboo-broadleaf trees-economic crops", with supporting microbial agent directional regulation and intelligent drip irrigation. This will not only increase economic income, but also enhance soil carbon sequestration capacity through root interaction.

[0120] The above disclosures are only several 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 protection scope 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 a communication module; 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; Step (3) Based on the decision-making plan, a three-dimensional canopy model is generated by using drone scanning, and the canopy density is adjusted, associated tree species are planted, and soil conditioners are applied through the forestry intelligent operation terminal; 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 directional control method for bamboo ecological soil restoration 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 a uniformly distributed multi-parameter soil sensor network micro-meteorological station.

3. The method for directional regulation of bamboo ecological soil restoration according to claim 1, characterized in that: 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, effective 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 method for directional regulation of bamboo ecological soil restoration according to claim 1, characterized in that: In step (3), drones are 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 the preset threshold. Acid-resistant companion tree species are replanted through intelligent equipment, and composite soil conditioners are automatically applied based on the real-time soil pH value.

5. The method for directional regulation of bamboo ecological soil restoration 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 soil available phosphorus growth rate is less than 5% for three consecutive seasons, the configuration plan for deep-rooted camphor tree species is retrained.

6. The method for directional regulation of bamboo ecological soil restoration according to claim 1, characterized in that: 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.

7. The method for directional regulation of bamboo ecological soil restoration according to claim 1, characterized in that: The dynamic control model described in step (2) dynamically adjusts the proportion of associated tree species according to the soil available phosphorus content and organic matter level, and generates a thinning plan based on the target value of canopy transmittance.

8. The method for directional regulation of bamboo ecological soil restoration according to claim 1, characterized in that: The construction of the dynamic control model includes the following steps: (a) Determine the correlation threshold rules between soil organic matter content and available phosphorus concentration, as well as the mapping relationship between forest light intensity and canopy transmittance through feature analysis; (b) generating a multi-dimensional decision-making scheme for dynamic mixed planting ratio adjustment suggestions, companion tree species adaptability scores, and canopy transmittance target values ​​based on the association threshold rules and mapping relationships; (c) According to the real-time monitoring results of soil pH value, 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.

9. The method for directional regulation of bamboo ecological soil restoration according to claim 1, characterized in that: The waste bamboo is processed into high-value materials to prepare a bacterial agent carrier with adsorption and sustained-release properties for soil remediation and the stabilization of bamboo forest ecosystems; the waste bamboo materials including bamboo chips, bamboo branches and bamboo roots are crushed to control the particle size below 2 mm, and porous bamboo charcoal is obtained through an oxygen-limited pyrolysis process; the bamboo charcoal powder is then mixed with Fe3O4 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 made into a granular bacterial agent through low-temperature spray drying.

10. The method for directional regulation of bamboo ecological soil restoration according to claim 1, characterized in that: The soil conditioner applied in step (3) includes a nano-modified bacterial agent containing phosphate-solubilizing bacteria and a pH-responsive shading film, wherein the shading film is used to neutralize acidic precipitation and adjust the light intensity under the forest.

11. A bamboo ecological soil restoration directional control device for implementing the bamboo ecological soil restoration directional control method according to any one of claims 1 to 10, 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, the edge computing gateway is data-connected to the cloud server cluster, and the cloud server cluster is used to run the cloud database and AI model; the cloud server cluster is data-connected to the forestry intelligent operation terminal for directional control of soil restoration.

12. The bamboo ecological soil restoration directional control device according to claim 11, 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 and a hyperspectral camera, and a shading film delivery chamber. 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 a laser radar and a hyperspectral camera for scanning the forest canopy to generate a three-dimensional model, and implements precise thinning according to the density heat map. 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 shading film delivery bins for delivering shading film to the forest area; The intelligent transplanting robot is equipped with an AI vision system, which includes a panoramic binocular camera and a lateral laser triangulation ranging 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 adsorption gripper; The intelligent transplanting robot is rear-mounted with a sowing unit, which includes three independent seed storage bins for storing camphor, nanmu, and Schima superba seeds, respectively. The intelligent transplanting robot is equipped with an air-suction seed metering device that matches 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 thinning operations and replanting of companion tree species; The intelligent drip irrigation system includes a bacterial agent storage tank, an irrigation water tank and an electromagnetic proportional valve. The bacterial agent storage tank and the irrigation water tank are connected to an electromagnetic proportional valve, which is used to dynamically adjust the mixing ratio of the bacterial 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 pipeline. The outside of the drip irrigation pipe is covered with a flexible solar film, and the flexible solar film is electrically connected to an energy storage battery pack.

Images