Bamboo forest water and fertilizer integrated drip irrigation fertilization method and system based on soil detection

Abstract

The invention discloses a water and fertilizer integrated drip irrigation and fertilization method and system for a bamboo forest based on soil detection, and belongs to the technical field of intelligent forestry and precise irrigation. According to the method, by arranging a soil multi-parameter sensor network, bamboo forest soil moisture and the content of key nutrients such as nitrogen, phosphorus and potassium are monitored in real time; based on the monitoring data, respectively calculating a deficit index reflecting the moisture condition and a demand index reflecting the multi-nutrient comprehensive demand degree; in combination with the current growth stage of the bamboo forest, dynamically determining the water demand of each irrigation and the application amount of the special fertilizer through an intelligent decision-making model, and accurately preparing a liquid fertilizer according to the actual deficit proportion of each nutrient; finally, according to the difference of water and fertilizer requirements of different areas in the land parcel, an irrigation system is controlled to achieve zoned variable precise fertilization. According to the method, collaborative intelligent decision and on-demand accurate supply of moisture and nutrients are realized, the utilization efficiency of water and fertilizer resources is remarkably improved, the labor cost and the environmental risk are reduced, and a complete technical solution is provided for modernization accurate management of the bamboo forest industry.

Description

Technical Field

[0001] This invention relates to the fields of smart forestry and precision forestry, and in particular to a method and system for integrated drip irrigation and fertilization of bamboo forests based on soil testing. Background Technology

[0002] Bamboo forests are an important forest resource and a distinctive economic forest species in my country, possessing ecological, economic, and cultural value. Their efficient cultivation places extremely high demands on the precision of water and fertilizer management. Traditional bamboo forest water and fertilizer management generally relies on farmers' experience, employing extensive methods such as manual flooding, furrow application, or broadcasting. This approach has a series of inherent drawbacks: First, water and fertilizer utilization rates are low, with large amounts of water lost through surface runoff and deep seepage, and nutrients such as nitrogen and phosphorus easily fixed, volatilized, or leached, with estimated utilization rates often below 40%. Second, it is labor-intensive and the timing of management is difficult to pinpoint, failing to meet the explosive demand for water and fertilizer during the rapid growth period of bamboo forests. Third, it easily leads to environmental pollution; excessive fertilization can cause soil acidification, salinization, and eutrophication of surrounding water bodies.

[0003] With the development of water-saving agricultural technologies, integrated water and fertilizer drip irrigation systems have begun to be applied in bamboo forest management. These systems typically dissolve soluble fertilizers in irrigation water and deliver them directly and evenly to the root zone of the bamboo forest through pipes and drippers, thus improving resource utilization efficiency to some extent. However, existing integrated water and fertilizer technologies applied to bamboo forests still lack sufficient intelligence and precision, mainly in the following three aspects: Firstly, in terms of control logic, most current systems employ simple "threshold triggering" or "timed and quantitative" control strategies. For example, irrigation is initiated only when the soil moisture sensor reading falls below a certain preset value, while fertilization is added with water at fixed intervals or in fixed proportions. This strategy mechanically separates water management from nutrient management, ignoring the significant differences in the dynamic demand ratios of nutrients such as nitrogen, phosphorus, and potassium in bamboo forests at different phenological stages (such as the shoot differentiation period, peak shoot emergence period, and bamboo growth period). It also fails to respond to real-time changes in the soil's own nutrient pool, potentially leading to insufficient nutrient supply during critical growth periods or nutrient redundancy during non-fertilizer-demanding periods.

[0004] Secondly, in terms of decision-making models, existing methods lack an intelligent decision-making core capable of integrating multi-source information and simulating the physiological needs of bamboo forests. Irrigation amounts are often determined solely based on the simple difference between the current soil moisture content and the target moisture content, without comprehensively considering the daily meteorological evaporation potential, the impact of bamboo canopy closure on the field microclimate, and the nonlinear characteristics of soil water infiltration. Fertilizer application is even more crudely determined, rarely based on simultaneous detection and scientific diagnosis of multiple soil nutrients; the decision-making models are static, rigid, and lack adaptability.

[0005] Finally, in terms of implementation, most existing technologies treat the entire bamboo forest as a homogeneous unit for unified management. However, due to factors such as topographic relief, spatial variations in soil texture, and uneven distribution of bamboo age structure, the water and fertilizer requirements within the bamboo forest exhibit significant spatial heterogeneity. Adopting a "one-size-fits-all" irrigation and fertilization scheme inevitably leads to insufficient water and fertilizer in some areas of the forest while excessive water and fertilizer is applied in others, failing to achieve optimal resource allocation and limiting the full potential of the drip irrigation system.

[0006] Therefore, the industry urgently needs a bamboo forest water and fertilizer management method that can overcome the aforementioned limitations. This method should be able to dynamically and collaboratively decide the timing, amount, and formula of irrigation and fertilization based on real-time, multi-point in-situ soil monitoring data, through an intelligent algorithm with a built-in bamboo forest growth physiological model, and possess spatial variable execution capabilities. This would truly achieve on-demand supply and precise regulation, promoting the transformation and upgrading of the bamboo forest industry towards a modern direction of resource conservation, environmental friendliness, high yield, and high efficiency. Summary of the Invention

[0007] The purpose of this invention is to overcome the aforementioned shortcomings of existing technologies and provide a method and system for integrated drip irrigation and fertilization of bamboo forests based on soil testing. This method constructs a collaborative calculation model of water deficit index and comprehensive nutrient demand index, coupled with bamboo forest phenological stages and environmental factors, to dynamically determine irrigation volume and fertilizer formulation, ultimately achieving precise execution of regional variables. This invention aims to significantly improve water and fertilizer utilization efficiency, reduce the risk of non-point source pollution, and promote the intelligent, precise, and sustainable development of the bamboo forest industry.

[0008] To achieve the above-mentioned objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for integrated water and fertilizer drip irrigation fertilization in bamboo forests based on soil testing, comprising the following steps: S1. Data collection: Multiple soil information monitoring points are set up in the bamboo forest plot according to a preset grid, and the soil volume moisture content θ and the content of various key soil nutrients at each monitoring point are regularly detected and obtained. S2. Demand Index Calculation: Based on the real-time data obtained in step S1, calculate the Water Deficiency Index (WDI), which represents the overall water status of the bamboo forest plot, and the Comprehensive Nutrient Demand Index (FNI), which represents the degree of comprehensive demand for multiple nutrients. S3. Dynamic Decision-Making: Based on the WDI and FNI calculated in step S2, and combined with the current phenological stage of the bamboo forest and the preset growth cycle-demand model, the target irrigation amount Q and the target fertilizer mother liquor injection amount M for this operation are determined by the intelligent decision-making model. S4. Variable execution: Based on the total amount determined in step S3, combined with the spatial differences of each monitoring point, generate zoning control instructions to drive the integrated water and fertilizer drip irrigation system to perform spatially variable irrigation and fertilization operations.

[0009] Furthermore, the various key soil nutrients mentioned in step S1 include at least available nitrogen, available phosphorus, and available potassium; the data collection cycle is once every 1-6 hours, and the data is transmitted to the central controller via the Internet of Things.

[0010] Furthermore, the formula for calculating the Water Deficiency Index (WDI) in step S2 is as follows: ; in, The field water holding capacity of the bamboo forest soil. The wilting coefficient of the bamboo forest soil. This is the area-weighted average of soil moisture content at all currently valid monitoring points.

[0011] Furthermore, the formula for calculating the Comprehensive Nutrient Demand Index (FNI) in step S2 is as follows: ; in, The types and quantities of key nutrients; For the first The current average soil content of key nutrients; In order to match the current bamboo forest phenology The corresponding number The optimal soil content threshold for nutrients; For the first The weighting factors of nutrients in the current phenological stage, and The The function ensures that only when Only then will the nutrient generate a positive contribution to demand.

[0012] Furthermore, the formula for calculating the target irrigation amount Q in step S3 is as follows: ; in, To incorporate reference crop evapotranspiration Bamboo forest leaf area index Real-time environmental adjustment coefficient; This represents the depth of the main root system activity layer in bamboo forests. per unit area; This is an empirical nonlinear correction coefficient, with a value range of 0.8-1.2; This function is used to limit WDI to a reasonable range.

[0013] Furthermore, the formula for calculating the target fertilizer mother liquor injection volume M in step S3 is as follows: ; in, In order to match the current phenological period Strength coefficient; This refers to the mass concentration of total available nutrients in the fertilizer stock solution prepared this time. This is a correction coefficient for the average nutrient utilization rate of the pre-set irrigation and fertilization system.

[0014] Furthermore, the specific proportion of the fertilizer mother liquor is dynamically determined based on the calculation process of the comprehensive nutrient requirement index (FNI), wherein the first... Relative concentration ratio of seed nutrients in mother liquor satisfy: ; That is, the fertilizer formula is proportional to the real-time deficiency of each nutrient in the soil and the phenological conditions.

[0015] Furthermore, the specific implementation of the spatial variableization operation in step S4 is as follows: the bamboo forest plot is divided into multiple independent irrigation zones corresponding to monitoring points; the central controller independently calculates the irrigation data for each zone based on the data from the monitoring points within that zone. and This determines the partition. and By controlling the electric valves and variable frequency fertilizer injection pumps on the branch pipes of each zone, each zone can receive a precise supply of different amounts of water and fertilizer within a unified operating time.

[0016] Secondly, the present invention provides an intelligent drip irrigation system for bamboo forests that integrates water and fertilizer management to implement the above-mentioned method, comprising: Sensing layer: Composed of multiple soil multi-parameter sensor nodes deployed within the bamboo forest plot, used to detect soil moisture content and nutrient content; Transport layer: Consists of IoT gateways and communication networks, used to upload data from the sensing layer; Decision layer: includes a central controller and intelligent decision model software stored therein, used to execute the calculation and decision steps described in claims 1-8 and generate control commands; The execution layer includes a water source, filtration device, fertilizer mother liquor preparation and storage device, fertilizer injection pump, main pipeline, zone branch pipe, zone electric valve and drip irrigation tape / pipe; the fertilizer injection pump and zone electric valve are controlled by the control commands of the decision layer.

[0017] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can perform the steps of the method described above.

[0018] Compared with the prior art, the present invention has the following advantages and beneficial effects: I. Improved Precision and Collaboration A water and fertilizer co-operation decision-making model was constructed by coupling the calculation of the water deficit index (WDI) and the comprehensive nutrient demand index (FNI). This method abandons the traditional extensive management model of "relying on experience" or "separating water and fertilizer" and realizes "supply on demand and synchronous response". It enables the water and fertilizer supply to be precisely matched with the real-time physiological needs of bamboo forests and soil conditions, and fundamentally solves the contradiction of insufficient supply or excessive waste.

[0019] II. Strong Decision-Making Intelligence and Adaptive Capabilities The core algorithm incorporates dynamic parameters of phenological periods ( , The model incorporates environmental regulation coefficients (α) and nonlinear response (k), enabling it to integrate multi-source information and achieve dynamic self-adaptation. The model can automatically adjust water and fertilizer strategies based on changes in bamboo forest growth stages, meteorological conditions, and soil characteristics, making it more scientific and aligned with actual production needs than static control methods based on fixed thresholds.

[0020] III. Resource utilization efficiency has been significantly improved. The "fertilize according to demand, irrigate as needed" model, combined with precise dynamic fertilizer ratio technology, can improve water and fertilizer utilization efficiency by more than 30%. Experiments show that, under the premise of achieving the same or better yield increase, water can be saved by 20%-35%, fertilizer by 25%-40%, significantly reducing production costs and effectively reducing agricultural non-point source pollution caused by nutrient leaching and volatilization.

[0021] IV. Support for refined variable operations to address spatial heterogeneity The zonal management strategy based on a high-density monitoring network can identify and respond to the spatial heterogeneity of water and fertilizer within bamboo forest plots. The system can provide differentiated water and fertilizer formulas and dosages for different areas, realizing a leap from "uniform" management to "prescription map"-style precision management, and improving the overall stand uniformity and productivity.

[0022] V. High degree of automation, saving labor costs The entire process achieves closed-loop automated management of automatic data collection, intelligent decision-making, and precise execution, which greatly reduces the reliance on human experience and frequent manual operations in traditional management, reduces labor intensity and management costs, and provides reliable technical support for the modern management of large-scale bamboo forest bases.

[0023] VI. A Win-Win Situation for Ecological and Economic Benefits While increasing yield and quality, it significantly reduces resource consumption and environmental pollution risks, and promotes the health of bamboo forest ecosystems. Attached Figure Description

[0024] Figure 1 This is a schematic diagram of the overall process of the method of the present invention; Figure 2This is a flowchart illustrating the computational logic of the intelligent decision-making model in this invention. Figure 3 This is a schematic diagram illustrating an implementation of the variable drip irrigation fertilization system using the method of the present invention in a bamboo forest. Figure 4 This is a schematic diagram comparing the effects of the method of the present invention with those of traditional methods. Detailed Implementation

[0025] The present invention will be further described in detail below with reference to experimental examples and specific embodiments. However, this should not be construed as limiting the scope of the above-mentioned subject matter of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0026] Example 1 This embodiment provides a method for integrated water and fertilizer drip irrigation fertilization in bamboo forests based on soil testing, including the following steps: S1. Data collection: Multiple soil information monitoring points are set up in the bamboo forest plot according to a preset grid, and the soil volume moisture content θ and the content of various key soil nutrients at each monitoring point are regularly detected and obtained. S2. Demand Index Calculation: Based on the real-time data obtained in step S1, calculate the Water Deficiency Index (WDI), which represents the overall water status of the bamboo forest plot, and the Comprehensive Nutrient Demand Index (FNI), which represents the degree of comprehensive demand for multiple nutrients. S3. Dynamic Decision-Making: Based on the WDI and FNI calculated in step S2, and combined with the current phenological stage of the bamboo forest and the preset growth cycle-demand model, the target irrigation amount Q and the target fertilizer mother liquor injection amount M for this operation are determined by the intelligent decision-making model. S4. Variable execution: Based on the total amount determined in step S3, combined with the spatial differences of each monitoring point, generate zoning control instructions to drive the integrated water and fertilizer drip irrigation system to perform spatially variable irrigation and fertilization operations.

[0027] For details, please refer to Figure 1 The overall process diagram was implemented in a 10-hectare bamboo forest.

[0028] S1. Data Acquisition Phase: For example... Figure 1 As shown at the top, 40 soil information monitoring points (corresponding to multiple soil sensor icons in the figure) were set up in a 50m×50m grid within the bamboo forest area. Each monitoring point is equipped with a multi-parameter soil sensor, which can detect the volumetric water content θ of the 0-40cm soil layer in real time. Through a dedicated IoT node, the water content data, along with sensor data on available nitrogen (N), phosphorus (P), and potassium (K), are packaged and uploaded to the cloud platform every 4 hours.

[0029] S2. Demand Index Calculation Phase: The cloud platform's data processing module aggregates data at 2 AM daily. For example... Figure 1 As shown on the left side of the middle section, the "Data Processing" module preprocesses the soil moisture content, and the "WDI Calculation" module calculates the soil moisture content based on preset bamboo forest soil parameters. , ) and the calculated area-weighted average moisture content The system automatically calculates WDI. Simultaneously, the "Nutrient Analysis" module analyzes the N, P, and K content, while the "FNI Calculation" module calculates FNI based on the parameters of the current "bamboo shoot development stage."

[0030] S3. Dynamic Decision-Making Stage: For example... Figure 1 The "Intelligent Decision Model" diagram on the right side of the middle section shows that the model receives WDI and FNI as inputs and calls the model parameters of the current phenological stage T ("bamboo shoot incubation stage"). After calculation by the built-in algorithm, it outputs the target irrigation amount Q (e.g., 125 m³ / hectare) and the target fertilizer mother liquor injection amount M (e.g., 15 L / hectare) for this operation.

[0031] S4. Variable Execution Phase: For example... Figure 1 As shown at the bottom, the central controller (or cloud platform) sends the Q and M total quantities and zoning instructions generated by the decision to the field "execution units". The execution units drive the water pumps, fertilizer pumps and solenoid valves of each zone of the drip irrigation system to complete this integrated water and fertilizer irrigation operation according to the instructions.

[0032] pass Figure 1 The complete closed-loop process shown enables fully automated management from data perception to precise execution.

[0033] Example 2 Furthermore, the various key soil nutrients mentioned in step S1 include at least available nitrogen, available phosphorus, and available potassium; the data collection cycle is once every 1-6 hours, and the data is transmitted to the central controller via the Internet of Things.

[0034] This embodiment details the data acquisition process. Building upon Embodiment 1, this embodiment focuses on the specific configuration of the sensor network. The detection of various key soil nutrients utilizes in-situ sensors based on the ion-selective electrode method to continuously monitor available nitrogen (N), available phosphorus (P), and available potassium (K) in the soil. The data acquisition cycle is set to once every 4 hours, which can be increased to once every 2 hours during the rapid growth period of the bamboo forest. All sensor nodes aggregate data via a LoRa wireless network to an IoT gateway deployed in the bamboo forest management room. The gateway then synchronizes the data to a central cloud database via a 4G network, completing the data transmission. Figure 1 The "soil sensor" icon at the top represents this distributed sensing network.

[0035] Example 3 Furthermore, the formula for calculating the Water Deficiency Index (WDI) in step S2 is as follows: ; in, The field water holding capacity of the bamboo forest soil. The wilting coefficient of the bamboo forest soil. This is the area-weighted average of soil moisture content at all currently valid monitoring points.

[0036] This embodiment details the calculation process of WDI. (See reference...) Figure 1 The "WDI Calculation" module. For a known... , In a bamboo forest, at a certain moment, the system acquired the moisture content of all 20 monitoring points. Based on the area proportion represented by each monitoring point, a weighted average moisture content was calculated for the current area. .

[0037] Substituting into the formula of claim 3: ; Calculation results indicate that the current soil moisture condition is in a state of slight to moderate deficit (WDI=0.35), and this index will be used as... Figure 1 One of the key inputs to the "intelligent decision-making model".

[0038] Example 4 Furthermore, the formula for calculating the Comprehensive Nutrient Demand Index (FNI) in step S2 is as follows: ; in, The types and quantities of key nutrients; For the first The current average soil content of key nutrients; In order to match the current bamboo forest phenology The corresponding number The optimal soil content threshold for nutrients; For the first The weighting factors of nutrients in the current phenological stage, and The The function ensures that only when Only then will the nutrient generate a positive contribution to demand.

[0039] This embodiment details the calculation process of FNI. (See reference...) Figure 1 The "FNI Calculation" module is used. The current bamboo forest phenological stage T is the "germination stage". The preset optimal soil content thresholds for this stage are: , , The weighting factor is set as follows: , , The current average content detected by the system is: , , ; Substitute into the formula: For nitrogen (N): The contribution is 0.5 × 0.15 = 0.075; For phosphorus (P): The contribution is 0.2 × 0 = 0; For potassium (K): The contribution is 0.3 × 0.125 = 0.0375; but: ; Calculation results This indicates a deficiency of nitrogen and potassium in the soil, with a more pronounced demand for nitrogen. This index is input along with WDI. Figure 1 The "intelligent decision-making model".

[0040] Example 5 Furthermore, the formula for calculating the target irrigation amount Q in step S3 is as follows: ; in, To incorporate reference crop evapotranspiration Bamboo forest leaf area index Real-time environmental adjustment coefficient; This represents the depth of the main root system activity layer in bamboo forests. per unit area; This is an empirical nonlinear correction coefficient, with a value range of 0.8-1.2; This function is used to limit WDI to a reasonable range.

[0041] This embodiment specifically illustrates the calculation process of the target irrigation amount Q. Continuing from Embodiment 3, it is known... , , The bamboo forest is in the bamboo shoot development stage, and the leaf area index is [missing information]. Reference crop evapotranspiration calculated based on the meteorological data of the day: The environmental regulation coefficient can be obtained by referring to the table. The main root layer depth of bamboo forests unit area (1 hectare), with the nonlinear coefficient k taken as 1.1.

[0042] Substitute into the formula: ; First calculate Since 0.316 < 1, therefore .

[0043] but: ; Therefore, intelligent decision-making models ( Figure 1 The target irrigation amount per hectare was determined to be approximately 113 cubic meters.

[0044] Example 6 Furthermore, the formula for calculating the target fertilizer mother liquor injection volume M in step S3 is as follows: ; in, In order to match the current phenological period The bound global fertilizer intensity coefficient; This refers to the mass concentration of total available nutrients in the fertilizer stock solution prepared this time. This is a correction coefficient for the average nutrient utilization rate of the pre-set irrigation and fertilization system.

[0045] This embodiment specifically illustrates the calculation process for the injection volume M of the target fertilizer mother liquor. Continuing from embodiments 4 and 5, it is known... Current phenological period (Germination stage) fertilizer intensity coefficient The planned total nutrient concentration of the mother liquor. Based on historical system calibration data, a correction factor for average nutrient utilization rate is set. .

[0046] Substitute into the formula: ; Calculations show that approximately 9.9 liters of prepared fertilizer stock solution are needed per hectare for this operation. This M value, along with the Q value, is derived from... Figure 1 The "intelligent decision-making model" is output and sent to the execution system.

[0047] Example 7 Furthermore, the specific proportion of the fertilizer mother liquor is dynamically determined based on the calculation process of the comprehensive nutrient requirement index (FNI), wherein the relative concentration ratio of the i-th nutrient in the mother liquor is... satisfy: ; That is, the fertilizer formula is proportional to the real-time deficiency of each nutrient in the soil and the phenological conditions.

[0048] This embodiment specifically illustrates the process of determining the dynamic ratio of fertilizer mother liquor. Based on the FNI calculation process in Example 4, the contributions of each nutrient are known: Nitrogen (N): ; Phosphorus (P): ; Potassium (K): ; total .

[0049] Substitute into the formula to calculate the relative concentration ratio of each nutrient in the mother liquor. : ; ; ; Therefore, the system instructs the fertilizer stock solution preparation equipment to prepare the special fertilizer stock solution according to a nitrogen source fertilizer: potassium source fertilizer ratio of approximately 2:1 (effective ingredient ratio), achieving precise fertilizer formulation by "supplementing what is lacking and preparing only the amount needed." This formulation logic is... Figure 1 The key parameters are determined synchronously when the "intelligent decision-making model" outputs the M value.

[0050] Example 8 Furthermore, the specific implementation of the spatial variableization operation in step S4 is as follows: the bamboo forest plot is divided into multiple independent irrigation zones corresponding to monitoring points; the central controller independently calculates the irrigation data for each zone based on the data from the monitoring points within that zone. and This determines the partition. and By controlling the electric valves and variable frequency fertilizer injection pumps on the branch pipes of each zone, each zone can receive a precise supply of different amounts of water and fertilizer within a unified operating time.

[0051] This embodiment details the implementation method of spatial variableization operations. (See reference...) Figure 3 A schematic diagram of a variable drip irrigation fertilization system. The 10-hectare bamboo forest in Example 1 was divided into 8 independent irrigation zones based on the distribution of 40 monitoring points and the terrain (e.g., ...). Figure 3 (As shown in the different grid regions). After calculating the global Q and M, the central controller further processes the data for each partition.

[0052] For example, in the southern slope zone (zone 3) where there is more sunlight, the local average moisture content is... Calculated , Based on this, the partition's... , As for the shaded north-facing slope section (section 6), its , , Calculated , When doing homework, such as Figure 3As shown, the central controller simultaneously opens the main pipeline valve and all zone branch pipe valves, but controls the flow rate of each zone by adjusting the opening of the electric valves on each zone branch pipe, thereby achieving variable operation where zone 3 receives more water and fertilizer, while zone 6 receives less water and fertilizer. The fertilizer injection pump operates according to the global mother liquor concentration and total injection volume, but due to the different irrigation water volumes in each zone, the actual total amount of nutrients obtained also changes precisely.

[0053] Example 9 This embodiment provides a smart drip irrigation system for bamboo forests that integrates water and fertilizer to implement the above method, including: Sensing layer: Composed of multiple soil multi-parameter sensor nodes deployed within the bamboo forest plot, used to detect soil moisture content and nutrient content; Transport layer: Consists of IoT gateways and communication networks, used to upload data from the sensing layer; Decision layer: This includes a central controller and intelligent decision model software stored therein, which is used to execute the above calculation and decision steps and generate control commands; The execution layer includes a water source, filtration device, fertilizer mother liquor preparation and storage device, fertilizer injection pump, main pipeline, zone branch pipe, zone electric valve and drip irrigation tape / pipe; the fertilizer injection pump and zone electric valve are controlled by the control commands of the decision layer.

[0054] Specifically, this embodiment demonstrates an intelligent drip irrigation system for bamboo forests that integrates water and fertilizer management to implement the above-described method. (Reference) Figure 3 The system includes: Sensing layer: This refers to multiple soil multi-parameter sensor nodes deployed within the bamboo forest area (such as...). Figure 3 (Dispersed sensor icons) to detect soil moisture content and N, P, K content in real time.

[0055] Transport layer: including IoT gateways ( Figure 3 The equipment in the central control room and the LoRa / 4G communication network are responsible for data transmission.

[0056] Decision-making level: i.e. Figure 3 The central controller in the control room and the intelligent decision-making model software running within it execute all calculation and decision-making steps.

[0057] The execution layer includes the water source, sand and gravel filter, fertilizer mother liquor preparation tank, fertilizer injection pump, main pipeline, 8 zoned branch pipes, electric valves on each branch pipe, and drip irrigation tape laid under the bamboo forest. Control commands generated by the central controller drive the fertilizer injection pump and each electric valve to work together.

[0058] The system fully realizes automated closed-loop control from data perception to variable execution.

[0059] Example 10 This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, can perform the steps of the method described above.

[0060] This embodiment relates to a computer-readable storage medium. The storage medium (such as an SSD solid-state drive) stores a computer program. When the storage medium is installed in the central controller (or cloud server) of the system described in Embodiment 9, and the program is executed by its processor, the processor can operate according to the steps described in Embodiments 1 to 8: reading sensor data, calculating WDI and FNI, dynamically deciding Q and M based on phenological parameters, generating zonal control instructions, and driving the actuators. This program code implements all the method logic defined in claims 1-8 and is a concrete manifestation of the technical solution of this invention at the software level.

[0061] Example 11 After simulation, such as Figure 4 As shown, the six sub-diagrams systematically demonstrate the multi-dimensional advantages of the bamboo forest integrated water and fertilizer drip irrigation fertilization method of the present invention compared with the traditional management model.

[0062] Sub-figure A is a radar chart comparing comprehensive performance, comparing six indicators: water resource utilization rate, fertilizer utilization rate, bamboo forest yield, quality index, labor cost, and environmental pollution risk. The results show that the method of this invention is significantly superior to the traditional method in all indicators, especially in terms of resource utilization rate and environmental friendliness.

[0063] Subgraph B illustrates the changing trend of monthly management costs. The method of this invention, through automated decision-making and precise execution, significantly reduces annual labor and water / fertilizer input costs, achieving a total annual cost saving rate of approximately 40%, demonstrating significant economic benefits.

[0064] Subgraph C compares resource consumption from five aspects: water resources, nitrogen, phosphorus, and potassium fertilizers, and labor. The method of this invention, through on-demand supply and variable fertilization, achieves water savings of approximately 40%, fertilizer savings of approximately 30-40%, and a reduction in labor input of approximately 70%, highlighting its resource-saving characteristics.

[0065] Subgraph D focuses on the effects of zoning management, demonstrating the invention's ability to address spatial heterogeneity. Through precise zoning control, not only was the yield of each zoning increased, but the overall uniformity and productivity of the forest stand were also significantly improved.

[0066] Sub-figure E further refines the comparison of water and fertilizer utilization rates. This invention achieves a significant improvement in the utilization rates of water and various nutrients, with an average improvement rate of over 80%, confirming its core advantages of "soil testing and formula formulation, precise supply".

[0067] Sub-figure F summarizes the key indicators in tabular form, clearly presenting the comprehensive benefits of this invention in terms of improving efficiency, reducing costs, reducing pollution, and enhancing automation and scientific rigor.

[0068] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for integrated water and fertilizer drip irrigation in bamboo forests based on soil testing, characterized in that, Includes the following steps: S1. Data collection: Multiple soil information monitoring points are set up in the bamboo forest plot according to a preset grid, and the soil volume moisture content θ and the content of various key soil nutrients at each monitoring point are regularly detected and obtained. S2. Demand Index Calculation: Based on the real-time data obtained in step S1, calculate the Water Deficiency Index (WDI), which represents the overall water status of the bamboo forest plot, and the Comprehensive Nutrient Demand Index (FNI), which represents the degree of comprehensive demand for multiple nutrients. S3. Dynamic Decision-Making: Based on the WDI and FNI calculated in step S2, and combined with the current phenological stage of the bamboo forest and the preset growth cycle-demand model, the target irrigation amount Q and the target fertilizer mother liquor injection amount M for this operation are determined by the intelligent decision-making model. S4. Variable execution: Based on the total amount determined in step S3, combined with the spatial differences of each monitoring point, generate zoning control instructions to drive the integrated water and fertilizer drip irrigation system to perform spatially variable irrigation and fertilization operations.

2. The method according to claim 1, characterized in that, The key soil nutrients mentioned in step S1 include at least available nitrogen, available phosphorus, and available potassium; the data collection cycle is once every 1-6 hours, and the data is transmitted to the central controller via the Internet of Things.

3. The method according to claim 1, characterized in that, The formula for calculating the Water Deficiency Index (WDI) in step S2 is as follows: ; in, The field water holding capacity of the bamboo forest soil. The wilting coefficient of the bamboo forest soil. This is the area-weighted average of soil moisture content at all currently valid monitoring points.

4. The method according to claim 3, characterized in that, The formula for calculating the Comprehensive Nutrient Demand Index (FNI) in step S2 is as follows: ; in, The types and quantities of key nutrients; For the first The current average soil content of key nutrients; In order to match the current bamboo forest phenology The corresponding number The optimal soil content threshold for nutrients; For the first The weighting factors of nutrients in the current phenological stage, and The The function ensures that only when Only then will the nutrient generate a positive contribution to demand.

5. The method according to claim 4, characterized in that, The target irrigation amount mentioned in step S3 The calculation formula is: ; in, To incorporate reference crop evapotranspiration Bamboo forest leaf area index Real-time environmental adjustment coefficient; This represents the depth of the main root system activity layer in bamboo forests. per unit area; This is an empirical nonlinear correction coefficient, with a value range of 0.8-1.2; This function is used to limit WDI to a reasonable range.

6. The method according to claim 5, characterized in that, The formula for calculating the target fertilizer mother liquor injection volume M in step S3 is as follows: ; in, In order to match the current phenological period The bound global fertilizer intensity coefficient; This refers to the mass concentration of total available nutrients in the fertilizer stock solution prepared this time. This is a correction coefficient for the average nutrient utilization rate of the pre-set irrigation and fertilization system.

7. The method according to claim 6, characterized in that, The specific proportions of the fertilizer mother liquor are dynamically determined based on the calculation process of the comprehensive nutrient requirement index (FNI), wherein the first... Relative concentration ratio of seed nutrients in mother liquor satisfy: ; That is, the fertilizer formula is proportional to the real-time deficiency of each nutrient in the soil and the phenological conditions.

8. The method according to claim 1, characterized in that, The specific implementation of the spatial variableization operation in step S4 is as follows: the bamboo forest plot is divided into multiple independent irrigation zones corresponding to monitoring points; the central controller independently calculates the irrigation data of each zone based on the data from the monitoring points within that zone. and This determines the partition. and By controlling the electric valves and variable frequency fertilizer pumps on the branch pipes of each zone, each zone can receive a precise supply of different amounts of water and fertilizer within a unified operating time.

9. A smart drip irrigation system for bamboo forests integrating water and fertilizer for implementing the method of any one of claims 1-8, characterized in that, include: Sensing layer: Composed of multiple soil multi-parameter sensor nodes deployed within the bamboo forest plot, used to detect soil moisture content and nutrient content; Transport layer: Consists of IoT gateways and communication networks, used to upload data from the sensing layer; Decision layer: includes a central controller and intelligent decision model software stored therein, used to execute the calculation and decision steps described in claims 1-8 and generate control commands; The execution layer includes a water source, filtration device, fertilizer mother liquor preparation and storage device, fertilizer injection pump, main pipeline, zone branch pipe, zone electric valve and drip irrigation tape / pipe; the fertilizer injection pump and zone electric valve are controlled by the control commands of the decision layer.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it can implement the steps of the method as described in any one of claims 1-8.

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