A fertilization water management control method and system for mulberry tree planting

Abstract

The present invention relates to the technical field of mulberry tree planting, and particularly relates to a fertilization and water management control method and system for mulberry tree planting. The method includes the following steps: collecting multi-source data of the mulberry tree planting area and performing spatio-temporal alignment preprocessing to obtain spatio-temporal alignment preprocessed data; extracting a regional soil data layer according to the spatio-temporal alignment preprocessed data to obtain a regional soil data layer; constructing a multi-source data layer according to the regional soil data layer and the spatio-temporal alignment preprocessed data to obtain a multi-source data layer; constructing a soil-mulberry tree system model according to the multi-source data layer and constructing a spatio-temporal dynamic database to obtain a spatio-temporal dynamic soil-mulberry tree system database. The present invention constructs a soil-mulberry tree system model and a spatio-temporal dynamic database, and combines the management zoning technology to realize digital and model-driven precise fertilization and water management, and achieve the goals of efficient utilization of water and fertilizer resources and water saving and yield increase.

Description

Technical Field

[0001] The present invention relates to the technical field of mulberry tree planting, and particularly to a fertilization and water management control method and system for mulberry tree planting. Background Art

[0002] In modern mulberry leaf production, fertilization and water management are key factors affecting the yield and quality of mulberry trees. Reasonable fertilization and water management can not only improve fertilizer utilization efficiency, save water and increase production, but also reduce non-point source pollution and achieve sustainable development of mulberry leaves. However, the traditional fertilization and water management control method for mulberry tree planting has problems such as extensive fertilization and water management methods and lack of precise management, which restricts the further development of mulberry leaf production. Traditional fertilization and water management mainly rely on the experience of planters, making artificial decisions based on the growth of mulberry trees and weather conditions. The fertilization and water management method for mulberry tree planting is extensive and lacks precise management. This method lacks scientific guidance, and it is difficult to accurately control the amount of fertilization and water use, easily causing excessive fertilization and irrigation, resulting in fertilizer loss and water resource waste, and it is difficult to meet the requirements of modern mulberry trees for efficient utilization of water and fertilizer resources and water saving and production increase.

[0003] Embodiment of the problem of extensive traditional fertilization and water management method: Traditional fertilization and water management rely too much on experience, lack scientific guidance, and have strong subjectivity in fertilization decision-making. Key factors such as soil characteristics, mulberry tree requirements, and environmental conditions are ignored, resulting in improper fertilization and excessive water use, causing loss of fertilizer nutrients and waste of water resources, not only increasing the planting cost, but also easily causing non-point source pollution and affecting the sustainable development of mulberry leaf production.

[0004] Embodiment of the problem of lack of precise management: Traditional management regards the mulberry tree planting farmland as a homogeneous whole, and "one-size-fits-all" fertilization and irrigation are carried out without considering the spatial variability of soil fertility and mulberry tree growth in the field. Mulberry trees in different regions are difficult to obtain the best water and fertilizer conditions, affecting the yield and quality and increasing resource consumption. Summary of the Invention

[0005] Based on this, it is necessary to provide a fertilization and water management control method and system for mulberry tree planting to solve at least one of the above technical problems.

[0006] To achieve the above object, a fertilization and water management control method for mulberry tree planting includes the following steps:

[0007] Step S1: Collect multi-source data for the mulberry tree planting area and perform spatio-temporal alignment preprocessing to obtain spatio-temporally aligned preprocessed data; extract the regional soil data layer based on the spatio-temporally aligned preprocessed data to obtain the regional soil data layer; construct a multi-source data layer based on the regional soil data layer and the spatio-temporally aligned preprocessed data to obtain the multi-source data layer; construct a soil-mulberry tree system model based on the multi-source data layer to obtain the soil-mulberry tree system model; construct a spatio-temporal dynamic database based on the soil-mulberry tree system model to obtain the spatio-temporal dynamic soil-mulberry tree system database;

[0008] Step S2: Predict the growth of mulberry trees based on the spatio-temporal dynamic soil-mulberry tree system database to obtain mulberry tree growth prediction data; input the mulberry tree growth prediction data into the soil-mulberry tree system model to perform soil-mulberry tree system simulation and obtain soil-mulberry tree system dynamic change data; generate a mulberry tree growth prediction map based on the soil-mulberry tree system dynamic change data to obtain the mulberry tree growth prediction map;

[0009] Step S3: Extract the target field data from the spatio-temporal dynamic soil-mulberry tree system database and perform management partition division to obtain the management partition coding map; obtain the precise fertilization and water management target data; generate and visualize the precise fertilization and water management map based on the precise fertilization and water management target data and the management partition coding map to obtain the precise fertilization and water management map;

[0010] Step S4: Obtain the real-time planting area data; predict the real-time mulberry tree coefficient based on the real-time planting area data and the mulberry tree growth prediction map to obtain the real-time mulberry tree coefficient data; calculate the actual water requirement of mulberry trees based on the real-time mulberry tree coefficient data to obtain the actual water requirement of mulberry trees; generate a fertilization and water irrigation plan based on the actual water requirement of mulberry trees and the spatio-temporal dynamic soil-mulberry tree system database to obtain the fertilization and water irrigation plan;

[0011] Step S5: Perform fertilization and water management association processing and perform scheme adaptive adjustment based on the fertilization and water irrigation plan and the precise fertilization and water management map to achieve fertilization and water management control operations.

[0012] Through multi-source data collection, spatio-temporal alignment preprocessing, regional soil data layer extraction, multi-source data layer construction, and spatio-temporal dynamic soil-mulberry system database construction, the present invention realizes the integration and association of multi-source heterogeneous data in the mulberry planting area, constructs a spatio-temporal dynamic database integrating information such as soil, mulberry, environment, irrigation, etc., and provides a solid data foundation for precise fertilization and water management. By analyzing the spatio-temporal dynamic soil-mulberry system database, combining with the mulberry growth model and future meteorological scenario data, the present invention realizes the mastery of the mulberry growth trend and the prediction of the future growth status, and generates a visual mulberry growth prediction map, providing a scientific prediction basis for precise fertilization and water management. According to the goal of precise fertilization and water management, combining the soil spatial heterogeneity of the target field, the mulberry growth prediction map, and the irrigation facility layout and other information, through a multi-objective optimization algorithm, a precise fertilization and water management plan that takes into account multiple objectives is formulated, and a visual precise fertilization and water management map is generated, providing an intuitive guidance for field operations. According to the real-time collected data in the planting area, including meteorology, micrometeorology, and mulberry physiological indicators, etc., combining with the mulberry growth prediction map and soil moisture information, the water requirement of the mulberry is predicted in real time, and a detailed fertilization and water irrigation plan is generated accordingly, realizing the automation and intelligence of irrigation decision-making. By combining the precise fertilization and water management plan with the irrigation equipment control, the implementation of the precise irrigation plan is realized, and according to the evaluation result of the irrigation effect, the plan is adaptively adjusted, forming a closed-loop control system for precise fertilization and water management, realizing the efficient utilization of water and fertilizer resources and the high and stable yield of mulberry. Therefore, the present invention provides a method for solving the problems of extensive fertilization and water management methods and lack of precise management existing in the traditional fertilization and water management control methods for mulberry planting. By constructing a soil-mulberry system model and a spatio-temporal dynamic database, and combining with the management zoning technology, the present invention realizes digital and model-driven precise fertilization and water management, solves the problems of extensive fertilization and water management methods and lack of precise management in the traditional methods, and thus realizes the goals of efficient utilization of water and fertilizer resources and water saving and yield increase.

[0013] Preferably, step S1 includes the following steps:

[0014] Step S11: Collect multi-source data for the mulberry planting area to obtain the original data of the planting area; perform spatio-temporal alignment preprocessing on the original data of the planting area to obtain spatio-temporal alignment preprocessed data, where the spatio-temporal alignment preprocessed data includes regional meteorological station data, soil sample data, mulberry growth data, and irrigation facility data;

[0015] Step S12: Perform environmental data interpolation on the regional meteorological station data to obtain a regional environmental data layer; extract a regional soil data layer according to the soil sample data and the regional environmental data layer to obtain a regional soil data layer;

[0016] Step S13: Construct a multi-source data layer from the regional soil data layer, regional environmental data layer, mulberry growth data, and irrigation facility data to obtain a multi-source data layer;

[0017] Step S14: Use the multi-source data layer to calibrate the parameters of a preset mulberry growth model to obtain a mulberry growth simulation model; simulate the mulberry growth process at the farmland plot scale according to the mulberry growth simulation model and output the spatio-temporal dynamic data of mulberry growth indicators to obtain mulberry growth simulation data and mulberry growth indicator data;

[0018] Step S15: Construct a soil-mulberry system model based on the mulberry growth indicator data, regional soil data layer, and regional environmental data layer to obtain a soil-mulberry system model;

[0019] Step S16: Construct a spatio-temporal dynamic database based on the soil-mulberry system model, mulberry growth simulation data, and multi-source data layer to obtain a spatio-temporal dynamic soil-mulberry system database.

[0020] Through multi-source data collection in the mulberry planting area and spatio-temporal alignment preprocessing, the present invention can break information islands, integrate data scattered from different sources and in different formats into a unified spatio-temporal framework, and provide a high-quality and consistent data basis for subsequent analysis and modeling. Through environmental data interpolation and soil property spatial prediction, discrete meteorological station data and soil sample data can be converted into continuous spatial data layers, visually showing the spatial distribution characteristics of regional environmental factors and soil properties, and providing a spatial decision-making basis for precise fertilization and water management. Integrating the regional soil data layer, regional environmental data layer, mulberry growth data, and irrigation facility data to construct a multi-source data layer realizes the fusion and association of multi-source information and provides data support for constructing a more accurate and comprehensive soil-mulberry system model. Using the multi-source data layer to calibrate the parameters of a preset mulberry growth model can improve the simulation accuracy of the model under specific regional and environmental conditions, and through model simulation, the mulberry growth dynamics can be predicted, providing a reference for subsequent precise management. Constructing a soil-mulberry system model based on the mulberry growth indicator data, regional soil data layer, and regional environmental data layer can simulate the interaction relationship between mulberry growth and the soil environment, such as the transport and transformation processes of water and nutrients, and the absorption and utilization processes of water and nutrients by mulberries, etc., providing a scientific basis for precise fertilization and water management. Constructing a spatio-temporal dynamic database based on the soil-mulberry system model, mulberry growth simulation data, and multi-source data layer can realize the dynamic monitoring and management of multi-faceted information such as soil, mulberries, environment, and irrigation in the mulberry planting area, provide data support and decision-making basis for precise fertilization and water management, and ultimately achieve the goals of efficient utilization of water and fertilizer resources and water-saving and yield increase.

[0021] Preferably, step S12 includes the following steps:

[0022] Step S121: Extract environmental factor data from the regional environmental data layer according to the soil sample data to obtain a soil sample environmental factor table;

[0023] Step S122: Conduct an association analysis of environmental factors and soil properties on the soil sample environmental factor table and the soil sample data to obtain association data of environmental factors and soil properties;

[0024] Step S123: Construct a soil property spatial prediction model based on the association between environmental factors and soil properties to obtain a soil property spatial prediction model;

[0025] Step S124: Use the soil property spatial prediction model to conduct a spatial prediction of the soil properties in the mulberry tree planting area to obtain a regional soil data layer.

[0026] In the present invention, by associating the soil sample data with the regional environmental data layer, extracting the environmental factor data corresponding to each soil sample point, and constructing a soil sample environmental factor table, a data basis is provided for analyzing the influence of environmental factors on soil properties. Through statistical analysis of the soil sample environmental factor table, such as correlation analysis, regression analysis, etc., the internal relationship between environmental factors and soil properties can be revealed, such as which environmental factors have a significant impact on soil properties such as soil organic matter content and soil texture, providing a theoretical basis for constructing a soil property spatial prediction model. According to the association relationship between environmental factors and soil properties, a suitable model, such as a multiple linear regression model, a random forest model, a neural network model, etc., is selected, with environmental factors as independent variables and soil properties as dependent variables, to construct a soil property spatial prediction model, thereby achieving the goal of predicting the spatial distribution of soil properties using environmental factor data. Using the constructed soil property spatial prediction model and the regional environmental data layer, the spatial prediction of soil properties in the entire mulberry tree planting area can be carried out to obtain a high-precision regional soil data layer, such as a soil organic matter content layer, a soil texture layer, a soil pH value layer, etc., providing detailed spatial decision-making information for precise fertilization and water management.

[0027] Preferably, step S2 includes the following steps:

[0028] Step S21: Extract key feature data from the spatio-temporal dynamic soil-mulberry tree system database to obtain key feature data; conduct an analysis of the growth trend of mulberry trees based on the key feature data to obtain mulberry tree growth trend data;

[0029] Step S22: Obtain the mulberry tree growth prediction target data; construct a mulberry tree growth prediction model based on the key feature data and the mulberry tree growth prediction target data to obtain a mulberry tree growth prediction model;

[0030] Step S23: Perform mulberry tree growth prediction on the mulberry tree growth prediction model and the preset future meteorological scenario data to obtain mulberry tree growth prediction data;

[0031] Step S24: Input the mulberry tree growth prediction data into the soil-mulberry tree system model for soil-mulberry tree system simulation to obtain soil-mulberry tree system dynamic change data;

[0032] Step S25: Perform growth limiting factor analysis on the soil-mulberry tree system dynamic change data according to the preset growth index threshold to obtain growth limiting factors;

[0033] Step S26: Perform fertilization and water management analysis based on the growth limiting factors to obtain a fertilization and water management analysis report; generate a mulberry tree growth prediction map based on the mulberry tree growth prediction data in the fertilization and water management analysis report to obtain a mulberry tree growth prediction map.

[0034] Through extracting key feature data from the spatio-temporal dynamic soil-mulberry tree system database and performing growth trend analysis, the present invention can reveal the laws of mulberry tree growth changing over time, such as the biomass accumulation rate, water consumption law, etc., providing a reference basis for predicting the future growth status of mulberry trees. According to the mulberry tree growth prediction objectives, such as predicting yield, quality, etc., a mulberry tree growth prediction model can be constructed by using machine learning algorithms in combination with key feature data and mulberry tree growth prediction target data, realizing the quantitative prediction of the future growth status of mulberry trees and providing a target orientation for precise fertilization and water management. Inputting the preset future meteorological scenario data into the constructed mulberry tree growth prediction model can predict the growth status of mulberry trees in the future for a period of time, such as yield, biomass, water consumption, etc., providing a basis for formulating a precise fertilization and water management plan in advance. Inputting the mulberry tree growth prediction data into the soil-mulberry tree system model for simulation can more comprehensively consider the interactions among the soil, mulberry tree, and environment, predicting the dynamic change process of the soil-mulberry tree system in the future for a period of time, such as the dynamic changes of soil moisture and nutrients, providing more refined reference information for precise fertilization and water management. According to the preset key threshold values of mulberry tree growth indicators, such as soil moisture content, nutrient content, etc., analyzing the simulated soil-mulberry tree system dynamic change data can timely discover the limiting factors occurring in the mulberry tree growth process, such as water stress, nutrient deficiency, etc., providing early warning information for precise fertilization and water management. According to the identified growth limiting factors of mulberry trees and combining the best management measures for fertilization and irrigation, a precise fertilization and water management plan can be formulated, and through the visual mulberry tree growth prediction map, information such as prediction results, key threshold values, fertilization and water management suggestions, etc. can be intuitively displayed, providing decision-making support that is easy to understand and operate.

[0035] Preferably, step S3 includes the following steps:

[0036] Step S31: Extract the target field data from the spatio-temporal dynamic soil-mulberry system database to obtain the target field data, where the target field data includes soil spatial heterogeneity data and irrigation facility layout data;

[0037] Step S32: Divide the management zones according to the soil spatial heterogeneity data to obtain the management zone coding map;

[0038] Step S33: Obtain the target data for precision fertilization and water management; construct a multi-objective function based on the target data for precision fertilization and water management to obtain the multi-objective function;

[0039] Step S34: Set the constraint conditions according to the irrigation facility layout data and the mulberry growth prediction map to obtain the fertilization and water management constraint condition data;

[0040] Step S35: Perform multi-objective solution of the fertilization and water management plan for the management zone coding map according to the fertilization and water management constraint condition data and the multi-objective function to obtain the fertilization and water management plan;

[0041] Step S36: Input the fertilization and water management plan into the soil-mulberry system model for plan simulation evaluation to obtain the plan simulation evaluation data;

[0042] Step S37: Set the target weights according to the multi-objective function to obtain the multi-objective function weight data; perform plan comparison weight analysis on the plan simulation evaluation data according to the multi-objective function weight data to obtain the plan comparison weight analysis data;

[0043] Step S38: Generate and visualize the precision fertilization and water management map according to the plan comparison weight analysis data and the plan simulation evaluation data to obtain the precision fertilization and water management map.

[0044] The present invention extracts data of a target field from a spatio-temporal dynamic soil-mulberry system database, including soil spatial heterogeneity data and irrigation facility layout data, which can provide detailed information on the target area for precise fertilization and water management and lay a foundation for formulating targeted solutions. According to the soil spatial heterogeneity data, the target field is divided into several management sub-areas with similar soil properties and mulberry growth trends, and a management sub-area coding map is generated, which can achieve refined management of the field and improve the utilization efficiency of water and fertilizer resources. According to actual requirements, such as maximizing yield, minimizing water and fertilizer resource consumption, minimizing environmental pollution, etc., the objectives of precise fertilization and water management are determined, and a multi-objective function is constructed, which can transform the actual problem into a mathematical model and provide a solution target for the multi-objective optimization algorithm. According to the irrigation facility layout data and the mulberry growth prediction map, the constraint conditions for fertilization and water management are set, such as the maximum irrigation amount and the maximum fertilization amount for each management sub-area, which can ensure the practical operability of the solution. Using a multi-objective optimization algorithm, such as a genetic algorithm, a particle swarm algorithm, etc., the management sub-area coding map is solved multi-objectively under the condition of meeting the constraint conditions, and the optimal fertilization and water management solution can be found to achieve the coordinated optimization of multiple objectives. The obtained optimal fertilization and water management solution is input into the soil-mulberry system model for simulation evaluation, which can predict the impacts on mulberry growth, yield, water and fertilizer utilization efficiency, etc. after the implementation of the solution and provide a basis for solution optimization. According to the weights of each objective in the multi-objective function, the simulation evaluation results of different solutions are compared and analyzed, which can quantify the advantages and disadvantages of different solutions and provide decision-making support for the selection of the final solution. According to the results of the solution comparison weight analysis and the solution simulation evaluation data, a precise fertilization and water management map is generated, and the solution information is visually displayed, which can intuitively guide field operations and facilitate understanding and implementation.

[0045] Preferably, step S32 includes the following steps:

[0046] Step S321: Perform data standardization processing on the soil spatial heterogeneity data to obtain standardized soil spatial heterogeneity data; perform soil attribute clustering analysis according to the standardized soil spatial heterogeneity data to obtain a soil management sub-area map;

[0047] Step S322: Perform filtering on the mulberry growth trend data of the mulberry growth prediction map to obtain filtered mulberry growth trend data; perform threshold segmentation on the filtered mulberry growth trend data according to a preset mulberry growth trend threshold to obtain a mulberry growth trend level map;

[0048] Step S323: Perform fusion of the partition results of the soil management sub-area map and the mulberry growth trend level map to obtain a fused management sub-area map; perform optimization of the partition boundary of the fused management sub-area map to obtain an optimized management sub-area map;

[0049] Step S324: Extract the partition attributes from the optimized management partition map, the standardized data of soil spatial heterogeneity, and the filtered data of mulberry tree growth, to obtain the management partition attribute table;

[0050] Step S325: Perform partition coding on the management partition attribute table and the optimized management partition map, to obtain the management partition coding map.

[0051] In the present invention, by standardizing the soil spatial heterogeneity data, the influence of the dimensional differences of different indicators is eliminated, and the target field is divided into several regions with similar soil attributes by using the clustering analysis method, to generate the soil management partition map, providing a basic partition for refined management. The mulberry tree growth prediction map is filtered to eliminate data noise, and threshold segmentation is performed according to the preset mulberry tree growth threshold, to divide the target field into regions with different mulberry tree growth levels, generating the mulberry tree growth level map, providing information on the growth status of mulberry trees for partition fusion. The soil management partition map and the mulberry tree growth level map are fused to generate the management partition fusion map, comprehensively considering the spatial variations of soil attributes and mulberry tree growth, and through boundary optimization, eliminating small and irregular partition boundaries, obtaining a more reasonable optimized management partition map, improving the accuracy and practicability of the partition result. According to the optimized management partition map, the soil attributes and mulberry tree growth information of each management partition are extracted to construct the management partition attribute table, providing detailed information for each partition for subsequent precise fertilization and water management. A unique code is assigned to each management partition and marked on the optimized management partition map to generate the management partition coding map, providing an intuitive reference for subsequent plan formulation and implementation.

[0052] Preferably, step S44 includes the following steps:

[0053] Step S41: Obtain the real-time planting area data; perform real-time mulberry tree coefficient prediction based on the real-time planting area data and the mulberry tree growth prediction map, to obtain the real-time mulberry tree coefficient data; calculate the actual water requirement of the mulberry tree according to the real-time mulberry tree coefficient data, to obtain the actual water requirement of the mulberry tree;

[0054] Step S42: Make a decision on the fertilization and irrigation amount based on the actual water requirement of the mulberry tree and the spatio-temporal dynamic soil-mulberry tree system database, to obtain the fertilization and irrigation amount data;

[0055] Step S43: Make a decision on the irrigation time based on the real-time planting area data, the mulberry tree growth prediction map, and the irrigation facility data in the spatio-temporal alignment preprocessing data, to obtain the irrigation time data;

[0056] Step S44: Generate a fertilization and irrigation plan based on the irrigation time data, the fertilization and irrigation amount data, and the irrigation facility data in the spatio-temporal alignment preprocessing data, to obtain the fertilization and irrigation plan.

[0057] The present invention can more accurately reflect the actual water requirement of mulberry trees under current environmental conditions by obtaining real-time planting area data and combining it with the mulberry tree growth prediction map, thereby providing a more reliable basis for precise irrigation. According to the actual water requirement of mulberry trees and combining with the soil moisture information, mulberry tree root distribution information, etc. stored in the spatio-temporal dynamic soil-mulberry tree system database, a more reasonable irrigation amount can be formulated to avoid over-irrigation or under-irrigation and improve the water resource utilization efficiency. According to the real-time planting area data, mulberry tree growth prediction map and irrigation facility data, a suitable irrigation time can be selected, such as avoiding the rainfall period and choosing the period when the mulberry tree has the largest water requirement, etc., which can improve the irrigation efficiency and reduce water resource waste. According to the irrigation time, fertilized water irrigation amount and irrigation facility data, a detailed fertilized water irrigation plan can be generated to guide the field operators to carry out precise irrigation and ensure the smooth implementation of the irrigation plan.

[0058] Preferably, step S411 includes the following steps:

[0059] Step S411: Obtain real-time planting area data; wherein the real-time planting area data includes real-time weather station data, real-time field micro-meteorological monitoring data, and real-time mulberry tree physiological index sets;

[0060] Step S412: Use the Penman formula and real-time weather station data to calculate the initial reference transpiration amount to obtain the initial reference mulberry tree water transpiration amount data;

[0061] Step S413: Calculate the environmental correction coefficient according to the real-time field micro-meteorological monitoring data and real-time weather station data to obtain the environmental correction coefficient data;

[0062] Step S414: Construct a mulberry tree coefficient prediction model according to the environmental correction coefficient data, real-time mulberry tree physiological index sets, and mulberry tree growth prediction map to obtain the mulberry tree coefficient prediction model; predict the real-time mulberry tree coefficient according to the mulberry tree coefficient prediction model to obtain the real-time mulberry tree coefficient data;

[0063] Step S415: Calculate the actual transpiration amount of the mulberry tree according to the real-time mulberry tree coefficient data, environmental correction coefficient data, and initial reference mulberry tree water transpiration amount data to obtain the actual transpiration amount of the mulberry tree;

[0064] Step S416: Calculate the effective rainfall amount using the soil water balance model according to the real-time rainfall data in the real-time weather station data and the regional soil data layer to obtain the effective rainfall amount data;

[0065] Step S417: Calculate the actual water requirement of the mulberry tree according to the effective rainfall amount data and the actual transpiration amount of the mulberry tree to obtain the actual water requirement of the mulberry tree.

[0066] By obtaining the meteorological data, field micro-meteorological data, and physiological index data of mulberry trees in real time in the planting area, the real-time changes in the growth environment and the tree's own state of mulberry trees can be comprehensively grasped, providing a more timely and accurate data basis for precise irrigation decision-making. Using the Penman formula and real-time weather station data to calculate the initial reference evapotranspiration can quickly estimate the evapotranspiration of reference mulberry trees under standard meteorological conditions, providing a reference benchmark for subsequent calculation of the actual evapotranspiration of mulberry trees. According to the real-time field micro-meteorological monitoring data and real-time weather station data, calculating the environmental correction coefficient can correct the difference between the standard meteorological conditions and the field microclimate, improving the accuracy of reference evapotranspiration estimation. Using the environmental correction coefficient, real-time physiological index data of mulberry trees, and the mulberry tree growth prediction map to construct a mulberry tree coefficient prediction model and conduct real-time prediction can more accurately reflect the difference between the actual evapotranspiration and the reference evapotranspiration of mulberry trees under specific growth stages and environmental conditions, improving the accuracy of calculating the water requirement of mulberry trees. According to the real-time mulberry tree coefficient, environmental correction coefficient, and initial reference evapotranspiration of mulberry trees, calculating the actual evapotranspiration of mulberry trees can accurately estimate the amount of water actually consumed by mulberry trees under the current environmental conditions, providing a direct basis for precise irrigation. According to the real-time rainfall data and the regional soil data layer, using the soil water balance model to calculate the effective rainfall can accurately estimate the rainfall that can actually be utilized by mulberry trees, avoiding over-irrigation and improving water resource utilization efficiency. According to the effective rainfall and the actual evapotranspiration of mulberry trees, calculating the actual water requirement of mulberry trees can accurately determine whether the mulberry trees need irrigation and how much water needs to be irrigated, achieving precise irrigation, avoiding water resource waste, and promoting the healthy growth of mulberry trees.

[0067] Preferably, step S5 includes the following steps:

[0068] Step S51: Perform fertilization and irrigation water management correlation processing according to the fertilization and irrigation water plan and the precise fertilization and irrigation water management map to obtain a precise fertilization and irrigation water management plan;

[0069] Step S52: Perform irrigation equipment control processing according to the precise fertilization and irrigation water management plan to obtain irrigation equipment control data;

[0070] Step S53: Evaluate the irrigation effect according to the irrigation equipment control data to obtain fertilization and irrigation water effect data;

[0071] Step S54: Perform self-adaptive adjustment of the precise fertilization and irrigation water management plan according to the fertilization and irrigation water effect data to achieve fertilization and irrigation water management control operations.

[0072] By associating the fertilized water irrigation plan with the precise fertilized water management map, combining irrigation and fertilization information with specific spatial management units, the present invention generates a precise fertilized water management plan, which can achieve differential management for different regions and different mulberry tree growth conditions, and improve the utilization efficiency of water and fertilizer resources. According to the precise fertilized water management plan, controlling the operation of irrigation equipment, such as the opening and closing of valves, the start and stop of water pumps, etc., can implement the precise management plan in field actual operations and achieve automated and intelligent precise irrigation. According to the irrigation equipment control data, combined with data such as soil moisture and nutrient content monitored by field sensors in real time, evaluating the irrigation effect can timely discover problems existing in the process of plan implementation, such as insufficient irrigation and excessive fertilization, etc., and provide a basis for the adaptive adjustment of the plan. According to the evaluation results of the irrigation effect, adaptively adjusting the precise fertilized water management plan, such as adjusting the irrigation amount and irrigation time according to soil moisture conditions, adjusting the fertilization plan according to the growth trend of mulberry trees, etc., can achieve dynamic optimization, continuously improve the utilization efficiency of water and fertilizer resources, promote the healthy growth of mulberry trees, and improve the yield and quality.

[0073] Preferably, the present invention also provides a fertilized water management control system for mulberry tree planting, which is used to execute the fertilized water management control method for mulberry tree planting as described above. The fertilized water management control system for mulberry tree planting includes:

[0074] A soil and mulberry tree data assimilation module, which is used to collect multi-source data for the mulberry tree planting area and perform spatio-temporal alignment preprocessing to obtain spatio-temporal alignment preprocessed data; extract the regional soil data layer according to the spatio-temporal alignment preprocessed data to obtain the regional soil data layer; construct a multi-source data layer according to the regional soil data layer and the spatio-temporal alignment preprocessed data to obtain the multi-source data layer; construct a soil-mulberry tree system model according to the multi-source data layer to obtain the soil-mulberry tree system model; construct a spatio-temporal dynamic database based on the soil-mulberry tree system model to obtain the spatio-temporal dynamic soil-mulberry tree system database;

[0075] A mulberry tree growth analysis module, which is used to predict the growth of mulberry trees according to the spatio-temporal dynamic soil-mulberry tree system database to obtain mulberry tree growth prediction data; input the mulberry tree growth prediction data into the soil-mulberry tree system model to perform soil-mulberry tree system simulation to obtain soil-mulberry tree system dynamic change data; generate a mulberry tree growth prediction map according to the soil-mulberry tree system dynamic change data to obtain the mulberry tree growth prediction map;

[0076] The fertilization and water zoning management module is used to extract target field data according to the spatio-temporal dynamic soil-mulberry system database and divide the management zones, obtaining the management zone coding map; acquire the precise fertilization and water management target data; generate and visualize the precise fertilization and water management map based on the precise fertilization and water management target data and the management zone coding map, obtaining the precise fertilization and water management map;

[0077] The fertilization and water irrigation analysis module is used to obtain real-time planting area data; predict the real-time mulberry coefficient based on the real-time planting area data and the mulberry growth prediction map, obtaining the real-time mulberry coefficient data; calculate the actual water requirement of the mulberry based on the real-time mulberry coefficient data, obtaining the actual water requirement of the mulberry; generate the fertilization and water irrigation plan based on the actual water requirement of the mulberry and the spatio-temporal dynamic soil-mulberry system database, obtaining the fertilization and water irrigation plan;

[0078] The fertilization and water management control module is used to perform the fertilization and water management association processing and perform the adaptive adjustment of the plan according to the fertilization and water irrigation plan and the precise fertilization and water management map, so as to realize the fertilization and water management control operation.

[0079] Through multi-source data collection, spatio-temporal alignment preprocessing, extraction of regional soil data layers, construction of multi-source data layers, and construction of a spatio-temporal dynamic soil-mulberry system database, the present invention realizes the integration and association of multi-source heterogeneous data in the mulberry planting area, constructs a spatio-temporal dynamic database integrating information such as soil, mulberry, environment, and irrigation, and provides a solid data foundation for precise fertilization and water management. By analyzing the spatio-temporal dynamic soil-mulberry system database, combining with the mulberry growth model and future meteorological scenario data, the growth trend of mulberry is mastered and the future growth status is predicted, and a visualized mulberry growth prediction map is generated, providing a scientific prediction basis for precise fertilization and water management. According to the goal of precise fertilization and water management, combining information such as the soil spatial heterogeneity of the target field, the mulberry growth prediction map, and the irrigation facility layout, through a multi-objective optimization algorithm, a precise fertilization and water management plan that takes into account multiple objectives is formulated, and a visualized precise fertilization and water management map is generated, providing intuitive guidance for field operations. According to the data collected in real time in the planting area, including meteorology, micrometeorology, and mulberry physiological indicators, etc., combining with the mulberry growth prediction map and soil moisture information, the water requirement of mulberry is predicted in real time, and a detailed fertilization and water irrigation plan is generated accordingly, realizing the automation and intelligence of irrigation decision-making. By combining the precise fertilization and water management plan with the control of irrigation equipment, the implementation of the precise irrigation plan is realized, and according to the evaluation result of the irrigation effect, the plan is adaptively adjusted, forming a closed-loop control system for precise fertilization and water management, and realizing the efficient utilization of water and fertilizer resources and the high and stable yield of mulberry. Therefore, the present invention provides a method for solving the problems of extensive fertilization and water management and lack of precise management existing in the traditional fertilization and water management control method for mulberry planting. By constructing a soil-mulberry system model and a spatio-temporal dynamic database, and combining with the management zoning technology, digital and model-driven precise fertilization and water management are realized, solving the problems of extensive fertilization and water management and lack of precise management in the traditional method, and thus realizing the goals of efficient utilization of water and fertilizer resources and water saving and yield increase. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 It is a schematic flow chart of the steps of a fertilization and water management control method for mulberry planting;

[0081] Figure 2 For Figure 1 It is a schematic detailed implementation step flow chart of step S3 in

[0082] Figure 3 For Figure 1 It is a schematic detailed implementation step flow chart of step S4 in

[0083] The realization of the object, functional characteristics and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0084] The technical method of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative work belong to the scope of protection of the present invention.

[0085] In addition, the accompanying drawings are only schematic diagrams of the present invention and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0086] It should be understood that although terms such as "first" and "second" may be used here to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used here includes any and all combinations of one or more of the listed associated items.

[0087] To achieve the above object, please refer to Figures 1 to 3 , a fertilization and water management control method for mulberry tree planting, comprising the following steps:

[0088] Step S1: Collect multi-source data for the mulberry tree planting area and perform spatio-temporal alignment preprocessing to obtain spatio-temporally aligned preprocessed data; extract the regional soil data layer according to the spatio-temporally aligned preprocessed data to obtain the regional soil data layer; construct a multi-source data layer according to the regional soil data layer and the spatio-temporally aligned preprocessed data to obtain the multi-source data layer; construct a soil-mulberry tree system model according to the multi-source data layer to obtain the soil-mulberry tree system model; construct a spatio-temporal dynamic database based on the soil-mulberry tree system model to obtain the spatio-temporal dynamic soil-mulberry tree system database;

[0089] Step S2: Predict the growth of mulberry trees according to the spatio-temporal dynamic soil-mulberry tree system database to obtain mulberry tree growth prediction data; input the mulberry tree growth prediction data into the soil-mulberry tree system model for soil-mulberry tree system simulation to obtain soil-mulberry tree system dynamic change data; generate a mulberry tree growth prediction map according to the soil-mulberry tree system dynamic change data to obtain the mulberry tree growth prediction map;

[0090] Step S3: Extract the target field data according to the spatio-temporal dynamic soil-mulberry system database and conduct management partition division to obtain the management partition coding map; obtain the target data for precise fertilization and water management; generate and visualize the precise fertilization and water management map according to the target data for precise fertilization and water management and the management partition coding map to obtain the precise fertilization and water management map;

[0091] Step S4: Obtain the real-time planting area data; predict the real-time mulberry coefficient according to the real-time planting area data and the mulberry growth prediction map to obtain the real-time mulberry coefficient data; calculate the actual water requirement of the mulberry according to the real-time mulberry coefficient data to obtain the actual water requirement of the mulberry; generate the fertilization and water irrigation plan according to the actual water requirement of the mulberry and the spatio-temporal dynamic soil-mulberry system database to obtain the fertilization and water irrigation plan;

[0092] Step S5: Conduct association processing of fertilization and water management according to the fertilization and water irrigation plan and the precise fertilization and water management map and perform adaptive adjustment of the plan to achieve the control operation of fertilization and water management.

[0093] In the embodiment of the present invention, with reference to Figure 1 As described, it is a schematic diagram of the step flow of the fertilization and water management control method for mulberry planting of the present invention. In this example, the fertilization and water management control method for mulberry planting includes the following steps:

[0094] Step S1: Collect multi-source data for the mulberry planting area and conduct spatio-temporal alignment preprocessing to obtain spatio-temporal alignment preprocessing data; extract the regional soil data layer according to the spatio-temporal alignment preprocessing data to obtain the regional soil data layer; construct a multi-source data layer according to the regional soil data layer and the spatio-temporal alignment preprocessing data to obtain the multi-source data layer; construct a soil-mulberry system model according to the multi-source data layer to obtain the soil-mulberry system model; construct a spatio-temporal dynamic database based on the soil-mulberry system model to obtain the spatio-temporal dynamic soil-mulberry system database;

[0095] In the embodiments of the present invention, multi-source data of the mulberry tree planting area are collected through sensors, remote sensing, field surveys, etc., including meteorological data, soil sample data, mulberry tree growth data, irrigation facility data, etc. Preprocessing such as data cleaning, format conversion, and coordinate unification is carried out, and alignment in time and space is performed to obtain spatio-temporally aligned preprocessed data. The meteorological data is processed using a spatial interpolation method to obtain a regional environmental data layer, and combined with the soil sample data and the environmental data layer, a soil property spatial prediction model is constructed to perform soil property spatial prediction to obtain a regional soil data layer. Finally, all data layers are integrated to construct a multi-source data layer, and based on this, combined with the mulberry tree growth model and the soil-mulberry tree system model, a spatio-temporal dynamic soil-mulberry tree system database is constructed. This database covers multi-faceted information such as the soil, mulberry trees, environment, irrigation, etc. in the research area, and can update in real time and dynamically display the state of the soil-mulberry tree system.

[0096] Step S2: Perform mulberry tree growth prediction based on the spatio-temporal dynamic soil-mulberry tree system database to obtain mulberry tree growth prediction data; input the mulberry tree growth prediction data into the soil-mulberry tree system model to perform soil-mulberry tree system simulation to obtain soil-mulberry tree system dynamic change data; generate a mulberry tree growth prediction map based on the soil-mulberry tree system dynamic change data to obtain a mulberry tree growth prediction map.

[0097] In the embodiments of the present invention, key feature data such as mulberry tree biomass, leaf area index, soil moisture, nutrient content, and environmental data are extracted from the spatio-temporal dynamic soil-mulberry tree system database, and time series analysis is performed to obtain mulberry tree growth trend data. According to prediction targets such as mulberry tree yield and water demand, a machine learning algorithm is used to construct a mulberry tree growth prediction model in combination with the key feature data and the mulberry tree growth prediction target data. The preset future meteorological scenario data is input into the model for mulberry tree growth prediction to obtain mulberry tree growth prediction data. Finally, the prediction data is input into the soil-mulberry tree system model for simulation to obtain soil-mulberry tree system dynamic change data, and the growth limiting factor analysis is performed according to the preset growth index threshold to generate a fertilization and water management analysis report, and finally a visual mulberry tree growth prediction map is generated.

[0098] Step S3: Extract target field block data from the spatio-temporal dynamic soil-mulberry tree system database and perform management partition division to obtain a management partition coding map; obtain accurate fertilization and water management target data; generate and visualize an accurate fertilization and water management map according to the accurate fertilization and water management target data and the management partition coding map to obtain an accurate fertilization and water management map.

[0099] In the embodiments of the present invention, soil spatial heterogeneity data and irrigation facility layout data of a target field are extracted from a spatio-temporal dynamic soil-mulberry system database. According to the soil spatial heterogeneity data, using methods such as cluster analysis and spatial interpolation, the field is divided into several management sub-areas with similar soil properties and mulberry tree growth conditions, and the boundaries are optimized to generate a management sub-area coding map. According to actual requirements, the goals of precise fertilization and water management are determined, such as maximizing yield, minimizing water and fertilizer resource consumption, minimizing environmental pollution, etc., and a multi-objective function is constructed accordingly. Combining the irrigation facility layout data and the mulberry tree growth prediction map, the constraint conditions of fertilization and water management are set, such as the maximum irrigation amount and the maximum fertilization amount for each management sub-area. Finally, using a multi-objective optimization algorithm, under the condition of meeting the constraint conditions, a multi-objective solution is carried out for the management sub-area coding map to find the optimal fertilization and water management plan, and through simulation evaluation and weight analysis, a visual precise fertilization and water management map is generated.

[0100] Step S4: Obtain real-time planting area data; perform real-time mulberry tree coefficient prediction based on the real-time planting area data and the mulberry tree growth prediction map to obtain real-time mulberry tree coefficient data; calculate the actual water requirement of the mulberry tree according to the real-time mulberry tree coefficient data; generate a fertilization and water irrigation plan according to the actual water requirement of the mulberry tree and the spatio-temporal dynamic soil-mulberry system database.

[0101] In the embodiments of the present invention, field sensors, remote sensing technology, etc. are used to obtain real-time planting area data in real time, including real-time meteorological station data, real-time field micro-meteorological monitoring data, and real-time mulberry tree physiological index sets. According to the real-time meteorological data, the initial reference mulberry tree transpiration is calculated using the Penman formula, and the environmental correction coefficient is calculated according to the field micro-meteorological monitoring data and the real-time meteorological station data. A mulberry tree coefficient prediction model is constructed using machine learning and other methods, and the real-time mulberry tree coefficient is predicted by combining the environmental correction coefficient, the real-time mulberry tree physiological index set, and the mulberry tree growth prediction map. Furthermore, the actual transpiration of the mulberry tree is calculated. At the same time, according to the real-time rainfall data and the regional soil data layer, the effective rainfall is calculated using the soil water balance model. Finally, by comparing the actual transpiration of the mulberry tree and the effective rainfall, the actual water requirement of the mulberry tree is calculated, and combined with soil moisture information, mulberry tree root distribution information, etc., the fertilization and water irrigation amount is determined, and finally a detailed fertilization and water irrigation plan is generated.

[0102] Step S5: Perform fertilization and water management association processing and perform adaptive adjustment of the plan according to the fertilization and water irrigation plan and the precise fertilization and water management map to achieve fertilization and water management control operations.

[0103] In the embodiments of the present invention, the fertilized water irrigation plan generated in step S4 is associated with the precise fertilized water management map generated in step S3 to form a precise fertilized water management plan including specific partition information, and the irrigation equipment is controlled according to this plan to achieve precise irrigation and fertilization. According to the irrigation equipment control data and the real-time monitoring data of the field sensors, the irrigation effect is evaluated, and the precise fertilized water management plan is adaptively adjusted according to the evaluation results, such as adjusting the irrigation amount, irrigation time, fertilization plan, etc., and finally the goals of improving the water and fertilizer utilization efficiency, promoting the growth of mulberry trees, and increasing the yield are achieved.

[0104] Preferably, step S1 includes the following steps:

[0105] Step S11: Collect multi-source data for the mulberry tree planting area to obtain the original planting area data; perform spatio-temporal alignment preprocessing on the original planting area data to obtain spatio-temporal alignment preprocessed data, where the spatio-temporal alignment preprocessed data includes regional meteorological station data, soil sample data, mulberry tree growth data, and irrigation facility data;

[0106] Step S12: Perform environmental data interpolation on the regional meteorological station data to obtain a regional environmental data layer; extract a regional soil data layer according to the soil sample data and the regional environmental data layer to obtain a regional soil data layer;

[0107] Step S13: Construct a multi-source data layer for the regional soil data layer, the regional environmental data layer, the mulberry tree growth data, and the irrigation facility data to obtain a multi-source data layer;

[0108] Step S14: Perform parameter calibration processing on a preset mulberry tree growth model using the multi-source data layer to obtain a mulberry tree growth simulation model; simulate the growth process of mulberry trees at the farmland plot scale according to the mulberry tree growth simulation model and output the spatio-temporal dynamic data of the mulberry tree growth indicators to obtain mulberry tree growth simulation data and mulberry tree growth indicator data;

[0109] Step S15: Construct a soil-mulberry tree system model according to the mulberry tree growth indicator data, the regional soil data layer, and the regional environmental data layer to obtain a soil-mulberry tree system model;

[0110] Step S16: Construct a spatio-temporal dynamic database based on the soil-mulberry tree system model, the mulberry tree growth simulation data, and the multi-source data layer to obtain a spatio-temporal dynamic soil-mulberry tree system database.

[0111] In the embodiments of the present invention, multi-source data of the mulberry tree planting area are collected by means of sensors, remote sensing technology, field surveys, etc., including data such as temperature, humidity, rainfall, wind speed, etc. of each meteorological station in the area, physical and chemical property data of the collected soil samples, data such as mulberry tree growth height, leaf area index, biomass, etc., and data such as irrigation facility type, location, irrigation capacity, etc. The collected original data is preprocessed, such as data cleaning, format conversion, coordinate unification, etc., and aligned in time and space. Finally, spatio-temporally aligned preprocessed data including regional meteorological station data, soil sample data, mulberry tree growth data, and irrigation facility data is obtained. Using spatial interpolation methods, such as inverse distance weighting method, Kriging interpolation method, etc., the discrete regional meteorological station data is interpolated to obtain continuous regional environmental data layers, such as temperature layer, humidity layer, rainfall layer, etc. Then, according to the soil sample data and the interpolated regional environmental data layers, using, for example, digital soil mapping methods, a spatial prediction model of soil properties is constructed, and spatial prediction of soil properties is carried out. Finally, a regional soil data layer is obtained, such as soil texture map layer, soil organic matter content map layer, soil pH value map layer, etc. The regional soil data layer and the regional environmental data layer obtained in step S12 are integrated with the mulberry tree growth data and the irrigation facility data to construct a multi-source data layer, and all data is unified under the same geographic coordinate system and time scale. According to the mulberry tree species and growth stage, a suitable mulberry tree growth model, such as AquaCrop, DSSAT, APSIM, etc., is selected. Using the constructed multi-source data layer, the key parameters in the model are calibrated, such as mulberry tree parameters, soil parameters, meteorological parameters, etc., to obtain a mulberry tree growth simulation model suitable for the planting area. Then, using this model, the growth process of mulberry trees is simulated at the farmland plot scale, and spatio-temporal dynamic data of mulberry tree growth indicators, such as mulberry tree biomass, leaf area index, soil moisture content, etc., are output to obtain mulberry tree growth simulation data and mulberry tree growth indicator data. Combining the mulberry tree growth indicator data obtained during the mulberry tree growth simulation process, as well as the regional soil data layer and the regional environmental data layer, a soil-mulberry tree system model is constructed. This model can simulate the interaction relationship between mulberry tree growth and soil environment, such as the migration and transformation process of water and nutrients, and the absorption and utilization process of water and nutrients by mulberry trees, etc. Based on the constructed soil-mulberry tree system model, mulberry tree growth simulation data, and multi-source data layer, a spatio-temporal dynamic soil-mulberry tree system database is constructed. This database covers multi-faceted information such as soil, mulberry trees, environment, irrigation, etc. in the research area, and can be updated in real time and dynamically display the state of the soil-mulberry tree system.

[0112] Preferably, step S12 includes the following steps:

[0113] Step S121: Extract environmental factor data from the regional environmental data layer based on the soil sample data to obtain a soil sample environmental factor table;

[0114] Step S122: Conduct an association analysis of environmental factors and soil properties on the soil sample environmental factor table and the soil sample data to obtain association data of environmental factors and soil properties;

[0115] Step S123: Construct a soil property spatial prediction model based on the association of environmental factors and soil properties to obtain a soil property spatial prediction model;

[0116] Step S124: Use the soil property spatial prediction model to conduct a spatial prediction of the soil properties in the mulberry tree planting area to obtain a regional soil data layer.

[0117] In the embodiment of the present invention, according to the spatial position information of the soil samples, environmental factor data at the corresponding positions are extracted from the regional environmental data layer, such as temperature, rainfall, altitude, etc., and the extracted environmental factor data are associated with the soil sample data to construct a soil sample environmental factor table, which contains the physical and chemical property data of each soil sample and the corresponding environmental factor data. Using statistical analysis methods, such as correlation analysis, regression analysis, etc., an association analysis of the environmental factors and soil properties in the soil sample environmental factor table is conducted, such as analyzing the relationship between soil organic matter content and temperature, rainfall, etc., to obtain association relationship data between environmental factors and soil properties, such as correlation coefficients, regression equations, etc. According to the association data of environmental factors and soil properties obtained in step S122, a suitable soil property spatial prediction model is selected, such as a multiple linear regression model, a random forest model, a neural network model, etc., with environmental factors as independent variables and soil properties as dependent variables, for model training and verification, and finally a soil property spatial prediction model capable of predicting soil properties based on environmental factors is obtained. Using the soil property spatial prediction model constructed in step S123 and the regional environmental data layer, a spatial prediction of the soil properties in the entire mulberry tree planting area is conducted, such as predicting the soil organic matter content, soil texture, soil pH value, etc. of each grid unit, and finally a regional soil data layer is obtained, such as a soil organic matter content layer, a soil texture layer, a soil pH value layer, etc.

[0118] Preferably, step S2 includes the following steps:

[0119] Step S21: Extract key feature data from the spatio-temporal dynamic soil-mulberry tree system database to obtain key feature data; conduct an analysis of the growth trend of mulberry trees based on the key feature data to obtain mulberry tree growth trend data;

[0120] Step S22: Obtain the target data for mulberry growth prediction; construct a mulberry growth prediction model based on the key feature data and the target data for mulberry growth prediction to obtain the mulberry growth prediction model;

[0121] Step S23: Perform mulberry growth prediction on the mulberry growth prediction model and the preset future meteorological scenario data to obtain mulberry growth prediction data;

[0122] Step S24: Input the mulberry growth prediction data into the soil-mulberry system model to conduct soil-mulberry system simulation and obtain the dynamic change data of the soil-mulberry system;

[0123] Step S25: Conduct an analysis of growth limiting factors on the dynamic change data of the soil-mulberry system according to the preset growth index threshold to obtain the growth limiting factors;

[0124] Step S26: Conduct fertilization and water management analysis based on the growth limiting factors to obtain a fertilization and water management analysis report; generate a mulberry growth prediction map for the mulberry growth prediction data according to the fertilization and water management analysis report to obtain the mulberry growth prediction map.

[0125] In the embodiments of the present invention, key feature data are extracted from the spatio-temporal dynamic soil-mulberry tree system database, such as the biomass, leaf area index, soil moisture, nutrient content, etc. of mulberry trees at different growth stages, as well as the corresponding environmental data, such as temperature, rainfall, etc. Using time series analysis methods, such as the moving average method, exponential smoothing method, etc., the extracted key feature data are analyzed to obtain mulberry tree growth trend data, such as the change trend of mulberry tree biomass over time, the change trend of soil moisture content over time, etc. According to actual needs, the goals of mulberry tree growth prediction are determined, such as predicting the mulberry tree yield, water demand, etc. in a future period of time. According to the prediction goals, appropriate machine learning algorithms are selected, such as support vector machines, neural networks, random forests, etc., and the key feature data obtained in step S21 and the mulberry tree growth prediction target data are used for model training and verification, and finally a mulberry tree growth prediction model capable of predicting mulberry tree growth indicators is obtained. According to historical meteorological data and climate model prediction results, meteorological scenario data for a future period of time are preset, such as the daily temperature, rainfall, etc. in a future period of time. The preset meteorological scenario data are input into the mulberry tree growth prediction model constructed in step S22 for mulberry tree growth prediction to obtain mulberry tree growth prediction data, such as the change trend of mulberry tree biomass in a future period of time, the change trend of soil moisture content, etc. The mulberry tree growth prediction data obtained in step S23 are input into the soil-mulberry tree system model constructed in step S15 to simulate the dynamic change process of the soil-mulberry tree system in a future period of time, such as the migration and transformation process of soil moisture, the absorption and utilization process of water and nutrients by mulberry trees, etc., to obtain soil-mulberry tree system dynamic change data, such as soil moisture content, nutrient content, mulberry tree biomass, etc. at different soil depths and time nodes. According to the growth law of mulberry trees and actual planting experience, thresholds for key mulberry tree growth indicators are preset, such as when the soil moisture content is lower than a certain threshold, the growth of mulberry trees will be affected by water stress. According to the preset growth indicator thresholds, the soil-mulberry tree system dynamic change data obtained in step S24 are analyzed to determine whether the growth of mulberry trees will be restricted by factors such as water, nutrients, temperature, etc. during the prediction period, and the specific growth limiting factors are determined. According to the growth limiting factors obtained in step S25, combined with the best management measures for fertilization and irrigation, such as determining the irrigation amount according to the degree of water stress, determining the fertilization amount according to the degree of nutrient deficiency, etc., a fertilization and water management analysis report is formed to provide a decision-making basis for precise fertilization and irrigation. At the same time, according to the fertilization and water management analysis report, the mulberry tree growth prediction data obtained in step S23 are visualized to generate a mulberry tree growth prediction map, which intuitively shows the growth status of mulberry trees and the growth limitations that occur in a future period of time.

[0126] Preferably, step S3 includes the following steps:

[0127] Step S31: Extract the target field data from the spatio-temporal dynamic soil-mulberry system database to obtain the target field data, where the target field data includes soil spatial heterogeneity data and irrigation facility layout data;

[0128] Step S32: Divide the management zones according to the soil spatial heterogeneity data to obtain the management zone coding map;

[0129] Step S33: Obtain the target data for precision fertilization and water management; construct a multi-objective function according to the target data for precision fertilization and water management to obtain the multi-objective function;

[0130] Step S34: Set the constraint conditions according to the irrigation facility layout data and the mulberry growth prediction map to obtain the fertilization and water management constraint condition data;

[0131] Step S35: Perform multi-objective solution of the fertilization and water management plan for the management zone coding map according to the fertilization and water management constraint condition data and the multi-objective function to obtain the fertilization and water management plan;

[0132] Step S36: Input the fertilization and water management plan into the soil-mulberry system model for plan simulation evaluation to obtain the plan simulation evaluation data;

[0133] Step S37: Set the target weights according to the multi-objective function to obtain the multi-objective function weight data; perform plan comparison weight analysis on the plan simulation evaluation data according to the multi-objective function weight data to obtain the plan comparison weight analysis data;

[0134] Step S38: Generate and visualize the precision fertilization and water management map according to the plan comparison weight analysis data and the plan simulation evaluation data to obtain the precision fertilization and water management map.

[0135] As an example of the present invention, refer to Figure 2 As shown, in this example, step S3 includes:

[0136] Step S31: Extract the target field data from the spatio-temporal dynamic soil-mulberry system database to obtain the target field data, where the target field data includes soil spatial heterogeneity data and irrigation facility layout data;

[0137] In the embodiment of the present invention, the soil spatial heterogeneity data of the target field, such as soil texture, organic matter content, pH value, etc. at different positions, and the irrigation facility layout data, such as irrigation facility type, location, irrigation capacity, etc., are extracted from the spatio-temporal dynamic soil-mulberry system database to construct the target field dataset.

[0138] Step S32: Divide the management zones according to the soil spatial heterogeneity data to obtain the management zone coding map;

[0139] In the embodiments of the present invention, by using methods such as cluster analysis and spatial interpolation, according to the soil spatial heterogeneity data of the target field, the field is divided into several management sub-areas with similar soil properties, and a unique code is assigned to each sub-area to generate a management sub-area coding map.

[0140] Step S33: Obtain the target data for precision fertilization and water management; construct a multi-objective function based on the target data for precision fertilization and water management to obtain the multi-objective function.

[0141] In the embodiments of the present invention, according to actual requirements, determine the goals of precision fertilization and water management, such as maximizing yield, minimizing water and fertilizer resource consumption, minimizing environmental pollution, etc., and construct a multi-objective function based on these goals. For example, take maximizing yield as the objective function and minimizing water and fertilizer resource consumption as the constraint condition.

[0142] Step S34: Set constraint conditions according to the irrigation facility layout data and the mulberry tree growth prediction map to obtain the fertilization and water management constraint condition data.

[0143] In the embodiments of the present invention, according to the irrigation facility layout data, such as irrigation range, irrigation capacity, etc., and the water requirements of mulberry trees in different management sub-areas in the mulberry tree growth prediction map, set the constraint conditions for fertilization and water management, such as the maximum irrigation amount and the maximum fertilization amount in each management sub-area.

[0144] Step S35: Perform multi-objective solution of the fertilization and water management plan for the management sub-area coding map according to the fertilization and water management constraint condition data and the multi-objective function to obtain the fertilization and water management plan.

[0145] In the embodiments of the present invention, use a multi-objective optimization algorithm, such as a genetic algorithm, a particle swarm algorithm, etc., to perform multi-objective solution on the management sub-area coding map under the condition of satisfying the fertilization and water management constraint conditions set in step S34, and find the optimal fertilization and water management plan. This plan can maximize the utilization of water and fertilizer resources while achieving the goals of precision fertilization and water management.

[0146] Step S36: Input the fertilization and water management plan into the soil-mulberry tree system model for plan simulation evaluation to obtain the plan simulation evaluation data.

[0147] In the embodiments of the present invention, input the optimal fertilization and water management plan obtained in step S35 into the soil-mulberry tree system model constructed in step S15 to simulate the implementation effect of this plan in the future for a period of time, such as mulberry tree yield, water and fertilizer utilization efficiency, environmental pollution degree, etc., to obtain the plan simulation evaluation data.

[0148] Step S37: Set target weights according to the multi-objective function to obtain multi-objective function weight data; perform scheme comparison weight analysis on the scheme simulation evaluation data according to the multi-objective function weight data to obtain scheme comparison weight analysis data;

[0149] In the embodiment of the present invention, according to the importance of the precise fertilization and water management objectives, weights are set for each objective in the multi-objective function. For example, the weight of the yield objective is set to 0.6, and the weight of the water and fertilizer resource consumption objective is set to 0.4. According to the set target weights, comparative analysis is performed on the scheme simulation evaluation data obtained in step S36. For example, the differences between different schemes in terms of yield, water and fertilizer utilization efficiency, environmental pollution degree, etc. are compared to obtain scheme comparison weight analysis data.

[0150] Step S38: Generate and visualize a precise fertilization and water management map according to the scheme comparison weight analysis data and the scheme simulation evaluation data to obtain a precise fertilization and water management map;

[0151] In the embodiment of the present invention, a precise fertilization and water management map is generated according to the scheme comparison weight analysis data and the scheme simulation evaluation data, and visual display is performed. The precise fertilization and water management map can intuitively display information such as fertilization amount, irrigation amount, fertilization time, irrigation time, etc. for different management zones.

[0152] Preferably, step S32 includes the following steps:

[0153] Step S321: Perform data standardization processing on the soil spatial heterogeneity data to obtain soil spatial heterogeneity standardized data; perform soil attribute clustering analysis according to the soil spatial heterogeneity standardized data to obtain a soil management zone map;

[0154] Step S322: Filter the mulberry tree growth data in the mulberry tree growth prediction map to obtain mulberry tree growth filtered data; perform mulberry tree growth threshold segmentation on the mulberry tree growth filtered data according to a preset mulberry tree growth threshold to obtain a mulberry tree growth grade map;

[0155] Step S323: Perform partition result fusion on the soil management zone map and the mulberry tree growth grade map to obtain a management zone fusion map; optimize the partition boundary of the management zone fusion map to obtain a management zone optimized map;

[0156] Step S324: Extract partition attributes from the management zone optimized map, the soil spatial heterogeneity standardized data, and the mulberry tree growth filtered data to obtain a management zone attribute table;

[0157] Step S325: Perform partition coding on the management zone attribute table and the management zone optimized map to obtain a management zone coding map.

[0158] In the embodiments of the present invention, data standardization processing is performed on the soil spatial heterogeneity data of the target field, such as soil texture, organic matter content, pH value, etc., to eliminate the influence of dimensional differences of different indicators, and soil spatial heterogeneity standardized data is obtained. Then, using clustering analysis methods, such as K-Means clustering, hierarchical clustering, etc., according to the soil spatial heterogeneity standardized data, the target field is divided into several regions with similar soil properties, and a soil management zoning map is generated. Filtering processing is performed on the mulberry tree growth prediction map, such as using a Gaussian filter, to smooth the mulberry tree growth data and remove data noise, and mulberry tree growth filtered data is obtained. Then, according to a preset mulberry tree growth threshold, for example, the mulberry tree growth is divided into three grades: good, medium, and poor, threshold segmentation is performed on the mulberry tree growth filtered data, and the target field is divided into regions with different mulberry tree growth grades, and a mulberry tree growth grade map is generated. The soil management zoning map obtained in step S321 and the mulberry tree growth grade map obtained in step S322 are fused, for example, the two are superimposed, and according to the comprehensive situation of soil properties and mulberry tree growth, the management zoning is re-divided to obtain a management zoning fusion map. Then, boundary optimization processing is performed on the management zoning fusion map, for example, eliminating small and irregular zoning boundaries, and merging adjacent and similar-property partitions, to obtain a management zoning optimized map. According to the management zoning optimized map, soil properties and mulberry tree growth information of each management zone are extracted from the soil spatial heterogeneity standardized data and the mulberry tree growth filtered data, such as the average soil organic matter content, average mulberry tree growth grade of each partition, etc., to construct a management zoning attribute table. According to the management zoning attribute table, a unique code is assigned to each management zone, such as using numerical coding, alphabetical coding, etc., and it is marked on the management zoning optimized map, and finally a management zoning coded map is obtained. Each code represents a management zone with specific soil properties and mulberry tree growth characteristics.

[0159] Preferably, step S44 includes the following steps:

[0160] Step S41: Obtain real-time planting area data; perform real-time mulberry tree coefficient prediction according to the real-time planting area data and the mulberry tree growth prediction map to obtain real-time mulberry tree coefficient data; calculate the actual water requirement of the mulberry tree according to the real-time mulberry tree coefficient data to obtain the actual water requirement of the mulberry tree;

[0161] Step S42: Make a decision on the fertilization and irrigation water volume according to the actual water requirement of the mulberry tree and the spatio-temporal dynamic soil-mulberry tree system database to obtain fertilization and irrigation water volume data;

[0162] Step S43: Make a decision on the irrigation time according to the real-time planting area data, the mulberry tree growth prediction map, and the irrigation facility data in the spatio-temporal alignment preprocessing data to obtain irrigation time data;

[0163] Step S44: Generate a fertilized water irrigation plan based on the irrigation time data, the fertilized water irrigation volume data, and the irrigation facility data in the spatio-temporal alignment preprocessing data, to obtain the fertilized water irrigation plan.

[0164] As an example of the present invention, refer to Figure 3 As shown, in this example, the said step S4 includes:

[0165] Step S41: Obtain the real-time planting area data; perform real-time mulberry tree coefficient prediction based on the real-time planting area data and the mulberry tree growth prediction map to obtain real-time mulberry tree coefficient data; calculate the actual water requirement of the mulberry tree according to the real-time mulberry tree coefficient data, to obtain the actual water requirement of the mulberry tree.

[0166] In the embodiment of the present invention, field sensors, remote sensing technology, etc. are used to obtain the planting area data in real time, such as real-time meteorological station data (temperature, humidity, wind speed, solar radiation, etc.), real-time field micro-meteorological monitoring data (mulberry tree canopy temperature, air humidity, etc.), and real-time mulberry tree physiological index set (leaf temperature, chlorophyll content, etc.). Combining the real-time planting area data and the mulberry tree growth prediction map, using, for example, a machine learning model, according to factors such as the mulberry tree growth stage and environmental conditions, the mulberry tree coefficient is predicted in real time to obtain real-time mulberry tree coefficient data. Finally, according to the real-time mulberry tree coefficient data, reference evapotranspiration, effective rainfall, etc., the actual water requirement of the mulberry tree is calculated.

[0167] Step S42: Make a decision on the fertilized water irrigation volume based on the actual water requirement of the mulberry tree and the spatio-temporal dynamic soil-mulberry tree system database, to obtain the fertilized water irrigation volume data.

[0168] In the embodiment of the present invention, according to the actual water requirement of the mulberry tree calculated in step S41, and the soil moisture information, mulberry tree root distribution information, etc. stored in the spatio-temporal dynamic soil-mulberry tree system database, it is judged whether the current soil moisture condition can meet the growth requirements of the mulberry tree. If the soil moisture is insufficient, then according to factors such as the soil moisture deficit, the water requirement of the mulberry tree, and the irrigation regime, the fertilized water irrigation volume is decided, and according to the mulberry tree growth stage and nutrient requirements, the fertilization plan is determined, and finally the fertilized water irrigation volume data is obtained.

[0169] Step S43: Make a decision on the irrigation time based on the real-time planting area data, the mulberry tree growth prediction map, and the irrigation facility data in the spatio-temporal alignment preprocessing data, to obtain the irrigation time data.

[0170] In the embodiments of the present invention, according to the real-time meteorological station data in the real-time planting area data, such as rainfall forecasts, evaporation predictions, etc., and the water requirements of mulberry trees in different management zones in the mulberry tree growth prediction map, a suitable irrigation time is selected. For example, irrigation is carried out avoiding rainfall periods, or irrigation is carried out during the period when the water requirements of mulberry trees are the greatest. At the same time, it is also necessary to consider irrigation facility data, such as the flow rate and working hours of the irrigation system, as well as other field management operations, such as spraying time, etc., and finally determine the irrigation time data.

[0171] Step S44: Generate a fertilized water irrigation plan based on the irrigation time data, the fertilized water irrigation volume data, and the irrigation facility data in the spatio-temporal alignment preprocessing data to obtain a fertilized water irrigation plan;

[0172] In the embodiments of the present invention, according to the fertilized water irrigation volume data obtained in step S42, the irrigation time data obtained in step S43, and the irrigation facility data in the spatio-temporal alignment preprocessing data, such as the type, location, and irrigation range of the irrigation system, a detailed fertilized water irrigation plan is generated. This plan includes information such as the irrigation time, irrigation volume, fertilization type, fertilization amount, etc. for each management zone, and can be adjusted according to the actual situation.

[0173] Preferably, step S411 includes the following steps:

[0174] Step S411: Obtain real-time planting area data; wherein the real-time planting area data includes real-time meteorological station data, real-time field micro-meteorological monitoring data, and a real-time mulberry tree physiological index set;

[0175] Step S412: Calculate the initial reference transpiration amount using the Penman formula and the real-time meteorological station data to obtain the initial reference mulberry tree water transpiration amount data;

[0176] Step S413: Calculate the environmental correction coefficient based on the real-time field micro-meteorological monitoring data and the real-time meteorological station data to obtain the environmental correction coefficient data;

[0177] Step S414: Construct a mulberry tree coefficient prediction model based on the environmental correction coefficient data, the real-time mulberry tree physiological index set, and the mulberry tree growth prediction map to obtain a mulberry tree coefficient prediction model; perform real-time mulberry tree coefficient prediction according to the mulberry tree coefficient prediction model to obtain real-time mulberry tree coefficient data;

[0178] Step S415: Calculate the actual transpiration amount of the mulberry tree based on the real-time mulberry tree coefficient data, the environmental correction coefficient data, and the initial reference mulberry tree water transpiration amount data to obtain the actual transpiration amount of the mulberry tree;

[0179] Step S416: Calculate the effective rainfall using the real-time rainfall data in the real-time weather station data and the regional soil data layer by means of the soil water balance model to obtain the effective rainfall data;

[0180] Step S417: Calculate the actual water requirement of the mulberry tree based on the effective rainfall data and the actual transpiration amount of the mulberry tree to obtain the actual water requirement of the mulberry tree.

[0181] In the embodiment of the present invention, the data of the planting area are collected in real time through the sensor network deployed in the field, including the data such as temperature, humidity, wind speed, solar radiation, etc. from the weather station, the data such as the mulberry tree canopy temperature, air humidity, etc. from the field micro-meteorological monitoring points, and the physiological index data such as the mulberry tree leaf temperature, chlorophyll content, etc. obtained through remote sensing or other sensors, and they are integrated to form the real-time planting area data set. According to the obtained real-time weather station data, such as temperature, humidity, wind speed, and solar radiation, etc., the transpiration amount of the reference mulberry tree (usually referring to the well-growing grassland) is calculated by using the Penman formula to obtain the initial reference mulberry tree water transpiration amount data, which is used as the basis for estimating the actual transpiration amount of the mulberry tree. Using the real-time field micro-meteorological monitoring data and the real-time weather station data, such as the difference between the canopy temperature and the air temperature, the difference in air humidity, etc., analyze the difference between the field microclimate and the standard meteorological conditions, and calculate the environmental correction coefficient according to these differences to correct the reference mulberry tree transpiration amount to make it closer to the actual field evapotranspiration situation. Using methods such as machine learning, construct a mulberry tree coefficient prediction model, take the environmental correction coefficient, the real-time mulberry tree physiological index set, and the mulberry tree growth stage in the mulberry tree growth prediction map as inputs, train the model and predict the real-time mulberry tree coefficient, so as to reflect the difference between the actual transpiration amount of the mulberry tree and the transpiration amount of the reference mulberry tree. Multiply the real-time mulberry tree coefficient obtained in step S414, the environmental correction coefficient calculated in step S413, and the initial reference mulberry tree water transpiration amount data calculated in step S412 to obtain the actual transpiration amount of the mulberry tree, that is, the amount of water actually consumed by the mulberry tree under the current environmental conditions. According to the real-time rainfall data in the real-time weather station data and the information such as soil texture and soil structure stored in the regional soil data layer, use the soil water balance model, such as the SWAT model, the HYDRUS model, etc., to simulate the rainfall process and the processes of soil water infiltration, evaporation, runoff, etc., and calculate the effective rainfall, that is, the rainfall that can actually be utilized by the mulberry tree. Compare the actual transpiration amount of the mulberry tree calculated in step S415 with the effective rainfall calculated in step S416. If the actual transpiration amount of the mulberry tree is greater than the effective rainfall, the water requirement of the mulberry tree is the difference between the two; if the actual transpiration amount of the mulberry tree is less than or equal to the effective rainfall, the water requirement of the mulberry tree is zero. Finally, obtain the actual water requirement of the mulberry tree, which is the irrigation water amount required to meet the growth of the mulberry tree.

[0182] Preferably, step S5 includes the following steps:

[0183] Step S51: Perform fertilization and irrigation water management association processing according to the fertilization and irrigation water plan and the precise fertilization and irrigation water management map to obtain a precise fertilization and irrigation water management plan;

[0184] Step S52: Perform irrigation equipment control processing according to the precise fertilization and irrigation water management plan to obtain irrigation equipment control data;

[0185] Step S53: Evaluate the irrigation effect according to the irrigation equipment control data to obtain fertilization and irrigation water effect data;

[0186] Step S54: Perform adaptive adjustment of the precise fertilization and irrigation water management plan according to the fertilization and irrigation water effect data to achieve fertilization and irrigation water management control operations.

[0187] In the embodiment of the present invention, the fertilization and irrigation water plan generated in step S44 is associated with the precise fertilization and irrigation water management map generated in step S38, and information such as the irrigation amount and fertilization amount in the irrigation plan is matched with the corresponding management sub-areas in the precise fertilization and irrigation water management map to form a precise fertilization and irrigation water management plan including specific sub-area information. For example, information such as the irrigation time, irrigation amount, fertilization type, and fertilization amount of a certain sub-area is integrated to form the precise fertilization and irrigation water management plan for this sub-area. The precise fertilization and irrigation water management plan contains information such as the irrigation time, irrigation amount, fertilization type, and fertilization amount of each management sub-area, and the irrigation equipment is controlled according to this information. For example, the opening and closing of the solenoid valve and the operation time of the water pump are controlled according to the irrigation time and irrigation amount to achieve precise irrigation; the operation of the fertilizer applicator is controlled according to the fertilization type and fertilization amount to achieve precise fertilization. By controlling the irrigation equipment, the precise fertilization and irrigation water management plan is applied to the actual field operation to generate irrigation equipment control data, such as the on / off state and operation time of each irrigation equipment. According to the irrigation equipment control data, combined with the data of soil moisture and nutrient content monitored by field sensors in real time, the irrigation effect is evaluated. For example, by comparing the change in soil moisture before and after irrigation, it is judged whether the irrigation amount is reasonable; by analyzing the growth status of mulberry trees, it is judged whether the fertilization plan is effective. Through evaluation, fertilization and irrigation water effect data is obtained, such as the actual irrigation amount, soil moisture change amount, and mulberry tree nutrient absorption amount. According to the fertilization and irrigation water effect data obtained in step S53, the implementation effect of the precise fertilization and irrigation water management plan is analyzed. If the irrigation effect does not meet the expectation, such as insufficient or excessive soil moisture, insufficient nutrient absorption of mulberry trees, etc., then according to the evaluation results and actual situations, the precise fertilization and irrigation water management plan is adaptively adjusted. For example, the irrigation amount and irrigation time are adjusted according to the soil moisture deficit situation, and the fertilization plan is adjusted according to the nutrient requirements of mulberry trees. Through continuous adjustment and optimization, the goal of fertilization and irrigation water management control is achieved, such as improving the utilization efficiency of water and fertilizer, promoting the growth of mulberry trees, and increasing the yield.

[0188] Preferably, the present invention further provides a fertilization and water management control system for mulberry tree planting, which is used to execute the fertilization and water management control method for mulberry tree planting as described above. The fertilization and water management control system for mulberry tree planting includes:

[0189] A soil and mulberry tree data assimilation module, which is used to collect multi-source data of the mulberry tree planting area and perform spatio-temporal alignment preprocessing to obtain spatio-temporal alignment preprocessed data; extract the regional soil data layer according to the spatio-temporal alignment preprocessed data to obtain the regional soil data layer; construct a multi-source data layer according to the regional soil data layer and the spatio-temporal alignment preprocessed data to obtain the multi-source data layer; construct a soil-mulberry tree system model according to the multi-source data layer to obtain the soil-mulberry tree system model; construct a spatio-temporal dynamic database based on the soil-mulberry tree system model to obtain the spatio-temporal dynamic soil-mulberry tree system database;

[0190] A mulberry tree growth analysis module, which is used to predict the growth of mulberry trees according to the spatio-temporal dynamic soil-mulberry tree system database to obtain mulberry tree growth prediction data; input the mulberry tree growth prediction data into the soil-mulberry tree system model to perform soil-mulberry tree system simulation to obtain soil-mulberry tree system dynamic change data; generate a mulberry tree growth prediction map according to the soil-mulberry tree system dynamic change data to obtain the mulberry tree growth prediction map;

[0191] A fertilization and water zoning management module, which is used to extract the target field data according to the spatio-temporal dynamic soil-mulberry tree system database and perform management zoning division to obtain the management zoning coding map; obtain the precise fertilization and water management target data; generate and visualize the precise fertilization and water management map according to the precise fertilization and water management target data and the management zoning coding map to obtain the precise fertilization and water management map;

[0192] A fertilization and water irrigation analysis module, which is used to obtain real-time planting area data; predict the real-time mulberry tree coefficient according to the real-time planting area data and the mulberry tree growth prediction map to obtain real-time mulberry tree coefficient data; calculate the actual water requirement of the mulberry tree according to the real-time mulberry tree coefficient data to obtain the actual water requirement of the mulberry tree; generate a fertilization and water irrigation plan according to the actual water requirement of the mulberry tree and the spatio-temporal dynamic soil-mulberry tree system database to obtain the fertilization and water irrigation plan;

[0193] A fertilization and water management control module, which is used to perform fertilization and water management association processing and perform scheme adaptive adjustment according to the fertilization and water irrigation plan and the precise fertilization and water management map to achieve fertilization and water management control operations.

[0194] Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to include all changes falling within the meaning and scope of the equivalent elements of the application documents within the present invention.

[0195] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features invented herein.

Claims

1. A fertilization and water management control method for mulberry tree planting, characterized in that, Including the following steps: Step S1: Collect multi-source data for the mulberry tree planting area and perform spatio-temporal alignment preprocessing to obtain spatio-temporally aligned preprocessed data; Extract the regional soil data layer based on the spatio-temporally aligned preprocessed data to obtain the regional soil data layer; construct a multi-source data layer based on the regional soil data layer and the spatio-temporally aligned preprocessed data to obtain the multi-source data layer; construct a soil-mulberry tree system model based on the multi-source data layer to obtain the soil-mulberry tree system model; construct a spatio-temporal dynamic database based on the soil-mulberry tree system model to obtain the spatio-temporal dynamic soil-mulberry tree system database; Step S2: Predict the growth of mulberry trees based on the spatio-temporal dynamic soil-mulberry tree system database to obtain mulberry tree growth prediction data; input the mulberry tree growth prediction data into the soil-mulberry tree system model to perform soil-mulberry tree system simulation to obtain soil-mulberry tree system dynamic change data; generate a mulberry tree growth prediction map based on the soil-mulberry tree system dynamic change data to obtain the mulberry tree growth prediction map; Step S3: Extract the target field data from the spatio-temporal dynamic soil-mulberry tree system database and perform management partition division to obtain the management partition coding map; obtain the accurate fertilization and water management target data; generate and visualize the accurate fertilization and water management map based on the accurate fertilization and water management target data and the management partition coding map to obtain the accurate fertilization and water management map; Step S4: Obtain the real-time planting area data; predict the real-time mulberry tree coefficient based on the real-time planting area data and the mulberry tree growth prediction map to obtain the real-time mulberry tree coefficient data; calculate the actual water requirement of the mulberry tree based on the real-time mulberry tree coefficient data to obtain the actual water requirement of the mulberry tree; generate a fertilization and water irrigation plan based on the actual water requirement of the mulberry tree and the spatio-temporal dynamic soil-mulberry tree system database to obtain the fertilization and water irrigation plan; Step S5: Perform fertilization and water management association processing and perform scheme adaptive adjustment based on the fertilization and water irrigation plan and the accurate fertilization and water management map to achieve fertilization and water management control operations.

2. The fertilization water management control method for mulberry tree planting according to claim 1, characterized in that Step S1 includes the following steps: Step S11: Collect multi-source data for the mulberry tree planting area to obtain the original data of the planting area; perform spatio-temporal alignment preprocessing on the original data of the planting area to obtain the spatio-temporally aligned preprocessed data, where the spatio-temporally aligned preprocessed data includes regional meteorological station data, soil sample data, mulberry tree growth data, and irrigation facility data; Step S12: Interpolate the environmental data of the regional meteorological station data to obtain the regional environmental data layer; extract the regional soil data layer based on the soil sample data and the regional environmental data layer to obtain the regional soil data layer; Step S13: Construct a multi-source data layer for the regional soil data layer, the regional environmental data layer, the mulberry tree growth data, and the irrigation facility data to obtain the multi-source data layer; Step S14: Calibrate the parameters of the preset mulberry growth model using multi-source data layers to obtain a mulberry growth simulation model; simulate the mulberry growth process at the farmland plot scale according to the mulberry growth simulation model and output the spatio-temporal dynamic data of mulberry growth indicators to obtain mulberry growth simulation data and mulberry growth indicator data; Step S15: Construct a soil-mulberry system model based on the mulberry growth indicator data, regional soil data layer, and regional environmental data layer to obtain a soil-mulberry system model; Step S16: Construct a spatio-temporal dynamic database based on the soil-mulberry system model, mulberry growth simulation data, and multi-source data layers to obtain a spatio-temporal dynamic soil-mulberry system database.

3. The fertilization water management control method for mulberry tree planting according to claim 2, wherein Step S12 includes the following steps: Step S121: Extract environmental factor data from the regional environmental data layer according to the soil sample data to obtain a soil sample environmental factor table; Step S122: Conduct an association analysis of environmental factors and soil properties on the soil sample environmental factor table and soil sample data to obtain association data of environmental factors and soil properties; Step S123: Construct a soil property spatial prediction model based on the association of environmental factors and soil properties to obtain a soil property spatial prediction model; Step S124: Use the soil property spatial prediction model to predict the soil properties in the mulberry planting area to obtain a regional soil data layer.

4. The fertilization and water management control method for mulberry tree planting according to claim 1, characterized in that, Step S2 includes the following steps: Step S21: Extract key feature data from the spatio-temporal dynamic soil-mulberry system database to obtain key feature data; analyze the mulberry growth trend based on the key feature data to obtain mulberry growth trend data; Step S22: Obtain the mulberry growth prediction target data; construct a mulberry growth prediction model based on the key feature data and the mulberry growth prediction target data to obtain a mulberry growth prediction model; Step S23: Predict the mulberry growth using the mulberry growth prediction model and the preset future meteorological scenario data to obtain mulberry growth prediction data; Step S24: Input the mulberry growth prediction data into the soil-mulberry system model to conduct soil-mulberry system simulation and obtain soil-mulberry system dynamic change data; Step S25: Analyze the growth limiting factors of the soil-mulberry system dynamic change data according to the preset growth index threshold to obtain growth limiting factors; Step S26: Conduct fertilization and water management analysis based on the growth limiting factors to obtain a fertilization and water management analysis report; generate a mulberry growth prediction map for the mulberry growth prediction data according to the fertilization and water management analysis report to obtain a mulberry growth prediction map.

5. The fertilization and water management control method for mulberry tree planting according to claim 1, wherein Step S3 includes the following steps: Step S31: Extract target plot data from the spatio-temporal dynamic soil-mulberry system database to obtain target plot data, where the target plot data includes soil spatial heterogeneity data and irrigation facility layout data; Step S32: Divide management zones according to the soil spatial heterogeneity data to obtain a management zone coding map; Step S33: Obtain the precise fertilization and water management target data; construct a multi-objective function based on the precise fertilization and water management target data to obtain a multi-objective function; Step S34: Set constraint conditions based on the irrigation facility layout data and the mulberry tree growth prediction map to obtain the fertilization and water management constraint condition data; Step S35: Perform multi-objective solution of the fertilization and water management plan for the management partition coding map according to the fertilization and water management constraint condition data and the multi-objective function to obtain the fertilization and water management plan; Step S36: Input the fertilization and water management plan into the soil-mulberry tree system model for scenario simulation evaluation to obtain scenario simulation evaluation data; Step S37: Set the target weights according to the multi-objective function to obtain the multi-objective function weight data; perform scenario comparison weight analysis on the scenario simulation evaluation data according to the multi-objective function weight data to obtain scenario comparison weight analysis data; Step S38: Generate and visualize the precise fertilization and water management map based on the scenario comparison weight analysis data and the scenario simulation evaluation data to obtain the precise fertilization and water management map.

6. The fertilization water management control method for mulberry tree planting according to claim 5, characterized in that, Step S32 includes the following steps: Step S321: Perform data standardization processing on the soil spatial heterogeneity data to obtain soil spatial heterogeneity standardized data; perform soil attribute clustering analysis according to the soil spatial heterogeneity standardized data to obtain the soil management partition map; Step S322: Filter the mulberry tree growth data of the mulberry tree growth prediction map to obtain the mulberry tree growth filtered data; perform mulberry tree growth threshold segmentation on the mulberry tree growth filtered data according to the preset mulberry tree growth threshold to obtain the mulberry tree growth level map; Step S323: Perform partition result fusion on the soil management partition map and the mulberry tree growth level map to obtain the management partition fusion map; optimize the partition boundary of the management partition fusion map to obtain the management partition optimized map; Step S324: Extract partition attributes from the management partition optimized map, the soil spatial heterogeneity standardized data, and the mulberry tree growth filtered data to obtain the management partition attribute table; Step S325: Perform partition coding on the management partition attribute table and the management partition optimized map to obtain the management partition coding map.

7. The fertilization water management control method for mulberry tree planting according to claim 1, characterized in that Step S44 includes the following steps: Step S41: Obtain the real-time planting area data; predict the real-time mulberry tree coefficient according to the real-time planting area data and the mulberry tree growth prediction map to obtain the real-time mulberry tree coefficient data; calculate the actual water requirement of the mulberry tree according to the real-time mulberry tree coefficient data to obtain the actual water requirement of the mulberry tree; Step S42: Make a decision on the fertilization and water irrigation amount according to the actual water requirement of the mulberry tree and the spatio-temporal dynamic soil-mulberry tree system database to obtain the fertilization and water irrigation amount data; Step S43: Make a decision on the irrigation time according to the real-time planting area data, the mulberry tree growth prediction map, and the irrigation facility data in the spatio-temporal alignment preprocessing data to obtain the irrigation time data; Step S44: Generate a fertilization and water irrigation plan according to the irrigation time data, the fertilization and water irrigation amount data, and the irrigation facility data in the spatio-temporal alignment preprocessing data to obtain the fertilization and water irrigation plan.

8. The fertilization and water management control method for mulberry tree planting according to claim 7, characterized in that, Step S411 includes the following steps: Step S411: Obtain the real-time planting area data; the real-time planting area data includes real-time weather station data, real-time field micro-meteorological monitoring data, and real-time mulberry tree physiological index sets; Step S412: Calculate the initial reference transpiration using the Penman formula and real-time weather station data to obtain the initial reference mulberry tree water transpiration data; Step S413: Calculate the environmental correction coefficient based on the real-time field microclimate monitoring data and real-time weather station data to obtain the environmental correction coefficient data; Step S414: Construct a mulberry tree coefficient prediction model based on the environmental correction coefficient data, real-time mulberry tree physiological index set, and mulberry tree growth prediction map to obtain the mulberry tree coefficient prediction model; Predict the real-time mulberry tree coefficient according to the mulberry tree coefficient prediction model to obtain the real-time mulberry tree coefficient data; Step S415: Calculate the actual transpiration of the mulberry tree based on the real-time mulberry tree coefficient data, environmental correction coefficient data, and initial reference mulberry tree water transpiration data to obtain the actual transpiration of the mulberry tree; Step S416: Calculate the effective rainfall using the soil water balance model based on the real-time rainfall data in the real-time weather station data and the regional soil data layer to obtain the effective rainfall data; Step S417: Calculate the actual water requirement of the mulberry tree based on the effective rainfall data and the actual transpiration of the mulberry tree to obtain the actual water requirement of the mulberry tree.

9. The fertilization water management control method for mulberry tree planting according to claim 1, characterized in that Step S5 includes the following steps: Step S51: Perform fertilization and irrigation management association processing according to the fertilization and irrigation plan and the precise fertilization and irrigation management map to obtain the precise fertilization and irrigation management plan; Step S52: Perform irrigation equipment control processing according to the precise fertilization and irrigation management plan to obtain the irrigation equipment control data; Step S53: Evaluate the irrigation effect based on the irrigation equipment control data to obtain the fertilization and irrigation effect data; Step S54: Perform adaptive adjustment of the precise fertilization and irrigation management plan according to the fertilization and irrigation effect data to achieve fertilization and irrigation management control operations.

10. A fertilization water management control system for mulberry tree planting, characterized in that, A fertilization and irrigation management control system for mulberry tree planting, which is used to execute the fertilization and irrigation management control method for mulberry tree planting as described in claim 1, includes: A soil and mulberry tree data assimilation module, which is used to collect multi-source data in the mulberry tree planting area and perform spatio-temporal alignment preprocessing to obtain spatio-temporal alignment preprocessing data; Extract the regional soil data layer according to the spatio-temporal alignment preprocessing data to obtain the regional soil data layer; Construct a multi-source data layer based on the regional soil data layer and the spatio-temporal alignment preprocessing data to obtain the multi-source data layer; Construct a soil-mulberry tree system model based on the multi-source data layer to obtain the soil-mulberry tree system model; Construct a spatio-temporal dynamic database based on the soil-mulberry tree system model to obtain the spatio-temporal dynamic soil-mulberry tree system database; A mulberry tree growth analysis module, which is used to predict the growth of mulberry trees according to the spatio-temporal dynamic soil-mulberry tree system database to obtain mulberry tree growth prediction data; Input the mulberry tree growth prediction data into the soil-mulberry tree system model to perform soil-mulberry tree system simulation to obtain soil-mulberry tree system dynamic change data; Generate a mulberry tree growth prediction map according to the soil-mulberry tree system dynamic change data to obtain the mulberry tree growth prediction map; The fertilization and water zoning management module is used to extract target field data according to the spatio-temporal dynamic soil-mulberry system database and divide the management zones, obtaining the management zone coding map; acquire the precise fertilization and water management target data; generate and visualize the precise fertilization and water management map based on the precise fertilization and water management target data and the management zone coding map, obtaining the precise fertilization and water management map; The fertilization and water irrigation analysis module is used to obtain real-time planting area data; predict the real-time mulberry coefficient according to the real-time planting area data and the mulberry growth prediction map, obtaining the real-time mulberry coefficient data; calculate the actual water requirement of the mulberry according to the real-time mulberry coefficient data, obtaining the actual water requirement of the mulberry; generate a fertilization and water irrigation plan according to the actual water requirement of the mulberry and the spatio-temporal dynamic soil-mulberry system database, obtaining the fertilization and water irrigation plan; The fertilization and water management control module is used to perform fertilization and water management correlation processing and perform scheme adaptive adjustment according to the fertilization and water irrigation plan and the precise fertilization and water management map to achieve fertilization and water management control operations.

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