A goji melon water and fertilizer integrated precision regulation system

Abstract

The present application relates to the technical field of intelligent regulation and control, and a water and fertilizer integrated precision regulation and control system for Gobi melon, which comprises a multi-source data integration module, a root zone water and fertilizer capacity atlas construction module, a water and fertilizer supply potential evaluation module, a preliminary decision generation module, a virtual deduction module and an instruction execution and control module, wherein: multi-source environmental data of Gobi melon is obtained; a root zone effective water and fertilizer capacity atlas is constructed; the water and fertilizer supply potential of the rhizosphere microenvironment is evaluated for capacity, and a water and fertilizer demand evaluation value is obtained; the water and fertilizer demand evaluation value is mapped to a water and fertilizer application strategy library of Gobi melon, and a preliminary water and fertilizer integrated application decision is obtained; the root zone state change is virtually deduced, the water and fertilizer mixing ratio and the application time length parameters are encoded and packaged, and a final execution instruction is obtained; according to the final execution instruction, the water and fertilizer integrated equipment is controlled to precisely irrigate and fertilize the Gobi melon planting area; and the present application can improve the efficiency of water and fertilizer integrated precision regulation and control of Gobi melon.

Description

Technical Field

[0001] This invention relates to the field of intelligent regulation technology, and in particular to a precision regulation system for integrated water and fertilizer management of Gobi melons. Background Technology

[0002] Existing integrated water and fertilizer management technologies for Gobi melons have significant limitations in data fusion. They fail to deeply integrate soil sensor data, meteorological monitoring data, and crop physiological image data from the planting area, and lack precise capture of key physiological characteristics such as leaf color and stem micro-changes. This results in an incomplete characterization of the effective water and fertilizer capacity in the root zone, failing to provide accurate data support for regulatory decisions. Furthermore, traditional technologies often rely on single-dimensional environmental parameters or empirical thresholds for water and fertilizer supply assessment, ignoring the dynamic correlation between environmental factors and crop physiological states. This leads to discrepancies between the assessed water and fertilizer demand and the actual demand, making it difficult to achieve precise supply-demand matching.

[0003] In the decision-making and execution stages of regulation, existing technologies lack effective virtual simulation mechanisms. Decision generation is mostly based on simple matching of fixed strategy libraries, failing to consider the dynamic response of soil moisture and nutrient concentration in the root zone after water and fertilizer application, resulting in insufficient adaptability and flexibility of the application strategies. Furthermore, traditional regulation systems lack fine-grained optimization of key parameters such as water-fertilizer mixing ratios and application duration, and the real-time linkage between equipment control and crop needs is poor. They cannot promptly correct execution commands based on changes in root zone conditions, ultimately leading to low accuracy and efficiency in water and fertilizer regulation. This results in resource waste and negatively impacts the growth stability and quality improvement of Gobi melons. Therefore, improving the efficiency of integrated water and fertilizer precision regulation for Gobi melons has become an urgent problem to be solved. Summary of the Invention

[0004] To achieve the above objectives, this invention provides a precise water and fertilizer integration system for Gobi melons, characterized in that the system includes a multi-source data integration module, a root zone water and fertilizer capacity map construction module, a water and fertilizer supply potential assessment module, a preliminary decision generation module, a virtual simulation module, and an instruction execution and control module, wherein:

[0005] The multi-source data integration module is used to integrate environmental data and crop physiological image data of the Gobi melon planting area into multi-source environmental data of Gobi melon;

[0006] The root zone water and fertilizer capacity map construction module is used to construct the root zone effective water and fertilizer capacity map of the Gobi melon based on the soil moisture distribution, light intensity and air temperature and humidity data and the growth correlation data of the Gobi melon in the multi-source environmental data, and based on the fusion characteristics of the leaf color, expansion degree and stem micro-change physiological data of the Gobi melon.

[0007] The water and fertilizer supply potential assessment module is used to assess the water and fertilizer supply potential of the rhizosphere microenvironment of the Gobi melon based on the effective water and fertilizer capacity map of the root zone, and obtain the water and fertilizer demand assessment value of the Gobi melon.

[0008] The preliminary decision generation module is used to map the water and fertilizer demand assessment value to the water and fertilizer application strategy library of the Gobi melon to obtain the preliminary water and fertilizer integrated application decision of the Gobi melon.

[0009] The virtual simulation module is used to virtually simulate the changes in the root zone state of the Gobi melon based on the effective water and fertilizer capacity map of the root zone and the preliminary water and fertilizer application decision, and encode and encapsulate the water and fertilizer mixing ratio and application duration parameters in the simulation results to obtain the final execution instructions for the Gobi melon planting area.

[0010] The instruction execution and control module is used to control the integrated water and fertilizer equipment to precisely irrigate and fertilize the Gobi melon planting area according to the final execution instruction.

[0011] In a preferred embodiment, when the multi-source data integration module integrates environmental data and crop physiological image data from the Gobi melon growing area into multi-source environmental data for Gobi melons, it is specifically used for:

[0012] Soil sensor data and meteorological monitoring data were collected from the Gobi melon growing area, and canopy multispectral image data and stem microscopic image data of the Gobi melon were acquired simultaneously.

[0013] The soil sensing data, meteorological monitoring data, canopy multispectral image data, and stem microscopic image data are spatiotemporally registered and aligned to obtain the original dataset of the Gobi melon.

[0014] The image data representing leaf color and spread in the original dataset are used as the physiological static feature set, and the data representing micro-changes in the stem epidermis are used as the physiological dynamic feature set.

[0015] The soil sensing data, the meteorological monitoring data, the physiological static feature set, and the physiological dynamic feature set are aggregated into multi-source environmental data for the Gobi melon.

[0016] In a preferred embodiment, the root zone water and fertilizer capacity map construction module, when constructing the effective water and fertilizer capacity map of the Gobi melon using the correlation data between soil moisture distribution, light intensity, and air temperature and humidity from the multi-source environmental data and the growth of the Gobi melon as a basis, and the fusion characteristics of leaf color, expansion, and stem micro-change physiological data of the Gobi melon as a criterion, is specifically used for:

[0017] The soil moisture distribution data, light intensity data, and air temperature and humidity data from the multi-source environmental data are used as the environmental baseline data for the Gobi melon.

[0018] The leaf color characteristics, leaf spread characteristics, and stem micro-change characteristics of the Gobi melon in the crop physiological image data are fused in multiple dimensions to obtain the physiological fusion feature data of the Gobi melon.

[0019] The environmental baseline data and the physiological fusion feature data are correlated and coupled at the spatial location corresponding to the root region in the Gobi melon to obtain the root region fusion data of the Gobi melon.

[0020] Based on the standard crop water and fertilizer demand response rules for Gobi melon, the root zone fusion data is mapped according to rules to obtain the effective water and fertilizer capacity map of the root zone of Gobi melon.

[0021] In a preferred embodiment, when the water and fertilizer supply potential assessment module performs a capacity assessment of the rhizosphere microenvironment water and fertilizer supply potential of the Gobi melon based on the effective water and fertilizer capacity map of the root zone, and obtains the water and fertilizer demand assessment value of the Gobi melon, it is specifically used for:

[0022] The effective water capacity distribution and effective nutrient capacity distribution information of the Gobi melon were determined from the effective water and fertilizer capacity map of the root zone.

[0023] The difference between the effective water capacity distribution information and the ideal root zone water saturation distribution threshold of the Gobi melon is obtained by performing a differential analysis.

[0024] The effective nutrient capacity distribution information is compared with the ideal root zone nutrient saturation distribution threshold of the Gobi melon to obtain the root zone nutrient supply potential difference value of the Gobi melon.

[0025] Based on the leaf spread and stem micro-change characteristics in the multi-source environmental data, the physiological state of water stress and nutrient deficiency of the Gobi melon is determined, and the physiological state is corrected for the difference in water supply potential and the difference in nutrient supply potential of the root zone according to the determination results.

[0026] Based on the corrected difference in root zone water supply potential and the difference in root zone nutrient supply potential, a comprehensive assessment is made of the water and fertilizer requirements for the growth of the Gobi melon, resulting in an assessment value for the water and fertilizer requirements of the Gobi melon.

[0027] In a preferred embodiment, the formula for calculating the water and fertilizer demand assessment value is as follows:

[0028] ;

[0029] In the formula, The water and fertilizer requirement assessment value is... The difference in water supply potential in the root zone. This is the normalization adjustment parameter for the coefficient of variation of the spatial distribution of root zone water capacity in the root zone effective nutrient capacity distribution information. The coefficient of variation of the spatial distribution of root zone water capacity in the effective nutrient capacity distribution information of the root zone is given. This refers to the infinitesimal change in the overall physiological state fusion index of the Gobi melon over time. The sampling and analysis cycle is fixed per unit time for the Gobi melon.

[0030] In a preferred embodiment, when the preliminary decision generation module maps the water and fertilizer demand assessment value to the water and fertilizer application strategy library of the Gobi melon to obtain the preliminary integrated water and fertilizer application decision for the Gobi melon, it is specifically used for:

[0031] Based on the growth stage identifiers and historical growth data of the Gobi melon and the soil type identifiers in the multi-source environmental data, a water and fertilizer application strategy library for the Gobi melon is constructed, and a candidate water and fertilizer application strategy set for the Gobi melon is selected.

[0032] The matching degree of the water and fertilizer demand assessment value is mapped with the strategy demand range in the water and fertilizer application strategy library to obtain the matching degree score of the water and fertilizer demand assessment value.

[0033] The candidate water and fertilizer application strategy with the highest matching score in the candidate water and fertilizer application strategy set is selected as the basic strategy.

[0034] Based on the specific magnitude of the water and fertilizer demand assessment value, the benchmark parameters of irrigation water volume, fertilizer application volume and water-fertilizer mixing ratio in the basic strategy are scaled proportionally to obtain the preliminary water and fertilizer application decision for the Gobi melon.

[0035] In a preferred embodiment, the matching score is calculated using the following formula:

[0036] ;

[0037] In the formula, Score the matching degree. Weighting coefficients are applied to the preset demand matching items. For the cosine similarity-based demand matching items of the Gobi melon, Let be a vector of the water and fertilizer demand assessment values. This represents the baseline demand vector for candidate strategies in the water and fertilizer application strategy library. The weighting coefficients are the preset environmental and growth stage adaptation factors. For the environmental and growth stage adaptation of the Gobi melon, The soil type suitability coefficient for the Gobi melon growing area is [missing information]. The adaptation coefficient for the growth stage of the Gobi melon is given. The importance weighting coefficient for the historical performance calibration term in the Gobi melon is given. This refers to the historical performance calibration item.

[0038] In a preferred embodiment, the virtual simulation module, when executing the virtual simulation of the root zone state changes of the Gobi melon based on the effective water and fertilizer capacity map of the root zone and applying the preliminary water and fertilizer application decision, and encoding and encapsulating the water and fertilizer mixing ratio and application duration parameters in the simulation results to obtain the final execution instruction for the Gobi melon planting area, is specifically used for:

[0039] Based on the effective water and fertilizer capacity map of the root zone and the preliminary water and fertilizer application decision, the root zone simulation and extrapolation conditions of the Gobi melon are determined;

[0040] Based on the simulation conditions of the root zone and the correlation between water and fertilizer capacity and soil environment in the effective water and fertilizer capacity map of the root zone, the dynamic response process of soil moisture and nutrient concentration in the root zone during the application of water and fertilizer in the Gobi melon planting area is deduced.

[0041] Based on the dynamic response process, the changes in key parameters in the initial fertigation decision are corrected to obtain the expected stable state of the Gobi melon.

[0042] The water-fertilizer mixing ratio and application duration obtained from the expected stable state are used as the key control parameters of the Gobi melon planting area.

[0043] According to the instruction encoding protocol of the integrated water and fertilizer equipment in the Gobi melon planting area, the key control parameters are formatted and encapsulated to obtain the final execution instructions for the Gobi melon planting area.

[0044] In a preferred embodiment, when the virtual simulation module determines the root zone simulation conditions for the Gobi melon based on the effective water and fertilizer capacity map of the root zone and the preliminary fertigation decision, it is specifically used for:

[0045] The spatial distribution data of the initial water and fertilizer capacity state of the rhizosphere microenvironment in the Gobi melon in the effective water and fertilizer capacity map of the root zone are used as the initial simulated state of the Gobi melon.

[0046] The parameters of irrigation water volume, fertilizer application volume, water-fertilizer mixing ratio and application duration in the preliminary water and fertilizer integration application decision-making process are used as external intervention factors for the Gobi melon.

[0047] Based on the soil moisture distribution data and air temperature and humidity data in the multi-source environmental data, the environmental variable constraints for the Gobi melon are determined.

[0048] The initial simulation state, the external intervention factors, and the environmental variable constraints are integrated into the root zone simulation and deduction conditions for the Gobi melon.

[0049] In a preferred embodiment, the instruction execution and control module, when executing the final execution instruction to control the integrated water and fertilizer equipment to precisely irrigate and fertilize the Gobi melon planting area, specifically performs the following functions:

[0050] The target irrigation water volume, target fertilizer application volume, target water-fertilizer mixing ratio, and target application area identifier in the final execution instruction are analyzed.

[0051] Based on the target application area identifier and the equipment area mapping relationship of the Gobi melon planting area, the water and fertilizer integrated equipment to be controlled is determined, and the control interface parameters and execution accuracy parameters of the water and fertilizer integrated equipment are obtained.

[0052] Based on the target irrigation water volume, target fertilizer application rate, target water-fertilizer mixing ratio, and the execution accuracy parameters, a set of underlying control instructions adapted to the integrated water and fertilizer equipment is generated.

[0053] The underlying control instruction set is sent to the corresponding integrated water and fertilizer equipment, and the integrated water and fertilizer equipment is driven to perform precision irrigation and fertilization operations in the Gobi melon planting area.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] 1. This invention utilizes multi-source data integration technology to comprehensively collect soil sensor data, meteorological monitoring data, and physiological data such as canopy multispectral images and stem microscopic images from the Gobi melon growing area. Through spatiotemporal registration, alignment, and feature classification, it forms a complete and closely correlated multi-source environmental data set, providing comprehensive and accurate data support for regulatory decisions. Simultaneously, it constructs an effective water and fertilizer capacity map of the root zone based on environmental baseline data and the physiological characteristics of leaves and stems, accurately depicting the water and fertilizer distribution in the root zone. Combined with a physiological state correction assessment mechanism, this significantly improves the accuracy of water and fertilizer demand assessment, laying a solid data and assessment foundation for subsequent precise regulation.

[0056] 2. This invention constructs a dedicated water and fertilizer application strategy library based on key information such as growth stage and soil type. Through matching degree mapping and proportional parameter scaling, it generates highly adaptable preliminary decisions. Then, a virtual simulation module is used to model the dynamic response process in the root zone after water and fertilizer application, real-time correction of control parameters, and encapsulation of standardized execution instructions to achieve dynamic optimization and precise implementation of decisions. Finally, by accurately parsing instructions, matching equipment control parameters, and issuing low-level control commands, it drives the integrated water and fertilizer equipment to efficiently execute irrigation and fertilization operations, significantly improving the accuracy and efficiency of water and fertilizer regulation, effectively ensuring the stability of the water and fertilizer environment in the root zone of Gobi melons, and contributing to the optimization of crop growth and quality improvement. Attached Figure Description

[0057] Figure 1 This is a system architecture diagram of a precision water and fertilizer integrated regulation system for Gobi melons provided in an embodiment of the present invention;

[0058] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments belong to some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “said” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0061] Depending on the context, the word "if" or "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0062] Furthermore, the timing of the steps in the following method embodiments is merely an example and not a strict limitation.

[0063] In practice, the server-side equipment deployed in a Gobi melon integrated water and fertilizer precision control system may consist of one or more devices. This Gobi melon integrated water and fertilizer precision control system can be implemented as: a business instance, a virtual machine, or hardware devices. For example, this Gobi melon integrated water and fertilizer precision control system can be implemented as a business instance deployed on one or more devices in a cloud node. Simply put, this Gobi melon integrated water and fertilizer precision control system can be understood as software deployed on a cloud node, used to provide a Gobi melon integrated water and fertilizer precision control system to various user terminals. Alternatively, this Gobi melon integrated water and fertilizer precision control system can also be implemented as a virtual machine deployed on one or more devices in a cloud node. This virtual machine contains application software for managing various user terminals. Alternatively, this Gobi melon integrated water and fertilizer precision control system can also be implemented as a server composed of numerous identical or different types of hardware devices, with one or more hardware devices configured to provide a Gobi melon integrated water and fertilizer precision control system to various user terminals.

[0064] In terms of implementation, the integrated water and fertilizer precision control system for Gobi melons and the user terminal are mutually compatible. That is, if the integrated water and fertilizer precision control system for Gobi melons is implemented as an application installed on a cloud service platform, then the user terminal is a client that establishes a communication connection with the application; or if the integrated water and fertilizer precision control system for Gobi melons is implemented as a website, then the user terminal is implemented as a webpage; or if the integrated water and fertilizer precision control system for Gobi melons is implemented as a cloud service platform, then the user terminal is implemented as a mini-program in an instant messaging application.

[0065] like Figure 1 The diagram shown is a system architecture diagram of a precision water and fertilizer integration system for Gobi melons provided in an embodiment of the present invention.

[0066] The Gobi melon integrated water and fertilizer precision control system 100 described in this invention can be set up in a cloud server. In terms of implementation, it can be used as one or more service devices, or as an application installed in the cloud (e.g., a mobile service operator's server, server cluster, etc.), or it can be developed into a website. Depending on the functions implemented, the Gobi melon integrated water and fertilizer precision control system 100 may include a multi-source data integration module 101, a root zone water and fertilizer capacity map construction module 102, a water and fertilizer supply potential assessment module 103, a preliminary decision generation module 104, a virtual simulation module 105, and an instruction execution and control module 106. The modules described in this invention can also be called units, referring to a series of computer program segments that can be executed by an electronic device's processor and perform a fixed function, stored in the electronic device's memory.

[0067] In this embodiment of the invention, in a precision water and fertilizer integration system for Gobi melons, each of the above-mentioned modules can be implemented independently and can be invoked by other modules. Invocation here can be understood as a module connecting to multiple modules of another type and providing corresponding services to the connected modules. In the precision water and fertilizer integration system for Gobi melons provided by this embodiment of the invention, the applicable scope of the system architecture can be adjusted by adding modules and directly invoking them without modifying the program code, achieving cluster-based horizontal expansion to quickly and flexibly expand the precision water and fertilizer integration system for Gobi melons. In practical applications, the above modules can be set in the same device or different devices, or they can be set in a virtual device, such as a service instance in a cloud server.

[0068] The following describes, with reference to specific embodiments, each component and specific workflow of a Gobi melon integrated water and fertilizer precision control system:

[0069] The multi-source data integration module 101 is used to integrate environmental data and crop physiological image data of the Gobi melon planting area into multi-source environmental data of Gobi melon.

[0070] In this embodiment of the invention, when the multi-source data integration module integrates environmental data and crop physiological image data of the Gobi melon planting area into multi-source environmental data for Gobi melons, it is specifically used for:

[0071] Soil sensor data and meteorological monitoring data were collected from the Gobi melon growing area, and canopy multispectral image data and stem microscopic image data of the Gobi melon were acquired simultaneously.

[0072] The soil sensing data, meteorological monitoring data, canopy multispectral image data, and stem microscopic image data are spatiotemporally registered and aligned to obtain the original dataset of the Gobi melon.

[0073] The image data representing leaf color and spread in the original dataset are used as the physiological static feature set, and the data representing micro-changes in the stem epidermis are used as the physiological dynamic feature set.

[0074] The soil sensing data, the meteorological monitoring data, the physiological static feature set, and the physiological dynamic feature set are aggregated into multi-source environmental data for the Gobi melon.

[0075] Sampling points were evenly distributed throughout the Gobi melon growing area to ensure comprehensive coverage and balanced distribution. Soil sensors were vertically embedded in the soil at each sampling point, with the sensor probes in close contact with the soil to avoid air gaps affecting data acquisition accuracy. Data on soil humidity, temperature, and pH were continuously collected from each sampling point, and the collected information was recorded and stored periodically. A meteorological monitoring station was installed in the center of the growing area, in an open and unobstructed location. The station's sensors avoided ground obstacles and plant obstructions to accurately capture the environmental meteorological conditions of the growing area. Real-time data on wind speed, wind direction, precipitation, temperature, air humidity, and sunshine duration were collected, recorded, and stored periodically. Simultaneously, a drone equipped with a multispectral camera was operated, maintaining stable flight altitude and clear imagery of the Gobi melons. The canopy was captured using a pre-designed flight path at a constant speed to ensure that the multispectral images captured completely covered the canopy of each Gobi melon plant, and that the image clarity was sufficient to distinguish the subtle morphology of the leaves. A portable biological microscope was used, adjusted to a magnification suitable for observing the microstructure of the stem epidermis. Typical parts of the stems of Gobi melon plants near each sampling point were selected, and the microscope lens was held firmly against the stem epidermis to avoid lens shake affecting the imaging effect. Multiple angles were used to capture the subtle features of the stem epidermis. During all data collection, the collection time and location of each data point were recorded simultaneously to ensure that the collection time of soil sensor data, meteorological monitoring data, canopy multispectral image data, and stem microscopic image data remained synchronized, and that the collection locations corresponded one-to-one, laying the foundation for subsequent data integration.

[0076] The collected soil sensor data, meteorological monitoring data, canopy multispectral image data, and stem microscopic image data were time-aligned and naturally grouped according to the collection time to ensure that all types of data within the same time period are grouped together. If a certain type of data is missing within a time period, the corresponding data from the nearest adjacent time period is selected to supplement the group, ensuring that each data group completely contains all four types of data. During spatial alignment, based on the sampling point identifiers set before collection, the soil sensor data corresponding to each sampling point and the stem microscopic image data of plants near the sampling point are associated with the image data of the area where the sampling point is located in the canopy multispectral image taken by the UAV. At the same time, the regional meteorological data collected by the meteorological monitoring station is synchronously associated with the corresponding data groups of all sampling points. Through the dual guarantee of time association and spatial identification, the complete matching and integration of the four types of data is achieved, and finally, the original dataset of Gobi melon containing time information, spatial information, soil sensor data, meteorological monitoring data, canopy multispectral image data, and stem microscopic image data is formed.

[0077] Extract the canopy multispectral image data from the original dataset, and meticulously examine the leaf morphology in each image. Using a standard color chart as a reference, compare and determine the color category of the leaves in each image, such as dark green, emerald green, light green, and yellowish green. Simultaneously, carefully observe the extension state of the leaf edges and midribs to determine whether the leaves are fully extended, partially curled, or severely curled. Organize all recorded leaf color descriptions and extension judgments, along with the corresponding canopy multispectral image fragments, to ensure that each feature description accurately corresponds to the original image data, forming a characterization of leaf color. Physiological static feature set of stem epidermis and slenderness; extract stem microscopic image data from the original dataset, magnify and observe the texture structure of the stem epidermis in each image, record the basic features such as the density of epidermal cell arrangement and texture direction, and carefully check for subtle changes such as microcracks, protrusions, and depressions in the epidermis. Record the morphology, location and range of these micro-changes in detail. Systematically organize all recorded descriptions of micro-changes in the stem epidermis and the corresponding stem microscopic image fragments to ensure that the feature data corresponds one-to-one with the original images, forming a physiological dynamic feature set of data characterizing micro-changes in the stem epidermis.

[0078] All soil sensor data from the original dataset were extracted and systematically organized according to the collection time sequence and sampling point identification. Duplicate data were removed, and missing data was added appropriately to ensure the continuity and accuracy of the soil sensor data. All meteorological monitoring data were sorted according to the collection time sequence to form a continuous and complete meteorological data sequence, ensuring that the meteorological data for each time period is clearly traceable. The organized physiological static feature set and physiological dynamic feature set were comprehensively checked to confirm that each data in the feature set accurately corresponds to a specific image in the original dataset, and that the feature description truly reflects the actual situation in the image. Finally, the organized soil sensor data, meteorological monitoring data, physiological static feature set, and physiological dynamic feature set were all aggregated into the same data storage medium and classified and arranged according to the "time-space-data type" hierarchy to clarify the correlation between various types of data and ensure that relevant data can be quickly retrieved and called in subsequent use. In the end, a multi-source environmental data of Gobi melons was compiled.

[0079] The beneficial effects include comprehensively capturing data related to environmental conditions and crop physiological states in the Gobi melon growing area. Through the scientific layout of sampling points and monitoring equipment, the collection of soil sensor data, meteorological monitoring data, canopy multispectral image data, and stem microscopic image data is ensured to be complete and highly targeted, accurately reflecting the overall and local environmental characteristics and crop growth status of the growing area. By synchronously recording the data collection time and location, combined with standardized spatiotemporal registration processing, precise alignment of various data in time and space dimensions is achieved, ensuring the integrity and consistency of the original dataset and avoiding analytical biases caused by data misalignment. Through clear feature extraction standards, the physiological static feature set and physiological dynamic feature set are accurately separated, clearly presenting key physiological information such as leaf color and expansion, and micro-changes in the stem epidermis, providing a clear basis for subsequent analysis of the correlation between crop growth status and environmental conditions. Through systematic data analysis, organization, and hierarchical summarization, a well-structured and clearly correlated multi-source environmental data is formed, ensuring data traceability and easy retrieval. This provides comprehensive, accurate, and reliable data support for environmental control, growth status monitoring, and planting strategy optimization in the Gobi melon growing process, effectively improving the scientific nature and targeted nature of planting management.

[0080] The root zone water and fertilizer capacity map construction module 102 is used to construct the root zone effective water and fertilizer capacity map of the Gobi melon based on the soil moisture distribution, light intensity and air temperature and humidity data and the growth correlation data of the Gobi melon in the multi-source environmental data, and based on the fusion characteristics of the leaf color, expansion degree and stem micro-change physiological data of the Gobi melon.

[0081] In this embodiment of the invention, when the root zone water and fertilizer capacity map construction module constructs a root zone effective water and fertilizer capacity map of the Gobi melon, based on the correlation data between soil moisture distribution, light intensity, and air temperature and humidity in the multi-source environmental data and the growth of the Gobi melon, and using the fusion characteristics of leaf color, expansion, and stem micro-change physiological data of the Gobi melon as criteria, it is specifically used for:

[0082] The soil moisture distribution data, light intensity data, and air temperature and humidity data from the multi-source environmental data are used as the environmental baseline data for the Gobi melon.

[0083] The leaf color characteristics, leaf spread characteristics, and stem micro-change characteristics of the Gobi melon in the crop physiological image data are fused in multiple dimensions to obtain the physiological fusion feature data of the Gobi melon.

[0084] The environmental baseline data and the physiological fusion feature data are correlated and coupled at the spatial location corresponding to the root region in the Gobi melon to obtain the root region fusion data of the Gobi melon.

[0085] Based on the standard crop water and fertilizer demand response rules for Gobi melon, the root zone fusion data is mapped according to rules to obtain the effective water and fertilizer capacity map of the root zone of Gobi melon.

[0086] Representative plants from the Gobi melon growing area were selected as monitoring subjects. The root zone of each melon plant was divided into surface, middle, and deep layers. Multiple monitoring points were evenly distributed horizontally at each depth, with a soil moisture sensor installed at each point. The sensor probe was fully inserted into the soil at a suitable distance from the roots. Soil moisture data was recorded once a day during three fixed periods when light and temperature were relatively stable. This monitoring was conducted continuously for a complete growth cycle to obtain soil moisture distribution data. Multiple light intensity sensors were evenly distributed within the growing area, installed at the same height as the top of the melon plant, avoiding leaf shading. Light intensity data was recorded at fixed intervals from sunrise to sunset each day, continuously monitoring the same growth cycle to obtain light intensity data. Air temperature and humidity sensors were installed at appropriate distances from each monitoring plant, with the sensors positioned at a suitable height above the ground. Air temperature and humidity data were recorded daily during three fixed periods plus one period before sunset, continuously monitoring the same period to collect air temperature and humidity data. The collected soil moisture distribution data, light intensity data, and air temperature and humidity data were compiled into environmental baseline data for Gobi melons.

[0087] Using a high-definition digital camera, the leaves of the monitored plants were photographed at fixed times each day under stable lighting conditions. During photography, the camera lens was kept at an appropriate distance from the leaves, perpendicular to the leaf surface, ensuring consistent resolution and no shadows in each image. By observing the color of the leaves in the photos, information such as the overall shade of green, the presence of yellowing or withered areas, and the uniformity of color distribution were recorded, forming leaf color characteristic data. The entire melon plant was photographed using the same high-definition digital camera, focusing on capturing the morphology of the connection between the leaves and the stem. By observing the extent of leaf spread, it was determined whether the leaf edges were curled, the angle between the leaves and the stem, and whether adjacent leaves overlapped or pressed together, thus determining the leaf's unfolding state and forming leaf unfolding characteristic data. Mark the middle of the plant's stem and use a high-precision laser rangefinder to measure the marked point at a fixed time each day. Record the changes in the lateral width of the stem at the marked point, whether there are slight bends or tilts, and whether there are shrinkage wrinkles or other subtle changes. Continuously monitor and organize the stem micro-change characteristic data to form the data. Integrate the leaf color characteristic data, leaf expansion characteristic data, and stem micro-change characteristic data, and record the specific manifestations of each characteristic in relation to each other. For example, when the leaf color is dark green, the corresponding leaf expansion state and stem micro-changes are recorded. Finally, physiological fusion characteristic data of Gobi melon are formed.

[0088] Based on the growth range of the Gobi melon root system, the root zone of each melon plant is divided horizontally into inner, middle, and outer zones centered on the stem, while maintaining the vertical division into surface, middle, and deep layers. This method effectively divides the root zone into multiple distinct spatial locations. For each root zone location, soil moisture distribution data, light intensity data, and air temperature and humidity data for the plant parts supplied with nutrients at that location are extracted, forming an environmental baseline data subset for that location. Then, based on the correspondence between the root zone spatial location and the above-ground parts of the plant, the leaves and stem parts supported by the roots at that location are identified, and their physiological fusion characteristic data are extracted, forming a physiological fusion characteristic data subset for that location. The environmental baseline data subset and the physiological fusion characteristic data subset for each root zone spatial location are then linked one-to-one, clearly indicating the environmental conditions and physiological characteristics simultaneously present at each root zone spatial location, ultimately yielding the root zone fusion data for the Gobi melon.

[0089] Pre-established standard crop water and fertilizer demand response rules for Gobi melons. These rules, based on the growth characteristics of Gobi melons, specify the effective water and fertilizer capacity requirements corresponding to different combinations of environmental conditions and physiological characteristics. For example, when environmental baseline data at a certain location in the root zone shows that soil moisture is within a suitable range, light intensity is within a suitable range, and air temperature and humidity are both at suitable levels, while physiological fusion characteristics show that leaves are dark green, fully expanded without curling, and the stem width is stable without shrinkage, the effective water and fertilizer capacity at that location is to maintain adequate water and nutrients per unit volume of soil. Conversely, when environmental baseline data shows that soil moisture is below the suitable range, light intensity is above the suitable range, air temperature is above the suitable level, and air humidity is below the suitable range, while physiological fusion characteristics show that leaves are yellowish, leaf edges are curled, and the stem width is slightly shrinking, the effective water and fertilizer capacity at that location is to maintain a small amount of water and adequate nutrients per unit volume of soil. Similar logic is used to define the effective water and fertilizer capacity standards corresponding to all possible environmental and physiological combinations. The environmental baseline data and physiological fusion feature data of each spatial location in the root zone fusion data are compared one by one with the above-mentioned standard crop water and fertilizer demand response rules. The rule entries that match perfectly are found, and the specific effective water and fertilizer capacity corresponding to the spatial location of the root zone is determined. The effective water and fertilizer capacity of all spatial locations of the root zone are arranged according to their actual spatial distribution in the root zone, and the effective water and fertilizer capacity of each spatial location is presented intuitively with different colors or brightness levels. Finally, the effective water and fertilizer capacity map of the root zone of Gobi melon is constructed.

[0090] The beneficial effects include: systematically collecting environmental data such as soil moisture distribution, light intensity, and air temperature and humidity in the Gobi melon planting area to form comprehensive environmental baseline data, providing a solid environmental foundation for root zone water and fertilizer capacity analysis. By capturing and fusing physiological characteristics such as leaf color, leaf spread, and micro-changes in stems from multiple dimensions, precise physiological fusion characteristic data reflecting plant growth status is obtained, ensuring accurate judgment of crop growth. The environmental baseline data and physiological fusion characteristic data are correlated and coupled at specific spatial locations in the root zone, enabling the root zone fusion data to accurately correspond to environmental conditions and crop physiological performance at different spatial locations, achieving a deep integration of environmental and physiological information. Mapping the root zone fusion data according to the standard water and fertilizer demand response rules for Gobi melons, the constructed root zone effective water and fertilizer capacity map can intuitively present the effective water and fertilizer requirements of different root zone spaces, providing a scientific basis for precise water and fertilizer management of Gobi melons, avoiding water and fertilizer waste or insufficient supply, ensuring healthy crop growth, and improving planting efficiency.

[0091] The water and fertilizer supply potential assessment module 103 is used to assess the water and fertilizer supply potential of the rhizosphere microenvironment of the Gobi melon based on the effective water and fertilizer capacity map of the root zone, and obtain the water and fertilizer demand assessment value of the Gobi melon.

[0092] In this embodiment of the invention, when the water and fertilizer supply potential assessment module performs a capacity assessment of the rhizosphere microenvironment water and fertilizer supply potential of the Gobi melon based on the effective water and fertilizer capacity map of the root zone, and obtains the water and fertilizer demand assessment value of the Gobi melon, it is specifically used for:

[0093] The effective water capacity distribution and effective nutrient capacity distribution information of the Gobi melon were determined from the effective water and fertilizer capacity map of the root zone.

[0094] The difference between the effective water capacity distribution information and the ideal root zone water saturation distribution threshold of the Gobi melon is obtained by performing a differential analysis.

[0095] The effective nutrient capacity distribution information is compared with the ideal root zone nutrient saturation distribution threshold of the Gobi melon to obtain the root zone nutrient supply potential difference value of the Gobi melon.

[0096] Based on the leaf spread and stem micro-change characteristics in the multi-source environmental data, the physiological state of water stress and nutrient deficiency of the Gobi melon is determined, and the physiological state is corrected for the difference in water supply potential and the difference in nutrient supply potential of the root zone according to the determination results.

[0097] Based on the corrected difference in root zone water supply potential and the difference in root zone nutrient supply potential, a comprehensive assessment is made of the water and fertilizer requirements for the growth of the Gobi melon, resulting in an assessment value for the water and fertilizer requirements of the Gobi melon.

[0098] The root zone water supply potential difference is obtained through measurement and calculation. During the measurement, soil moisture sensors are used to collect the actual soil moisture content at different locations in the root zone of Gobi melon. At the same time, the suitable water content in the root zone is determined by combining the suitable water range for the growth stage of Gobi melon. The difference between the suitable water content and the actual water content is the root zone water supply potential difference.

[0099] The normalization adjustment parameter for the coefficient of variation of the spatial distribution of effective nutrient capacity in the root zone is a pre-set fixed value. When setting it, a large amount of spatial distribution data of root zone water capacity is first analyzed to determine the normal range of the coefficient of variation. The maximum value of this range is used as the benchmark. The normalization coefficient is obtained by dividing 1 by the benchmark value. This coefficient is the normalization adjustment parameter for the coefficient of variation of the spatial distribution of root zone water capacity, ensuring that the coefficient of variation is within the range of 0 to 1 after adjustment.

[0100] The coefficient of variation of the spatial distribution of root zone water capacity in the information on the distribution of effective nutrient capacity in the root zone is obtained by statistically analyzing the root zone water capacity data. During the statistical analysis, the root zone is divided into multiple uniform sampling units, the water capacity of each unit is measured, the average water capacity of all units is calculated, the difference between the water capacity of each unit and the average value is calculated and squared, the average of all squared differences is calculated and the square root is taken to obtain the standard deviation, and the result obtained by dividing the standard deviation by the average value is the coefficient of variation of the spatial distribution of root zone water capacity.

[0101] The infinitesimal change in the overall physiological state fusion index of Gobi melon over time is calculated through continuous monitoring. During monitoring, core indicators that can reflect the physiological state of Gobi melon are selected, and these indicators are fused into an overall physiological state fusion index according to preset weights. The values ​​of the fusion index are recorded in two adjacent sampling periods. The difference between the value of the next period and the value of the previous period is the infinitesimal change in the overall physiological state fusion index over time.

[0102] The fixed sampling and analysis cycle per unit time for Gobi melons is set based on the growth characteristics of Gobi melons. When setting the cycle, the physiological metabolic rate of Gobi melons at different growth stages is taken into account. Shorter time intervals are selected during the rapid growth period and longer time intervals are selected during the slow growth period. Taking into account the actual convenience of field management, a fixed time length is determined as the unit sampling and analysis cycle. Once the cycle is determined, it remains unchanged throughout the entire evaluation process.

[0103] The water and fertilizer demand assessment value is a quantitative indicator that comprehensively reflects the current water and fertilizer demand of Gobi melons. Its value directly reflects the amount of water and fertilizer resources needed to meet the growth needs of melons.

[0104] The difference in root zone water supply potential is the basis for assessment. The larger the difference, the greater the gap between the current water supply and the appropriate supply in the root zone, and the higher the basic value of water and fertilizer demand.

[0105] The coefficient of variation of the spatial distribution of root zone water capacity reflects the uniformity of water distribution in the root zone. The larger the coefficient of variation, the more uneven the water distribution. After being corrected by the normalization adjustment parameter, it is added to 1 to form an adjustment term, so that the evaluation value is increased accordingly when the water distribution is uneven, in order to make up for the impact of local water shortage.

[0106] The time change rate of the overall physiological state fusion index reflects the dynamic changes in the physiological state of melons. A positive change rate indicates that the physiological state is improving and the demand for water and fertilizer is increasing accordingly. The greater the change rate, the faster the demand is increasing.

[0107] Multiplying the root zone water supply potential difference, the spatial distribution regulation term, and the physiological state time change rate, the resulting water and fertilizer demand assessment value integrates three factors: water supply difference, spatial distribution uniformity, and physiological dynamic changes, which can accurately match the actual water and fertilizer needs of Gobi melons.

[0108] When the difference in the potential water supply in the root zone increases, the assessment value of water and fertilizer demand will also increase, and the increase is positively correlated with the increase in the difference, indicating that the larger the water supply gap, the more urgent the need for water and fertilizer supplementation.

[0109] When the coefficient of variation of the spatial distribution of root zone water capacity increases, the value after normalization adjustment also increases, leading to an increase in the sum of 1 and the adjusted value, which in turn increases the water and fertilizer demand assessment value. This indicates that the more uneven the distribution of water in the root zone, the more water and fertilizer needs to be supplemented to ensure the growth of melons in all areas.

[0110] When the time change rate of the overall physiological state fusion index of Gobi melon increases, that is, the faster the physiological state improves in adjacent sampling periods, the water and fertilizer demand assessment value will increase synchronously, because the rapid improvement of physiological state means that the melon consumes water and fertilizer at a faster rate and needs more water and fertilizer to support growth.

[0111] When the difference in root zone water supply potential and the rate of change of physiological state over time increase simultaneously, they will have a synergistic effect, making the increase in the water and fertilizer demand assessment value greater than the increase when a single parameter increases. The increase in the coefficient of variation of spatial distribution will further amplify this synergistic effect, forming a high demand scenario of "large gap, rapid consumption, and poor distribution". Conversely, when all three decrease, the assessment value will decrease significantly, corresponding to a low demand state of "small gap, slow consumption, and even distribution".

[0112] The beneficial effects are as follows: By accurately dividing the distribution of effective water capacity and effective nutrient capacity in the root zone from the effective water and fertilizer capacity map, clear basic data support is provided for assessing water and fertilizer supply potential. Difference analysis between the effective water capacity distribution and the ideal root zone water saturation distribution threshold accurately yields the difference in root zone water supply potential, clarifying the surplus or deficit of water supply. By comparing the deviation between the effective nutrient capacity distribution and the ideal root zone nutrient saturation distribution threshold, the difference in root zone nutrient supply potential is accurately obtained, clearly understanding the supply and demand differences of nutrients. Combining leaf expansion and stem micro-change characteristics to determine the plant's water stress and nutrient deficit status, targeted corrections are made to the differences in water and nutrient supply potential, improving the accuracy and relevance of the differences. Based on the corrected differences, a comprehensive assessment of the required supplemental water and fertilizer for growth is obtained, yielding accurate water and fertilizer demand assessment values. This provides a scientific basis for water and fertilizer management of Gobi melons, achieving precise water and fertilizer supply, avoiding waste or insufficient supply, optimizing the rhizosphere microenvironment, ensuring healthy plant growth, and improving yield and quality.

[0113] The preliminary decision generation module 104 is used to map the water and fertilizer demand assessment value to the water and fertilizer application strategy library of the Gobi melon to obtain the preliminary water and fertilizer integrated application decision of the Gobi melon.

[0114] In this embodiment of the invention, when the preliminary decision generation module maps the water and fertilizer demand assessment value to the water and fertilizer application strategy library of the Gobi melon to obtain the preliminary integrated water and fertilizer application decision for the Gobi melon, it is specifically used for:

[0115] Based on the growth stage identifiers and historical growth data of the Gobi melon and the soil type identifiers in the multi-source environmental data, a water and fertilizer application strategy library for the Gobi melon is constructed, and a candidate water and fertilizer application strategy set for the Gobi melon is selected.

[0116] The matching degree of the water and fertilizer demand assessment value is mapped with the strategy demand range in the water and fertilizer application strategy library to obtain the matching degree score of the water and fertilizer demand assessment value.

[0117] The candidate water and fertilizer application strategy with the highest matching score in the candidate water and fertilizer application strategy set is selected as the basic strategy.

[0118] Based on the specific magnitude of the water and fertilizer demand assessment value, the benchmark parameters of irrigation water volume, fertilizer application volume and water-fertilizer mixing ratio in the basic strategy are scaled proportionally to obtain the preliminary water and fertilizer application decision for the Gobi melon.

[0119] The matching score is calculated using the following formula:

[0120] ;

[0121] In the formula, Score the matching degree. Weighting coefficients are applied to the preset demand matching items. For the cosine similarity-based demand matching items of the Gobi melon, Let be a vector of the water and fertilizer demand assessment values. This represents the baseline demand vector for candidate strategies in the water and fertilizer application strategy library. The weighting coefficients are the preset environmental and growth stage adaptation factors. For the environmental and growth stage adaptation of the Gobi melon, The soil type suitability coefficient for the Gobi melon growing area is [missing information]. The adaptation coefficient for the growth stage of the Gobi melon is given. The importance weighting coefficient for the historical performance calibration term in the Gobi melon is given. This refers to the historical performance calibration item.

[0122] First, the growth stage of the Gobi melon was determined by observing its plant height, leaf quantity, flowering status, and fruiting condition. Historical growth data was compiled by collecting records of water and fertilizer application and growth performance data from previous plantings of this variety in the same area at different growth stages. Then, soil type was identified from multi-source environmental data by touching the soil texture, observing soil particle structure, and assessing water and fertilizer retention capacity. The growth stage, historical growth data, and soil type were correlated. For each growth stage and soil type combination, appropriate irrigation water volume, fertilizer application rate, and water-fertilizer mixing ratio were determined. These specific water and fertilizer application parameter combinations constituted a water and fertilizer application strategy library for the Gobi melon. From this library, all water and fertilizer application parameter combinations that perfectly matched the current growth stage and soil type of the Gobi melon were selected. These selected parameter combinations were then integrated to form a candidate water and fertilizer application strategy set for the Gobi melon.

[0123] The water and fertilizer requirement ranges for each candidate water and fertilizer application strategy are extracted one by one. These ranges include both water and nutrient requirement intervals. The water requirement assessment portion of the obtained water and fertilizer requirement evaluation value for Gobi melons is compared with the water requirement interval of each strategy, and the nutrient requirement assessment portion is also compared with the nutrient requirement interval of each strategy. If both the water and nutrient requirements of the water and fertilizer requirement evaluation value are completely within the requirement interval of a certain strategy and close to the midpoint of that interval, a high matching score is given to that strategy; if only one is within the interval and the other is close to the interval boundary, a medium matching score is given; if both are outside the interval range, a low matching score is given. This comparison method yields the matching score between the water and fertilizer requirement evaluation value and each candidate strategy.

[0124] The matching scores of all candidate water and fertilizer application strategies were organized and ranked, and the scores of each strategy were compared one by one to identify the candidate water and fertilizer application strategy with the highest score. If two or more candidate strategies had the same score and were all the highest, historical growth data were consulted to compare the application effects of these strategies with the same score under the same growth stage and soil type conditions in the past. The strategy that resulted in better growth and higher yield of Gobi melons was selected as the basic strategy to ensure the applicability and effectiveness of the basic strategy.

[0125] The specific magnitude of the water and fertilizer demand assessment value is clearly defined and compared with the median value of the water and fertilizer demand range in the basic strategy. If the assessed water and fertilizer demand value is higher than the median value, the irrigation water and fertilizer application in the basic strategy are increased proportionally according to the ratio between the assessed value and the median value, while keeping the water and fertilizer mixing ratio unchanged. If the assessed water and fertilizer demand value is lower than the median value, the irrigation water and fertilizer application in the basic strategy are reduced proportionally according to the same ratio, while the water and fertilizer mixing ratio remains unchanged. Through this proportional scaling adjustment, the parameters of the basic strategy are precisely matched with the actual water and fertilizer demand assessment value of the Gobi melon, ultimately forming a preliminary decision on the integrated water and fertilizer application for Gobi melons.

[0126] The preset weighting coefficients for demand matching items are set based on the importance of the demand matching items to the matching score. During the setting process, a large amount of historical matching data on water and fertilizer application strategies are collected, and the correlation between the matching results of demand matching items and the final strategy implementation effect is statistically analyzed. The higher the correlation, the larger the weighting coefficient. At the same time, it is ensured that the sum of this coefficient and other weighting coefficients and importance weighting coefficients is a fixed benchmark. This fixed benchmark is predetermined according to the scoring range requirements, and finally, the corresponding quantitative value is obtained.

[0127] The cosine similarity-based demand matching term for Gobi melons is obtained by calculating the cosine similarity of two vectors. The calculation first extracts the vector of water and fertilizer demand assessment values ​​and the baseline demand vector of candidate strategies in the water and fertilizer application strategy library. The vector of water and fertilizer demand assessment values ​​contains quantitative information on the specific needs of Gobi melons for various nutrients and water. The baseline demand vector of candidate strategies contains quantitative information on the baseline water and fertilizer needs adapted to that strategy. Then, the dot product of the two vectors is calculated, and the magnitude of each vector is calculated separately. The magnitude of the vector is obtained by the square root of the sum of the squares of each component of the vector. Finally, the dot product of the vectors is divided by the product of the magnitudes of the two vectors. The result is the demand matching term based on cosine similarity. The closer the result is to the baseline fit value, the higher the demand matching degree.

[0128] The vector of water and fertilizer demand assessment values ​​is formed by expanding the water and fertilizer demand assessment values. During the expansion, the water and fertilizer demand assessment values ​​are taken as the core, and combined with the proportion of different types of nutrients required by Gobi melons, the assessment values ​​are decomposed into multiple nutrient demand components and water demand components according to the proportion. These components are arranged in a predetermined unified order to form an ordered set of values, which is the vector of water and fertilizer demand assessment values.

[0129] The baseline demand vector of the candidate strategies in the water and fertilizer application strategy library comes from the water and fertilizer application strategy library. When constructing this strategy library, for each candidate strategy, the water and fertilizer demand characteristics of the Gobi melon that it is applicable to are analyzed, and the baseline information of various nutrient and water requirements that the strategy can meet is determined. These baseline information are arranged in the same order as the water and fertilizer demand assessment value vector to form an ordered set of values ​​and are entered into the strategy library. This set is the baseline demand vector of the candidate strategy.

[0130] The preset weighting coefficients for environment and growth stage adaptation items are set based on the degree of influence of environment and growth stage adaptation items. When setting them, the proportion of the influence of environment and growth stage adaptation on the strategy implementation effect in historical data is referenced. The higher the proportion of influence, the larger the weighting coefficient. At the same time, it is combined with the preset weighting coefficients for demand matching items to ensure that the sum of the two and the importance weight coefficients meets the balance requirements of the scoring range, and finally the corresponding quantitative value is determined.

[0131] The environmental and growth stage suitability of Gobi melons is obtained by calculating normalized difference values. In the calculation, the range of soil type suitability coefficient and growth stage suitability coefficient is first defined as a fixed range. The absolute difference between the two coefficients is calculated, and the difference is divided by the upper limit of the range. The result is the normalized environmental and growth stage suitability. The closer the result is to the suitability benchmark value, the better the environmental and growth stage suitability.

[0132] The soil type suitability coefficient for Gobi melon growing areas is determined based on the compatibility between soil type and candidate strategies. When determining the soil type suitability coefficient, the soil physicochemical properties of the candidate strategies are analyzed, including water and fertilizer retention capacity, pH balance, etc. The actual physicochemical indicators of the soil in the growing area are obtained through professional testing methods. The actual indicators are compared with the physicochemical indicators of the candidate strategies to quantify the degree of fit between the two and obtain the corresponding value. The higher the degree of fit, the closer the value is to the upper limit of suitability. This value is the soil type suitability coefficient.

[0133] The growth stage fit coefficient of Gobi melon is determined based on the degree of matching between the growth stage and the candidate strategy. When determining the growth stage, the candidate strategy is specifically targeted at the growth stage of Gobi melon, including key stages such as seedling stage, flowering and fruit setting stage, and fruit expansion stage. The actual growth stage of Gobi melon is determined by observing plant morphology, growth status and other characteristics. The degree of fit between the actual stage and the fit stage of the candidate strategy is quantified to obtain the corresponding value. When there is a perfect fit, the value reaches the upper limit of fit. The greater the deviation, the closer the value is to the lower limit of fit. This value is the growth stage fit coefficient.

[0134] The importance weighting coefficient of the historical performance calibration item in Gobi melon is set based on the calibration effect of the historical performance calibration item. When setting it, the improvement effect of the historical performance calibration item on the accuracy of the matching score is statistically analyzed in historical data. The more significant the improvement effect, the larger the weighting coefficient. At the same time, it is combined with the weighting coefficients of the first two items to ensure that the sum of the three meets the overall balance requirements of the score calculation, and finally the corresponding quantitative value is determined.

[0135] Historical performance calibration items are obtained through historical data statistics. During the statistics, historical implementation cases with the same planting conditions, melon varieties, and candidate strategies as the current ones are collected. The ratio of the actual implementation effect to the expected effect of the strategy in these cases is calculated. The average level of the ratios of all cases is taken, and this average level is the historical performance calibration item. If the ratio exceeds the expected benchmark, it means that the historical effect is better than expected, and the calibration item will improve the matching score accordingly.

[0136] The matching score is a quantitative indicator that comprehensively measures the degree to which candidate strategies in the water and fertilizer application strategy library are adapted to the current needs, growth environment, and historical effects of Gobi melons. Its value directly determines the priority ranking of candidate strategies. The demand matching item is the core foundation of the score, directly reflecting the degree of fit between the baseline demand of the candidate strategies and the actual water and fertilizer needs of the melons. This part amplifies its core role in the score through corresponding weighting coefficients, ensuring that strategies with high demand matching scores receive a basic score advantage.

[0137] The adaptation of environment and growth stage is transformed into a positive score contribution by subtracting the normalized difference value from the fixed baseline value. The better the adaptation, the greater the contribution value of this part. This effectively makes up for the shortcomings of only considering demand matching while ignoring the limitations of environment and growth stage, and makes the score more in line with the actual planting scenario.

[0138] The historical effectiveness calibration item adjusts the score based on historical implementation results, avoiding the problem of a disconnect between theoretical matching and actual application effects. Its influence on the final score is adjusted by corresponding importance weight coefficients, making the score results more practically valuable. After adjusting the contribution ratio of the three factors through their respective weighting coefficients, they are summed to obtain a matching score that comprehensively integrates key information from the three dimensions of demand alignment, environmental adaptability, and historical effectiveness, providing precise quantitative basis for the scientific selection of candidate strategies.

[0139] As demand matching items based on cosine similarity approach the benchmark value, the matching score increases accordingly, and the increase is positively correlated with the degree of fit of the demand matching items. The closer the demand matching items are to a perfect fit, the more significant their positive contribution to the score.

[0140] When the normalized difference value of the adaptation items for environment and growth stage approaches the adaptation benchmark value, the result of subtracting the difference value from the fixed benchmark value will increase, and the matching score will increase accordingly. The better the fit, the more obvious the improvement effect of this part on the score.

[0141] When historical performance calibration items improve towards the optimal benchmark value, their positive contribution to the score increases directly, provided the importance weight coefficient remains constant. The better the historical implementation effect is than expected, the more significant the improvement in the score by the calibration item.

[0142] When the weighting coefficient of the preset demand matching item increases towards the weighting benchmark value, the impact of the demand matching item on the score is amplified. Even a small increase in the demand matching item will lead to a significant change in the score, while the impact of the other two items is relatively weakened. Similarly, when the weighting coefficient or importance weighting coefficient of the preset environment and growth stage adaptation item increases towards the weighting benchmark value, the dominant role of the corresponding evaluation dimension in the score will be enhanced, making the score more focused on the adaptation of that dimension.

[0143] When the demand matching item improves towards the benchmark value, the adaptation item difference value approaches the benchmark value, and the historical performance calibration item improves towards the superiority benchmark value simultaneously, the three will produce a synergistic gain effect, making the increase in the matching score much greater than the increase when a single factor changes, forming an optimal matching scenario of "high demand matching, high environmental adaptation, and high historical performance". Conversely, if all three change in an unfavorable direction, the score will decrease significantly, clearly distinguishing unsuitable candidate strategies.

[0144] The beneficial effects include constructing a water and fertilizer application strategy library based on growth stage identifiers, historical growth data, and soil type identifiers, and screening a set of candidate strategies. This provides a basis for decision-making that aligns with actual planting conditions, ensuring the relevance and practicality of the strategies. By mapping and quantifying the matching degree between water and fertilizer demand assessment values ​​and strategy demand ranges, candidate strategies with high compatibility with actual needs are accurately identified, preventing decisions from deviating from crop requirements. The strategy with the highest score or the best application effect is selected as the base strategy, ensuring the applicability and reliability of the decision and reducing planting risks caused by unreasonable strategies. By proportionally scaling the base strategy parameters according to the specific magnitude of the water and fertilizer demand assessment values, the final preliminary integrated water and fertilizer application decision is precisely adapted to the current water and fertilizer needs of Gobi melons. This satisfies the nutrient and water supply for crop growth while avoiding water and fertilizer waste or insufficient supply, providing clear guidance for the scientific water and fertilizer management of Gobi melons, helping to maintain good growth conditions and improve planting efficiency.

[0145] The virtual simulation module 105 is used to virtually simulate the changes in the root zone state of the Gobi melon based on the effective water and fertilizer capacity map of the root zone and the preliminary water and fertilizer application decision, and encode and encapsulate the water and fertilizer mixing ratio and application duration parameters in the simulation results to obtain the final execution instructions for the Gobi melon planting area.

[0146] In this embodiment of the invention, the virtual simulation module, when executing the virtual simulation of the root zone state changes of the Gobi melon based on the effective water and fertilizer capacity map of the root zone and applying the preliminary water and fertilizer integration application decision, and encoding and encapsulating the water and fertilizer mixing ratio and application duration parameters in the simulation results to obtain the final execution instruction for the Gobi melon planting area, is specifically used for:

[0147] Based on the effective water and fertilizer capacity map of the root zone and the preliminary water and fertilizer application decision, the root zone simulation and extrapolation conditions of the Gobi melon are determined;

[0148] Based on the simulation conditions of the root zone and the correlation between water and fertilizer capacity and soil environment in the effective water and fertilizer capacity map of the root zone, the dynamic response process of soil moisture and nutrient concentration in the root zone during the application of water and fertilizer in the Gobi melon planting area is deduced.

[0149] Based on the dynamic response process, the changes in key parameters in the initial fertigation decision are corrected to obtain the expected stable state of the Gobi melon.

[0150] The water-fertilizer mixing ratio and application duration obtained from the expected stable state are used as the key control parameters of the Gobi melon planting area.

[0151] According to the instruction encoding protocol of the integrated water and fertilizer equipment in the Gobi melon planting area, the key control parameters are formatted and encapsulated to obtain the final execution instructions for the Gobi melon planting area.

[0152] When the virtual simulation module executes the root zone simulation simulation conditions for the Gobi melon based on the effective water and fertilizer capacity map of the root zone and the preliminary water and fertilizer application decision, it is specifically used for:

[0153] The spatial distribution data of the initial water and fertilizer capacity state of the rhizosphere microenvironment in the Gobi melon in the effective water and fertilizer capacity map of the root zone are used as the initial simulated state of the Gobi melon.

[0154] The parameters of irrigation water volume, fertilizer application volume, water-fertilizer mixing ratio and application duration in the preliminary water and fertilizer integration application decision-making process are used as external intervention factors for the Gobi melon.

[0155] Based on the soil moisture distribution data and air temperature and humidity data in the multi-source environmental data, the environmental variable constraints for the Gobi melon are determined.

[0156] The initial simulation state, the external intervention factors, and the environmental variable constraints are integrated into the root zone simulation and deduction conditions for the Gobi melon.

[0157] This study extracts the distribution of effective water and nutrient capacities at different spatial locations within the root zone from the effective water and fertilizer capacity map, along with the clearly defined spatial divisions of the root zone and the soil environmental characteristics of each region. Simultaneously, core application parameters such as irrigation volume, fertilizer application rate, and water-fertilizer mixing ratio are extracted from the preliminary fertigation decision-making process. These parameters are then mapped one-to-one with the spatial distribution of the root zone, clarifying the water and fertilizer application rate and mixing ratio to be received at each spatial location. By integrating the existing water and fertilizer capacities and soil environmental characteristics at each spatial location within the root zone with the corresponding water and fertilizer application parameters, the initial and input conditions to be followed during the simulation and extrapolation process are defined, collectively constituting the root zone simulation and extrapolation conditions for Gobi melons.

[0158] This study elucidates the established relationships between water and fertilizer capacity and soil environment in the effective water and fertilizer capacity map of the root zone, namely, the variation patterns of water and fertilizer capacity corresponding to different soil environmental characteristics, and the inherent characteristics of water and fertilizer infiltration and diffusion in different soil environments. Based on the root zone simulation conditions, the process is simulated step by step in chronological order from the initial moment of water and fertilizer application: after the water and fertilizer mixture is applied to the surface of the root zone through the irrigation system, the process of water and nutrients gradually infiltrating into the middle and deep layers of the root zone is simulated according to the permeability characteristics of the soil environment. At the same time, the changes in soil moisture at each spatial location of the root zone from the initial state are recorded. Based on the fertilizer retention capacity and nutrient diffusion characteristics of the soil environment, the diffusion process of nutrients between soil particles is simulated, and the changes in nutrient concentration at each spatial location of the root zone from the initial state to a tendency towards uniformity are recorded. This fully presents the dynamic response process of soil moisture and nutrient concentration in the root zone during water and fertilizer application.

[0159] During the dynamic response simulation of soil moisture and nutrient concentration in the root zone, the root zone status at each time point was continuously compared with the ideal root zone status required for the growth of Gobi melons. If the simulation revealed that the soil moisture in a certain root zone location increased too rapidly, potentially leading to waterlogging, the irrigation water parameters for the corresponding area in the initial fertigation decision were reduced according to the adjustment logic corresponding to the soil water retention characteristics of that area. If the nutrient concentration increased slowly and was difficult to reach the ideal value, the fertilization parameters in the initial decision were appropriately increased based on the soil nutrient adsorption characteristics, while maintaining a reasonable water-fertilizer mixing ratio. If some areas had excessive moisture or nutrient concentration while others had insufficient concentration, the order of water and fertilizer application or the amount of local application was adjusted. Through multiple fine-tuning simulations, the soil moisture and nutrient concentration in the root zone were stabilized within the ideal range, forming the expected stable state for Gobi melons.

[0160] A detailed analysis of the expected steady state was conducted, and the core parameters for maintaining stable soil moisture and nutrient concentration in the root zone under this state were extracted: the water-fertilizer mixing ratio was the ratio finally determined during the simulation process, which could fully dissolve nutrients and adapt to the soil adsorption characteristics, and this ratio would not change under the steady state; the application time was the complete time from the start of water and fertilizer application until the root zone fully reached the expected steady state. This time ensured that water and fertilizer could fully penetrate into all spatial locations of the root zone, while avoiding waste or environmental pressure caused by over-application. These two parameters were identified as the key control parameters for the Gobi melon planting area.

[0161] The instruction encoding protocol for the integrated water and fertilizer system in the Gobi melon growing area was pre-obtained. This protocol clearly defines the transmission format, arrangement order, identifiers, and data representation specifications of the control parameters. For example, parameters must be arranged in the order of "water and fertilizer mixing ratio - application duration," with the ratio described in text using a fixed identifier identifiable by the equipment, and the duration represented by a code corresponding to a standard time unit. Following the protocol requirements, the parsed key control parameters were formatted: first, the water and fertilizer mixing ratio was converted into the identifiers specified in the protocol, and then the application duration was converted into the corresponding encoding format, ensuring that the representation of each parameter conformed to the equipment's recognition requirements. The formatted parameters were then combined according to the arrangement order specified in the protocol, and start and end identifiers as required by the protocol were added to complete the encoding and encapsulation of the key control parameters, ultimately yielding the final execution instructions for the Gobi melon growing area.

[0162] Data related to the rhizosphere microenvironment of Gobi melons were extracted from the effective water and fertilizer capacity map of the root zone, focusing on the initial effective water and nutrient capacity information corresponding to each spatial location in the root zone. The water and fertilizer capacity data for each spatial location were verified one by one to clarify the sufficiency of initial water and the enrichment of initial nutrients in different areas. Simultaneously, by combining the relative spatial relationships marked in the map, these water and fertilizer capacity data were precisely linked to specific spatial locations, forming a complete dataset containing initial water and nutrient capacity information indexed by spatial location. This dataset was then used as the initial simulated state for Gobi melons.

[0163] The core application parameters, clearly defined in the initial decision-making process for integrated water and fertilizer application, are extracted as follows: Irrigation volume refers to the total water volume specified in the decision for root zone irrigation, which needs to be further mapped to different spatial locations within the root zone to clarify the water allocation for each area; Fertilizer application amount refers to the specific total amount of various nutrients applied as determined in the decision, also broken down according to the spatial location of the root zone to clarify the nutrient allocation for each area; Water-fertilizer mixing ratio refers to the mixing ratio of water and various nutrients specified in the decision, clarifying the specific proportion of each nutrient to be mixed in each unit of water; Application duration refers to the complete time span from the start of water and fertilizer application to its completion, as set in the decision. These extracted and broken-down parameters—irrigation volume, fertilizer application amount, water-fertilizer mixing ratio, and application duration—are systematically organized and used as external intervention factors for Gobi melons.

[0164] Soil moisture distribution data and air temperature and humidity data recorded in multi-source environmental data were retrieved. Soil moisture distribution data represents the initial soil moisture at each spatial location in the root zone before water and fertilizer application; this data needs to be extracted individually for each spatial location to clarify the initial dry and wet state of the soil in each area. Air temperature and humidity data represents the current air temperature and humidity in the Gobi melon growing area; this data needs to be extracted to determine the current stable temperature and humidity levels. Based on the basic patterns of water and fertilizer changes in the root zone, the constraints of these data on the extrapolation process were clarified: air temperature affects the rate of water evaporation, thus constraining the increase and duration of soil moisture in the root zone; air humidity affects the rate of soil moisture loss, indirectly constraining changes in root zone humidity; initial soil moisture affects the efficiency of soil moisture increase after water and fertilizer application, with slower increases in dry areas and faster increases in humid areas. These constraints, combined with the corresponding data, were identified as the environmental variable constraints for Gobi melons.

[0165] The established initial simulation state, external intervention factors, and environmental constraints are systematically integrated. First, a correspondence is established between these three: using each spatial location in the root region as the core link, the initial simulation state data, corresponding external intervention factor parameters, and corresponding environmental constraint conditions for each spatial location are matched one-to-one. Then, the integrated information is verified for completeness, ensuring that each spatial location in the root region has a corresponding initial state, intervention parameters, and constraints, without omissions or mismatches. Finally, all the matched information is uniformly organized to form a complete dataset covering the initial state, applied parameters, and constraint requirements of each spatial location in the root region. This dataset constitutes the root region simulation and extrapolation conditions for Gobi melons.

[0166] The beneficial effects include combining the effective water and fertilizer capacity map of the root zone with the preliminary decision-making conditions for integrated water and fertilizer application, providing accurate and realistic basis for virtual simulations, and ensuring that the simulation direction is closely linked to the current status of the crop root zone and the preliminary decision. Based on the correlation, the dynamic response process of water and fertilizer in the root zone is simulated, clearly understanding the changes in soil moisture and nutrient concentration in the root zone during water and fertilizer application, avoiding water and fertilizer imbalance caused by blind application. The expected stable state is obtained by correcting the preliminary decision parameters through dynamic response, ensuring that water and fertilizer parameters are precisely adapted to the growth needs of Gobi melons and that the root zone environment is within a suitable range. Key control parameters in the expected stable state are extracted, focusing on the core points of water and fertilizer management, providing clear objectives for equipment operation. Parameters are encapsulated according to the equipment instruction coding protocol, ensuring that the final execution instructions can be accurately identified and executed by the integrated water and fertilizer equipment, achieving precise regulation of water and fertilizer in the root zone. This avoids water and fertilizer waste and damage to the root zone environment, while meeting the crop's growth needs, maintaining good growth status, and improving the scientific nature and practical benefits of Gobi melon planting and management.

[0167] By extracting initial water and fertilizer capacity data from various spatial locations within the root zone's effective water and fertilizer capacity map and binding spatial information, the determined initial simulation state accurately reflects the true initial state of the rhizosphere microenvironment of Gobi melons, providing a reliable basis for virtual extrapolation. Core application parameters are extracted from the initial integrated water and fertilizer application decision and organized spatially according to the root zone, ensuring that external intervention factors clearly correspond to each root zone area, guaranteeing the pertinence and feasibility of the intervention parameters. Combining soil and air temperature and humidity data from multi-source environmental data clarifies the constraints, and the determined environmental variable constraints ensure that the extrapolation process closely matches the actual planting environment, avoiding extrapolation deviations caused by detachment from the environmental context. By spatially linking and fully verifying the initial simulation state, external intervention factors, and environmental variable constraints, the resulting root zone simulation extrapolation conditions comprehensively cover all kinds of key information required for extrapolation, ensuring the accuracy and realism of the virtual extrapolation process. This provides solid support for the scientific and accurate extrapolation of subsequent root zone state changes and facilitates the reasonable correction of subsequent water and fertilizer parameters.

[0168] The instruction execution and control module 106 is used to control the integrated water and fertilizer equipment to perform precise irrigation and fertilization on the Gobi melon planting area according to the final execution instruction.

[0169] In this embodiment of the invention, the instruction execution and control module, when executing the final execution instruction to control the integrated water and fertilizer equipment to precisely irrigate and fertilize the Gobi melon planting area, is specifically used for:

[0170] The target irrigation water volume, target fertilizer application volume, target water-fertilizer mixing ratio, and target application area identifier in the final execution instruction are analyzed.

[0171] Based on the target application area identifier and the equipment area mapping relationship of the Gobi melon planting area, the water and fertilizer integrated equipment to be controlled is determined, and the control interface parameters and execution accuracy parameters of the water and fertilizer integrated equipment are obtained.

[0172] Based on the target irrigation water volume, target fertilizer application rate, target water-fertilizer mixing ratio, and the execution accuracy parameters, a set of underlying control instructions adapted to the integrated water and fertilizer equipment is generated.

[0173] The underlying control instruction set is sent to the corresponding integrated water and fertilizer equipment, and the integrated water and fertilizer equipment is driven to perform precision irrigation and fertilization operations in the Gobi melon planting area.

[0174] The core information encapsulated according to the device coding protocol in the final execution instruction is extracted. Following the parameter arrangement order and identifiers specified in the protocol, the target irrigation water volume, target fertilizer application volume, target water-fertilizer mixing ratio, and target application area identifier are parsed one by one. Specifically, the target irrigation water volume is obtained by parsing the corresponding water delivery identifier and associated quantitative description in the instruction, clarifying the total volume of water to be delivered to the planting area; the target fertilizer application volume is obtained by parsing the identifiers of various nutrients and their corresponding delivery volume descriptions in the instruction, clarifying the specific application volume of each nutrient; the target water-fertilizer mixing ratio is obtained by parsing the combination identifiers of water and various nutrients in the instruction, clarifying the mixing ratio of water to each nutrient; and the target application area identifier is obtained by parsing the preset area code in the instruction. This code corresponds one-to-one with the root zone spatial location of the Gobi melon planting area, clarifying the specific area range where water and fertilizer need to be applied, ensuring that the parsed information is complete and completely consistent with the description in the final execution instruction.

[0175] A pre-established equipment area mapping relationship is created for the Gobi melon planting area. This relationship clearly defines the fertigation equipment number and the area it is responsible for for each root zone spatial location within the planting area, ensuring that each root zone spatial location has a unique corresponding control device. Based on the parsed target application area identifier, the corresponding equipment number is searched in the equipment area mapping relationship to determine the fertigation equipment to be controlled. The control interface parameters of the fertigation equipment are obtained through the equipment's built-in information interface or a pre-set equipment parameter file, including interface type, data transmission method, and command reception format, clarifying how to send control commands to the equipment. Simultaneously, the equipment's execution accuracy parameters are obtained, including irrigation volume control accuracy, fertilization volume control accuracy, and water-fertilizer mixing ratio control accuracy, clarifying the error control range during operation and providing a basis for subsequent generation of underlying control commands.

[0176] Based on the analyzed target irrigation water volume, target fertilizer application rate, and target water-fertilizer mixing ratio, and combined with the acquired execution accuracy parameters, the underlying control instructions adapted to the integrated water and fertilizer system are generated one by one. For the target irrigation water volume, the opening degree of the irrigation valves and the water flow rate are determined according to the equipment's execution accuracy requirements to ensure that the deviation between the actual irrigation water volume and the target value is within the execution accuracy range, generating the corresponding irrigation volume control instruction. For the target fertilizer application rate, the operating speed of the fertilizer delivery pump is adjusted according to the equipment's fertilization accuracy requirements to ensure that the actual delivery amount of each nutrient is consistent with the target value, generating the corresponding fertilization volume control instruction. For the target water-fertilizer mixing ratio, the matching relationship between the water delivery speed and the fertilizer delivery speed is coordinated according to the equipment's mixing accuracy requirements to ensure that water and various nutrients are uniformly mixed according to the target ratio, generating the corresponding mixing ratio control instruction. These control instructions for different operations are arranged in a sequence recognizable by the equipment to form a complete underlying control instruction set, ensuring that each instruction can be accurately recognized and executed by the equipment.

[0177] Based on the acquired control interface parameters of the integrated water and fertilizer system, the generated low-level control command set is completely transmitted to the designated integrated water and fertilizer system using the corresponding transmission method. Upon receiving the low-level control command set, the system initiates the execution process according to the command sequence: First, it adjusts the water and fertilizer mixing device according to the mixing ratio control command, uniformly mixing water and various nutrients according to the target ratio; then, according to the irrigation and fertilization control commands, it opens the corresponding delivery channels, adjusts the valve opening degree and pump speed to ensure accurate output of the mixed water and fertilizer according to the target amount; simultaneously, based on the target application area identifier and the corresponding equipment responsibility area, it accurately delivers water and fertilizer to the designated root zone location. Throughout the entire execution process, the system performs real-time self-calibration based on the execution accuracy parameters to avoid deviations in irrigation, fertilization, or mixing ratios, ensuring accurate completion of irrigation and fertilization operations in the Gobi melon growing area.

[0178] The beneficial effects are as follows: By accurately analyzing the core parameters in the final execution instructions, the target volume, proportion, and area of ​​water and fertilizer application are clearly defined, providing a clear and definite execution basis for subsequent precise control and avoiding application deviations caused by ambiguous parameters. The equipment to be controlled is determined based on the mapping relationship between the target area identifier and the equipment area, and the equipment control interface and execution accuracy parameters are obtained, ensuring that the control instructions are accurately adapted to the equipment characteristics, guaranteeing the feasibility and accuracy of the control process. A low-level control instruction set is generated by combining the target parameters and the equipment execution accuracy, refining the control requirements of each operation link, ensuring that equipment operation always revolves around the target parameters, and avoiding execution deviations exceeding the allowable range. The low-level control instruction set is issued according to the adaptation method, driving the equipment to complete water and fertilizer mixing, precise delivery, and application to designated areas according to the instructions. Simultaneously, real-time self-calibration of the equipment ensures execution accuracy, achieving precise irrigation and fertilization in the Gobi melon planting area. This not only meets the crop's water and fertilizer needs for growth but also avoids water and fertilizer waste, improves water and fertilizer utilization efficiency, ensures healthy crop growth, and enhances the scientific and effective nature of planting management.

[0179] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0180] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0181] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A precision water and fertilizer integrated regulation system for Gobi melons, characterized in that, The system includes a multi-source data integration module, a root zone water and fertilizer capacity map construction module, a water and fertilizer supply potential assessment module, a preliminary decision generation module, a virtual simulation module, and an instruction execution and control module, wherein: The multi-source data integration module is used to integrate environmental data and crop physiological image data of the Gobi melon planting area into multi-source environmental data of Gobi melon; The root zone water and fertilizer capacity map construction module is used to construct the root zone effective water and fertilizer capacity map of the Gobi melon based on the soil moisture distribution, light intensity and air temperature and humidity data and the growth correlation data of the Gobi melon in the multi-source environmental data, and based on the fusion characteristics of the leaf color, expansion degree and stem micro-change physiological data of the Gobi melon. The water and fertilizer supply potential assessment module is used to assess the water and fertilizer supply potential of the rhizosphere microenvironment of the Gobi melon based on the effective water and fertilizer capacity map of the root zone, and obtain the water and fertilizer demand assessment value of the Gobi melon. The preliminary decision generation module is used to map the water and fertilizer demand assessment value to the water and fertilizer application strategy library of the Gobi melon to obtain the preliminary water and fertilizer integrated application decision of the Gobi melon. The virtual simulation module is used to virtually simulate the changes in the root zone state of the Gobi melon based on the effective water and fertilizer capacity map of the root zone and the preliminary water and fertilizer application decision, and encode and encapsulate the water and fertilizer mixing ratio and application duration parameters in the simulation results to obtain the final execution instructions for the Gobi melon planting area. The instruction execution and control module is used to control the integrated water and fertilizer equipment to precisely irrigate and fertilize the Gobi melon planting area according to the final execution instruction.

2. The integrated water and fertilizer precision regulation system for Gobi melons as described in claim 1, characterized in that, When the multi-source data integration module integrates environmental data and crop physiological image data from the Gobi melon growing area into multi-source environmental data for Gobi melons, it is specifically used for: Soil sensor data and meteorological monitoring data were collected from the Gobi melon growing area, and canopy multispectral image data and stem microscopic image data of the Gobi melon were acquired simultaneously. The soil sensing data, meteorological monitoring data, canopy multispectral image data, and stem microscopic image data are spatiotemporally registered and aligned to obtain the original dataset of the Gobi melon. The image data representing leaf color and spread in the original dataset are used as the physiological static feature set, and the data representing micro-changes in the stem epidermis are used as the physiological dynamic feature set. The soil sensing data, the meteorological monitoring data, the physiological static feature set, and the physiological dynamic feature set are aggregated into multi-source environmental data for the Gobi melon.

3. The integrated water and fertilizer precision control system for Gobi melons as described in claim 1, characterized in that, The root zone water and fertilizer capacity mapping module, when constructing an effective water and fertilizer capacity map of the Gobi melon using the correlation data between soil moisture distribution, light intensity, and air temperature and humidity from the multi-source environmental data and the growth of the Gobi melon as a basis, and the fusion characteristics of leaf color, expansion, and stem micro-change physiological data of the Gobi melon as a criterion, is specifically used for: The soil moisture distribution data, light intensity data, and air temperature and humidity data from the multi-source environmental data are used as the environmental baseline data for the Gobi melon. The leaf color characteristics, leaf spread characteristics, and stem micro-change characteristics of the Gobi melon in the crop physiological image data are fused in multiple dimensions to obtain the physiological fusion feature data of the Gobi melon. The environmental baseline data and the physiological fusion feature data are correlated and coupled at the spatial location corresponding to the root region in the Gobi melon to obtain the root region fusion data of the Gobi melon. Based on the standard crop water and fertilizer demand response rules for Gobi melon, the root zone fusion data is mapped according to rules to obtain the effective water and fertilizer capacity map of the root zone of Gobi melon.

4. The integrated water and fertilizer precision control system for Gobi melons as described in claim 1, characterized in that, When the water and fertilizer supply potential assessment module performs a capacity assessment of the rhizosphere microenvironment water and fertilizer supply potential of the Gobi melon based on the effective water and fertilizer capacity map of the root zone, and obtains the water and fertilizer demand assessment value of the Gobi melon, it is specifically used for: The effective water capacity distribution and effective nutrient capacity distribution information of the Gobi melon were determined from the effective water and fertilizer capacity map of the root zone. The difference between the effective water capacity distribution information and the ideal root zone water saturation distribution threshold of the Gobi melon is obtained by performing a differential analysis. The effective nutrient capacity distribution information is compared with the ideal root zone nutrient saturation distribution threshold of the Gobi melon to obtain the root zone nutrient supply potential difference value of the Gobi melon. Based on the leaf spread and stem micro-change characteristics in the multi-source environmental data, the physiological state of water stress and nutrient deficiency of the Gobi melon is determined, and the physiological state is corrected for the difference in water supply potential and the difference in nutrient supply potential of the root zone according to the determination results. Based on the corrected difference in root zone water supply potential and the difference in root zone nutrient supply potential, a comprehensive assessment is made of the water and fertilizer requirements for the growth of the Gobi melon, resulting in an assessment value for the water and fertilizer requirements of the Gobi melon.

5. The integrated water and fertilizer precision control system for Gobi melons as described in claim 4, characterized in that, The formula for calculating the water and fertilizer demand assessment value is as follows: ； In the formula, The water and fertilizer requirement assessment value is... The difference in water supply potential in the root zone. This is the normalization adjustment parameter for the coefficient of variation of the spatial distribution of root zone water capacity in the root zone effective nutrient capacity distribution information. The coefficient of variation of the spatial distribution of root zone water capacity in the effective nutrient capacity distribution information of the root zone is given. This refers to the infinitesimal change in the overall physiological state fusion index of the Gobi melon over time. The sampling and analysis cycle is fixed per unit time for the Gobi melon.

6. The integrated water and fertilizer precision control system for Gobi melons as described in claim 1, characterized in that, When the preliminary decision generation module maps the water and fertilizer demand assessment value to the water and fertilizer application strategy library of the Gobi melon to obtain the preliminary integrated water and fertilizer application decision for the Gobi melon, it is specifically used for: Based on the growth stage identifiers and historical growth data of the Gobi melon and the soil type identifiers in the multi-source environmental data, a water and fertilizer application strategy library for the Gobi melon is constructed, and a candidate water and fertilizer application strategy set for the Gobi melon is selected. The matching degree of the water and fertilizer demand assessment value is mapped with the strategy demand range in the water and fertilizer application strategy library to obtain the matching degree score of the water and fertilizer demand assessment value. The candidate water and fertilizer application strategy with the highest matching score in the candidate water and fertilizer application strategy set is selected as the basic strategy. Based on the specific magnitude of the water and fertilizer demand assessment value, the benchmark parameters of irrigation water volume, fertilizer application volume and water-fertilizer mixing ratio in the basic strategy are scaled proportionally to obtain the preliminary water and fertilizer application decision for the Gobi melon.

7. The integrated water and fertilizer precision control system for Gobi melons as described in claim 6, characterized in that, The matching score is calculated using the following formula: ； In the formula, Score the matching degree. Weighting coefficients are applied to the preset demand matching items. For the cosine similarity-based demand matching items of the Gobi melon, Let be a vector of the water and fertilizer demand assessment values. This represents the baseline demand vector for candidate strategies in the water and fertilizer application strategy library. The weighting coefficients are the preset environmental and growth stage adaptation factors. For the environmental and growth stage adaptation of the Gobi melon, The soil type suitability coefficient for the Gobi melon growing area is [missing information]. The adaptation coefficient for the growth stage of the Gobi melon is given. The importance weighting coefficient for the historical performance calibration term in the Gobi melon is given. This refers to the historical performance calibration item.

8. The integrated water and fertilizer precision control system for Gobi melons as described in claim 1, characterized in that, The virtual simulation module, when executing the virtual simulation of the root zone state changes of the Gobi melon based on the effective water and fertilizer capacity map of the root zone and applying the preliminary water and fertilizer integration application decision, and encoding and encapsulating the water and fertilizer mixing ratio and application duration parameters in the simulation results to obtain the final execution instruction for the Gobi melon planting area, is specifically used for: Based on the effective water and fertilizer capacity map of the root zone and the preliminary water and fertilizer application decision, the root zone simulation and extrapolation conditions of the Gobi melon are determined; Based on the simulation conditions of the root zone and the correlation between water and fertilizer capacity and soil environment in the effective water and fertilizer capacity map of the root zone, the dynamic response process of soil moisture and nutrient concentration in the root zone during the application of water and fertilizer in the Gobi melon planting area is deduced. Based on the dynamic response process, the changes in key parameters in the initial fertigation decision are corrected to obtain the expected stable state of the Gobi melon. The water-fertilizer mixing ratio and application duration obtained from the expected stable state are used as the key control parameters of the Gobi melon planting area. According to the instruction encoding protocol of the integrated water and fertilizer equipment in the Gobi melon planting area, the key control parameters are formatted and encapsulated to obtain the final execution instructions for the Gobi melon planting area.

9. The integrated water and fertilizer precision control system for Gobi melons as described in claim 8, characterized in that, When the virtual simulation module executes the root zone simulation simulation conditions for the Gobi melon based on the effective water and fertilizer capacity map of the root zone and the preliminary water and fertilizer application decision, it is specifically used for: The spatial distribution data of the initial water and fertilizer capacity state of the rhizosphere microenvironment in the Gobi melon in the effective water and fertilizer capacity map of the root zone are used as the initial simulated state of the Gobi melon. The parameters of irrigation water volume, fertilizer application volume, water-fertilizer mixing ratio and application duration in the preliminary water and fertilizer integration application decision-making process are used as external intervention factors for the Gobi melon. Based on the soil moisture distribution data and air temperature and humidity data in the multi-source environmental data, the environmental variable constraints for the Gobi melon are determined. The initial simulation state, the external intervention factors, and the environmental variable constraints are integrated into the root zone simulation and deduction conditions for the Gobi melon.

10. The Gobi melon integrated water and fertilizer precision regulation system as described in claim 1, characterized in that, The instruction execution and control module, when executing the final execution instruction to control the integrated water and fertilizer equipment to precisely irrigate and fertilize the Gobi melon planting area, is specifically used for: The target irrigation water volume, target fertilizer application volume, target water-fertilizer mixing ratio, and target application area identifier in the final execution instruction are analyzed. Based on the target application area identifier and the equipment area mapping relationship of the Gobi melon planting area, the water and fertilizer integrated equipment to be controlled is determined, and the control interface parameters and execution accuracy parameters of the water and fertilizer integrated equipment are obtained. Based on the target irrigation water volume, target fertilizer application rate, target water-fertilizer mixing ratio, and the execution accuracy parameters, a set of underlying control instructions adapted to the integrated water and fertilizer equipment is generated. The underlying control instruction set is sent to the corresponding integrated water and fertilizer equipment, and the integrated water and fertilizer equipment is driven to perform precision irrigation and fertilization operations in the Gobi melon planting area.

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