Polygonatum sibiricum fertilization method and system based on Internet of Things

Abstract

The embodiment of the invention provides a polygonatum sibiricum fertilization method and system based on the Internet of Things. The method comprises the steps that soil condition information of polygonatum sibiricum and the current growth period of the polygonatum sibiricum are obtained; wherein the soil condition information comprises soil nutrient information, soil dryness and humidity and environment temperature; comparing and analyzing the nutrient information of the soil, the dry and wet degree of the soil and the environment temperature through a preset information characteristic database in combination with the current growth period, and determining a water and fertilizer diagnosis result of the rhizoma polygonati; and based on the water and fertilizer diagnosis result, performing precise fertilization on the polygonatum sibiricum through a preset polygonatum sibiricum fertilization model and a preset fertilization control model. According to the scheme, the water and fertilizer utilization rate and the polygonatum sibiricum yield can be effectively improved.

Description

Technical Field

[0001] This application relates to the field of agricultural technology, specifically to a method and system for applying Polygonatum sibiricum fertilizer based on the Internet of Things. Background Technology

[0002] Polygonatum is a product that is both food and medicine, widely used in consumption. It has excellent functions of "tonifying the middle qi, calming the five internal organs, strengthening the spleen, moistening the lungs and benefiting the kidneys, and promoting longevity with long-term use." The annual demand is over 20,000 tons, and the population accepting it is growing, with demand increasing year by year. However, due to the current traditional cultivation methods, the yield is not high. At the same time, there are also high labor costs. Summary of the Invention

[0003] This application aims to provide a method and system for fertilizing Polygonatum based on the Internet of Things, which can improve water and fertilizer utilization and increase the yield of Polygonatum.

[0004] The technical solution of this application is implemented as follows: In a first aspect, embodiments of this application provide a method for fertilizing Polygonatum sibiricum based on the Internet of Things, the method comprising: Obtain soil condition information and the current growth stage of the Polygonatum sibiricum; wherein, the soil condition information includes: soil nutrient information, soil moisture level and ambient temperature; By using a pre-set information feature database and combining it with the current growth stage, the soil nutrient information, soil moisture level and ambient temperature are compared and analyzed to determine the water and fertilizer diagnosis result of the Polygonatum. Based on the water and fertilizer diagnosis results, precise fertilization of the Polygonatum is carried out by using a preset Polygonatum fertilization model and a preset fertilization control model.

[0005] In the above scheme, the step of comparing and analyzing the soil nutrient information, soil moisture level, and ambient temperature by using a preset information feature database and combining them with the current growth stage to determine the water and fertilizer diagnosis result of the Polygonatum includes: Select growth characteristic data corresponding to the current growth stage of the Polygonatum from the preset information feature database; The growth characteristic data are compared and analyzed with the soil nutrient information, the soil moisture level, and the ambient temperature to determine the comparison results of the soil nutrient information, the soil moisture level, and the ambient temperature. Based on the comparison results of soil nutrient information, soil moisture level, and ambient temperature, the water and fertilizer diagnosis results of the Polygonatum were determined.

[0006] In the above scheme, the step of precisely fertilizing the Polygonatum based on the water and fertilizer diagnosis results using a preset Polygonatum fertilization model and a preset fertilizer control model includes: Based on the water and fertilizer diagnosis results, a sub-preset fertilization model corresponding to the current growth stage of Polygonatum is selected from the preset fertilization model. The fertilization data of Polygonatum at the current growth stage is determined by analyzing the fertilization of Polygonatum using the sub-preset Polygonatum fertilization model. The pre-fertilization control model is used to precisely fertilize the Polygonatum according to the Polygonatum fertilization data.

[0007] In the above scheme, the step of precisely fertilizing the Polygonatum sibiricum according to the Polygonatum sibiricum fertilization data through the pre-fertilization control model includes: The fertilization instruction is generated based on the Polygonatum fertilization data using the pre-fertilization control model. Based on the fertilization command, the fertilization equipment is precisely fertilized by controlling the fertilization equipment.

[0008] In the above scheme, before performing precise fertilization of the Polygonatum based on the water and fertilizer diagnosis results using a preset Polygonatum fertilization model and a preset facility fertilization control model, the method further includes: Obtain historical fertilization data for different growth stages of Polygonatum sibiricum; Based on the historical fertilization data of the different growth stages, establish the fertilization model of the seed Polygonatum corresponding to the different growth stages of Polygonatum. The preset fertilization model of Polygonatum was determined by the aforementioned fertilization model of Polygonatum sibiricum. Soil EC values ​​are extracted based on the historical fertilization data, and the pre-fertilization control model is established based on the soil EC values.

[0009] In the above scheme, the soil EC value is a soil electrochemical parameter that reflects soil moisture, soil salinity, soil nutrient content, etc.

[0010] In the above scheme, the pre-fertilizer control model is used to adjust the EC value of the fertilizer solution, which reflects the concentration of soluble ions in the fertilizer solution.

[0011] Secondly, embodiments of this application provide an IoT-based fertilization system for Polygonatum sibiricum, comprising: an acquisition module, a determination module, and a control module, wherein... The acquisition module is used to acquire soil condition information of the location of the Polygonatum and the current growth stage of the Polygonatum; wherein, the soil condition information includes: soil nutrient information, soil moisture level and ambient temperature; The determining module is used to compare and analyze the soil nutrient information, soil moisture level and ambient temperature by using a preset information feature database and combining the current growth period, to determine the water and fertilizer diagnosis result of the Polygonatum. The control module is used to precisely fertilize the Polygonatum based on the water and fertilizer diagnosis results, using a preset Polygonatum fertilization model and a preset fertilization control model.

[0012] Thirdly, embodiments of this application provide an IoT-based fertilization device for Polygonatum sibiricum, comprising: a processor and a memory; wherein, The memory is used to store computer programs; The processor is configured to call and run the computer program from the memory to perform the method as described in the first aspect.

[0013] Fourthly, embodiments of this application provide a computer-readable storage medium storing executable instructions for causing a processor to perform the method described in the first aspect.

[0014] This application provides an IoT-based method and system for fertilizing Polygonatum sibiricum. The method includes: acquiring soil condition information and the current growth stage of the Polygonatum sibiricum; wherein the soil condition information includes soil nutrient information, soil moisture level, and ambient temperature; comparing and analyzing the soil nutrient information, soil moisture level, and ambient temperature using a preset information feature database and the current growth stage to determine the water and fertilizer diagnosis result of the Polygonatum sibiricum; and based on the water and fertilizer diagnosis result, precisely fertilizing the Polygonatum sibiricum using a preset fertilization model and a pre-set fertilization control model. In the above solution, precise fertilization of Polygonatum sibiricum using the preset fertilization model and pre-set fertilization control model can reduce the workload of Polygonatum sibiricum planting and management while improving the yield, water and fertilizer utilization rate, and economic benefits of greenhouse-grown Polygonatum sibiricum. Attached Figure Description

[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the specification, serve to explain the technical solutions of this application. Obviously, the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0016] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0017] Figure 1 A schematic diagram of an optional process for applying Polygonatum sibiricum fertilizer based on the Internet of Things, provided as an embodiment of this application; Figure 2 A schematic diagram of the structure of a Polygonatum sibiricum fertilization system based on the Internet of Things is provided for an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a Polygonatum sibiricum fertilization device based on the Internet of Things, provided as an embodiment of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the specific technical solutions of this application will be further described in detail below with reference to the accompanying drawings of the embodiments of this application. The following embodiments are used to illustrate this application, but are not intended to limit the scope of this application.

[0019] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used in this application is for the purpose of describing embodiments of this application only and is not intended to be limiting of this application.

[0020] In the following description, references to "some embodiments," "this embodiment," "this application embodiment," and examples, etc., describe a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subset of all possible embodiments and may be combined with each other without conflict.

[0021] If the application documents contain similar descriptions such as "first / second", the following explanation shall be added: In the following description, the terms "first / second / third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first / second / third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0022] This application provides a method for fertilizing Polygonatum sibiricum based on the Internet of Things. Figure 1 This application provides an optional flowchart illustrating an IoT-based fertilization method for Polygonatum sibiricum, which will be combined with... Figure 1 The steps shown are explained.

[0023] S101. Obtain information on the soil conditions where Polygonatum is located and its current growth stage; the soil condition information includes: soil nutrient information, soil moisture level and ambient temperature.

[0024] In some embodiments of this application, the seedlings of Polygonatum sibiricum are derived from three-year-old seedlings. The main characteristics of this variety are: drought resistance, strong resistance to diseases and pests, high yield, and good taste. The rhizome of this variety is thick, usually beaded or nodular, rarely nearly cylindrical, with a diameter of 1-2 cm. The stem is 50-100 cm tall, usually with 10-15 leaves. The leaves are alternate, elliptic, ovate-lanceolate to oblong-lanceolate, rarely slightly falcate. The inflorescence has (1-)2-7(-14) flowers, umbel-shaped, with a peduncle 1-4(-6) cm long and a pedicel 0.5-1.5(-3) cm long; the perianth is yellowish-green. This variety prefers to grow in deep, fertile soil with sufficient surface moisture, in shady areas with ample upper light penetration, such as forest edges, thickets, valleys, or shady slopes. Polygonatum is cold-resistant, shade-loving, moisture-loving, and intolerant of drought and waterlogging. It has a strong habitat selectivity and grows best in fertile sandy loam soil with good drainage and water retention. It is not suitable for planting in heavy clay soil, saline-alkali soil, low-lying areas, and dry plots.

[0025] In some embodiments of this application, the IoT-based fertilization method for Polygonatum is adapted to Polygonatum cultivation scenarios.

[0026] In some embodiments of this application, the IoT-based method for fertilizing Polygonatum sibiricum is adapted to an IoT-based system for fertilizing Polygonatum sibiricum.

[0027] In some embodiments of this application, information on the soil conditions where Polygonatum is located and the current growth stage of Polygonatum are obtained; wherein, the soil condition information includes: soil nutrient information, soil moisture level and ambient temperature.

[0028] S102. By using a pre-set information feature database and combining it with the current growth stage, compare and analyze the soil nutrient information, soil moisture level and ambient temperature to determine the water and fertilizer diagnosis results for Polygonatum.

[0029] In some embodiments of this application, growth characteristic data corresponding to the current growth stage of Polygonatum are selected from a preset information characteristic database; the growth characteristic data are compared and analyzed with soil nutrient information, soil moisture level, and ambient temperature to determine the comparison results of soil nutrient information, soil moisture level, and ambient temperature; based on the comparison results of soil nutrient information, soil moisture level, and ambient temperature, the water and fertilizer diagnosis results of Polygonatum are determined.

[0030] S103. Based on the water and fertilizer diagnosis results, precise fertilization of Polygonatum is carried out by pre-setting a Polygonatum fertilization model and a pre-setting fertilizer control model.

[0031] In some embodiments of this application, the fertilization model for Polygonatum sibiricum is the theoretical basis and prerequisite for realizing intelligent control of water and fertilizer in Polygonatum sibiricum. The fertilizer requirements of Polygonatum sibiricum vary at different growth stages. Based on the nutrient balance fertilization method and the fertilizer requirements of Polygonatum sibiricum at each growth stage, a fertilization decision model for each growth stage of Polygonatum sibiricum is constructed to provide a basis for the total amount of fertilizer applied and the amount of fertilizer applied at each stage.

[0032] It should be noted that the preset Polygonatum fertilization model is the same as the Polygonatum fertilization model. The preset fertilization control model is used to adjust the EC value of the fertilizer solution, which reflects the concentration of soluble ions in the fertilizer solution.

[0033] In some embodiments of this application, based on the water and fertilizer diagnosis results, a sub-preset fertilization model corresponding to the current growth stage of Polygonatum is selected from the preset fertilization model; the fertilization analysis of Polygonatum in the current growth stage is performed through the sub-preset fertilization model to determine the fertilization data; and the Polygonatum is precisely fertilized according to the fertilization data through the preset fertilization control model.

[0034] In some embodiments of this application, a pre-set fertilization control model is used to generate fertilization instructions based on Polygonatum sibiricum fertilization data; based on the fertilization instructions, the fertilization equipment is precisely fertilized by the control equipment.

[0035] It is understandable that this application uses a pre-set fertilization model and a pre-set fertilization control model to precisely fertilize Polygonatum, which can reduce the workload of Polygonatum planting and management while improving the yield, water and fertilizer utilization rate and economic benefits of Polygonatum planting in facilities.

[0036] In some embodiments of this application, before performing precise fertilization of Polygonatum based on water and fertilizer diagnostic results using a preset Polygonatum fertilization model and a preset fertilization control model, the method further includes: Obtain historical fertilization data for different growth stages of Polygonatum sibiricum; Based on historical fertilization data at different growth stages, establish fertilization models for each of the different growth stages of Polygonatum sibiricum. The pre-set fertilization model for Polygonatum was determined using the fertilization model for Polygonatum sibiricum. Soil EC values ​​were extracted based on historical fertilization data, and a pre-fertilization control model was established based on the soil EC values.

[0037] In some embodiments of this application, the soil EC value is a soil electrochemical parameter reflecting soil moisture, soil salinity, soil nutrient content, etc.

[0038] In some embodiments of this application, the IoT-based method for fertilizing Polygonatum sibiricum further includes the following steps: 1. Research on fertilization models The fertilization model for Polygonatum sibiricum is the theoretical basis and prerequisite for realizing intelligent control of water and fertilizer in Polygonatum sibiricum. The fertilizer requirements of Polygonatum sibiricum vary at different growth stages. Based on the nutrient balance fertilization method and the fertilizer requirements of Polygonatum sibiricum at each growth stage, a fertilization decision model for each growth stage of Polygonatum sibiricum is constructed to provide a basis for the total amount of fertilizer and the amount of fertilizer applied at each stage.

[0039] Soil testing and fertilizer recommendation are based on soil testing, combined with factors such as crop type, soil condition, and planting area. Theoretical analysis and experiments are used to derive the theoretical fertilizer application rate. The project team adopted the nutrient balance fertilization method for fertilization modeling. The principle of the nutrient balance fertilization method is to calculate the fertilizer application rate based on the relationship between crop nutrient requirements and soil fertility. The nutrient balance fertilization method has the advantages of short experimental cycle and high decision-making accuracy, and can serve as the basis for fertilization decisions for Polygonatum sibiricum in greenhouse facilities. The specific theoretical formula is as follows: In the formula This refers to the application rate of a fertilizer containing a certain element. This refers to the nutrient requirements of crops. For soil nutrient supply, To improve fertilizer utilization, This refers to the nutrient content of fertilizers. Based on the experimental results of the project team, a decision-making model for the amount of Polygonatum sibiricum fertilizer in Poyang County was constructed.

[0040] Fertilization System Decisions. The nutrient requirements of Polygonatum are the foundation of its fertilization system. Through expert consultation, literature review, field surveys, and experimental results, the nutrient requirements of Polygonatum were summarized to derive its nutrient demand patterns (focusing on macronutrients). Based on this, and combined with the production and planting experience of local farmers, the percentage of nitrogen, phosphorus, and potassium applied as macronutrients in the total fertilizer application at each growth stage of Polygonatum was determined, thus establishing the nutrient application ratios for each stage of Polygonatum growth.

[0041] During fertilization, different fertilization frequencies can affect the transport and distribution of fertilizers in the soil, influencing the absorption of nutrients by Polygonatum sibiricum, and consequently affecting its growth and yield. Therefore, by reviewing relevant standards and literature, consulting experts, and combining the results of field experiments, a fertilization system for Polygonatum sibiricum was determined. Since the types and amounts of fertilizer required by Polygonatum sibiricum vary at different growth stages, specific fertilization systems for different periods were constructed.

[0042] 2. Construction of the fertilizer application control model Soil EC value, as a soil electrochemical parameter reflecting soil moisture, soil salinity, and soil nutrient content, is increasingly being used in intelligent control of facility agriculture. Existing research shows that soil EC value is closely related to soil nutrients such as nitrogen, phosphorus, and potassium, and can reflect the soil nutrient status under specific conditions.

[0043] The EC value of fertilizer solution reflects the concentration of soluble ions in the solution and can be used as a standard to measure the amount of fertilizer applied. It is also the most direct factor affecting the soil EC value. Therefore, the target soil EC value should be used as the target value for fertilizer solution preparation to ensure that the soil EC value does not exceed the appropriate threshold range for tomato growth during drip irrigation.

[0044] During fertilizer solution preparation, the fertilizer suction device draws the mother liquor into the mixing pipeline for initial mixing, then it enters the mixing tank where agitation accelerates the mixing of the mother liquor with irrigation water. Because the mixing of the mother liquor and irrigation water is delayed, this process can be considered a combination of two states: natural mixing and instantaneous mixing via agitation. This project employs PID control in the fertilizer preparation process, dynamically adjusting the EC value of the fertilizer solution to control its concentration.

[0045] 3. Implementation of integrated water and fertilizer system By monitoring soil condition information through front-end sensors and intelligently comparing and analyzing it with a dynamic database of growth indicators and an information feature database, the system can accurately monitor and diagnose water and fertilizer deficiencies in Polygonatum sibiricum forests. With the help of a computer, the system can read the data transmitted back from the sensors in real time, monitor soil nutrients, soil moisture and humidity, and ambient temperature. Combined with the constructed integrated water and fertilizer decision-making model, the system can formulate a water and fertilizer supply plan, intelligently set the required total amount of water and fertilizer irrigation, time, and frequency, issue irrigation and fertilization instructions, and automatically control the water valves to carry out precise irrigation and fertilization control, thereby effectively improving water and fertilizer utilization.

[0046] 3.1 Design of IoT Lower-Level System The lower-level control system is the core component of the integrated water and fertilizer system, serving as the foundation and prerequisite for data acquisition and equipment control. As the core of the system, the lower-level control system mainly consists of a main control unit, power supply module, control equipment, sensing devices, data transmission module, pressurization equipment, and fertilization equipment. The main control unit, as the core of the lower-level control system, primarily receives and processes data transmitted from the sensing devices and data transmission module, generates instructions according to predetermined rules, and controls the pressurized fertilization equipment through the control equipment. The sensing module, composed of various sensors, cameras, and signal conversion devices, enables real-time sensing of the soil environment, fertilizer solution information, and equipment status information within the greenhouse, providing a data foundation for precise system control. The data transmission module acts as a communication bridge between the upper-level and lower-level control systems. Based on the site conditions, it uses appropriate communication technologies to upload environmental and image data collected by the lower-level control system to the upper-level control system, and transmits instructions and time data sent from the upper-level control system to the lower-level control system's main control unit. After receiving control commands from the main control unit, the control equipment, pressurizing equipment, and fertilizing equipment work together to complete the system's control actions, realizing the system's automatic fertilization function. The control equipment mainly includes several relays, the pressurizing equipment includes a water pump and a fertilizer pump, and the fertilizing equipment includes a mixer and a solenoid valve.

[0047] 3.2 Software System Design To enhance the interaction between target users and the Polygonatum sibiricum integrated water and fertilizer system, and to further verify the applicability and stability of the integrated water and fertilizer system, this study designed a Polygonatum sibiricum integrated water and fertilizer software system, and implemented the system based on the design of the lower-level computer system and the software system. The Polygonatum sibiricum integrated water and fertilizer software system mainly consists of two parts: a host computer and a mobile APP, which can provide users with perception and control services for physical objects. The host computer system mainly receives, analyzes, and stores greenhouse environmental data and equipment control data, and generates real-time control commands to send to the lower-level computer system to complete the control operations of related equipment. The mobile APP, as a part to improve the system's usability, can realize functions such as displaying real-time data, historical data, images and videos, and remote equipment management.

[0048] Based on the IoT-based fertilization method for Polygonatum sibiricum described in the above embodiments, this application also provides an IoT-based fertilization system for Polygonatum sibiricum, such as... Figure 2 As shown, Figure 2 This application provides a schematic diagram of the structure of an IoT-based Polygonatum fertilization system. The IoT-based Polygonatum fertilization system 2 includes: an acquisition module 201, a determination module 202, and a control module 203. The acquisition module 201 is used to acquire soil condition information of the Solomon's seal and the current growth stage of the Solomon's seal; wherein, the soil condition information includes: soil nutrient information, soil moisture level and ambient temperature; The determining module 202 is used to compare and analyze the soil nutrient information, soil moisture level and ambient temperature by using a preset information feature database and combining the current growth period, to determine the water and fertilizer diagnosis result of the Polygonatum. The control module 203 is used to perform precise fertilization of the Polygonatum based on the water and fertilizer diagnosis results, through a preset Polygonatum fertilization model and a preset fertilization control model.

[0049] In some embodiments of this application, the determining module 202 is further configured to select growth characteristic data corresponding to the current growth stage of the Polygonatum from the preset information feature database; compare and analyze the growth characteristic data with the soil nutrient information, the soil moisture level, and the ambient temperature to determine the soil nutrient information comparison result, the soil moisture level comparison result, and the ambient temperature comparison result; and determine the water and fertilizer diagnosis result of the Polygonatum based on the soil nutrient information comparison result, the soil moisture level comparison result, and the ambient temperature comparison result.

[0050] In some embodiments of this application, the determining module 202 is further configured to select a sub-preset fertilization model corresponding to the current growth stage of the Polygonatum from the preset fertilization model based on the water and fertilizer diagnosis results; and to perform fertilization analysis on the Polygonatum at the current growth stage through the sub-preset fertilization model to determine the fertilization data of Polygonatum. The control module 203 is also used to precisely fertilize the Polygonatum according to the Polygonatum fertilization data through the pre-fertilization control model.

[0051] In some embodiments of this application, the control module 203 is further configured to generate fertilization instructions according to the Polygonatum fertilization data through the pre-fertilization control model; and to perform precise fertilization on the fertilization equipment through the control device based on the fertilization instructions.

[0052] In some embodiments of this application, the acquisition module 201 is used to acquire historical fertilization data of different growth stages of Polygonatum before precisely fertilizing Polygonatum based on the water and fertilizer diagnosis results and through a preset Polygonatum fertilization model and a preset fertilization control model; and to establish a fertilization model for each of the different growth stages of Polygonatum based on the historical fertilization data of different growth stages. The determining module 202 is further configured to determine the preset fertilization model of Polygonatum sibiricum through the fertilization model of Polygonatum sibiricum; extract soil EC values ​​based on the historical fertilization data; and establish the preset fertilization control model based on the soil EC values.

[0053] Based on the IoT-based fertilization method for Polygonatum sibiricum described in the above embodiments, this application also provides an IoT-based fertilization device for Polygonatum sibiricum, such as... Figure 3 As shown, Figure 3 This application provides a schematic diagram of the structure of an IoT-based Polygonatum fertilization device 3, which includes a processor 301 and a memory 302. The memory 302 stores a computer program; the processor 301 retrieves and runs the computer program from the memory to execute the IoT-based Polygonatum fertilization method described in the above embodiment.

[0054] In the embodiments of this application, the processor 301 described above can be at least one of the following: Application-Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), Central Processing Unit (CPU), Controller, Microcontroller, and Microprocessor. It is understood that for different devices, the electronic device used to implement the above processor function can also be other types, and the embodiments of this application do not specifically limit it.

[0055] This application provides a computer-readable storage medium storing a computer program for implementing the IoT-based fertilization method for Polygonatum as described in any of the above embodiments when executed by a processor.

[0056] For example, the program instructions corresponding to the IoT-based fertilization method of Polygonatum in this embodiment can be stored on storage media such as optical discs, hard disks, and USB flash drives. When the program instructions corresponding to the IoT-based fertilization method of Polygonatum in the storage media are read or executed by an electronic device, the IoT-based fertilization method of Polygonatum as described in any of the above embodiments can be realized.

[0057] Furthermore, in the embodiments of this application, the functional modules can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional module.

[0058] If the integrated unit is implemented as a software functional module and is not sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this embodiment, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the method of this embodiment. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0059] It should be understood that the phrases "one embodiment," "an embodiment," or "some embodiments" mentioned throughout the specification mean that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment," "in one embodiment," or "in some embodiments" appearing throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above-described processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application. The sequence numbers of the embodiments in this application are merely for descriptive purposes and do not represent the superiority or inferiority of the embodiments. The descriptions of the various embodiments above tend to emphasize the differences between the various embodiments; their similarities or commonalities can be referred to mutually, and for the sake of brevity, these will not be repeated here.

[0060] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules. They may be located in one place or distributed across multiple network units. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0061] In addition, each functional module in the various embodiments of this application can be integrated into one processing unit, or each module can be a separate unit, or two or more modules can be integrated into one unit; the integrated modules can be implemented in hardware or in the form of hardware plus software functional units.

[0062] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.

[0063] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0064] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0065] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method or device embodiments.

[0066] The above description is merely an embodiment of this application, but the protection scope of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the protection scope of this application. Therefore, the protection scope of this application should be determined by the protection scope of the claims.

Claims

1. A method for fertilizing Polygonatum sibiricum based on the Internet of Things, characterized in that, The method includes: Obtain soil condition information and the current growth stage of the Polygonatum sibiricum; wherein, the soil condition information includes: soil nutrient information, soil moisture level and ambient temperature; By using a pre-set information feature database and combining it with the current growth stage, the soil nutrient information, soil moisture level and ambient temperature are compared and analyzed to determine the water and fertilizer diagnosis result of the Polygonatum. Based on the water and fertilizer diagnosis results, precise fertilization of the Polygonatum is carried out by using a preset Polygonatum fertilization model and a preset fertilization control model.

2. The method according to claim 1, characterized in that, The step involves comparing and analyzing the soil nutrient information, soil moisture level, and ambient temperature using a preset information feature database, combined with the current growth stage, to determine the water and fertilizer diagnosis result for the Polygonatum sibiricum, including: Select growth characteristic data corresponding to the current growth stage of the Polygonatum from the preset information feature database; The growth characteristic data are compared and analyzed with the soil nutrient information, the soil moisture level, and the ambient temperature to determine the comparison results of the soil nutrient information, the soil moisture level, and the ambient temperature. Based on the comparison results of soil nutrient information, soil moisture level, and ambient temperature, the water and fertilizer diagnosis results of the Polygonatum were determined.

3. The method according to claim 1, characterized in that, Based on the water and fertilizer diagnosis results, the precise fertilization of the Polygonatum is carried out through a preset fertilization model and a preset fertilization control model, including: Based on the water and fertilizer diagnosis results, a sub-preset fertilization model corresponding to the current growth stage of Polygonatum is selected from the preset fertilization model. The fertilization data of Polygonatum at the current growth stage is determined by analyzing the fertilization of Polygonatum using the sub-preset Polygonatum fertilization model. The pre-fertilization control model is used to precisely fertilize the Polygonatum according to the Polygonatum fertilization data.

4. The method according to claim 3, characterized in that, The precise fertilization of Polygonatum sibiricum according to the Polygonatum sibiricum fertilization data through the pre-fertilization control model includes: The fertilization instruction is generated based on the Polygonatum fertilization data using the pre-fertilization control model. Based on the fertilization command, the fertilization equipment is precisely fertilized by controlling the fertilization equipment.

5. The method according to claim 1, characterized in that, Before applying precise fertilization to the Polygonatum sibiricum using a pre-set fertilization model and a pre-set fertilization control model based on the water and fertilizer diagnostic results, the method further includes: Obtain historical fertilization data for different growth stages of Polygonatum sibiricum; Based on the historical fertilization data of the different growth stages, establish the fertilization model of the seed Polygonatum corresponding to the different growth stages of Polygonatum. The preset fertilization model of Polygonatum was determined by the aforementioned fertilization model of Polygonatum sibiricum. Soil EC values ​​are extracted based on the historical fertilization data, and the pre-fertilization control model is established based on the soil EC values.

6. The method according to claim 5, characterized in that, The soil EC value is a soil electrochemical parameter that reflects soil moisture, soil salinity, soil nutrient content, etc.

7. The method according to claim 1, characterized in that, The pre-fertilizer control model is used to adjust the EC value of the fertilizer solution, which reflects the concentration of soluble ions in the fertilizer solution.

8. A Polygonatum sibiricum fertilization system based on the Internet of Things, characterized in that, The IoT-based Polygonatum fertilization system includes: an acquisition module, a determination module, and a control module, wherein, The acquisition module is used to acquire soil condition information of the location of the Polygonatum and the current growth stage of the Polygonatum; wherein, the soil condition information includes: soil nutrient information, soil moisture level and ambient temperature; The determining module is used to compare and analyze the soil nutrient information, soil moisture level and ambient temperature by using a preset information feature database and combining the current growth period, to determine the water and fertilizer diagnosis result of the Polygonatum. The control module is used to precisely fertilize the Polygonatum based on the water and fertilizer diagnosis results, using a preset Polygonatum fertilization model and a preset fertilization control model.

9. A Polygonatum sibiricum fertilization device based on the Internet of Things, characterized in that, include: Processor and memory, of which, The memory is used to store computer programs; The processor is configured to call and run the computer program from the memory to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores executable instructions for causing a processor to execute, thereby implementing the method of any one of claims 1 to 7.

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