Crop growth management method and device based on big data, equipment and storage medium
By using big data-based crop growth management methods and electronic devices to identify and adjust crop growth status, the problems of low efficiency and high cost in traditional planting have been solved, and automated and standardized management of crop growth has been achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-08-26
- Publication Date
- 2026-04-14
AI Technical Summary
In traditional agriculture, crop management relies on manual methods, which are inefficient, costly, and cannot achieve standardized processing.
A big data-based crop growth management method is adopted, which obtains crop names through electronic devices, uses big data to obtain standard growth status, identifies actual growth status, and controls crop adjustment modules to adjust growth status, so as to achieve automated management and standardized operation.
It has improved the efficiency of crop management, reduced costs, and enabled standardized and automated management of crop growth.
Smart Images
Figure CN121860797A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of planting, and in particular to a method, apparatus, equipment and storage medium for crop growth management based on big data. Background Technology
[0002] In traditional agriculture, crops are managed through manual planting, care, and monitoring. This management relies on the individual planting experience of the staff.
[0003] Traditional agriculture relies on manual labor for crop management, which is inefficient, lacks standardization, and is costly. Summary of the Invention
[0004] In order to improve efficiency and reduce costs, this application provides a crop growth management method, apparatus, equipment and storage medium based on big data.
[0005] Firstly, the crop growth management method based on big data provided in this application adopts the following technical solution: A big data-based crop growth management method includes: Get crop name; The standard growth status corresponding to the crop name is obtained based on big data. Acquire images and identify the actual growth status of the crop in the images; Determine whether the actual growth state conforms to the standard growth state; If the conditions are not met, the crop adjustment module will be activated to adjust the growth status of the crop.
[0006] By adopting the above technical solution, the electronic device acquires the crop name, then uses big data technology to obtain the corresponding standard growth state based on the crop name. The electronic device acquires an image, identifies the actual growth state of the crop in the image, and determines whether the actual growth state meets the standard growth state. If not, the electronic device controls the crop adjustment module to adjust the crop's growth state so that the crop can grow better. This achieves automated crop growth management, reduces manual monitoring, standardizes operations, reduces costs, and improves efficiency.
[0007] Optionally, the actual growth status includes the actual crop height and the actual crop color; The standard growth status includes standard crop height and standard crop color; The determination of whether the actual growth state meets the standard growth state includes: Determine whether the actual crop height meets the standard growth height; If the actual crop height does not meet the standard growth height, then the steps for controlling the operation of the crop adjustment module are executed. Determine whether the actual crop color conforms to the standard crop color; If the actual crop color does not conform to the standard crop color, then the steps for controlling the operation of the crop adjustment module are executed.
[0008] By adopting the above technical solution, the electronic device determines whether the actual growth state meets the standard growth state by: the electronic device determining whether the actual crop height meets the standard growth height; if the actual crop height does not meet the standard growth height, the electronic device controls the crop adjustment module to work, thereby adjusting the crop growth to change the crop height, and then gradually making the crop height meet the standard growth height.
[0009] Optionally, before the crop regulation module is executed, the following steps are included: Obtain actual environmental parameters; Obtain standard environmental parameters based on big data; Determine whether the actual environmental parameters are the same as the standard environmental parameters; If the actual environmental parameters are the same as the standard environmental parameters, then the step of controlling the operation of the crop regulation module will not be executed; If the actual environmental parameters differ from the standard environmental parameters, the crop regulation module is controlled based on the standard environmental parameters to correct the actual environmental parameters.
[0010] By adopting the above technical solution, the electronic device acquires the actual environmental parameters, namely the actual growth environment parameters of the crop, and simultaneously obtains standard environmental parameters based on big data. It then determines whether the actual environmental parameters are the same as the standard environmental parameters. If the actual environmental parameters are the same as the standard environmental parameters, the electronic device does not execute the step of controlling the crop regulation module. If the actual environmental parameters are different from the standard environmental parameters, the electronic device controls the crop regulation module based on the standard environmental parameters, thereby correcting the actual environmental parameters. This allows the crop to grow better.
[0011] Optionally, before the step of not performing the step of controlling the operation of the crop regulation module, the method further includes: Obtain a first quantity value of the crops whose actual crop color does not conform to the standard crop color; Obtain a second quantity value for all the crops mentioned; The percentage of actual crop colors that do not conform to the standard crop color is calculated based on the first and second quantity values; Determine whether the percentage is greater than a threshold; If the percentage is greater than the threshold, then the crop regulation module is controlled to work.
[0012] By adopting the above technical solution, the electronic device obtains a first quantity value of crops whose actual crop color does not conform to the standard crop color, and then obtains a second quantity value of all crops. The electronic device calculates the proportion of actual crop color that does not conform to the standard crop color based on the first and second quantity values. The electronic device determines whether the proportion is greater than a threshold. If the proportion is greater than the threshold, the electronic device controls the crop adjustment module to work.
[0013] Optionally, before determining whether the actual growth state conforms to the standard growth state, the method further includes: Obtain the actual growth stage of the crop; Based on the big data, obtain the processing solution corresponding to the actual growth stage; The control display module displays the processing solution; and... The locations of the crops that have not received the corresponding treatment are marked.
[0014] By adopting the above technical solution, the electronic device obtains the actual growth stage of the crop, and then obtains the corresponding treatment plan based on big data. The electronic device controls the display module to display the treatment plan so that the staff can understand it. In addition, the electronic device marks the location of the crop that has been treated so that the staff can better distinguish it.
[0015] Optionally, after marking the location of the crop for which no corresponding treatment has been performed, the method further includes: Control the timing module to start timing and obtain the timing time; It is determined in real time whether the timing time is equal to the preset time value; If the timing time is equal to the preset time value, then the crop adjustment module is controlled to stop the nutrient supply.
[0016] By adopting the above technical solution, after the electronic device obtains the processing plan, the electronic device controls the timing module to start timing and obtain the timing time. Then, the electronic device judges in real time whether the timing time is equal to the preset time value. If the timing time is equal to the preset time value, the electronic device controls the crop adjustment module to stop the nutrient supply. If the corresponding treatment is not taken in time within the specified preset time, the subsequent growth of this crop will be poor. Therefore, this crop is abandoned to a certain extent, that is, the nutrient supply is stopped, thereby reducing costs.
[0017] Optionally, obtain the nutrient supply within a preset range for the marked crop; Calculate the difference between the nutrient supply amount and the preset upper limit; Determine whether the difference is greater than the preset nutrient supply value; If the difference is greater than the preset nutrient supply value, then a removal instruction is added to the marked crop.
[0018] By employing the above technical solution, the electronic device acquires the nutrient supply within a preset range for the marked crop, calculates the difference between the nutrient supply and the preset upper limit, and determines whether the difference exceeds the preset nutrient supply value. If the difference exceeds the preset nutrient supply value, a removal instruction is added to the marked crop. After the nutrient supply is stopped, the nutrient status around the marked crop is monitored to determine whether the marked crop is affecting other normally growing crops in the vicinity. If there is an impact, a removal instruction is added to ensure that other crops can grow normally.
[0019] Secondly, the crop growth management device based on big data provided in this application adopts the following technical solution: The first acquisition module is used to acquire crop names; The second acquisition module is used to acquire the standard growth status corresponding to the crop name based on big data. An acquisition and recognition module is used to acquire images and identify the actual growth status of the crop in the images; The judgment module is used to determine whether the actual growth state meets the standard growth state; if the actual growth state does not meet the standard growth state, the process is transferred to the control module. The control module is used to control the operation of the crop regulation module to adjust the growth status of the crop.
[0020] Thirdly, the electronic device provided in this application adopts the following technical solution: An electronic device includes a processor coupled to a memory; the processor is configured to execute a computer program stored in the memory such that the electronic device performs the method as described in the first aspect.
[0021] Fourthly, the computer-readable storage medium provided in this application adopts the following technical solution: A computer-readable storage medium includes a computer program or instructions that, when executed on a computer, cause the computer to perform the method as described in the first aspect. Attached Figure Description
[0022] Figure 1 This is a flowchart of a crop growth management method based on big data, as described in this application.
[0023] Figure 2 This is a block diagram of a crop growth management device based on big data, according to an embodiment of this application.
[0024] Figure 3This is a block diagram of an electronic device according to an embodiment of this application. Implementation
[0025] The following is in conjunction with the appendix Figure 1-3 This application will be described in further detail.
[0026] This specific embodiment is merely an explanation of this application and is not intended to limit it. Users skilled in the art can make modifications to this embodiment without contributing any inventive step after reading this specification, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.
[0027] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by users of ordinary skills in the art without creative effort are within the scope of protection of this application.
[0028] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article, unless otherwise specified, generally indicates that the preceding and following related objects have an "or" relationship.
[0029] This application discloses a crop growth management method based on big data. This big data-based crop growth management method can be executed by electronic devices.
[0030] This application discloses a crop growth management method based on big data. (Refer to...) Figure 1 The main processes of a big data-based crop growth management method are described below (S100~S500): Step S100: Obtain the crop name; Step S200: Obtain the standard growth status corresponding to the crop name based on big data; Step S300: Acquire an image and identify the actual growth status of the crop in the image; Step S400: Determine whether the actual growth state meets the standard growth state; if the actual growth state does not meet the standard growth state, proceed to step S500. Step 500: Control the crop adjustment module to adjust the crop's growth status.
[0031] The electronic device acquires the crop name and then, based on big data, obtains the standard growth status corresponding to that crop name. The standard growth status includes the crop's height and color at various stages of growth; in other words, the labeled growth status encompasses various aspects of the crop's data. The electronic device then acquires an image of the crop to identify its actual growth status. It then determines whether the actual growth status conforms to the standard growth status. If not, the electronic device controls the crop adjustment module to adjust the crop's growth status, transforming it towards the standard growth status.
[0032] As an optional implementation of this application, the actual growth state includes the actual crop height and the actual crop color; the standard growth state includes the standard crop height and the standard crop color; determining whether the actual growth state meets the standard growth state includes: determining whether the actual crop height meets the standard growth height; if the actual crop height does not meet the standard growth height, then executing the step of controlling the operation of the crop adjustment module; determining whether the actual crop color meets the standard crop color; if the actual crop color does not meet the standard crop color, then executing the step of controlling the operation of the crop adjustment module.
[0033] The actual growth status includes the actual crop height and actual crop color. The standard growth status includes the standard crop height and standard crop color. The electronic device determines whether the actual growth status meets the standard growth status by: determining whether the actual crop height meets the standard growth height; if the actual crop height does not meet the standard growth height, the electronic device executes the steps to control the crop adjustment module; and determining whether the actual crop color meets the standard crop color; if the actual crop color does not meet the standard crop color, the electronic device executes the steps to control the crop adjustment module.
[0034] As an optional implementation of this application, before executing the operation of the crop regulation module, the method includes: acquiring actual environmental parameters; acquiring standard environmental parameters based on big data; determining whether the actual environmental parameters are the same as the standard environmental parameters; if the actual environmental parameters are the same as the standard environmental parameters, then the step of controlling the operation of the crop regulation module is not executed; if the actual environmental parameters are different from the standard environmental parameters, then the operation of the crop regulation module is controlled based on the standard environmental parameters to correct the actual environmental parameters.
[0035] Before executing the crop regulation module, the electronic device acquires environmental parameters and obtains standard environmental parameters based on big data. The electronic device then determines whether the actual environmental parameters are the same as the standard environmental parameters. If the actual environmental parameters are the same as the standard environmental parameters, the electronic device does not execute the steps of controlling the crop regulation module. If the actual environmental parameters are different from the standard environmental parameters, the electronic device controls the crop regulation module based on the standard environmental parameters, thereby correcting the actual environmental parameters and enabling the crop to grow better.
[0036] As an optional implementation of this application, before performing the step of controlling the operation of the crop adjustment module, a first quantity value of crops whose actual crop color does not conform to the standard crop color is obtained; a second quantity value of all crops is obtained; the proportion of actual crop color that does not conform to the standard crop color is calculated based on the first quantity value and the second quantity value; it is determined whether the proportion is greater than a threshold; if the proportion is greater than the threshold, the operation of the crop adjustment module is controlled.
[0037] Before the electronic device activates the crop adjustment module, it acquires a first quantity value indicating that the actual crop color does not conform to the standard crop color, and a second quantity value indicating that all crops do not conform to the standard crop color. Based on the first and second quantity values, the electronic device calculates the percentage of actual crops whose color does not conform to the standard crop color. Then, the electronic device determines whether the percentage is greater than a threshold. If the percentage is greater than the threshold, the electronic device activates the adjustment module. If a large number of crops do not conform to the standard crop color, adjustments are necessary even if the actual environmental parameters differ from the standard environmental parameters, so that the crops can gradually return to normal.
[0038] The percentage is obtained by dividing the first quantity value by the second quantity value.
[0039] As an optional implementation of this application, before step S400, the method further includes: obtaining the actual growth stage of the crop; obtaining the processing plan corresponding to the actual growth stage based on big data; controlling the display module to display the processing plan; and marking the location of the crop that has not received the corresponding processing.
[0040] Before step S400, the electronic device acquires the actual growth stage of the crop, obtains the corresponding treatment plan based on big data, controls the display module to display the treatment plan, and marks the location of crops that have not received corresponding treatment, so that workers can identify them more quickly and improve efficiency.
[0041] As an optional implementation of this application, after marking the location of the crop that has not undergone corresponding treatment, the method further includes: controlling the timing module to start timing and obtaining the timing time; determining in real time whether the timing time is equal to the preset time value; if the timing time is equal to the preset time value, controlling the crop adjustment module to stop nutrient supply.
[0042] After marking the locations of crops that haven't received corresponding treatment, the electronic device controls the timing module to start timing and obtain the time. The electronic device then checks in real time whether the time equals a preset time value. If the time equals the preset time value, the electronic device controls the crop adjustment module to stop nutrient supply. In other words, if a crop that needs treatment hasn't been treated within a certain time, it's determined that the crop has missed its treatment window, and subsequent treatment is futile. Therefore, stopping nutrient supply at this point avoids nutrient waste and reduces costs. Meanwhile, the marked crops still have some value, so apart from stopping nutrient supply, other aspects of the treatment continue normally.
[0043] As an optional implementation of this application, the nutrient supply amount within a preset range of the marked crop is obtained; the difference between the nutrient supply amount and the preset upper limit is calculated; it is determined whether the difference is greater than the preset nutrient supply value; if the difference is greater than the preset nutrient supply value, a removal instruction is added to the marked crop.
[0044] The electronic device acquires the nutrient supply within a preset range for the marked crop. Within this range, other crops may or may not be present. The device calculates the difference between the acquired nutrient supply and a preset upper limit, determining if this difference exceeds the preset nutrient supply value. This determines whether the marked crop is diverting nutrients from other crops within a certain range, leading to an increase in their nutrient supply. When the increase in nutrient supply to other crops reaches a certain level, a removal instruction is added for the marked crop, meaning it is removed. Because the marked crop is not only not addressed promptly but also excessively impacts the nutrient supply to other crops, a removal instruction is added to remind staff to take appropriate action.
[0045] The aforementioned crop regulation module includes functions such as watering, nutrient supply, and light intensity adjustment. The crop regulation module is a comprehensive module that can be uniformly controlled by electronic equipment, thereby performing related tasks according to the instructions output by the electronic equipment.
[0046] Figure 2 A structural block diagram of a crop growth management device 600 based on big data, provided for embodiments of this application, is shown below. Figure 2 As shown, the big data-based crop growth management device 600 includes: The first acquisition module 601 is used to acquire crop names; The second acquisition module 602 is used to acquire the standard growth status corresponding to the crop name based on big data. The acquisition and recognition module 603 is used to acquire images and identify the actual growth status of crops in the images; The judgment module 604 is used to determine whether the actual growth state meets the standard growth state; if the actual growth state does not meet the standard growth state, the process is transferred to the control module 605. The control module 605 is used to control the operation of the crop regulation module to adjust the crop growth status.
[0047] Specifically, the judgment module 604 includes: The first judgment submodule is used to determine whether the actual crop height meets the standard growth height; if the actual crop height does not meet the standard growth height, the steps of controlling the crop adjustment module are executed. The second judgment submodule is used to determine whether the actual crop color conforms to the standard crop color; if the actual crop color does not conform to the standard crop color, the steps of controlling the operation of the crop adjustment module are executed.
[0048] The actual growth status includes the actual crop height and actual crop color; the standard growth status includes the standard crop height and standard crop color. In this optional embodiment, the big data-based crop growth management device 600 further includes: The first acquisition submodule is used to acquire actual environmental parameters before the crop regulation control module is executed. The second acquisition submodule is used to acquire standard environmental parameters based on big data. The third judgment submodule is used to determine whether the actual environmental parameters are the same as the standard environmental parameters. If the actual environmental parameters are the same as the standard environmental parameters, the steps to control the operation of the crop regulation module are not executed. If the actual environmental parameters are different from the standard environmental parameters, the operation of the crop regulation module is controlled based on the standard environmental parameters to correct the actual environmental parameters.
[0049] In this optional embodiment, the big data-based crop growth management device 600 further includes: The third acquisition submodule is used to acquire a first quantity value of crops whose actual crop color does not conform to the standard crop color before executing the steps of controlling the operation of the crop adjustment module; The fourth submodule is used to obtain the second quantity value of all crops; The first calculation submodule is used to calculate the percentage of actual crop colors that do not conform to the standard crop colors based on the first quantity value and the second quantity value. The fourth judgment submodule is used to determine whether the proportion is greater than the threshold; if the proportion is greater than the threshold, the crop regulation module is controlled to work.
[0050] In this optional embodiment, the big data-based crop growth management device 600 further includes: The fifth acquisition submodule is used to acquire the actual growth stage of the crop before determining whether the actual growth state meets the standard growth state; The sixth acquisition submodule is used to acquire the processing solutions corresponding to the actual growth stage based on big data; The first control submodule is used to control the display module's display processing scheme; The tagging submodule is used to mark the locations of crops that have not received the corresponding treatment.
[0051] In this optional embodiment, the big data-based crop growth management device 600 further includes: The second control submodule is used to control the timing module to start timing and obtain the timing time after marking the location of the crop that has not been treated. The fifth judgment submodule is used to determine in real time whether the timing time is equal to the preset time value; if the timing time is equal to the preset time value, the crop adjustment module is controlled to stop the nutrient supply.
[0052] In this optional embodiment, the big data-based crop growth management device 600 further includes: The seventh acquisition submodule is used to acquire the nutrient supply within a preset range for the marked crop; The second calculation submodule is used to calculate the difference between the nutrient supply and the preset upper limit. The sixth judgment submodule is used to determine whether the difference is greater than the preset value of nutrient supply; if the difference is greater than the preset value of nutrient supply, a removal instruction is added to the marked crop.
[0053] Figure 3 This is a structural block diagram of an electronic device 700 provided in an embodiment of this application. The electronic device 700 can be a mobile phone, tablet computer, PC, server, or other similar device. Figure 3 As shown, the electronic device 700 includes a memory 701, a processor 702, and a communication bus 703; the memory and the processor 702 are connected via the communication bus 703. The memory 701 stores a computer program that can be loaded by the processor 702 and executed as described in the above embodiments, which is a big data-based crop growth management method.
[0054] The memory 701 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 701 may include a stored program area and a stored managed data area. The stored program area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the big data-based crop growth management method provided in the above embodiments, etc. The stored managed data area may store managed data involved in the big data-based crop growth management method provided in the above embodiments, etc.
[0055] Processor 702 may include one or more processing cores. Processor 702 executes instructions, programs, code sets, or instruction sets stored in memory 701, and calls managed data stored in memory 701 to perform various functions of this application and process managed data. Processor 702 may 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 devices used to implement the functions of processor 702 may also be other types, and this application embodiment does not specifically limit the specific devices used.
[0056] The communication bus 703 may include a path for transmitting information between the aforementioned components. The communication bus 703 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 703 can be divided into an address bus, a managed data bus, a control bus, etc. For ease of representation, Figure 3 The symbol is represented by a single double arrow, but this does not mean that there is only one bus or one type of bus.
[0057] This application provides a computer storage medium storing a computer program that can be loaded by a processor and executed as described in the above embodiments, which is a big data-based crop growth management method.
[0058] In this embodiment, the computer storage medium can be a tangible device that holds and stores instructions used by the instruction execution device. The computer storage medium can be, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof. Specifically, the computer storage medium can be a portable computer disk, a hard disk, a USB flash drive, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), speaker random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory stick, floppy disk, optical disk, magnetic disk, mechanical encoding device, or any combination thereof.
[0059] The terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.
[0060] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.
Claims
1. A crop growth management method based on big data, characterized in that, include: Get crop name; The standard growth status corresponding to the crop name is obtained based on big data. Acquire images and identify the actual growth status of the crop in the images; Determine whether the actual growth state conforms to the standard growth state; If the conditions are not met, the crop adjustment module will be activated to adjust the growth status of the crop.
2. The method according to claim 1, characterized in that, include: The actual growth status includes the actual crop height and the actual crop color; The standard growth status includes standard crop height and standard crop color; The determination of whether the actual growth state meets the standard growth state includes: Determine whether the actual crop height meets the standard growth height; If the actual crop height does not meet the standard growth height, then the steps for controlling the operation of the crop adjustment module are executed. Determine whether the actual crop color conforms to the standard crop color; If the actual crop color does not conform to the standard crop color, then the steps for controlling the operation of the crop adjustment module are executed.
3. The method according to claim 2, characterized in that, Before the crop regulation module is executed, the following steps are included: Obtain actual environmental parameters; Obtain standard environmental parameters based on big data; Determine whether the actual environmental parameters are the same as the standard environmental parameters; If the actual environmental parameters are the same as the standard environmental parameters, then the step of controlling the operation of the crop regulation module will not be executed; If the actual environmental parameters differ from the standard environmental parameters, the crop regulation module is controlled based on the standard environmental parameters to correct the actual environmental parameters.
4. The method according to claim 3, characterized in that, Prior to the step of not performing the operation of the crop regulation module, the method further includes: Obtain a first quantity value of the crops whose actual crop color does not conform to the standard crop color; Obtain a second quantity value for all the crops mentioned; The percentage of actual crop colors that do not conform to the standard crop color is calculated based on the first and second quantity values; Determine whether the percentage is greater than a threshold; If the percentage is greater than the threshold, then the crop regulation module is controlled to work.
5. The method according to claim 1, characterized in that, Before determining whether the actual growth state conforms to the standard growth state, the method further includes: Obtain the actual growth stage of the crop; Based on the big data, obtain the processing solution corresponding to the actual growth stage; The control display module displays the processing solution; and... The locations of the crops that have not received the corresponding treatment are marked.
6. The method according to claim 5, characterized in that, Following the location of the crop where the marking did not receive corresponding treatment, the following is also included: Control the timing module to start timing and obtain the timing time; It is determined in real time whether the timing time is equal to the preset time value; If the timing time is equal to the preset time value, then the crop adjustment module is controlled to stop the nutrient supply.
7. The method according to claim 6, characterized in that, include: Obtain the nutrient supply within a preset range for the labeled crop; Calculate the difference between the nutrient supply amount and the preset upper limit; Determine whether the difference is greater than the preset nutrient supply value; If the difference is greater than the preset nutrient supply value, then a removal instruction is added to the marked crop.
8. A crop growth management device based on big data, characterized in that, include: The first acquisition module is used to acquire crop names; The second acquisition module is used to acquire the standard growth status corresponding to the crop name based on big data. An acquisition and recognition module is used to acquire images and identify the actual growth status of the crop in the images; The judgment module is used to determine whether the actual growth state meets the standard growth state; if the actual growth state does not meet the standard growth state, the process is transferred to the control module. The control module is used to control the operation of the crop regulation module to adjust the growth status of the crop.
9. An electronic device, characterized in that, The device includes a processor coupled to a memory; the processor is configured to execute a computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 7.
10. A computer-readable storage medium, characterized in that, It includes a computer program or instructions that, when run on a computer, cause the computer to perform the method as described in any one of claims 1 to 7.