Intelligent rice planting decision-making system construction method

Abstract

The invention relates to the technical field of smart agriculture, in particular to an intelligent rice planting decision system construction method. The system integrates planting decision suggestion, planting production monitoring, planting plan making, farming record filling and reporting, material management, land parcel management and equipment management, comprehensively considers multiple factors such as farm land parcels, agricultural materials, environment, rice growth, farming operation and the like, and is based on decision demands in the rice production process and combined with an artificial intelligence algorithm. Scientific, quantifiable and standardized planting decisions are provided for users, and the problem that new farmers have difficulty in planting rice can be well solved.

Description

Technical Field

[0001] The present invention relates to the field of smart agricultural technology, and in particular to a method for constructing an intelligent rice planting decision system. Background Art

[0002] With the rapid development of digital technology and artificial intelligence technology, more and more intelligent technologies are being used to improve the efficiency of rice planting and production.

[0003] However, existing smart rice decision-making tools are mainly based on pest and disease identification and fertilization recommendations, and mainly focus on single-point problems in the rice planting process. The degree of technical integration is not high, and there is a lack of comprehensive decision-making and management capabilities for rice planting. Farm management, agricultural supplies management, agricultural management and crop planting management are rarely coordinated for planning and decision-making.

[0004] Based on this, the present invention provides a method for constructing an intelligent rice planting decision system to solve the above-mentioned technical problems. Summary of the invention

[0005] The purpose of the present invention is to provide a method for constructing an intelligent rice planting decision system, which comprehensively considers multiple factors such as farm plots, agricultural materials, environment, rice growth, and farming operations, based on the decision-making needs in the rice production process, combined with artificial intelligence algorithms, to provide users with scientific, quantifiable, and standardized planting decisions, which can better solve the problem of new farmers' difficulty in getting started in rice planting.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides a method for constructing an intelligent rice planting decision system, comprising the following steps:

[0008] S1. Build a park module for park management and use the park module to create park parameters;

[0009] S2. Construct a plot management module to associate the planting plan with the planting plot. At the same time, create plot parameters using the plot management module and associate the park module with the plot management module.

[0010] S3. Build a material management module for the management of agricultural consumables and input material information through the material management module;

[0011] S4. Build an equipment management module for comprehensive management of equipment data, create equipment parameters, and associate the equipment management module with the plot management module;

[0012] S5. Construct a planting plan making module to provide users with a rice planting plan making function, where users input parameters to make plan parameters, and associate the planting plan making module with the park module and the plot management module;

[0013] S6. Construct a farming record reporting module for manual farming operation record reporting operations, store storage parameters after reporting is completed, and associate the farming record reporting module with the park module, plot management module, material management module, and planting plan formulation module;

[0014] S7. Construct a planting production monitoring module, wherein the planting production monitoring module is divided into two parts: data acquisition and algorithm monitoring. The data acquisition part obtains the associated plot number through the planting plan formulation module, and then obtains the data collected by the equipment management module through the associated plot number. The algorithm monitoring part provides monitoring of the rice production process based on the acquired equipment data. The monitoring content includes crop growth monitoring, farming operation monitoring and environmental data monitoring. At the same time, the planting production monitoring module is associated with the plot management module and the planting plan formulation module;

[0015] S8. Construct a planting management suggestion module to provide agricultural decision-making suggestions in the rice planting production process, and associate the planting management suggestion module with the material management module, the agricultural record filling module and the planting production monitoring module.

[0016] The present invention is further configured as follows: in the step S1, the park parameters include a park serial number, a park name, a park coordinate, a park address and a park photo.

[0017] The present invention is further configured as follows: in the step S2, the plot parameters include the plot number, plot name, plot type, land rent and park number.

[0018] The present invention is further configured as follows: in step S3, the material information includes the agricultural material serial number, agricultural material name, agricultural material type, unit price, description and ingredient information.

[0019] The present invention is further configured as follows: in the step S4, the equipment parameters include equipment serial number, equipment name, equipment type and plot serial number.

[0020] The present invention is further configured as follows: in step S5, the plan parameters include plan number, plan name, start time, end time, sowing method, transplanting method, planting density, planting variety, park number and plot number.

[0021] The present invention is further configured as follows: in step S6, the reported content includes land preparation, fertilization, plant protection, irrigation and manual data collection information.

[0022] The present invention is further configured as follows: in step S7, the storage parameters include agricultural record number, start time, end time, agricultural type, agricultural content, park number, plot number, plan number and agricultural material number.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The present invention integrates planting decision suggestions, planting production monitoring, planting plan formulation, agricultural record filling, material management, plot management and equipment management, and comprehensively considers multiple factors such as farm plots, agricultural materials, environment, rice growth, and agricultural operations. Based on the decision-making needs in the rice production process, combined with artificial intelligence algorithms, it provides users with scientific, quantifiable, and standardized planting decisions, which can better solve the problem of new farmers' difficulty in getting started in rice planting. The intelligent rice planting decision system construction method provided by the present invention has broad application prospects and is worthy of promotion. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a data relationship diagram of each functional module in the method for constructing the intelligent rice planting decision system of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] like Figure 1 As shown, the present invention provides a method for constructing an intelligent rice planting decision system, comprising the following steps:

[0028] S1. Build a park module for park management and use the park module to create park parameters.

[0029] Among them, the park parameters include park serial number, park name, park coordinates, park address and park photos.

[0030] S2. Construct a plot management module to associate the planting plan with the planting plot. At the same time, use the plot management module to create plot parameters and associate the park module with the plot management module.

[0031] Among them, the plot parameters include plot number, plot name, plot type, land rent and park number.

[0032] S3. Build a material management module for the management of agricultural consumables and input material information through the material management module.

[0033] Among them, material information includes agricultural material serial number, agricultural material name, agricultural material type, unit price, description and ingredient information.

[0034] S4. Build an equipment management module for comprehensive management of equipment data, create equipment parameters, and associate the equipment management module with the plot management module.

[0035] Among them, the equipment parameters include equipment serial number, equipment name, equipment type and plot number.

[0036] S5. Construct a planting plan making module to provide users with a rice planting plan making function, and the user inputs parameters to make plan parameters, and associates the planting plan making module with the park module and the plot management module.

[0037] Among them, the planning parameters include planning number, planning name, start time, end time, sowing method, transplanting method, planting density, planting variety, park number and plot number.

[0038] S6. Construct a farming record reporting module for manual farming operation record reporting operations, store the storage parameters after the reporting is completed, and associate the farming record reporting module with the park module, plot management module, material management module and planting plan formulation module.

[0039] Among them, the content to be filled in includes land preparation, fertilization, plant protection, irrigation and manual data collection information.

[0040] S7. Construct a planting production monitoring module, wherein the planting production monitoring module is divided into two parts: data acquisition and algorithm monitoring. The data acquisition part obtains the associated plot number through the planting plan making module, and then obtains the data collected by the equipment management module through the associated plot number. The algorithm monitoring part provides monitoring of the rice production process based on the acquired equipment data. The monitoring content includes crop growth monitoring, agricultural operation monitoring and environmental data monitoring. At the same time, the planting production monitoring module is associated with the plot management module and the planting plan making module.

[0041] The storage parameters include the farming record number, start time, end time, farming type, farming content, park number, plot number, plan number and farming material number.

[0042] S8. Construct a planting management suggestion module to provide agricultural decision-making suggestions in the rice planting production process, and associate the planting management suggestion module with the material management module, the agricultural record filling module and the planting production monitoring module.

[0043] Among them, it provides agricultural decision-making suggestions in the rice planting production process, and its functions are realized through the following steps: (1) Acquire data, obtain environmental, soil, and image data through S7, obtain agricultural operation data and agricultural material numbers in S6 through the associated plan number, and obtain agricultural material data in S3 through the agricultural material number; (2) Construct a crop growth model (DSSAT, WOFOST, GECROS can be used) to realize rice growth simulation, including vegetative growth stage simulation and reproductive growth stage simulation. The model inputs are temperature (degrees Celsius), relative humidity (%), radiation (MJ / m 2 ), the output is a sequence of data in days, including crop dry matter mass, growth period, and nutrient distribution ratio of each crop organ; (3) manually collect measured data, and use sensitivity analysis to realize automatic calibration of sensitive parameters in the actual crop growth process; (4) based on the crop model output, combined with the agricultural record data and planting monitoring data in S6 and S7, train a large model and generate planting management decision recommendations, including land preparation, fertilization, plant protection and irrigation.

[0044] Example 1

[0045] This embodiment provides a method for constructing an intelligent rice planting decision system, which is as follows:

[0046] S1. Park module, to realize the management of the park, creating parameters: park number "Park number 1", park name "Park 1", park coordinates (xxxx, yyyy), park address "xxxxx", and a park photo.

[0047] S2, the plot management module realizes the association between the planting plan and the planting plot, and creates the parameters of the plot number "plot number 1", the plot name "plot 1", the plot type "field", the rent 1000 yuan / year, and the park number "park number 1". The plot is associated with the park in step 1 through the park number.

[0048] S3, material management module, realizes the management of agricultural consumables. Users enter the following through this module: agricultural material serial number "agricultural material serial number 1", agricultural material name "compound fertilizer. 20-10-10", agricultural material type "fertilizer", unit price 5 yuan / kg, description "quick-acting compound fertilizer", ingredient information "nitrogen, phosphorus and potassium ratio 20:10:10".

[0049] S4, equipment management module, realizes the comprehensive management of equipment data, and creates data: equipment serial number "equipment serial number 1", equipment name "comprehensive sensor 1", equipment type "environmental sensor", plot serial number "plot serial number 1"; equipment serial number "equipment serial number 2", equipment name "smart camera 1", equipment type "camera", plot serial number "plot serial number 1". Equipment is associated with the plot through the plot serial number.

[0050] S5. Planting plan making module provides users with rice planting plan making function. Users make plans by manually inputting parameters and entering data: plan number "Plan No. 1", plan name "Plan 1", start time "2024-05-01", end time "2025-10-01", sowing method "transplanting", transplanting method "machine transplanting", planting density "20cm×30cm", planting variety "Tsuen Yu 822", park number "park number 1", plot number "plot number 1". The planting plan is associated with the plot through the plot number.

[0051] S6, agricultural record reporting module, realizes manual agricultural operation record reporting operation, and users fill in: agricultural record number "agricultural record number 1", start time "2024-05-01", end time "2024-05-01", agricultural type "fertilization", agricultural content "basal fertilizer application on May 1", park number "park number 1", plot number "plot number 1", plan number "plan number 1", agricultural material number "agricultural material number 1". The agricultural reporting record is associated with the park in S1, the plot in S2, the agricultural material in S3, and the plan in S5 through the park number, plot number, agricultural material number, and plan number.

[0052] S7, the planting production monitoring module is divided into two parts: data acquisition and algorithm monitoring. The data acquisition part obtains the associated plot number "plot number 1" through the planting plan data "plan number 1" in step 5, and then obtains the environment, soil, and image data associated with the equipment "equipment number 1" and "equipment number 2" in S4 through the associated plot number "plot number 1". The algorithm monitoring part provides monitoring of the rice production process based on the acquired equipment data. The monitoring content includes crop growth monitoring, agricultural operation monitoring, and environmental data monitoring: (1) Build a YOLO convolutional neural network algorithm, use field weeds and pests and diseases image data to train the model to perform the target monitoring task; obtain rice multi-light (1) Spectral satellite images were used to construct a multispectral algorithm to monitor the rice normalized vegetation index (NDVI): (NIR-R) / (NIR+R), where NDVI is the normalized vegetation index, NIR is near infrared light, and R is red light; (2) a YOLO convolutional neural network algorithm was built to train a model using image data of rice land preparation, fertilization, plant protection, and irrigation operations to perform target monitoring tasks and identify agricultural operations involving humans, agricultural machinery, and drones; (3) field meteorological soil sensors were used to collect and monitor environmental data, including temperature (degrees Celsius), humidity (%), and radiation (MJ / m 2 ), rainfall (mm), wind speed (m / s), soil moisture content (%), and soil temperature (Celsius).

[0053] S8, planting management suggestion module, provides agricultural decision-making suggestions in the rice planting production process. Its functions are realized through the following steps: (1) Acquire data, obtain environmental, soil, and image data through S7, obtain agricultural operation data and agricultural material number in S6 through the associated plan number "plan number 1", and obtain agricultural material data in S3 through the agricultural material number "agricultural material number 1"; (2) Construct the crop growth model GECROS to realize rice growth simulation, including vegetative growth stage simulation and reproductive growth stage simulation. The model inputs are temperature (degrees Celsius), relative humidity (%), radiation (MJ / m 2 ), the output result is a sequence data in days, including crop dry matter mass, growth period, and nutrient distribution ratio of each crop organ; (3) manually collect measured data, and use sensitivity analysis to realize automatic calibration of sensitive parameters in the actual crop growth process; (4) based on the crop model output, combined with the agricultural record data and planting monitoring data in S6 and S7, the large model Meta-Lama-3 is used to generate planting management decision recommendations, suggesting "inadequate crop nutrition growth, additional nitrogen fertilizer 5kg / mu".

[0054] The present invention integrates planting decision suggestions, planting production monitoring, planting plan formulation, agricultural record filling, material management, plot management and equipment management, and comprehensively considers multiple factors such as farm plots, agricultural materials, environment, rice growth, and agricultural operations. Based on the decision-making needs in the rice production process, combined with artificial intelligence algorithms, it provides users with scientific, quantifiable, and standardized planting decisions, which can better solve the problem of new farmers' difficulty in getting started in rice planting.

[0055] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0056] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for constructing an intelligent rice planting decision system, characterized in that: The following steps are involved: S1. Build a park module for park management and use the park module to create park parameters; S2. Construct a plot management module to associate the planting plan with the planting plot. At the same time, create plot parameters using the plot management module and associate the park module with the plot management module. S3. Build a material management module for the management of agricultural consumables and input material information through the material management module; S4. Build an equipment management module for comprehensive management of equipment data, create equipment parameters, and associate the equipment management module with the plot management module; S5. Construct a planting plan making module to provide users with a rice planting plan making function, where users input parameters to make plan parameters, and associate the planting plan making module with the park module and the plot management module; S6. Construct a farming record reporting module for manual farming operation record reporting operations, store storage parameters after reporting is completed, and associate the farming record reporting module with the park module, plot management module, material management module, and planting plan formulation module; S7. Construct a planting production monitoring module, wherein the planting production monitoring module is divided into two parts: data acquisition and algorithm monitoring. The data acquisition part obtains the associated plot number through the planting plan formulation module, and then obtains the data collected by the equipment management module through the associated plot number. The algorithm monitoring part provides monitoring of the rice production process based on the acquired equipment data. The monitoring content includes crop growth monitoring, farming operation monitoring and environmental data monitoring. At the same time, the planting production monitoring module is associated with the plot management module and the planting plan formulation module; S8. Construct a planting management suggestion module to provide agricultural decision-making suggestions in the rice planting production process, and associate the planting management suggestion module with the material management module, the agricultural record filling module and the planting production monitoring module.

2. The method for constructing an intelligent rice planting decision system according to claim 1, characterized in that: In the step S1, the park parameters include park serial number, park name, park coordinates, park address and park photos.

3. The method for constructing an intelligent rice planting decision system according to claim 1, characterized in that: In step S2, the plot parameters include plot number, plot name, plot type, land rent and park number.

4. The method for constructing an intelligent rice planting decision system according to claim 1, characterized in that: In step S3, the material information includes the agricultural material serial number, agricultural material name, agricultural material type, unit price, description and ingredient information.

5. The method for constructing an intelligent rice planting decision system according to claim 1, characterized in that: In the step S4, the equipment parameters include equipment serial number, equipment name, equipment type and plot serial number.

6. The method for constructing an intelligent rice planting decision system according to claim 1, characterized in that: In step S5, the plan parameters include plan number, plan name, start time, end time, sowing method, transplanting method, planting density, planting variety, park number and plot number.

7. The method for constructing an intelligent rice planting decision system according to claim 1, characterized in that: In step S6, the reported content includes land preparation, fertilization, plant protection, irrigation and manual data collection information.

8. The method for constructing an intelligent rice planting decision system according to claim 1, characterized in that: In step S7, the storage parameters include the farming record number, start time, end time, farming type, farming content, park number, plot number, plan number and agricultural material number.

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