A Method and System for Optimizing the Grid-based Blueberry Planting Layout

Abstract

The present invention discloses a grid-based blueberry planting layout optimization method and system, and relates to the field of electronic digital data processing technology. The grid-based blueberry planting layout optimization method comprises the following steps: obtaining the pest and disease status of blueberry plants, searching for pest and disease grid areas, and obtaining pest and disease levels and performing secondary partitioning. The present invention obtains a pest and disease infection index from pest and disease data, and compares it with the pest and disease warning value to obtain the blueberry plant pest and disease status. The grids where the blueberry plant pest and disease status is first-level breeding pests and diseases are affected are then marked as pest and disease grid areas. The graded control index obtained based on the pest and disease infection coefficient is then compared with the graded control interval to obtain the pest and disease level and perform secondary partitioning accordingly. This achieves the effect of improving the accuracy of graded pest and disease management during blueberry planting, and solves the problem of low correlation between grid-based blueberry planting layout and pest and disease control in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic digital data processing, and in particular to a gridded blueberry planting layout optimization method and system. Background Art

[0002] With the advancement of agricultural technology, precision agriculture and smart farming are becoming key trends in modern agriculture. Grid-based planting layouts, incorporating advanced technologies such as the Internet of Things, big data, and artificial intelligence, enable digital and intelligent management of agricultural production, providing new approaches and solutions for increasing crop yields, conserving resources, and reducing environmental impact. This grid-based layout divides the planting area into multiple small grids, each equipped with sensors and monitoring equipment to collect real-time data on soil moisture, temperature, pH, and other parameters. This data is analyzed by intelligent systems to generate precise irrigation, fertilization, and pest control plans.

[0003] The existing grid-based blueberry planting layout utilizes the Internet of Things (IoT) and precision agriculture technologies to divide the planting area into multiple small grid cells. Sensors are installed in each cell to monitor key agricultural parameters such as soil moisture, temperature, pH, and light intensity in real time. The data collected by these sensors is transmitted via a wireless network to a central control system, which uses data analytics to generate optimized irrigation, fertilization, and pest control strategies. Existing technologies also include automated equipment such as drip irrigation systems, drones, and robots for precise implementation of management plans.

[0004] For example, the invention patent announcement with announcement number: CN113177345B discloses a grid-based crop planting layout optimization method, which includes: establishing a grid model for the target planting area, obtaining the potential crop yield and suitable planting area, minimum crop irrigation water requirement, crop fertilization intensity, cultivated land area and irrigation area data in each grid unit, combining the county-level statistical planting data of the target planting area, allocating the crop planting data in each grid unit, taking the minimum total irrigation water requirement as the optimization goal, optimizing the planting layout based on predetermined constraints, and obtaining the crop planting area in each grid unit after optimization.

[0005] For example, the invention patent publication number CN117150636B discloses a method and system for indoor plant planting layout, comprising: an indoor two-dimensional plan acquisition module, a building BIM model acquisition module, a candidate plant planting area acquisition module, a plant information acquisition module, and a plant planting layout plan output module. This method matches the plant's suitable temperature range and suitable light range with the temperature and light data of the indoor planting area, respectively, and then analyzes the fitness of each individual plant to determine whether the corresponding plant can grow appropriately in the selected planting area. This is then used as a constraint for genetic algorithm simulation, which can better meet the indoor plant planting layout requirements and eliminates the need for professional personnel to design based on experience.

[0006] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the existing technology, pest and disease control is a major challenge faced in blueberry cultivation, especially in the case of a grid layout. Pests and diseases may spread rapidly between different grids, and there is a problem of low correlation between the grid blueberry planting layout and pest and disease control. Summary of the Invention

[0008] The embodiments of the present application provide a grid-based blueberry planting layout optimization method and system, thereby solving the problem of low correlation between grid-based blueberry planting layout and pest and disease control in the prior art, and improving the accuracy of graded pest and disease management during blueberry planting.

[0009] The embodiment of the present application provides a grid-based blueberry planting layout optimization method, comprising the following steps: S1, collecting pest and disease data of a blueberry plantation to be optimized in real time through a blueberry monitoring device, and analyzing the environmental compliance of the blueberry plants based on the pest and disease data to obtain a pest and disease infection index, and comparing the pest and disease infection index with a pest and disease warning value obtained from a preset database to obtain a blueberry plant pest and disease status, wherein the pest and disease infection index is used to reflect the degree to which the blueberry plants are susceptible to pests and diseases, and the blueberry plant pest and disease status includes healthy and first-level pest and disease impact; S2, classifying blueberry plants whose pest and disease status is first-level pest and disease impact The corresponding grid is marked as a pest and disease grid area, and the pest and disease status of the blueberry plants in the adjacent areas of the pest and disease grid area is found to be affected by the first-level breeding pests and diseases; S3, the graded control index obtained based on the pest and disease infection coefficient of the pest and disease grid area is compared with the graded control interval to obtain the pest and disease level of the pest and disease grid area, the pest and disease grid area is secondary partitioned according to the pest and disease level, and corresponding pest and disease management measures are taken for the blueberry plantations to be optimized after the secondary partitioning. The graded control index is used to quantify the degree to which blueberry plants in a region are susceptible to pests and diseases, and the pest and disease management measures include primary management and secondary management.

[0010] Furthermore, the method for obtaining the pest and disease data is as follows: environmental data is obtained by monitoring the environmental conditions of a preset number of blueberry plants in a preset representative grid area within a preset time period through an environmental sensor, the environmental sensor includes a temperature sensor, a humidity sensor and a light sensor, the environmental data includes ambient temperature, ambient humidity and ambient light intensity, and the preset representative grid area represents a range sampled and selected in the blueberry plantation to be optimized for monitoring the growth conditions of blueberry plants; soil data is obtained by monitoring the soil conditions of a preset number of blueberry plants in a preset representative grid area within a preset time period through a soil sensor, the soil sensor includes a soil moisture sensor, a soil temperature sensor and a soil pH sensor, and the soil data includes soil moisture, soil temperature and soil pH value; a multispectral image is obtained by monitoring the preset representative grid area through a multispectral camera equipped on a drone; the pest and disease data includes environmental data, soil data and multispectral images; the blueberry monitoring equipment includes an environmental sensor, a soil sensor, a drone and a multispectral camera.

[0011] Furthermore, the process of obtaining the pest and disease infection index is as follows: an environmental assessment is performed on the blueberry plantation to be optimized based on environmental data and reference environmental data obtained from a preset database to obtain an environmental impact index, and the environmental impact index is used to evaluate the compliance of the blueberry plantation's growth environment with the pest and disease environment; a soil assessment is performed on the blueberry plantation to be optimized based on soil data and reference soil data obtained from a preset database to obtain a soil impact index, and the soil impact index is used to evaluate the compliance of the soil environment where the roots of the blueberry plants are located with the pest and disease environment; a red light band and a near-infrared band are extracted from the multispectral image, and the corresponding pixel points in the red light band and the near-infrared band are substituted into the normalized vegetation index formula to obtain a normalized vegetation index; the pest and disease infection index includes an environmental impact index, a soil impact index and a normalized vegetation index.

[0012] Furthermore, the specific process of performing environmental assessment on the blueberry plantation to be optimized based on the environmental data and the reference environmental data obtained from the preset database to obtain the environmental impact index is as follows: obtaining reference environmental data from the preset database, the reference environmental data including reference environmental temperature, reference environmental humidity and reference environmental light intensity, the environmental temperature range including the maximum environmental temperature and the minimum environmental temperature, the environmental humidity range including the maximum environmental humidity and the minimum environmental humidity, and the environmental light intensity range including the maximum environmental light intensity and the minimum environmental light intensity; numbering the preset representative grid areas, if the environmental data meets the environmental abnormality condition, the corresponding environmental impact index is recorded as 1, otherwise the environmental impact index is obtained based on the environmental data and the reference environmental data, and the environmental impact index is calculated using the following formula:

[0013] ;

[0014] Where n represents the number of the preset representative grid area, , N represents the total number of preset representative grid areas, represents the ambient temperature of the nth preset representative grid area, Indicates the minimum ambient temperature. Indicates the maximum ambient temperature. Represents the ambient humidity of the nth preset representative grid area, Indicates the minimum value of ambient humidity. Indicates the maximum ambient humidity. Represents the ambient light intensity of the nth preset representative grid area, Indicates the minimum ambient light intensity. Indicates the maximum ambient light intensity. Represents the environmental impact index of the nth preset representative grid area.

[0015] Furthermore, the specific process of performing soil assessment on the blueberry plantation to be optimized based on the soil data and the reference soil data obtained from the preset database to obtain the soil impact index is as follows: obtaining reference soil data from the preset database, the reference soil data including reference soil temperature, reference soil moisture and reference soil pH value, the soil temperature range including the maximum soil temperature and the minimum soil temperature, the soil moisture range including the maximum soil moisture and the minimum soil moisture, and the soil pH value range including the maximum soil pH value and the minimum soil pH value; judging whether the soil data meets the soil abnormality condition based on the reference soil data, if the soil data meets the soil abnormality condition, the corresponding soil impact index is recorded as 1, otherwise the soil impact index is obtained based on the soil data and the reference soil data, and the soil impact index is calculated using the following formula:

[0016] ;

[0017] Where n represents the preset representative grid area, , N represents the total number of preset representative grid areas, represents the soil temperature of the nth preset representative grid area, Indicates the minimum soil temperature, represents the maximum soil temperature, represents the soil moisture of the nth preset representative grid area, Indicates the minimum soil moisture. represents the maximum soil moisture, represents the soil pH value of the nth preset representative grid area, Indicates the minimum soil pH value. Indicates the maximum soil pH value. Represents the soil impact index of the nth preset representative grid area.

[0018] Furthermore, the process of obtaining the disease and pest status of the blueberry plant is as follows: step one, obtaining a disease and pest warning value from a preset database, wherein the disease and pest warning value includes an environmental assessment warning value, a soil assessment warning value, and a vegetation index warning value; step two, comparing the disease and pest infection index with the corresponding disease and pest warning value; if the environmental impact index is greater than the environmental assessment warning value, the disease and pest status of the blueberry plant is recorded as a first-level breeding disease and pest impact, otherwise, step three is executed; step three, if the soil impact index is greater than the soil assessment warning value, the disease and pest status of the blueberry plant is recorded as a first-level breeding disease and pest impact, otherwise, step four is executed; step four, if the normalized vegetation index is less than the vegetation index warning value, the disease and pest status of the blueberry plant is recorded as a first-level breeding disease and pest impact, otherwise, the disease and pest status of the blueberry plant is recorded as healthy.

[0019] Furthermore, the process of obtaining the graded control index is as follows: number the pest grid areas and obtain the assessment weights from a preset database, wherein the assessment weights include the environmental assessment weight, the soil assessment weight, and the vegetation assessment weight; obtain the graded control index according to the pest infection index corresponding to the pest grid area, and the graded control index is calculated using the following formula:

[0020] ;

[0021] Where h represents the number of the pest grid area, , H represents the total number of pest and disease grid areas, represents the environmental impact index of the hth pest grid area, represents the environmental assessment weight, represents the soil impact index of the hth pest grid area, represents the soil assessment weight, represents the normalized vegetation index of the hth pest grid area, represents the vegetation assessment weight, Represents the hierarchical control index of the hth pest grid area.

[0022] Furthermore, the specific process of the secondary partitioning is as follows: obtaining the level control interval from the preset database, the level control interval includes the first level control interval and the second level control interval; comparing the graded control index with the level control interval to obtain the pest and disease level, the pest and disease level includes the first level pest and disease and the second level pest and disease; using the depth-first search algorithm to perform secondary partitioning according to the pest and disease level, recording the first level pest and disease partition as the first level management area, and recording the second level pest and disease partition as the second level management area, and the pest and disease management partition is used to accurately manage the pest and disease grid area.

[0023] Furthermore, the corresponding pest and disease management measures are taken for the blueberry plantation to be optimized after the secondary partition, and then the following is also included: continuing to monitor the blueberry plants in the first-level management area within a preset time period; if the pest and disease status of the blueberry plants in the first-level management area is still affected by first-level breeding pests and diseases, then the first-level management area is re-divided into the second-level management area for second-level management; if the pest and disease status of the blueberry plants in the first-level management area is healthy, then the first-level management area is re-marked as healthy, and no further pest and disease management measures are needed.

[0024] The embodiment of the present application provides a grid-based blueberry planting layout optimization system, which is characterized by including an infection grid judgment module, an infection grid search module and a pest and disease zoning management module: wherein the infection grid judgment module is used to collect pest and disease data of the blueberry plantation to be optimized in real time through a blueberry monitoring device within a preset time period, and analyze the environmental compliance of the blueberry plants based on the pest and disease data to obtain a pest and disease infection index, and judge the pest and disease infection index with the pest and disease warning value obtained from a preset database to obtain the pest and disease status of the blueberry plant, the pest and disease infection index is used to reflect the degree to which the blueberry plant is susceptible to pests and diseases, and the pest and disease status of the blueberry plant includes health and primary breeding pests and diseases; the infection grid search module is used to The grid corresponding to the blueberry plant whose disease and pest status is affected by the first-level breeding pests is marked as the disease and pest grid area, and the disease and pest status of the blueberry plant in the adjacent area of the disease and pest grid area is searched to see whether it is affected by the first-level breeding pests; the disease and pest zoning management module is used to compare the graded control index obtained based on the disease and pest infection coefficient of the disease and pest grid area with the grade control interval to obtain the disease and pest level of the disease and pest grid area, and perform secondary partitioning on the disease and pest grid area according to the disease and pest level, and take corresponding disease and pest management measures for the blueberry plantation to be optimized after the secondary partitioning, the graded control index is used to quantify the degree to which blueberry plants in a region are susceptible to pests and diseases, and the disease and pest management measures include primary management and secondary management.

[0025] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0026] 1. The pest and disease infection index is obtained by analyzing the environmental conditions of the blueberry plants through pest and disease data. The pest and disease status of the blueberry plants is judged in combination with the pest and disease warning value. The grids corresponding to the blueberry plants affected by the first-level breeding pests are marked as pest and disease grid areas. The corresponding pest and disease levels are then obtained based on the graded control index obtained based on the pest and disease infection coefficient of the pest and disease grid area. Finally, the pest and disease grid area is secondary partitioned according to the pest and disease level to adopt corresponding pest and disease management measures, thereby achieving accurate management of blueberry plants infected with pests and diseases, and further achieving improved accuracy of graded pest and disease management during blueberry planting, effectively solving the problem of low correlation between grid-based blueberry planting layout and pest and disease control in the existing technology.

[0027] 2. An environmental assessment of the blueberry plantation to be optimized is conducted using environmental data and reference environmental data to obtain an environmental impact index. Then, a soil assessment of the blueberry plantation to be optimized is conducted based on soil data and reference soil data obtained from a preset database to obtain a soil impact index. Then, the red light band and near-infrared band are extracted from the multispectral image, and the corresponding pixel points in the red light band and the near-infrared band are substituted into the normalized vegetation index formula to obtain the normalized vegetation index, thereby determining the infection status of the blueberry plants and optimizing the pest and disease management layout of the blueberry plantation to be optimized.

[0028] 3. By numbering the pest and disease grid areas and obtaining the evaluation weights from the preset database, a graded control index is obtained according to the pest and disease infection index corresponding to the pest and disease grid area, thereby realizing secondary partitioning of the pest and disease grid area, and then achieving accurate management when blueberry plants are infected with pests and diseases. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A flowchart of a gridded blueberry planting layout optimization method provided in an embodiment of the present application;

[0030] Figure 2 A schematic diagram of the changes in the hierarchical control index provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] The embodiment of the present application solves the problem of low correlation between grid blueberry planting layout and pest and disease control in the prior art by providing a grid blueberry planting layout optimization method and system. The blueberry monitoring equipment is used to collect pest and disease data of the blueberry plantation to be optimized in real time, and the environmental impact index is obtained by performing an environmental assessment on the blueberry plantation to be optimized based on the environmental data and the reference environmental data. Then, the soil of the blueberry plantation to be optimized is assessed based on the soil data and the reference soil data obtained from the preset database to obtain the soil impact index. Then, the red light band and the near-infrared band are extracted from the multispectral image, and the corresponding pixel points in the red light band and the near-infrared band are substituted into the normalized vegetation index formula to obtain the normalized vegetation index. The pest and disease infection index includes the environmental impact index, the soil impact index and the normalized vegetation index. The pest and disease infection index is judged with the pest and disease warning value to obtain the pest and disease status of the blueberry plants, and then the grids corresponding to the blueberry plants whose pest and disease status is the first-level breeding pests are marked as the pest and disease grid area, and the pest and disease status of the blueberry plants in the adjacent areas of the pest and disease grid area is found to be the first-level breeding pests and disease; then, the evaluation weight is obtained from the preset database, and the graded control index is obtained according to the pest and disease infection index corresponding to the pest and disease grid area, and compared with the grade control interval to obtain the pest and disease level of the pest and disease grid area, and the pest and disease grid area is secondary partitioned according to the pest and disease level, and corresponding pest and disease management measures are taken for the blueberry plantations to be optimized after the secondary partitioning, so as to improve the accuracy of graded pest and disease management in the blueberry planting process.

[0032] The technical solution in the embodiment of the present application is to solve the problem of low correlation between the above-mentioned grid-based blueberry planting layout and pest and disease control. The overall idea is as follows:

[0033] The pest and disease grid area is obtained through the pest and disease infection index and the pest and disease warning value. Then, the corresponding pest and disease level is obtained based on the graded control index of the pest and disease grid area. Finally, the pest and disease grid area is secondary divided according to the pest and disease level to take corresponding pest and disease management measures, achieving the effect of improving the accuracy of graded pest and disease management during blueberry cultivation.

[0034] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0035] like Figure 1As shown, it is a flow chart of a gridded blueberry planting layout optimization method provided by an embodiment of the present application, the method comprising the following steps: S1, collecting pest and disease data of the blueberry plantation to be optimized in real time through a blueberry monitoring device, and analyzing the environmental compliance of the blueberry plants based on the pest and disease data to obtain a pest and disease infection index, and judging the pest and disease infection index with the pest and disease warning value obtained from a preset database to obtain the pest and disease status of the blueberry plants, the blueberry monitoring device is used to observe the growth status of the blueberry plants in each initial partition of the strawberry plantation to be optimized in real time within a preset time period, the pest and disease data is used to reflect the health status of the blueberry plants, the pest and disease infection index is used to reflect the degree to which the blueberry plants are susceptible to pests and diseases, the pest and disease status of the blueberry plants includes health and first-level breeding pests and diseases, the pest and disease warning value is used to quantify the maximum infection level that the blueberry plants can withstand, and the pest and disease status of the blueberry plants is used to define the current health status of the blueberry plants; S2, comparing the pest and disease of the blueberry plants The grid corresponding to the blueberry plant affected by the first-level breeding pests and diseases is marked as the pest and disease grid area, and the pest and disease status of the blueberry plants in the adjacent areas of the pest and disease grid area is found to be affected by the first-level breeding pests and diseases; S3, the graded control index obtained based on the pest and disease infection coefficient of the pest and disease grid area is compared with the graded control interval to obtain the pest and disease level of the pest and disease grid area, the pest and disease grid area is secondary partitioned according to the pest and disease level, and corresponding pest and disease management measures are taken for the blueberry plantations to be optimized after the secondary partitioning. The graded control index is used to quantify the degree to which blueberry plants in an area are susceptible to pests and diseases, and the graded control interval is used to judge the degree to which blueberry plants in an area are susceptible to pests and diseases. The pest and disease management measures include primary management and secondary management. The primary management controls the degree of pest and disease infection of blueberry plants through drug intervention, and the secondary management means sending prompt instructions to clean up severely infected blueberry plants and replant blueberry plants.

[0036] In this embodiment, the blueberry monitoring device is used to collect real-time data on pests and diseases in a blueberry plantation. It continuously monitors the growth of blueberry plants in the plantation within a preset time period, focusing on relevant data on pests and diseases. The pest and disease warning value is obtained from a preset database and is generally expressed as a limit on the maximum degree of infection that a blueberry plant can withstand. Once an area is marked as a pest and disease grid area, the system will check all other unmarked areas around the pest and disease grid area to see whether the blueberry plants in these areas are also in an infected state, so as to have a more comprehensive understanding of the spread of the infection. By calculating the graded control index and performing grade assessment, the infected areas can be reasonably zoned and managed, and targeted intervention measures can be taken to reduce the impact of pests and diseases on blueberry plants, thereby improving the accuracy of graded pest and disease management during blueberry cultivation.

[0037] Furthermore, the method of obtaining pest and disease data is as follows: environmental data is obtained by monitoring the environmental conditions of a preset number of blueberry plants in a preset representative grid area within a preset time period through an environmental sensor, the environmental sensor includes a temperature sensor, a humidity sensor and a light sensor, and the environmental data includes ambient temperature, ambient humidity and ambient light intensity. The preset representative grid area represents a range sampled and selected in the blueberry plantation to be optimized for monitoring the growth conditions of blueberry plants. The temperature sensor is used to obtain the ambient temperature by monitoring the temperature of the growth environment of the blueberry plants. The humidity sensor is used to obtain the ambient humidity by monitoring the humidity of the growth environment of the blueberry plants. The light sensor is used to obtain the ambient light intensity by monitoring the light intensity of the growth environment of the blueberry plants. The ambient temperature represents the temperature of the growth environment of the blueberry plants. The ambient humidity represents the humidity of the growth environment of the blueberry plants. The ambient light intensity represents the light intensity of the growth environment of the blueberry plants. The soil sensor is used to monitor the environmental conditions of a preset number of blueberry plants in a preset representative grid area within a preset time period. The soil data is obtained by monitoring the soil conditions of the blueberry plants. The soil sensors include soil moisture sensors, soil temperature sensors and soil pH sensors. The soil data include soil moisture, soil temperature and soil pH value. The soil moisture sensor is used to measure the water content in the soil to obtain soil moisture, the soil temperature sensor is used to detect the temperature in the soil to obtain soil temperature, and the soil pH sensor is used to measure the acidity and alkalinity of the soil to obtain soil pH value. Soil moisture indicates the moisture of the soil where the roots of the blueberry plants are located, soil temperature indicates the temperature of the soil where the roots of the blueberry plants are located, and soil pH value indicates the acidity and alkalinity of the soil where the roots of the blueberry plants are located. Multispectral images are obtained by monitoring the preset representative grid areas with a multispectral camera carried by a drone. The multispectral images are used to capture the reflection or radiation characteristics of the vegetation in the blueberry plantation to be optimized in different spectral bands. Pest and disease data include environmental data, soil data and multispectral images. Blueberry monitoring equipment includes environmental sensors, soil sensors, drones and multispectral cameras

[0038] In this embodiment, the preset representative grid area is selected based on the percentage of infected plants in the area during a historical time period. For example, if the number of blueberry plants infected with pests and diseases in a certain area of the blueberry plantation to be optimized exceeds 50% during a historical time period (the specific setting can be based on actual conditions), then this area is selected as the preset representative grid area for key monitoring and management. A multispectral camera is a camera that can capture images in different spectral bands (such as visible light and near-infrared light). A multispectral camera can analyze the reflective properties of plants in different bands, thereby helping to identify the health of the vegetation. Environmental sensors continuously monitor ambient temperature, humidity, and light intensity, helping farmers understand the environmental conditions required for blueberry growth and promptly adjust agricultural measures such as irrigation and shading. For example, in a blueberry plantation in the summer, if environmental sensors detect that the temperature has risen above 35°C and the humidity has dropped below 30%, farmers can use this data to promptly implement measures such as sprinkler irrigation to cool the plant and increase humidity to prevent damage to the blueberry plants caused by high temperature and dryness.

[0039] Specifically, soil sensors are placed in the soil at the roots of blueberries to measure soil moisture, temperature, and pH. This data helps farmers understand the growth environment of blueberry roots and ensure that soil conditions are suitable for the healthy growth of blueberries. For example, if the soil pH sensor shows that the soil pH is higher than the range suitable for blueberry growth (usually pH 4.5-5.5), farmers can apply sulfur or other acidifiers to adjust the soil acidity to ensure normal growth of blueberries.

[0040] Specifically, drones equipped with multispectral cameras are used to regularly monitor blueberry plantations and generate multispectral images. These images can reflect the health of blueberry plants, such as detecting areas that may be invaded by pests and diseases or lack nutrients. For example, multispectral images taken by drones show that blueberry plants in a certain area have weaker reflectivity in the red light band, indicating that these plants may be suffering from disease. Farmers can take timely measures based on this information, such as spraying fungicides or adjusting fertilization strategies. Through the above method, farmers can obtain environmental data, soil data and multispectral image data.

[0041] Overall, these data can be combined to form a comprehensive understanding of the blueberry growing environment, especially in terms of pest and disease management. Farmers can integrate this information and quickly take targeted agricultural measures to reduce the occurrence of blueberry pests and diseases and improve yield and quality.

[0042] Furthermore, the process of obtaining the pest and disease infection index is as follows: an environmental assessment is conducted on the blueberry plantation to be optimized based on the environmental data and the reference environmental data obtained from the preset database to obtain the environmental impact index, which is used to evaluate the compliance of the blueberry plantation's growth environment with the pest and disease environment; a soil assessment is conducted on the blueberry plantation to be optimized based on the soil data and the reference soil data obtained from the preset database to obtain the soil impact index, which is used to evaluate the compliance of the soil environment where the blueberry plant roots are located with the pest and disease environment; the red light band and the near-infrared band are extracted from the multispectral image, and the corresponding pixel points in the red light band and the near-infrared band are substituted into the normalized vegetation index formula to obtain the normalized vegetation index, which is used to evaluate the compliance of the vegetation in the blueberry plantation to be optimized with the pest and disease environment; the pest and disease infection index includes the environmental impact index, the soil impact index and the normalized vegetation index.

[0043] In this embodiment, the combined analysis of the environmental impact index, soil impact index, and normalized vegetation index can provide a comprehensive risk assessment of pest and disease infection for a blueberry plantation, facilitating the adoption of early preventive measures. The normalized vegetation index formula is as follows:

[0044] ;

[0045] It should be understood that NIR is the reflectivity of the near infrared band, and R is the reflectivity of the red light band. NDVI stands for Normalized Difference Vegetation Index. Healthy vegetation typically has high reflectance in the near-infrared band and low reflectance in the red band. A low NDVI value may indicate that the blueberry plants are infected by pests or are lacking water. By analyzing multispectral imagery of a blueberry plantation, the overall health of the vegetation can be quickly assessed.

[0046] Furthermore, the specific process of conducting an environmental assessment on the optimized blueberry plantation based on the environmental data and the reference environmental data obtained from the preset database to obtain the environmental impact index is as follows: obtaining the reference environmental data from the preset database, the reference environmental data including the reference environmental temperature, the reference environmental humidity and the reference environmental light intensity, the reference environmental temperature indicating the environmental temperature range suitable for the growth of blueberry plants, the environmental temperature range including the maximum environmental temperature and the minimum environmental temperature, the reference environmental humidity indicating the environmental humidity range suitable for the growth of blueberry plants, the environmental humidity range including the maximum environmental humidity and the minimum environmental humidity, the reference environmental light intensity indicating the environmental light intensity range suitable for the growth of blueberry plants, the environmental light intensity range including the maximum environmental light intensity and the minimum environmental light intensity; numbering the preset representative grid areas, if the environmental data meets the environmental abnormality condition, the corresponding environmental impact index is recorded as 1, otherwise the environmental impact index is obtained based on the environmental data and the reference environmental data, the environmental abnormality condition indicating that the environmental temperature does not fall within the environmental temperature range or the environmental humidity does not fall within the environmental humidity range or the environmental light intensity does not fall within the environmental light intensity range, and the environmental impact index is calculated using the following formula:

[0047] ;

[0048] Where n represents the number of the preset representative grid area, , N represents the total number of preset representative grid areas, represents the ambient temperature of the nth preset representative grid area, Indicates the minimum ambient temperature. Indicates the maximum ambient temperature. Represents the ambient humidity of the nth preset representative grid area, Indicates the minimum value of ambient humidity. Indicates the maximum ambient humidity. Represents the ambient light intensity of the nth preset representative grid area, Indicates the minimum ambient light intensity. Indicates the maximum ambient light intensity. Represents the environmental impact index of the nth preset representative grid area.

[0049] In this embodiment, the algorithm combines the environmental data and the reference environmental data for comprehensive analysis to obtain the environmental impact index, and the respective variables are independent of each other, but jointly affect the environmental impact index. In the formula, as the ambient temperature, ambient humidity and ambient pH value increase, the environmental impact index also increases, indicating that the ambient temperature, ambient humidity and ambient pH value are positively correlated with the environmental impact index; the difference between the maximum ambient temperature and the minimum ambient temperature represents the maximum ambient temperature deviation, and the difference between the ambient temperature and the minimum ambient temperature represents the ambient temperature deviation. The larger the ratio of the ambient temperature deviation to the maximum ambient temperature deviation, the more unfavorable the ambient temperature is for the growth of blueberry plants; similarly, the difference between the maximum ambient humidity and the minimum ambient humidity represents the maximum ambient humidity deviation, and the difference between the ambient humidity and the minimum ambient humidity represents the ambient humidity deviation. The larger the ratio of the ambient humidity deviation to the maximum ambient humidity deviation, the more unfavorable the ambient humidity is for the growth of blueberry plants; similarly, the difference between the maximum ambient light intensity and the minimum ambient light intensity represents the maximum ambient light deviation. Ambient light intensity deviation: The difference between the ambient light intensity and the minimum ambient light intensity represents the ambient light intensity deviation. The larger the ratio of the ambient light intensity deviation to the maximum ambient light intensity deviation, the more unfavorable the ambient light intensity is for the growth of blueberry plants. However, the increase or decrease of one independent variable cannot completely determine the changing trend of the environmental impact index. When the three independent variables all change in the same direction, the environmental impact index also increases in the same direction. In a high humidity environment, if the temperature is high, it will provide favorable conditions for the reproduction of pathogens, which may easily lead to the occurrence of diseases such as mold and bacterial spot. When under strong light, if the humidity is insufficient, blueberries are prone to water loss. Under high humidity conditions, transpiration is reduced, which may cause excessive water to remain on the leaf surface, increasing the risk of disease. In addition, light intensity and temperature jointly determine the efficiency of photosynthesis of blueberry plants. It can be seen that real-time collection of environmental data of blueberry plants is conducive to analyzing the health status of blueberry plants, and preventing pests and diseases or taking appropriate pest and disease management measures based on the monitoring situation.

[0050] Specifically, the reference ambient temperature is obtained from a preset database. In one specific embodiment, the reference ambient temperature is obtained based on research results on blueberry growing conditions from agricultural research institutions, universities, or other academic institutions. For example, research from Northeast Agricultural University concluded that the optimal growing temperature for blueberries is between 18°C and 25°C, where 18°C is the minimum ambient temperature and 25°C is the maximum ambient temperature.

[0051] Specifically, the reference ambient humidity is obtained from a preset database. In one specific embodiment, the reference ambient humidity is obtained based on research results on blueberry growing conditions from agricultural research institutions, universities, or other academic institutions. For example, research from China Agricultural University concluded that the optimal growth humidity for blueberries is between 60% and 70%, where 60% is the minimum ambient humidity and 70% is the maximum ambient humidity.

[0052] Specifically, the reference ambient light intensity is obtained from a preset database. In one specific embodiment, the reference ambient light intensity is obtained based on research results on blueberry growing conditions from agricultural research institutions, universities, or other academic institutions. For example, research from Huazhong Agricultural University concluded that the optimal growth light intensity for blueberries is between 15,000 and 25,000 lux. Therefore, 15,000 lux is the minimum ambient light intensity, and 25,000 lux is the maximum ambient light intensity.

[0053] Furthermore, the specific process of conducting soil evaluation on the optimized blueberry plantation to obtain the soil impact index based on the soil data and the reference soil data obtained from the preset database is as follows: obtaining reference soil data from the preset database, the reference soil data including reference soil temperature, reference soil moisture and reference soil pH value, the reference soil temperature indicating the soil temperature range suitable for the root growth of blueberry plants, the soil temperature range including the maximum soil temperature and the minimum soil temperature, the reference soil moisture indicating the soil moisture range suitable for the root growth of blueberry plants, the soil moisture range including the maximum soil moisture and the minimum soil moisture, the reference soil pH value indicating the soil pH range suitable for the root growth of blueberry plants, the soil pH range including the maximum soil pH and the minimum soil pH; judging whether the soil data meets the soil abnormality condition based on the reference soil data, if the soil data meets the soil abnormality condition, the corresponding soil impact index is recorded as 1, otherwise the soil impact index is obtained based on the soil data and the reference soil data, the soil abnormality condition refers to the soil temperature not belonging to the soil temperature range or the soil moisture not belonging to the soil moisture range or the soil pH value not belonging to the soil pH range, the soil impact index is calculated using the following formula:

[0054] ;

[0055] Where n represents the preset representative grid area, , N represents the total number of preset representative grid areas, represents the soil temperature of the nth preset representative grid area, Indicates the minimum soil temperature, represents the maximum soil temperature, represents the soil moisture of the nth preset representative grid area, Indicates the minimum soil moisture. represents the maximum soil moisture, represents the soil pH value of the nth preset representative grid area, Indicates the minimum soil pH value. Indicates the maximum soil pH value. Represents the soil impact index of the nth preset representative grid area.

[0056] In this embodiment, the algorithm combines soil data and reference soil data for comprehensive analysis to obtain the soil impact index, and each variable is independent of each other, but jointly affects the soil impact index. In the formula, as soil temperature, soil moisture and soil pH value increase, the soil impact index also increases, indicating that soil temperature, soil moisture and soil pH value are positively correlated with the soil impact index; the difference between the maximum soil temperature and the minimum soil temperature represents the maximum soil temperature deviation, and the difference between the soil temperature and the minimum soil temperature represents the soil temperature deviation. The larger the ratio of the soil temperature deviation to the maximum soil temperature deviation, the more unfavorable the soil temperature is for the growth of blueberry plants; similarly, the difference between the maximum soil moisture and the minimum soil moisture represents the maximum soil moisture deviation, and the difference between the soil moisture and the minimum soil moisture represents the soil moisture deviation. The larger the ratio of the soil moisture deviation to the maximum soil moisture deviation, the more unfavorable the soil moisture is for the growth of blueberry plants; similarly, the soil p The difference between the maximum H value and the minimum soil pH value represents the maximum soil pH deviation, and the difference between the soil pH value and the minimum soil pH value represents the soil pH deviation. The larger the ratio of the soil pH deviation to the maximum soil pH deviation, the more unfavorable the soil pH value is for the growth of blueberry plants. However, the increase or decrease of one independent variable cannot completely determine the changing trend of the dependent variable soil impact index. When the three independent variables change in the same direction, the dependent variable soil impact index also increases in the same direction. Soil temperature and humidity jointly affect the activity of soil microorganisms. If the soil temperature rises, it will also accelerate the chemical reactions in the soil, thereby affecting the rate of change of soil pH. At the same time, changes in soil humidity may also promote chemical reactions in the soil, thereby affecting soil pH. Therefore, monitoring soil temperature, humidity and pH is an important factor that cannot be ignored in observing the growth of blueberry plants. It is beneficial to prevent blueberry plants from being infected with diseases and pests and increase blueberry yield.

[0057] Specifically, the reference soil temperature is obtained from a preset database. In one specific embodiment, the reference soil temperature is obtained based on research results on blueberry growing conditions from agricultural research institutions, universities, or other academic institutions. For example, research from Northeast Agricultural University concluded that the optimal soil temperature range for blueberries is 15-22°C, where 15°C is the minimum soil temperature and 22°C is the maximum soil temperature.

[0058] Specifically, the reference soil moisture is obtained from a preset database. In one specific embodiment, the reference soil moisture is obtained based on research findings on blueberry growing conditions from agricultural research institutions, universities, or other academic institutions. For example, research from South China Agricultural University concluded that the optimal soil moisture range for blueberries is 20%-30%, where 20% is the minimum soil moisture value and 30% is the maximum soil moisture value.

[0059] Specifically, the reference soil pH value is obtained from a preset database. In one specific embodiment, the reference soil pH value is obtained based on research results on blueberry growing conditions from agricultural research institutions, universities, or other academic institutions. For example, research from Zhejiang University concluded that the optimal soil pH range for blueberries is 4.5-5.5, where 4.5 is the minimum soil pH value and 5.5 is the maximum soil pH value.

[0060] Furthermore, the process of obtaining the disease and pest status of blueberry plants is as follows: Step 1, obtaining disease and pest warning values from a preset database, the disease and pest warning values include environmental assessment warning values, soil assessment warning values and vegetation index warning values, the environmental assessment warning values are used to warn of environmental diseases and pests, the soil assessment warning values are used to warn of soil diseases and pests, and the vegetation index warning values are used to warn of blueberry plant vegetation diseases and pests; Step 2, comparing the disease and pest infection index with the corresponding disease and pest warning value, if the environmental impact index is greater than the environmental assessment warning value, then the disease and pest status of the blueberry plant is recorded as a first-level breeding disease and pest impact, otherwise, execute step 3; Step 3, if the soil impact index is greater than the soil assessment warning value, then the disease and pest status of the blueberry plant is recorded as a first-level breeding disease and pest impact, otherwise, execute step 4; Step 4, if the normalized vegetation index is less than the vegetation index warning value, then the disease and pest status of the blueberry plant is recorded as a first-level breeding disease and pest impact, otherwise, the disease and pest status of the blueberry plant is recorded as healthy.

[0061] In this embodiment, each influencing factor (environment, soil, vegetation) has a corresponding warning value. By gradually comparing these warning values, it is possible to determine whether the blueberry plants are infected by pests and diseases, improving the accuracy and reliability of the judgment and ensuring that only when certain key conditions exceed the acceptable range will they be marked as "level one pest and disease impact."

[0062] Specifically, the environmental assessment warning value is obtained from preset data. In one specific embodiment, the environmental assessment warning value is represented by the minimum value of the environmental impact index corresponding to blueberry plants affected by level 1 pests and diseases during a historical period. For example, if the minimum value of the environmental impact index corresponding to blueberry plants affected by level 1 pests and diseases during a historical period is 0.85, then the environmental assessment warning value is set to 0.85.

[0063] Specifically, the soil assessment warning value is obtained from preset data. In one specific embodiment, the soil assessment warning value is represented by the minimum value of the soil impact index corresponding to blueberry plants affected by level 1 pests and diseases within a historical time period. For example, if the minimum value of the soil impact index corresponding to blueberry plants affected by level 1 pests and diseases within a historical time period is 0.8, then the soil assessment warning value is set to 0.8.

[0064] Specifically, the vegetation assessment warning value is obtained from preset data. In one specific embodiment, the vegetation assessment warning value is represented by the maximum value of the normalized vegetation index corresponding to blueberry plants affected by level 1 pests and diseases during a historical time period. For example, if the maximum value of the normalized vegetation index corresponding to blueberry plants affected by level 1 pests and diseases during a historical time period is 0.2, then the vegetation assessment warning value is set to 0.2.

[0065] Furthermore, the process of obtaining the graded control index is as follows: the pest grid areas are numbered, and the assessment weights are obtained from the preset database. The assessment weights include environmental assessment weights, soil assessment weights, and vegetation assessment weights. The environmental assessment weights are used to measure the degree of influence of the environment on the pest level, the soil assessment weights are used to measure the degree of influence of the soil on the pest level, and the vegetation assessment weights are used to measure the degree of influence of the vegetation on the pest level. The graded control index is obtained according to the pest infection index corresponding to the pest grid area. The graded control index is calculated using the following formula:

[0066] ;

[0067] Where h represents the number of the pest grid area, , H represents the total number of pest and disease grid areas, represents the environmental impact index of the hth pest grid area, represents the environmental assessment weight, represents the soil impact index of the hth pest grid area, represents the soil assessment weight, represents the normalized vegetation index of the hth pest grid area, represents the vegetation assessment weight, Represents the hierarchical control index of the hth pest grid area.

[0068] In this embodiment, the algorithm combines the pest infection index and the evaluation weight for comprehensive analysis to obtain a graded control index. Each variable is independent of each other but jointly affects the graded control index. In the formula, when the evaluation weight is determined, as the environmental impact index and the soil impact index increase, the graded control index gradually decreases, while as the normalized vegetation index increases, the graded control index also increases, indicating that the graded control index is negatively correlated with the independent variables of the environmental impact index and the soil impact index, while the normalized vegetation index is positively correlated with the graded control index; when the environmental impact index and the soil impact index are larger, the more severe the impact of the environment and soil on the blueberry plants, the smaller the graded control index; and when the normalized vegetation index is larger, the more prosperous the blueberry vegetation is and the less likely it is to be infected by pests and diseases, the larger the graded control index is. It can be seen that judging the severity of blueberry plant infection from the three aspects of environment, soil and vegetation is more comprehensive. Therefore, the method provided by this embodiment is conducive to accurately grading the pest grid area, saving management costs and time, and improving the efficiency of pest and disease management of blueberry plants.

[0069] Specifically, assuming that the environmental assessment weight is 0.4, the soil assessment weight is 0.4, the vegetation assessment weight is 0.2, and the normalized vegetation index is 0.5, the change diagram of the graded control index is obtained by combining the environmental impact index and the soil impact index, as shown in the figure: Figure 2 As shown in the figure, it is a schematic diagram of the changes in the graded control index provided in the embodiment of the present application. It can be seen from the figure that as the environmental impact index and the soil impact index increase, the image shows a downward trend, indicating that the graded control index is negatively correlated with the environmental impact index and the soil impact index, and the value range of the environmental impact index and the soil impact index are both between 0 and 1. Therefore, the smaller the environmental impact index and the soil impact index, the less likely the blueberry plants are to be infected by pests and diseases, which is more conducive to the growth of the blueberry plants.

[0070] Specifically, assuming that the environmental assessment weight is 0.4, the soil assessment weight is 0.4, and the vegetation assessment weight is 0.2, the graded control index change table is obtained by combining the environmental impact index, soil impact index, and normalized vegetation index, as shown in Table 1:

[0071] surface Grading Control Index Change Table

[0072]

[0073] It can be seen from the table that when the environmental impact index increases, the corresponding hierarchical control index decreases. For example, the environmental impact index in the first row of data is 0.00, and the corresponding hierarchical control index is 1.20, which is the largest hierarchical control index in the table (the maximum value of the hierarchical control index in Table 1), while the environmental control index in the fifth row of data is 0.82, and the corresponding hierarchical control index is 0.95. It can be seen that when the environmental impact index is larger, the corresponding hierarchical control index is smaller, which fully demonstrates that the environmental impact index and the hierarchical control index are negatively correlated. Similarly, the soil impact index is also negatively correlated with the hierarchical control index. However, the normalized vegetation index and the hierarchical control index show a significant positive correlation. For example, the normalized vegetation index in the first row of data is 1.00, and the corresponding hierarchical control index is 1.20, while the normalized vegetation index in the sixth row of data is 0.26, and the corresponding hierarchical control index is 0.93 (smaller than the hierarchical control index corresponding to the first row of data).

[0074] Specifically, the environmental assessment weights are obtained from a preset database. In one specific embodiment, a mapping set of environmental impact indices and their corresponding weighting factors is constructed based on historical data of ambient temperature, ambient humidity, and ambient light intensity and a graded control index. The real-time environmental impact index is input into the mapping set to obtain the corresponding environmental assessment weights.

[0075] Specifically, the soil assessment weights are obtained from a preset database. In one specific embodiment, a mapping set of environmental impact indices and their corresponding weighting factors is constructed based on historical data of soil temperature, soil moisture, and soil pH, and a hierarchical control index. The real-time soil impact index is then input into the mapping set to obtain the corresponding soil assessment weights.

[0076] Specifically, the vegetation assessment weights are obtained from a preset database. In one specific embodiment, a mapping set of normalized vegetation indices and their corresponding weighting factors is constructed based on the normalized vegetation index and the hierarchical control index in historical data, and the real-time normalized vegetation index is input into the mapping set to obtain the corresponding vegetation assessment weights.

[0077] Furthermore, the specific process of secondary partitioning is as follows: obtaining the grade control interval from the preset database, the grade control interval includes the first grade control interval and the second grade control interval; comparing the graded control index with the grade control interval to obtain the pest and disease level, the pest and disease level includes the first grade pest and disease and the second grade pest and disease; if the graded control index belongs to the first grade control interval, the pest and disease level is the first grade pest and disease; if the graded control index belongs to the second grade control interval, the pest and disease level is the second grade pest and disease; using the depth-first search algorithm to perform secondary partitioning according to the pest and disease level, the first grade pest and disease zone is recorded as the first grade management area, and the second grade pest and disease zone is recorded as the second grade management area. The depth-first search algorithm is used to merge the pest and disease grid areas with the same pest and disease level and adjacent to each other in the initial partition into new pest and disease management zones. The pest and disease management zones are used to accurately manage the pest and disease grid areas.

[0078] In this embodiment, the first-level control interval represents the pest and disease interval where drug intervention is performed. When the graded control index falls within the first-level control interval, the pest and disease level is assessed as a first-level pest and disease; the second-level control interval represents a more serious pest and disease interval. When the graded control index falls within this interval, the pest and disease level is assessed as a second-level pest and disease; through the method provided in this embodiment, management areas can be accurately divided according to different levels of pests and diseases, and pest and disease management resources can be optimized. By merging adjacent pest and disease areas, decentralized management is reduced, and the efficiency of pest and disease prevention and control is improved.

[0079] Specifically, the graded control intervals are obtained from a preset database. In one specific embodiment, the graded control intervals are set based on historical graded control indices. The historical graded control indexes are obtained by taking the graded control indices corresponding to blueberry plants infected to the point of non-viability during a historical time period. The range corresponding to the minimum to maximum graded control indices corresponding to blueberry plants infected to the point of non-viability during the historical time period is the second graded control interval, and the range corresponding to the minimum to maximum graded control indices corresponding to blueberry plants infected to the point of survivability during the historical time period is the first graded control interval.

[0080] Specifically, the depth-first search algorithm is used in this embodiment to merge adjacent areas with the same pest and disease level. For example, suppose a field is divided into multiple grids, each with a pest and disease level, either Level 1 or Level 2. If the system finds some grids with a Level 1 pest and disease level, it will start with the first Level 1 pest and disease grid it finds and use the depth-first search algorithm to find other adjacent grids with the same pest and disease level, continuing to expand until there are no adjacent Level 1 pest and disease grids. After the depth-first search algorithm has been used, all adjacent Level 1 pest and disease grids will be merged into a larger Level 1 management area, and Level 2 pest and disease areas will be merged in the same way.

[0081] Furthermore, corresponding pest and disease management measures are taken for the blueberry plantations to be optimized after the secondary zoning, which also includes: after drip irrigation of the blueberry plants in the primary management area, the blueberry plants in the primary management area are continued to be monitored within a preset time period. If the pest and disease status of the blueberry plants in the primary management area is still affected by primary breeding pests and diseases, the primary management area is re-divided into the secondary management area for secondary management. If the pest and disease status of the blueberry plants in the primary management area is healthy, the primary management area is re-marked as healthy, and no further pest and disease management measures are required.

[0082] In this embodiment, drug drip irrigation involves applying drugs directly to the roots or leaves of plants, improving treatment efficiency and reducing drug waste. Through secondary zoning and dynamic adjustment of management areas, refined management of blueberry plantations is achieved, which helps to more effectively utilize resources and improve the targeted and efficient management of pests and diseases. Furthermore, through monitoring within a preset time period and real-time assessment of pest and disease conditions, pest and disease problems can be promptly identified and appropriate management measures can be implemented to prevent the spread and worsening of the disease. Furthermore, effective pest and disease management can protect blueberry plants from pests and diseases, thereby improving blueberry yield and quality.

[0083] The embodiment of the present application provides a grid-based blueberry planting layout optimization system, including an infection grid judgment module, an infection grid search module and a pest and disease zoning management module: wherein the infection grid judgment module is used to collect pest and disease data of the blueberry plantation to be optimized in real time through a blueberry monitoring device within a preset time period, and analyze the environmental compliance of the blueberry plants based on the pest and disease data to obtain a pest and disease infection index, and the pest and disease infection index is judged with the pest and disease warning value obtained from a preset database to obtain the pest and disease status of the blueberry plant, the blueberry monitoring device is used to observe the growth status of the blueberry plant in real time, the pest and disease data represents data reflecting the health status of the blueberry plant, the pest and disease infection index is used to reflect the degree to which the blueberry plant is susceptible to pest diseases, the pest and disease status of the blueberry plant includes health and first-level breeding pests and diseases, the pest and disease warning value is used to quantify the maximum infection level that the blueberry plant can withstand, and the pest and disease status of the blueberry plant is used to define the current health status of the blueberry plant; the infection grid search module is used to The grid corresponding to the blueberry plant with the first-level breeding pest and disease status is marked as the pest and disease grid area, and the pest and disease status of the blueberry plants in the adjacent areas of the pest and disease grid area is found to be affected by the first-level breeding pest and disease; the pest and disease zoning management module is used to compare the graded control index obtained based on the pest and disease infection coefficient of the pest and disease grid area with the graded control interval to obtain the pest and disease level of the pest and disease grid area, and perform secondary partitioning of the pest and disease grid area according to the pest and disease level, and take corresponding pest and disease management measures for the blueberry plantation to be optimized after the secondary partitioning. The graded control index is used to quantify the degree to which blueberry plants in an area are susceptible to pests and diseases, and the graded control interval is used to judge the degree to which blueberry plants in an area are susceptible to pests and diseases. The pest and disease management measures include primary management and secondary management. The primary management controls the degree of pest and disease infection of blueberry plants through drug intervention, and the secondary management means sending prompt instructions to clean up severely infected blueberry plants and replant blueberry plants.

[0084] In this embodiment, the primary management mainly controls the degree of pest and disease infection of blueberry plants through drug intervention; the secondary management generally includes sending prompt instructions to clean up severely infected blueberry plants and replant blueberry plants, which is usually a measure taken when pests and diseases have seriously affected the health and yield of blueberry plants; and the grids corresponding to the blueberry plants infected with pests and diseases are marked as pest and disease grid areas, and the environmental conditions of adjacent areas are searched for compliance, which helps to accurately locate the areas where pests and diseases occur and provide a basis for subsequent zoning management; at the same time, secondary zoning is carried out according to the pest and disease levels of the pest and disease grid areas, and corresponding pest and disease management measures are taken, realizing dynamic zoning and refined management of blueberry plantations, which helps to more effectively utilize resources and improve the pertinence and efficiency of pest and disease management; and through the drug intervention of the primary management and the cleaning and replanting of the secondary management, the prevention and control of blueberry pests and diseases are combined, which helps to reduce the damage of pests and diseases to blueberry plants and ensure the yield and quality of blueberries.

[0085] In summary, the embodiment of the present application analyzes the environmental compliance of blueberry plants through pest and disease data to obtain a pest and disease infection index, combines the pest and disease warning value to make a judgment to obtain the pest and disease status of the blueberry plants, and then marks the grids corresponding to the blueberry plants affected by the first-level breeding pests as the pest and disease grid area. Then, the graded control index obtained based on the pest and disease infection coefficient of the pest and disease grid area is used to obtain the corresponding pest and disease level. Finally, the pest and disease grid area is secondary partitioned according to the pest and disease level to take corresponding pest and disease management measures, thereby achieving accurate management of blueberry plants infected with pests and diseases, and further achieving improved accuracy of graded pest and disease management during blueberry planting, effectively solving the problem of low correlation between gridded blueberry planting layout and pest and disease control in the prior art.

[0086] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0087] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0088] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0089] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0090] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0091] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A gridded blueberry planting layout optimization method, characterized in that: The following steps are involved: S1, collecting pest and disease data of the blueberry plantation to be optimized in real time through blueberry monitoring equipment, analyzing the environmental compliance of the blueberry plants based on the pest and disease data to obtain a pest and disease infection index, and comparing the pest and disease infection index with a pest and disease warning value obtained from a preset database to obtain the pest and disease status of the blueberry plants. The pest and disease infection index is used to reflect the degree to which the blueberry plants are susceptible to pests and diseases. The pest and disease status of the blueberry plants includes health and primary pest and disease impact; S2, marking the grids corresponding to the blueberry plants with a first-level pest and disease condition as a pest and disease grid area, and finding whether the blueberry plants in the adjacent areas of the pest and disease grid area have a first-level pest and disease condition, and merging the adjacent pest and disease grid areas with the same level into a new pest and disease management zone; S3, comparing a graded control index obtained based on the pest infection index of the pest grid area with the graded control interval to obtain the pest grade of the pest grid area, performing secondary partitioning of the pest grid area according to the pest grade, and taking corresponding pest management measures for the blueberry plantations to be optimized after the secondary partitioning, wherein the graded control index is used to quantify the degree to which blueberry plants in a region are susceptible to pests and diseases, the pest management measures include primary management and secondary management, the pest data include environmental data, soil data, and multispectral images, and the pest infection index includes an environmental impact index, a soil impact index, and a normalized difference vegetation index; The specific process of obtaining the environmental impact index by conducting an environmental assessment of the blueberry plantation to be optimized based on the environmental data and the reference environmental data obtained from the preset database is as follows: Acquire reference environmental data from a preset database, wherein the reference environmental data includes reference environmental temperature, reference environmental humidity, and reference environmental light intensity; The preset representative grid areas are numbered. If the environmental data meets the environmental anomaly conditions, the corresponding environmental impact index is recorded as 1. Otherwise, the environmental impact index is obtained based on the environmental data and the reference environmental data. The environmental impact index is calculated using the following formula: ； Where n represents the number of the preset representative grid area, , N represents the total number of preset representative grid areas, represents the ambient temperature of the nth preset representative grid area, Indicates the minimum ambient temperature. Indicates the maximum ambient temperature. Represents the ambient humidity of the nth preset representative grid area, Indicates the minimum value of ambient humidity. Indicates the maximum ambient humidity. Represents the ambient light intensity of the nth preset representative grid area, Indicates the minimum ambient light intensity. Indicates the maximum ambient light intensity. Represents the environmental impact index of the nth preset representative grid area; The specific process of evaluating the soil for the blueberry plantation to be optimized and obtaining the soil impact index based on the soil data and the reference soil data obtained from the preset database is as follows: Acquire reference soil data from a preset database, wherein the reference soil data includes reference soil temperature, reference soil moisture, and reference soil pH value; Based on the reference soil data, it is determined whether the soil data meets the soil anomaly condition. If the soil data meets the soil anomaly condition, the corresponding soil impact index is recorded as 1. Otherwise, the soil impact index is obtained based on the soil data and the reference soil data. The soil impact index is calculated using the following formula: ； Where n represents the preset representative grid area, , N represents the total number of preset representative grid areas, represents the soil temperature of the nth preset representative grid area, Indicates the minimum soil temperature, represents the maximum soil temperature, represents the soil moisture of the nth preset representative grid area, Indicates the minimum soil moisture. represents the maximum soil moisture, represents the soil pH value of the nth preset representative grid area, Indicates the minimum soil pH value. Indicates the maximum soil pH value. Represents the soil impact index of the nth preset representative grid area; The process of obtaining the hierarchical control index is as follows: Numbering the pest and disease grid areas and obtaining assessment weights from a preset database, wherein the assessment weights include environmental assessment weights, soil assessment weights, and vegetation assessment weights; The graded control index is obtained according to the pest infection index corresponding to the pest grid area; The hierarchical control index is calculated using the following formula: ； Where h represents the number of the pest grid area, , H represents the total number of pest and disease grid areas, represents the environmental impact index of the hth pest grid area, represents the environmental assessment weight, represents the soil impact index of the hth pest grid area, represents the soil assessment weight, represents the normalized vegetation index of the hth pest grid area, represents the vegetation assessment weight, Represents the hierarchical control index of the hth pest grid area.

2. A gridded blueberry planting layout optimization method as claimed in claim 1, characterized in that: The method for obtaining the pest and disease data is as follows: Environmental data is obtained by monitoring the environmental conditions of a preset number of blueberry plants within a preset representative grid area within a preset time period using environmental sensors, wherein the environmental sensors include a temperature sensor, a humidity sensor, and a light sensor, and the environmental data includes ambient temperature, ambient humidity, and ambient light intensity. The preset representative grid area represents a range sampled and selected in the blueberry plantation to be optimized for monitoring the growth conditions of the blueberry plants; soil data is obtained by monitoring the soil conditions of a preset number of blueberry plants in a preset representative grid area within a preset time period using a soil sensor, wherein the soil sensor includes a soil moisture sensor, a soil temperature sensor, and a soil pH sensor, and the soil data includes soil moisture, soil temperature, and soil pH value; The multispectral image is obtained by monitoring the preset representative grid area with a multispectral camera carried by the UAV; The pest and disease data include environmental data, soil data and multispectral images; The blueberry monitoring equipment includes environmental sensors, soil sensors, drones and multispectral cameras.

3. A gridded blueberry planting layout optimization method as claimed in claim 2, characterized in that: The process of obtaining the pest infection index is as follows: An environmental impact index is obtained by performing an environmental assessment on the blueberry plantation to be optimized based on the environmental data and reference environmental data obtained from a preset database. The environmental impact index is used to assess the pest and disease environment compliance of the blueberry plant growth environment; A soil impact index is obtained by performing a soil assessment on the blueberry plantation to be optimized based on the soil data and reference soil data obtained from a preset database. The soil impact index is used to assess the compatibility of the soil environment where the blueberry plant roots are located with respect to pests and diseases; Extracting red light band and near infrared band from multispectral image, and substituting corresponding pixel points in red light band and near infrared band into normalized vegetation index formula to obtain normalized vegetation index; The pest infection index includes an environmental impact index, a soil impact index and a normalized vegetation index.

4. A gridded blueberry planting layout optimization method as claimed in claim 1, characterized in that: The process of obtaining the disease and insect pest status of the blueberry plant is as follows: Step 1: Obtain pest and disease warning values from a preset database, wherein the pest and disease warning values include an environmental assessment warning value, a soil assessment warning value, and a vegetation index warning value; Step 2: Compare the pest infection index with the corresponding pest warning value. If the environmental impact index is greater than the environmental assessment warning value, the blueberry plant pest and disease condition is recorded as a first-level breeding pest and disease impact. Otherwise, proceed to step 3. Step 3: If the soil impact index is greater than the soil assessment warning value, the blueberry plant pest and disease condition is recorded as a level one pest and disease impact. Otherwise, proceed to step 4. Step 4: If the normalized vegetation index is less than the vegetation index warning value, the blueberry plant pest and disease condition is recorded as level one breeding pest and disease impact; otherwise, the blueberry plant pest and disease condition is recorded as healthy.

5. A gridded blueberry planting layout optimization method as claimed in claim 1, characterized in that: The specific process of the secondary partitioning is as follows: Obtaining a level control interval from a preset database, wherein the level control interval includes a first level control interval and a second level control interval; Comparing the graded control index with the graded control interval to obtain the pest and disease grade, wherein the pest and disease grade includes primary pests and diseases and secondary pests and diseases; The depth-first search algorithm was used to perform secondary partitioning according to the level of pests and diseases. The partitions with the first-level pests and diseases were recorded as the first-level management areas, and the partitions with the second-level pests and diseases were recorded as the second-level management areas.

6. A gridded blueberry planting layout optimization method as claimed in claim 5, characterized in that: The said taking corresponding pest and disease management measures for the blueberry plantation to be optimized after the secondary zoning, further includes: Continue to monitor the blueberry plants in the first-level management area within the preset time period. If the disease and pest status of the blueberry plants in the first-level management area is still affected by first-level breeding pests and diseases, the first-level management area will be re-divided into the second-level management area for second-level management. If the disease and pest status of the blueberry plants in the first-level management area is healthy, the first-level management area will be re-marked as healthy and no further disease and pest management measures will be required.

7. A gridded blueberry planting layout optimization system, applied to the gridded blueberry planting layout optimization method according to any one of claims 1 to 6, characterized in that: It includes infection grid judgment module, infection grid search module and pest and disease zoning management module: The infection judgment grid module is used to collect pest and disease data of the blueberry plantation to be optimized in real time through the blueberry monitoring equipment within a preset time period, and analyze the environmental compliance of the blueberry plants based on the pest and disease data to obtain a pest and disease infection index, and compare the pest and disease infection index with the pest and disease warning value obtained from the preset database to obtain the pest and disease status of the blueberry plants. The pest and disease infection index is used to reflect the degree to which the blueberry plants are susceptible to pests and diseases. The pest and disease status of the blueberry plants includes health and primary pest and disease impact; The infection grid search module is used to mark the grid corresponding to the blueberry plant with the first-level breeding pest and disease status as the pest and disease grid area, and to find whether the blueberry plant pest and disease status in the adjacent area of the pest and disease grid area is affected by the first-level breeding pest and disease; The pest and disease zoning management module is used to compare a graded control index obtained based on the pest and disease infection index of the pest and disease grid area with the grade control interval to obtain the pest and disease grade of the pest and disease grid area, perform secondary zoning of the pest and disease grid area according to the pest and disease grade, and adopt corresponding pest and disease management measures for the blueberry plantations to be optimized after the secondary zoning. The graded control index is used to quantify the degree to which blueberry plants in a region are susceptible to pests and diseases. The pest and disease management measures include primary management and secondary management.

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