Rice leaffish ecological breeding management method and system

Abstract

This invention discloses a rice-duckweed-fish ecological farming management method and system, specifically relating to the field of agricultural ecological management technology. It involves collecting data on rice growth stages, duckweed cover images, dissolved oxygen in water, fish load, and meteorological data to construct an ecological farming management data table. The duckweed cover images are then gridded to form a coverage-dissolved oxygen coupling sequence. A threshold discrimination method is used to determine the duckweed cover status. Based on the moving difference method, the dissolved oxygen decline trend is analyzed to generate a critical transition level for duckweed. A task priority table is then called to determine the execution order and amount of field collaborative control operations. Finally, a regression prediction model is used to optimize and update the task priority table, thereby achieving efficient collaborative management among rice, duckweed, and fish, and improving the overall benefits and stability of the ecosystem.

Description

Technical Field

[0001] This invention relates to the field of agricultural ecological management technology, and more specifically, to a rice-fish ecological farming management method and system. Background Technology

[0002] Rice-duckweed-fish ecological farming is an agricultural ecological model that utilizes the ecological relationship between rice, duckweed, and fish to achieve nutrient recycling and multiple benefits in the paddy field environment. In existing rice-duckweed-fish ecological farming management practices, farmers generally rely on their own experience to manage the paddy field ecology. This typically manifests as independent operations lacking effective coordination, and management decisions being largely based on human experience. There is a lack of a unified identification method and comprehensive control measures for the interactions between ecological elements among rice plants, duckweed, and fish. Consequently, management decisions often interfere with each other in actual production, making it difficult to achieve continuous, stable, and synergistic benefits among the three.

[0003] The existing rice-fish ecological farming management method makes it difficult to uniformly identify and judge the interaction between the red duckweed coverage status and the dissolved oxygen conditions in the water during the rice plant growth stage. This results in a lack of effective coordination among ecological management measures, leading to instability in the overall benefits of the rice-fish ecosystem. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a rice-fish ecological farming management method and system to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for the ecological farming and management of rice-fish, comprising the following steps:

[0007] S1. Obtain rice plant growth period, red duckweed cover image, dissolved oxygen in water, fish load and meteorological data for the same rice-duckweed-fish field, and generate an ecological farming management data table according to the collection time.

[0008] S2. Perform grid-based recognition on the duckweed-covered image to obtain the duckweed coverage rate and edge aggregation degree, and form a coverage dissolved oxygen coupling sequence with the dissolved oxygen in the water body at the same collection time.

[0009] S3. Based on the coupled sequence of rice plant growth period and dissolved oxygen under cover, the threshold discrimination method is used to mark the ecological gain state, critical transition state and ecological stress state corresponding to the red duckweed cover state;

[0010] S4. When the coverage state of Duckweed is in a critical transition state and an ecological stress state, the sliding difference method is used in combination with fish load and meteorological data to calculate the dissolved oxygen decline trend and generate the critical transition level of Duckweed.

[0011] S5. Based on the critical conversion level of the red duckweed, call the operation priority table to determine the execution order and amount of field coordinated regulation operations;

[0012] S6. Write the execution order and execution volume of field coordinated regulation operations into the ecological farming management data table, and update the operation priority table according to the dissolved oxygen in the water and the coverage rate of red duckweed at the next collection time.

[0013] S7. Based on the ecological farming management data table, establish a regression prediction model. When the same critical conversion level of duckweed occurs again, use the regression prediction model to determine the range of execution values ​​that will keep the dissolved oxygen in the water body within the ecological gain range, and update the operation priority table.

[0014] In a preferred embodiment, S1 specifically refers to:

[0015] Using the same rice-duckweed-fish field as the data collection object, the rice plant growth period in the field management record was obtained according to the collection time, images of red duckweed coverage were obtained by fixed-point shooting, dissolved oxygen in the water was obtained by dissolved oxygen detection, fish load was obtained by stocking records and sampling weighing records, and meteorological data was obtained by meteorological records.

[0016] The rice plant growth period, images of duckweed cover, dissolved oxygen in the water, fish load, and meteorological data were entered into the ecological farming management data table according to the collection time.

[0017] In a preferred embodiment, S2 specifically refers to:

[0018] Images of duckweed cover and dissolved oxygen in water collected at the same time were retrieved from the ecological farming management data table. The field boundaries in the duckweed cover images were used as the identification range. The identification range was divided into equal-area grids, and the duckweed grids and non-duckweed grids were marked according to the color characteristics of duckweed.

[0019] The coverage rate of Hongping grid is obtained by statistically analyzing the proportion of Hongping grids among all grids.

[0020] The edge clustering degree is obtained by calculating the proportion of the number of adjacencies between red-ping grids to the total number of adjacencies in the red-ping grid.

[0021] The coverage rate of duckweed, the edge aggregation degree, and the dissolved oxygen in the water were used to form a coverage-dissolved oxygen coupling sequence according to the collection time.

[0022] In a preferred embodiment, S3 specifically refers to:

[0023] The growth period of rice plants was read from the ecological farming management data table, and the coverage rate, edge aggregation degree and dissolved oxygen of duckweed at the same collection time were read from the coverage dissolved oxygen coupling sequence.

[0024] According to the rice plant growth period, the red duckweed coverage threshold, the edge aggregation threshold, and the dissolved oxygen threshold of the water body are matched;

[0025] The coverage rate, edge aggregation degree, and dissolved oxygen in the water were compared with the corresponding thresholds, and the coverage status of duckweed was marked as ecological gain state, critical transition state, or ecological stress state.

[0026] In a preferred embodiment, S4 specifically refers to:

[0027] When the coverage status of duckweed is marked as a critical transitional state or an ecological stress state, fish load and meteorological data at the same collection time are read from the ecological farming management data table, and dissolved oxygen in water bodies at adjacent collection times is extracted from the coverage dissolved oxygen coupling sequence according to the collection time order.

[0028] The sliding difference method was used to calculate the difference in dissolved oxygen in water between adjacent sampling times, and the decreasing trend of dissolved oxygen was determined by combining fish load and meteorological data.

[0029] The critical conversion level of red duckweed is generated according to the decreasing trend of dissolved oxygen.

[0030] In a preferred embodiment, S5 specifically refers to:

[0031] Based on the critical conversion level of duckweed, the corresponding field coordinated regulation operation combination is retrieved from the operation priority table; the field coordinated regulation operation combination includes the operation content corresponding to the critical conversion level of duckweed among duckweed harvesting, watering, feeding, fertilization and oxygenation;

[0032] The execution order of field coordinated regulation operations is determined according to the operation arrangement relationship recorded in the operation priority table, and the execution amount of field coordinated regulation operations is determined in combination with the coverage rate of duckweed, fish load and dissolved oxygen in the water.

[0033] In a preferred embodiment, S6 specifically refers to:

[0034] The execution sequence and amount of field coordinated regulation operations are entered into the ecological farming management data table according to the collection time;

[0035] At the next acquisition time, dissolved oxygen and duckweed coverage in the water body were read from the coverage-dissolved oxygen coupling sequence.

[0036] The dissolved oxygen in the water at the next sampling time was compared with that at the previous sampling time, and the coverage rate of duckweed at the next sampling time was compared with that at the previous sampling time.

[0037] Based on the comparison results, adjust the job arrangement and execution range for jobs with the same critical conversion level in the job priority table.

[0038] In a preferred embodiment, S7 specifically refers to:

[0039] Extract the cumulative dissolved oxygen in the water, duckweed coverage, fish load, meteorological data, and the execution volume of field collaborative regulation operations from the ecological farming management data table for at least two collection periods;

[0040] Using the amount of field coordinated regulation operations as the independent variable and dissolved oxygen in water as the dependent variable, a regression prediction model was obtained by fitting.

[0041] When the same critical transition level of duckweed appears again, multiple candidate field coordinated regulation operation execution volumes are input into the regression prediction model to obtain the expected dissolved oxygen in the water body corresponding to each candidate execution volume.

[0042] The execution quantities are selected from the candidate execution quantities to determine the range of execution quantities where the dissolved oxygen in the water body is expected to be within the range of ecological gain.

[0043] Replace the execution value range corresponding to the same critical conversion level in the job priority table with the execution value range.

[0044] On the other hand, the present invention provides a rice-fish ecological farming management system, comprising:

[0045] Data collection and table creation module: Acquires rice plant growth period, red duckweed cover image, dissolved oxygen in water, fish load and meteorological data for the same rice-duckweed-fish field, and generates an ecological farming management data table according to the collection time;

[0046] Coverage recognition module: performs grid-based recognition on the duckweed coverage image to obtain the duckweed coverage rate and edge aggregation degree, and forms a coverage dissolved oxygen coupling sequence with the dissolved oxygen in the water body at the same acquisition time;

[0047] State discrimination module: Based on the coupled sequence of rice plant growth period and dissolved oxygen under cover, the threshold discrimination method is used to mark the ecological gain state, critical transition state and ecological stress state corresponding to the red duckweed cover state;

[0048] Trend grading module: When the coverage state of duckweed is in the critical transition state and the ecological stress state, the sliding difference method is used in combination with fish load and meteorological data to calculate the dissolved oxygen decline trend and generate the critical transition level of duckweed;

[0049] Operation control module: Based on the critical conversion level of duckweed, the operation priority table is called to determine the execution order and amount of field coordinated control operations;

[0050] Feedback Update Module: Writes the execution order and execution volume of field collaborative regulation operations into the ecological farming management data table, and updates the operation priority table based on the dissolved oxygen in the water and the coverage rate of red duckweed at the next collection time;

[0051] Interval Update Module: Based on the ecological farming management data table, a regression prediction model is established. When the same critical conversion level of duckweed occurs again, the regression prediction model is used to determine the range of execution quantity values ​​that will keep the expected dissolved oxygen in the water body within the ecological gain state range, and the operation priority table is updated.

[0052] The technical effects and advantages of the rice-fish ecological farming management method and system of the present invention are as follows:

[0053] By acquiring data on rice plant growth period, duckweed cover images, dissolved oxygen in the water, fish load, and meteorological data for the same rice-duckweed-fish paddy field, and generating an ecological farming management data table according to the collection time, a unified management foundation for rice, duckweed, fish, and environmental data is established. Duckweed coverage rate and edge aggregation degree are obtained through grid-based identification, and a coverage-dissolved oxygen coupling sequence is formed, establishing a correspondence between duckweed distribution and dissolved oxygen changes in the water. Ecological gain state, critical transition state, and ecological stress state are marked using a threshold discrimination method, providing a tiered identification basis for duckweed coverage status. Finally, the sliding difference method, combined with fish... Load and meteorological data are used to calculate the dissolved oxygen decline trend and generate critical transition levels for duckweed, so that changes in duckweed coverage can be matched with dissolved oxygen risk. The execution order and amount of field coordinated regulation operations are determined by an operation priority table, and the operation priority table is updated according to the data of the next collection time to improve the continuity of field operation scheduling. The execution amount range is determined by a regression prediction model, so that when the same critical transition level of duckweed occurs again, the execution amount can be corrected based on historical data, thereby reducing management target conflicts and improving the stability and coordination of rice-duckweed-fish ecological farming management. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of an ecological farming and management method for rice-fish in accordance with the present invention;

[0055] Figure 2 This is a schematic diagram of the structure of a rice-fish ecological farming management system according to the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0057] Example 1

[0058] Figure 1 This invention provides a method for the ecological farming and management of rice-fish, which includes the following steps:

[0059] S1. Obtain rice plant growth period, red duckweed cover image, dissolved oxygen in water, fish load and meteorological data for the same rice-duckweed-fish field, and generate an ecological farming management data table according to the collection time.

[0060] S2. Perform grid-based recognition on the duckweed-covered image to obtain the duckweed coverage rate and edge aggregation degree, and form a coverage dissolved oxygen coupling sequence with the dissolved oxygen in the water body at the same collection time.

[0061] S3. Based on the coupled sequence of rice plant growth period and dissolved oxygen under cover, the threshold discrimination method is used to mark the ecological gain state, critical transition state and ecological stress state corresponding to the red duckweed cover state;

[0062] S4. When the coverage state of Duckweed is in a critical transition state and an ecological stress state, the sliding difference method is used in combination with fish load and meteorological data to calculate the dissolved oxygen decline trend and generate the critical transition level of Duckweed.

[0063] S5. Based on the critical conversion level of the red duckweed, call the operation priority table to determine the execution order and amount of field coordinated regulation operations;

[0064] S6. Write the execution order and execution volume of field coordinated regulation operations into the ecological planting and breeding management data table, and update the operation priority table according to the dissolved oxygen in the water and the coverage rate of red duckweed at the next collection time.

[0065] S7. Based on the ecological farming management data table, establish a regression prediction model. When the same critical conversion level of duckweed occurs again, use the regression prediction model to determine the range of execution values ​​that will keep the dissolved oxygen in the water body within the ecological gain range, and update the operation priority table.

[0066] S1. Obtain rice plant growth period, red duckweed cover image, dissolved oxygen in water, fish load, and meteorological data for the same rice-duckweed-fish field, and generate an ecological farming management data table according to the collection time, including:

[0067] In this embodiment, the implementation process of step S1 is as follows: The same rice-duckweed-fish field is taken as the data collection object. The rice-duckweed-fish field refers to a paddy field unit in which rice planting, duckweed cultivation and fish farming are carried out simultaneously within the boundary of the same plot. The boundary of the rice-duckweed-fish field is determined according to the physical boundary of the field ridge. There is no water body disconnected area inside the rice-duckweed-fish field.

[0068] Data collection time refers to the specific time points at which data is collected from rice-duckweed-fish fields. The timing of data collection must consider the rice plant's growth cycle, the duckweed's growth period, and the fish's physiological rhythms. During the rice tillering and jointing stages, duckweed grows rapidly and significantly impacts dissolved oxygen in the water. Therefore, the collection interval should be set to once or twice daily, for example, once at 07:00 and once at 15:00 daily, to cover the dissolved oxygen changes before and after the peak of photosynthesis. During the rice flowering and grain-filling stages, the impact mechanism of duckweed cover on rice pollination and grain filling differs from that during the tillering stage. The collection interval can be adjusted to once daily, for example, at 08:00 daily. The recording format for data collection time should uniformly adopt the standard format of "year-month-day-hour-minute".

[0069] The rice plant growth period refers to the developmental stage of a rice plant throughout its entire growth cycle, including but not limited to the seedling stage, tillering stage, jointing stage, booting stage, flowering stage, grain-filling stage, and maturity stage. The data source for the rice plant growth period is field management records, which are filled out simultaneously by field managers during agricultural operations. These records include the date of the operation, the type of operation, and the field observation results. The field observation results record the criteria for determining the rice plant growth period, including but not limited to the main stem leaf age, the trend of tiller number changes, the degree of panicle differentiation, and the heading percentage. In each data collection operation corresponding to the current collection time, the rice plant growth period marked in the most recent record for the current date is read from the field management records and written into the rice plant growth period field of the ecological farming management data table. The value of the rice plant growth period field is a discrete growth stage name, such as tillering stage or booting stage; numerical codes are not used to replace the growth stage names.

[0070] A duckweed-covered image refers to a top-down or near-top-down image acquired through fixed-point shooting that completely covers the water surface area of ​​a rice-duckweed-fish paddy field. The shooting equipment is fixedly mounted on a bracket at the corner of the paddy field, with the bracket height set to ensure the shooting equipment's field of view completely covers the entire water surface area while maintaining clear visibility of the paddy field boundaries in the image. The camera lens is oriented vertically downwards or at an angle not exceeding 15 degrees to the vertical to minimize perspective distortion and reduce the impact on gridded recognition accuracy. The image resolution is set so that the smallest resolvable spatial unit area in each image does not exceed 0.01 square meters to ensure the accuracy of determining the duckweed coverage status within a single grid during gridded recognition. The shooting time is consistent with the data acquisition time; the shooting equipment automatically triggers shooting at the designated acquisition time, acquiring one duckweed-covered image per acquisition time. The images of duckweed cover are saved as digital image files. The file naming rule adopts the format of field number-collection time. The image file path is written into the duckweed cover image field of the ecological farming management data table to realize the association between the image file and the collection time of other data fields.

[0071] Dissolved oxygen in water refers to the mass concentration of dissolved oxygen in the water of rice-fish farming plots, measured in milligrams per liter (mg / L). Dissolved oxygen is obtained through dissolved oxygen detection. The sensor used for detection is fixedly installed in the central water area of ​​the rice-fish farming plot, with the sensor probe installed 10 to 15 centimeters below the water surface to detect the dissolved oxygen status of a representative water layer. The sensor operates continuously online, with a data sampling frequency set to once per minute. At each sampling time, 11 sampling data points are extracted from the continuous sampling data of the sensor, taking 5 minutes before and after the sampling time as the sampling time. The arithmetic mean of these 11 sampling data points is calculated as the dissolved oxygen value corresponding to that sampling time. The dissolved oxygen value is rounded to two decimal places and is expressed in milligrams per liter. The dissolved oxygen value is then entered into the dissolved oxygen field of the ecological farming management data table.

[0072] Fish load refers to the total mass of cultured fish per unit water surface area in a rice-fishpond, measured in grams per square meter. The calculation of fish load is based on stocking records and sampling weighing records. Stocking records document the species, quantity, and initial average weight of fish stocked in each batch, and are completed immediately after each stocking operation. Sampling weighing records document the measured weight of each sample fish during periodic sampling inspections. Sampling inspections are conducted every 7 to 14 days, with each sample containing no less than 3% of the total number of cultured fish in the rice-fishpond and no less than 10 fish. The sampled fish are randomly caught from the rice-fishpond, and after weighing, they are released back into the rice-fishpond. In each data collection operation corresponding to the collection time, the total number of fish released for the current date is obtained from the stocking record. The arithmetic mean of the sample fish weights is obtained from the most recent sampling and weighing record to be used as the current average weight. The fish load is obtained by dividing the product of the total number of fish released and the current average weight by the water surface area of ​​the rice-fish paddy field. The fish load value is retained to one decimal place and written into the fish load field of the ecological farming management data table.

[0073] Meteorological data refers to the set of meteorological observations within the same time period as the rice-fish farming plots. The data includes temperature, relative humidity, wind speed, light intensity, and rainfall. These parameters are obtained from meteorological stations or field microclimate observation equipment located no more than 2 kilometers from the rice-fish farming plots. The time correspondence of each parameter is based on the most recent hourly observation. Temperature is measured in degrees Celsius, relative humidity in percentage, wind speed in meters per second, light intensity in lux, and rainfall in millimeters per hour. These five meteorological parameters are respectively entered into the temperature, relative humidity, wind speed, light intensity, and rainfall fields of the ecological farming management data table.

[0074] Each record in the ecological farming and aquaculture management data table corresponds to a collection time. Each record includes fields for plot number, collection time, rice plant growth stage, duckweed cover image, dissolved oxygen in water, fish load, temperature, relative humidity, wind speed, light intensity, and rainfall. After the data collection operation corresponding to each collection time is completed, the rice plant growth stage, duckweed cover image file path, dissolved oxygen in water, fish load, temperature, relative humidity, wind speed, light intensity, and rainfall are sequentially written into the corresponding fields of the ecological farming and aquaculture management data table according to the acquisition method of each field. The collection time is used as a unique index key to ensure that all types of data from the same collection time are in the same record in the ecological farming and aquaculture management data table.

[0075] S2. Grid-based identification is performed on the duckweed cover image to obtain the duckweed coverage rate and edge aggregation degree, and a coverage-dissolved oxygen coupling sequence is formed with the dissolved oxygen in the water body collected at the same time, including:

[0076] In this embodiment, step S2 is implemented as follows: using the collection time field as the search key, the data row corresponding to the current processing target is located in the ecological aquaculture management data table. The file storage path of the duckweed-covered image is read from the duckweed-covered image field, and the digital image file of the duckweed-covered image is loaded according to the file storage path. The dissolved oxygen value of the water body corresponding to the collection time is read from the dissolved oxygen field. The unit of the dissolved oxygen value of the water body is milligrams per liter, and two decimal places are retained. The reading operation is performed sequentially for all valid collection times in the ecological aquaculture management data table. Each time, the duckweed-covered image and dissolved oxygen of the water body corresponding to one collection time are processed. The processing order is arranged according to the time order of the collection time field.

[0077] Images of duckweed-covered paddy fields were acquired using a camera fixed at the corners of the paddy field plots. The camera lens was oriented vertically downwards or at an angle not exceeding 15 degrees to the vertical. The image region corresponding to the field boundary in the duckweed-covered image is the projected boundary of the field ridge outline on the image plane. The process for extracting the field boundary is as follows: the duckweed-covered image is converted to grayscale to obtain a grayscale image; edge detection processing is applied to the grayscale image to identify the closed contour line corresponding to the field boundary on the continuous pixel band with the most significant grayscale gradient change; the image region enclosed by the closed contour line is used as the recognition range. The image region within the recognition range corresponds to the entire water surface area of ​​the paddy field plot, while the image region outside the recognition range corresponds to the field ridge and the area outside the field plot, and is not involved in grid division and recognition. To ensure the consistency of field boundary extraction results across different acquisition times, the first image of duckweed cover is manually verified at the beginning of the acquisition cycle. After confirming that the automatically extracted field boundaries match the physical boundaries of the field ridges, the pixel coordinate sequence of the field boundaries is saved as field boundary parameters. These parameters are reused throughout the entire acquisition process, and are only re-extracted when the physical boundaries of the rice-duckweed-fish field change.

[0078] The area of ​​a single grid cell in the equal-area grid is determined based on the spatial resolution of the red duckweed-covered image. The spatial resolution is determined by the image resolution parameters of the shooting device. Step S1 stipulates that the area of ​​the smallest resolvable spatial unit in each red duckweed-covered image does not exceed 0.01 square meters. Therefore, the side length of a single grid cell is set so that the number of the smallest resolvable spatial units contained in the grid cell is not less than 4. For example, when the image spatial resolution is 0.002 square meters per pixel, the side length of a single grid cell is set to the number of pixels corresponding to an actual area of ​​0.1 square meters. The grid division process is as follows: Within the image region corresponding to the recognition range, starting from the top-left pixel coordinates of the recognition range, grid rows and columns are divided along the horizontal and vertical directions with a step size equal to the side length of a single grid cell, respectively, generating a regular grid array covering the entire recognition range. For incomplete grids located at the edge of the recognition range and whose image region is less than the complete area of ​​a single grid cell, if the effective image region area of ​​the incomplete grid cell is not less than 50% of the standard area of ​​a single grid cell, the incomplete grid cell is included in the statistics of all grid cells; if the effective image region area of ​​the incomplete grid cell is less than 50% of the standard area of ​​a single grid cell, the incomplete grid cell is excluded from the statistics of all grid cells. After grid division is completed, the total number of grid cells is recorded as the total number of grid cells. , The value can be a positive integer.

[0079] The color characteristics of duckweed are manifested in a specific range of hues in visible light images. Under normal growth conditions, duckweed is green to yellowish-green, dark green under sufficient nitrogen conditions, and reddish-brown under strong light or low temperature stress conditions. The above hue ranges are distinguishable in the hue-saturation-brightness color space of visible light images. The color feature marking process is as follows: The image covered by duckweed is converted from the red-green-blue color space to the hue-saturation-brightness color space. For the distribution range of duckweed in the hue-saturation-brightness color space, based on reference pixel samples collected at the beginning of the collection period from areas covered by and without duckweed in the rice-duckweed-fish paddy field, the numerical distribution intervals of the reference pixel samples in the duckweed-covered areas in the three channels of hue, saturation, and brightness are calculated. The lower limit of the numerical distribution interval for each channel is set as the mean of the reference pixel sample in the corresponding channel minus twice the standard deviation, and the upper limit of the numerical distribution interval for each channel is set as the mean of the reference pixel sample in the corresponding channel plus twice the standard deviation. This determines the duckweed color feature judgment threshold. For all pixels within each grid, the proportion of pixels whose hue, saturation, and brightness values ​​simultaneously fall within the duckweed color feature judgment threshold range is counted. When the proportion is not less than 60%, the grid is marked as a duckweed grid; when the proportion is less than 60%, the grid is marked as a non-duckweed grid. After all grids have been marked, the number of Hongping grids is recorded as the Hongping grid number. The number of non-red grid lines is recorded as the non-red grid line count. , and The sum equals the total number of grid cells. .

[0080] Red duckweed coverage rate refers to the number of red duckweed grids. Total number of grid cells The ratio is used to characterize the ratio between the actual area of ​​duckweed coverage in the water surface area of ​​a rice-duckweed-fish paddy field and the total water surface area of ​​the field. The duckweed coverage rate is calculated using the following formula:

[0081] ;in, The red duckweed coverage rate is rounded to 4 decimal places. The dimension is a dimensionless ratio, and the value ranges from 0 to 1. A value of 0 indicates that there are no red duckweed grids within the recognition range, and a value of 1 indicates that all grids within the recognition range are red duckweed grids. The number of red grid lines, expressed in units, is a non-negative integer. The total number of grid cells is expressed in units of a positive integer.

[0082] Edge clustering refers to the proportion of adjacent contacts between red duckweed grids out of the total number of adjacent contacts involving red duckweed. It characterizes the degree of aggregation of red duckweed in the spatial distribution of rice-duckweed-fish paddy fields. A higher edge clustering indicates that red duckweed tends to be concentrated in contiguous areas, while a lower edge clustering indicates that red duckweed tends to be dispersed. Adjacency relationships are defined using the 4-adjacency rule, meaning that each grid has an adjacency relationship with its horizontally adjacent left, right, and vertically adjacent upper and lower grids. Grids located at the edge of the identification range are not counted as having adjacency relationships with areas outside the identification range. The number of adjacencies between red duckweed grids is defined as follows: traverse all red duckweed grids, count the number of adjacent grids belonging to red duckweed grids for each red duckweed grid under the 4-adjacency rule, sum the statistical values ​​of all red duckweed grids, divide by 2 to eliminate duplicate counts, and obtain the number of adjacencies between red duckweed grids, which is recorded as the adjacency number. The unit is "number", and the value is a non-negative integer. The total number of adjacencies of a red-ping grid is defined as follows: Traverse all red-ping grids, count the number of adjacent grids within the recognition range for each red-ping grid under the 4-adjacency rule, sum the statistical values ​​of all red-ping grids, divide by 2 to eliminate duplicate counts with non-red-ping grids, and add the adjacency count between red-ping grids and non-red-ping grids. That is, the total number of adjacencies of a red-ping grid equals the number of adjacencies between red-ping grids. Number of adjacencies between red grit grids and non-red grit grids The sum is denoted as the total number of adjacent nodes. The unit is "number", and the value is a positive integer. The marginal clustering degree is calculated using the following formula:

[0083] ;in, The value represents the edge clustering degree, which is rounded to four decimal places and is a dimensionless ratio. The value ranges from 0 to 1. A value close to 1 indicates that the internal adjacency between red duckweed grids is dominant, i.e., red duckweed is highly clustered. A value close to 0 indicates that the adjacency between red duckweed grids and non-red duckweed grids is dominant, i.e., red duckweed is highly dispersed. This represents the number of adjacencies between red-ping grids, expressed as a non-negative integer. This represents the number of adjacencies between red Ping grids and non-red Ping grids, expressed as a non-negative integer. and The sum is the total number of adjacent nodes. When the total number of adjacencies is equal to 0 (i.e., the number of Hongping grid cells), (When the value is 0), the edge clustering degree takes the value of 0.

[0084] The dissolved oxygen coupling sequence is an ordered sequence indexed by collection time and containing data elements such as duckweed coverage rate, edge aggregation degree, and dissolved oxygen in the water. Each element in the dissolved oxygen coupling sequence corresponds to a collection time, and each element contains the duckweed coverage rate, edge aggregation degree, and dissolved oxygen value corresponding to that collection time. The generation of the dissolved oxygen coupling sequence involves processing all valid collection times in the ecological aquaculture management data table in chronological order. For each collection time, grid-based recognition of the duckweed coverage image, calculation of duckweed coverage rate, and calculation of edge aggregation degree are performed, and the dissolved oxygen value for the corresponding collection time is read from the ecological aquaculture management data table. The collection time, duckweed coverage rate, edge aggregation degree, and dissolved oxygen value are appended to the dissolved oxygen coupling sequence as a coupling record in chronological order of collection time. After all valid collection times have been processed, the dissolved oxygen coupling sequence contains the same number of coupling records as the valid records in the ecological aquaculture management data table. The dissolved oxygen coupling sequence uses the collection time field as an index, supporting the retrieval of coupling records at any position by collection time.

[0085] S3. Based on the coupled sequence of rice plant growth stage and dissolved oxygen under cover, a threshold discrimination method was used to label the ecological gain state, critical transition state, and ecological stress state corresponding to the red duckweed cover state, including:

[0086] In this embodiment, step S3 is implemented as follows: Using the collection time field as the search key, the data row corresponding to the current processing target is located in the ecological farming management data table. The rice plant growth period corresponding to the current collection time is read from the rice plant growth period field. The rice plant growth period value is a discrete growth stage name. Using the same collection time as the search key, the coupling record corresponding to the current collection time is located in the coverage dissolved oxygen coupling sequence. The red duckweed coverage rate, edge aggregation degree, and dissolved oxygen value of the water body are read from the coupling record. The reading operation is performed sequentially on all valid coupling records in the coverage dissolved oxygen coupling sequence. Each time, the rice plant growth period, red duckweed coverage rate, edge aggregation degree, and dissolved oxygen value of the water body corresponding to one collection time are processed. The processing order is arranged according to the time order of the collection time field.

[0087] The threshold values ​​for duckweed coverage, edge aggregation, and dissolved oxygen in water were all set in groups based on the rice plant growth stage. The impact mechanisms of duckweed on rice growth and dissolved oxygen differ at different rice plant growth stages; therefore, the range of each threshold value was adjusted according to the rice plant growth stage. The methodology for setting each threshold was as follows: Before the start of the rice-duckweed-fish ecological farming management cycle, based on historical field trial data and control group comparison results, the trends in dissolved oxygen, the degree of impact on rice yield, and the changes in fish survival rate were statistically analyzed at different levels of duckweed coverage for each rice plant growth stage. The ecological gain state was determined by dissolved oxygen not falling below the critical value for fish survival and rice growth not being significantly inhibited by shading. The critical transition state was determined by dissolved oxygen approaching but not falling below the critical value for fish survival or the degree of rice shading approaching but not reaching a level affecting photosynthetic efficiency. The critical transition state was determined by low dissolved oxygen. The critical value for fish survival or the degree of rice shading significantly affecting photosynthetic efficiency were used as the criteria for determining the state of ecological stress. Based on the above criteria and the measured distribution range of duckweed coverage and edge aggregation during the corresponding rice growth stages, the values ​​of duckweed coverage threshold, edge aggregation threshold, and dissolved oxygen threshold for each rice growth stage were determined. Each threshold was stored in the form of a two-dimensional lookup table. The row index of the lookup table was the name of the rice growth stage, and the column indexes were the upper limit of duckweed coverage threshold, the lower limit of duckweed coverage threshold, the upper limit of edge aggregation threshold, the lower limit of edge aggregation threshold, the upper limit of dissolved oxygen threshold, and the lower limit of dissolved oxygen threshold.

[0088] During the tillering stage, rice plants are spaced far apart and the canopy has not yet closed. Moderate coverage with duckweed helps suppress weeds and provides shade for fish. However, excessive duckweed coverage can obstruct gas exchange on the water surface, leading to a decrease in dissolved oxygen. Therefore, the upper limit of the duckweed coverage threshold during the tillering stage is set based on the duckweed coverage reaching a level that reduces the surface gas exchange area to a critical value. For example, the upper limit of the duckweed coverage threshold is set at 0.60, the lower limit is set at 0.20, the upper limit of the edge aggregation threshold is set at 0.75, the lower limit is set at 0.40, the upper limit of the dissolved oxygen threshold is set at 7.00 mg / L, and the lower limit is set at 4.00 mg / L. During the booting stage, rice's light requirements increase significantly. The upper limit of the red duckweed coverage threshold should be tightened accordingly compared to the tillering stage. For example, during the booting stage, the upper limit of the red duckweed coverage threshold can be set to 0.45, and the lower limit to 0.15. The upper limit of the edge aggregation threshold can be set to 0.70, and the lower limit to 0.35. The upper limit of the dissolved oxygen threshold can be set to 7.00 mg / L, and the lower limit to 4.00 mg / L. During the flowering stage, the dispersal and pollination of rice pollen require good airflow over the water surface. The upper limit of the red duckweed coverage threshold needs to be further reduced. For example, during the flowering stage, the upper limit of the red duckweed coverage threshold can be set to 0.30, and the lower limit to 0.10. The upper and lower limits of the dissolved oxygen threshold should remain consistent with those during the booting stage. The above values ​​are examples; the actual values ​​for each threshold should be determined methodologically based on historical field trial data from specific rice-duckweed-fish fields. Threshold matching specifically involves using the rice plant growth stage name corresponding to the current collection time as the row index, retrieving all threshold columns of the corresponding row in the two-dimensional lookup table, and extracting the upper limit of red duckweed coverage threshold, the lower limit of red duckweed coverage threshold, the upper limit of edge aggregation threshold, the lower limit of edge aggregation threshold, the upper limit of dissolved oxygen threshold, and the lower limit of dissolved oxygen threshold as the basis for determining the status marking of the current collection time.

[0089] The ecological benefit state refers to a state where the coverage and spatial distribution of duckweed on the water surface of rice-duckweed-fish co-culture fields are within a range that positively promotes both rice growth and fish survival. Under this state, duckweed coverage provides shade and food for fish, does not cause dissolved oxygen levels to drop to levels harmful to fish health, and does not significantly negatively impact light interception by the rice canopy. The critical transition state refers to a state where the duckweed coverage or dissolved oxygen level is in the transitional zone between the ecological benefit and ecological stress states. Under this state, a certain indicator of duckweed coverage or dissolved oxygen levels shows a tendency to exceed the suitable range, but has not yet reached a level that has a definitive negative impact on rice growth or fish survival. An early warning system should be triggered, and intervention should be prepared. The ecological stress state refers to a state where the duckweed coverage or dissolved oxygen levels exceed the self-regulating range of the rice-duckweed-fish symbiotic system. Under this state, dissolved oxygen levels are below the minimum level required for safe fish survival, or duckweed coverage has definitively inhibited rice photosynthetic efficiency. Immediate field intervention is required.

[0090] For the duckweed coverage rate, edge aggregation degree, and dissolved oxygen value corresponding to the current collection time, combined with the upper and lower thresholds for duckweed coverage rate, edge aggregation degree, and dissolved oxygen value obtained from the rice growth stage, the following judgment rules are applied for comparison item by item: When the duckweed coverage rate is not higher than the upper threshold and not lower than the lower threshold, the edge aggregation degree is not higher than the upper threshold and not lower than the lower threshold, and the dissolved oxygen value is not lower than the upper threshold, all three indicators are within the ecological gain range, and the duckweed coverage status corresponding to the current collection time is marked as ecological gain. The ecological stress state is defined as follows: when dissolved oxygen in the water is below the lower limit of the dissolved oxygen threshold, or when the combined conditions of duckweed coverage exceeding the upper limit of the duckweed coverage threshold and edge aggregation exceeding the upper limit of the edge aggregation threshold are met, the duckweed coverage state at the current sampling time is marked as an ecological stress state. When the duckweed coverage is above the upper limit of the duckweed coverage threshold or below the lower limit of the duckweed coverage threshold, or the edge aggregation is above the upper limit of the edge aggregation threshold or below the lower limit of the edge aggregation threshold, or the dissolved oxygen in the water is below the upper limit of the dissolved oxygen threshold but not below the lower limit of the dissolved oxygen threshold, and none of the three indicators has triggered the judgment conditions corresponding to the ecological stress state, the duckweed coverage state at the current sampling time is marked as a critical transition state. In the judgment rules, the judgment priority of the ecological stress state is higher than that of the critical transition state. That is, when the comparison results of the indicators at the same sampling time simultaneously meet the judgment conditions of the critical transition state and the ecological stress state, the duckweed coverage state is marked as an ecological stress state. The labeling results of the duckweed coverage status are recorded in text form, with values ​​of ecological gain status, critical transition status, or ecological stress status. The duckweed coverage status labeling results are jointly correlated with the duckweed coverage rate, edge aggregation degree, and dissolved oxygen value of the water body at the corresponding collection time.

[0091] S4. When the coverage state of Dalbergia odorifera is in a critical transition state and an ecological stress state, the dissolved oxygen decline trend is calculated using the sliding difference method combined with fish load and meteorological data to generate the critical transition level of Dalbergia odorifera, including:

[0092] In this embodiment, step S4 is implemented as follows: When the duckweed coverage status is marked as a critical transitional state or an ecological stress state, step S4 is triggered. The triggering condition is determined based on the duckweed coverage status marking result. For each collection time in the coverage dissolved oxygen coupling sequence, the duckweed coverage status marking result associated with the current collection time is read.

[0093] Using the collection time that triggers step S4 as the search key, locate the corresponding data row in the ecological farming management data table, and read the fish load value corresponding to the current collection time from the fish load field. The unit of the fish load value is grams per square meter. Read the temperature, relative humidity, wind speed, light intensity, and rainfall corresponding to the current collection time from the temperature, relative humidity, wind speed, light intensity, and rainfall fields, respectively. The units of each field are degrees Celsius, percentage, meters per second, lux, and millimeters per hour, respectively.

[0094] Adjacent acquisition time refers to the acquisition time sequence that is immediately adjacent to the acquisition time of the current triggering step S4 in the dissolved oxygen coupling sequence. The extraction range is set to the dissolved oxygen value of the water body corresponding to the current acquisition time and several consecutive acquisition times before the current acquisition time. The number of acquisition times extracted is determined by the calculation window length of the sliding difference method. Taking the current acquisition time of triggering step S4 as the end position in the time series, a continuous sequence of dissolved oxygen values ​​in the water body is extracted by backtracking. The number of acquisition times extracted is denoted as the window length W. The value of the window length W is determined based on the acquisition time interval and the ecological response time of dissolved oxygen changes. The ecological response time of dissolved oxygen changes refers to the time span required for observable changes in dissolved oxygen in the water body after the coverage state of duckweed changes. When the acquisition time interval is twice a day (i.e., once every 8 hours), for example, setting the window length W to 5 means extracting the dissolved oxygen values ​​corresponding to 5 consecutive acquisition times, including the current acquisition time, corresponding to a dissolved oxygen change process of approximately 40 hours. When the acquisition time interval is once a day, for example, setting the window length W to 4 means extracting the dissolved oxygen values ​​corresponding to 4 consecutive acquisition times, corresponding to a dissolved oxygen change process of approximately 4 days. When the number of effective coupling records before the current acquisition time in the dissolved oxygen coupling sequence is insufficient to fill the window length W, the actual number of extractable effective coupling records is used as the actual window length for the current calculation. The actual window length must not be less than 2 acquisition times. After extraction, the collection times and corresponding dissolved oxygen values ​​in the water body within the window are arranged in chronological order to form a dissolved oxygen time series. The length of the dissolved oxygen time series is equal to the actual window length, and the unit of each element is milligrams per liter.

[0095] The sliding difference method involves calculating the difference between two adjacent dissolved oxygen values ​​in a water body's dissolved oxygen time series, and then summarizing and statistically analyzing all the difference results to reflect the direction and magnitude of the change in dissolved oxygen over time. Specifically, let the dissolved oxygen value at the i-th sampling time in the water body's dissolved oxygen time series be... The unit is milligrams per liter. The value of i ranges from 1 to the actual window length. i=1 corresponds to the earliest acquisition time in the time series, and i equal to the actual window length corresponds to the latest acquisition time in the time series, which is the acquisition time that triggers step S4. The first-order difference is calculated for each pair of adjacent acquisition times in the time series. The first-order difference between the i-th acquisition time and the (i-1)-th acquisition time is denoted as... The calculation formula is as follows:

[0096] ;in, The first-order difference value of dissolved oxygen in the water body at the i-th sampling time relative to the (i-1)-th sampling time is expressed in milligrams per liter. A positive value indicates an increase in dissolved oxygen, a negative value indicates a decrease in dissolved oxygen, and a value of 0 indicates no change in dissolved oxygen. The dissolved oxygen value of the water body corresponding to the i-th collection time is expressed in milligrams per liter. The dissolved oxygen value in the water body corresponding to the (i-1)th collection time is expressed in milligrams per liter; the value of i ranges from 2 to the actual window length, and a total of the actual window length minus one first-order difference value is obtained.

[0097] The arithmetic mean of all first-order differences is calculated to obtain the average rate of change of dissolved oxygen, denoted as . The calculation formula is as follows:

[0098] ;in, The average dissolved oxygen change rate is expressed in milligrams per liter per sampling time interval; W is the actual window length, expressed in units of 1, and takes a value that is not less than 2. Let be the first-order difference value of dissolved oxygen in water at the i-th sampling time, in milligrams per liter; the summation range is all first-order difference values ​​from i to W. A negative value and a larger absolute value indicate a more significant downward trend in dissolved oxygen in the water. A positive value indicates that the dissolved oxygen in the water is on an upward trend.

[0099] The dissolved oxygen decline trend refers to the comprehensive assessment of the rate and magnitude of continued decline in dissolved oxygen in the water body during the future sampling period, taking into account the historical rate of change of dissolved oxygen, fish oxygen consumption pressure, and the impact of meteorological conditions on the water body's reoxygenation capacity. The correction mechanism for the dissolved oxygen decline trend based on fish load is as follows: the higher the fish load, the greater the oxygen consumption of fish respiration per unit time, and the faster the rate of decline in dissolved oxygen in the water body. Therefore, a fish load correction coefficient is introduced. Fish load correction factor The method for setting the parameters is as follows: Based on historical field trial data, establish the correspondence between fish load and fish oxygen consumption rate, and divide the range of fish load values ​​into low load, medium load, and high load ranges. For example, a fish load below 30 grams per square meter is defined as the low load range, a fish load between 30 and 80 grams per square meter is defined as the medium load range, and a fish load above 80 grams per square meter is defined as the high load range. The low load range corresponds to a fish load correction factor. For example, a value of 1.00 represents the fish load correction factor for the medium load range. For example, a value of 1.20 represents the fish load correction factor for the high-load range. For example, a value of 1.45 is used for the fish load correction factor. The value is determined based on historical measured data from specific rice-fish farming plots. The correction mechanism for the declining dissolved oxygen trend in meteorological data is as follows: light intensity directly affects the photosynthetic oxygen production rate of Aucklandia lappa and the reoxygenation capacity of the water; wind speed affects the gas exchange rate at the water surface; rainfall affects the water level and water dilution in the plot; and air temperature affects the oxygen solubility in the water. Therefore, a meteorological correction coefficient is introduced. Weather correction factor The setting method is as follows: when the light intensity is not lower than the set light intensity benchmark value and the wind speed is not lower than the set wind speed benchmark value, the water body has a strong reoxygenation capacity, and the meteorological correction coefficient is [not specified]. The value is less than 1; when the light intensity is lower than the light intensity reference value or the wind speed is lower than the wind speed reference value, the water body's reoxygenation capacity is weak, and the meteorological correction coefficient is applied. The value should be no less than 1; the baseline values ​​for light intensity and wind speed are determined based on the lower limits of light intensity and wind speed corresponding to the conditions in historical field observations when dissolved oxygen in water bodies can remain stable or slightly increase. For example, if the baseline value for light intensity is set to 20,000 lux and the baseline value for wind speed is set to 1.0 m / s, the meteorological correction factor is used under the condition that the light intensity is no less than 20,000 lux and the wind speed is no less than 1.0 m / s. For example, a value of 0.85 is a weather correction factor under conditions where the light intensity is below 20,000 lux and the wind speed is below 1.0 m / s. For example, a value of 1.30 is used for the meteorological correction factor. The segmented values ​​were determined based on historical measured data from specific rice-fish farming plots. The comprehensive assessment value for the dissolved oxygen decline trend is denoted as... The calculation formula is as follows:

[0100] ;in, This is a comprehensive assessment value for the dissolved oxygen decline trend, expressed in milligrams per liter per collection time interval. The smaller the value (i.e., the larger the absolute value of the negative value), the more severe the dissolved oxygen decline trend. The average rate of change in dissolved oxygen is expressed in milligrams per liter per sampling time interval. This is a fish load correction factor, which is dimensionless and takes a positive value. This is a meteorological correction factor, which is dimensionless and takes a positive value.

[0101] The critical transition level of duckweed refers to the classification of the urgency of dissolved oxygen deterioration in the water body under the current duckweed coverage state based on the comprehensive assessment value of dissolved oxygen decline trend. The critical transition level of duckweed is divided into three levels: Level 1, Level 2, and Level 3. Level 1 corresponds to the least urgent situation of dissolved oxygen decline trend, and Level 3 corresponds to the most urgent situation of dissolved oxygen decline trend. The classification criteria for the critical transition level of duckweed are as follows: The classification threshold of the critical transition level of duckweed is set according to the duckweed coverage state marking results corresponding to the current collection time. When the duckweed coverage state is in a critical transition state, the classification threshold of the comprehensive assessment value of dissolved oxygen decline trend is determined based on the remaining margin of dissolved oxygen in the water body from the lower limit of the dissolved oxygen threshold under the critical transition state and the estimated number of collection times required to reach the lower limit of the threshold. For example, when the comprehensive assessment value of dissolved oxygen decline trend is not lower than -0.20 mg / L per collection time interval, it is marked as Level 1; when the comprehensive assessment value of dissolved oxygen decline trend is lower than -0.20 mg / L per collection time interval but not lower than -0.20 mg / L per collection time interval, it is marked as Level 1. A level 2 is defined as a dissolved oxygen concentration of 50 mg / L per sampling interval. A level 3 is defined as a dissolved oxygen concentration of -0.50 mg / L per sampling interval. When the duckweed coverage is under ecological stress, the dissolved oxygen in the water is already below the lower limit of the dissolved oxygen threshold. The grading threshold for the dissolved oxygen concentration decline trend should be tightened overall based on the critical transition state. For example, a level 2 is defined as a dissolved oxygen concentration decline trend of not less than -0.10 mg / L per sampling interval, and a level 3 is defined as a dissolved oxygen concentration decline trend of less than -0.10 mg / L per sampling interval. No level 1 is set under ecological stress. The above grading thresholds are examples. The actual grading thresholds for each level are determined based on historical measured data of specific rice-duckweed-fish fields and the impact of dissolved oxygen on fish safety. The results of the duckweed critical transition level are recorded in text form, with values ​​of level 1, 2, or 3. The duckweed critical transition level is associated with the duckweed coverage status marking result at the corresponding sampling time and the dissolved oxygen concentration decline trend assessment value.

[0102] S5. Based on the critical transition level of the red duckweed, call the operation priority table to determine the execution order and amount of field coordinated regulation operations, including:

[0103] In this embodiment, the implementation process of step S5 is as follows: The operation priority table refers to a pre-established structured table that uses the critical conversion level of duckweed as the retrieval key and records the combination of field coordinated regulation operations and the corresponding operation arrangement relationship. The structure of the operation priority table is as follows: The row index of the operation priority table is the critical conversion level of duckweed, and the value is level one, level two, or level three; the columns of the operation priority table include an operation content column and an operation arrangement relationship column. The operation content column records the names of operation items associated with the corresponding critical conversion level of duckweed in duckweed harvesting, water replenishment, feeding, fertilization, and oxygenation. The operation arrangement relationship column records the execution order number of each operation item under the current critical conversion level of duckweed. The execution order number is a positive integer, and the smaller the number, the higher the execution priority. The task priority table is filled out in advance based on historical field management experience and control group test results before the start of the rice-fish ecological farming management cycle. The methodology for setting the task content and arrangement relationship corresponding to each critical conversion level of red duckweed in the task priority table is as follows: Based on historical field test data, the contribution of each task of harvesting duckweed, replenishing water, feeding, fertilizing and aeration to the rate of recovery of dissolved oxygen and the rate of decrease of red duckweed coverage is statistically analyzed under the condition of decreased dissolved oxygen in the water body corresponding to each critical conversion level of red duckweed. The task items that contribute the most significantly to the recovery of dissolved oxygen or the decrease of red duckweed coverage are arranged first, and the task items that contribute less are arranged later, so as to determine the task arrangement relationship under each critical conversion level of red duckweed.

[0104] Using the critical conversion level of the red duckweed corresponding to the current collection time of triggering step S5 as the search key, locate the corresponding row in the operation priority table, read all operation item names in the operation content column of the corresponding row, and the set of all operation item names constitutes the field coordinated regulation operation combination corresponding to the current collection time. The field coordinated regulation operation combination includes the operations corresponding to the current critical conversion level of red duckweed, such as duckweed harvesting, water replenishment, feeding, fertilization, and oxygenation. The meanings of each operation item are as follows: Duckweed harvesting refers to the field operation of scooping and removing red duckweed that exceeds the suitable coverage level from the water surface of the rice-duckweed-fish field; Water replenishment refers to the field operation of injecting external water sources into the rice-duckweed-fish field to raise the water level, dilute the water body, and increase the air-liquid contact area on the water surface; Feeding refers to the field operation of supplementing the farmed fish in the rice-duckweed-fish field with artificial compound feed to reduce the intensity of fish consumption of natural food and thus indirectly reduce the oxygen consumption of fish metabolism; Fertilization refers to the field operation of applying nitrogen fertilizer to the rice-duckweed-fish field to regulate the growth rate of red duckweed; Oxygenation refers to the field operation of supplementing dissolved oxygen in the water body of the rice-duckweed-fish field using physical oxygenation methods. The differences in field coordinated regulation operation combinations corresponding to different critical transition levels of duckweed are as follows: Level 1 corresponds to the least urgent situation of dissolved oxygen decline. The field coordinated regulation operation combination for Level 1 usually includes duckweed harvesting and water replenishment, mainly for preventive regulation. For example, the field coordinated regulation operation combination for Level 1 can be set to include duckweed harvesting and water replenishment. Level 2 corresponds to the situation of more significant dissolved oxygen decline. The field coordinated regulation operation combination for Level 2 adds feeding and aeration to the Level 1 operation, in order to reduce the oxygen consumption pressure on fish and directly replenish dissolved oxygen. For example, the field coordinated regulation operation combination for Level 2 can be set to include feeding and aeration. The coordinated control operation combination is set as four operations: duckweed harvesting, water replenishment, feeding, and oxygenation. Level 3 corresponds to the most urgent situation of dissolved oxygen decline. The field coordinated control operation combination corresponding to Level 3 continues to add fertilization on the basis of Level 2, so as to inhibit the spread of duckweed coverage from the root by regulating the growth rate of duckweed. For example, the field coordinated control operation combination corresponding to Level 3 is set as five operations: duckweed harvesting, water replenishment, feeding, oxygenation, and fertilization. The above operation combination is just an example. The actual operation combination for each critical conversion level of duckweed is determined by methodology based on the historical field management experience of specific rice-duckweed-fish fields.

[0105] From the operation arrangement column corresponding to the current critical conversion level of the red duckweed in the operation priority table, read the execution sequence number of each operation item in the field coordinated regulation operation combination, and arrange all operation items in the field coordinated regulation operation combination according to the execution sequence number from smallest to largest to obtain the execution order of the field coordinated regulation operation. Under each critical transition level of duckweed, the operational arrangement is set according to the following: the execution sequence of aeration operations is ranked first in the field coordinated regulation operation combinations corresponding to Level 3 and Level 2. This is because aeration operations have the most direct effect on increasing dissolved oxygen in the water and the shortest response time, which can alleviate the risk of dissolved oxygen stress in fish in the shortest time. For example, in the operational arrangement corresponding to Level 3, the execution sequence of aeration is set as 1, duckweed harvesting as 2, water replenishment as 3, feeding as 4, and fertilization as 5. In the operational arrangement corresponding to Level 1, the execution sequence of duckweed harvesting is set as 1, and water replenishment as 2. The above numbers are just examples. The actual operational arrangement for each level is determined through methodology based on historical field management experience.

[0106] The execution volume of field coordinated regulation operations refers to the number or intensity of operations required for each operation item in the field coordinated regulation operation combination after the execution sequence of field coordinated regulation operations is determined. The calculation method for the execution volume of each operation item is determined according to the operation type.

[0107] The amount of duckweed harvesting is expressed as the proportion of the duckweed-covered area to be removed from the rice-duckweed-fish paddy field to the total water surface area of ​​the paddy field, measured in a dimensionless ratio. The amount of duckweed harvesting is calculated based on the duckweed coverage rate at the current collection time and the upper limit of the duckweed coverage rate threshold matched to the rice plant growth stage at the current collection time. The amount of duckweed harvesting is equal to the difference between the duckweed coverage rate at the current collection time and the upper limit of the duckweed coverage rate threshold. When the difference is positive, the amount of duckweed harvesting is the difference, indicating that a proportion of the duckweed coverage area equal to the difference needs to be removed. When the difference is not positive, the amount of duckweed harvesting is 0, indicating that the reason for triggering step S5 is not due to the duckweed coverage rate exceeding the limit. The duckweed harvesting operation still needs to be performed, but the amount of harvesting is the minimum maintenance operation amount. For example, the minimum maintenance operation amount is set to 0.05, which means removing 5% of the total water surface area of ​​the rice-duckweed-fish paddy field.

[0108] The water replenishment volume is expressed as the ratio of the water injected into the rice-fish farming plot to the current water volume of the plot, measured in a dimensionless ratio. The water replenishment volume is calculated based on the difference between the current dissolved oxygen level and the lower limit of the dissolved oxygen threshold. When the dissolved oxygen level is below the upper limit but not below the lower limit, the water replenishment volume is set as the injection ratio corresponding to the dilution ratio required to raise the dissolved oxygen level back to the upper limit. For example, setting the water replenishment volume to 0.15 means injecting fresh water equivalent to 15% of the current water volume of the rice-fish farming plot. When the dissolved oxygen level is below the lower limit, the water replenishment volume is increased accordingly, for example, setting it to 0.30. These ratios are examples; the actual value of the water replenishment volume is determined based on the difference between the current dissolved oxygen level and the upper limit of the dissolved oxygen threshold, and historical data on the reoxygenation rate of the rice-fish farming plot.

[0109] Oxygenation execution volume is expressed as the duration of oxygenation operations, measured in minutes. The calculation of oxygenation execution volume is based on the difference between the current dissolved oxygen level and the upper limit of the dissolved oxygen threshold, as well as the fish load. When the fish load is in the low-load range, the required duration of oxygenation operations is relatively short. When the fish load is in the high-load range, the fish consume oxygen at a higher rate, requiring a longer oxygenation duration to raise the dissolved oxygen level back to the upper limit of the dissolved oxygen threshold. For example, when the fish load is in the low-load range and the dissolved oxygen level is between 0.50 mg / L and 1.00 mg / L below the upper limit of the dissolved oxygen threshold, the oxygenation execution volume is set to 20 minutes; when the fish load is in the high-load range and the dissolved oxygen level is more than 1.00 mg / L below the upper limit of the dissolved oxygen threshold, the oxygenation execution volume is set to 45 minutes. These durations are examples; the actual value of the oxygenation execution volume is determined methodologically based on historical oxygenation response data and the current fish load of a specific rice-fish paddy field.

[0110] The feeding and fertilization rates were determined based on the fish load and the duckweed coverage rate, respectively. The feeding rate was expressed as the ratio of the amount of feed given in a given time to the fish load, and the fertilization rate was expressed as the amount of nitrogen applied per unit water surface area. The values ​​were determined based on historical field trial data of the daily feed requirements of fish in a specific rice-duckweed-fish field under different load levels and the response of duckweed to nitrogen under different coverage levels.

[0111] Once the execution sequence and amount of field coordinated regulation operations are determined, a complete execution plan for the field coordinated regulation operations is listed in ascending order of execution sequence number. Each record in the execution plan includes the operation item name, execution sequence number, and execution amount. The execution plan is associated with the current data collection time.

[0112] S6. Record the execution sequence and amount of field coordinated regulation operations into the ecological farming management data table, and update the operation priority table based on the dissolved oxygen in the water and the coverage rate of red duckweed at the next data collection time, including:

[0113] In this embodiment, step S6 is implemented as follows: The complete execution plan of the field coordinated regulation operation is associated with the current collection time. Each record in the complete execution plan includes the operation project name, execution sequence number, and execution quantity. The ecological farming management data table is expanded by adding an operation execution record field. The data type of the operation execution record field is text. The content of the operation execution record field is stored in a serialized manner, containing the operation project name, execution sequence number, and execution quantity of all operation projects in the complete execution plan corresponding to the current collection time. The storage format is that each operation project record is separated by a delimiter. Each operation project record contains, in sequence, an operation project name field, an execution sequence number field, and an execution quantity field, with fields separated by a predefined field delimiter. Using the current collection time as the search key, the corresponding data row is located in the ecological farming management data table, and the serialized complete execution plan is written into the operation execution record field, ensuring that the execution sequence and execution quantity of the field coordinated regulation operation are in the same record of the ecological farming management data table as the current collection time.

[0114] The next acquisition time refers to the acquisition time immediately following the acquisition time of the current triggering step S6 in the dissolved oxygen coupling sequence. The next acquisition time is determined as follows: in the dissolved oxygen coupling sequence, using the acquisition time of the current triggering step S6 as a reference position, search forward one position in chronological order; the resulting acquisition time is the next acquisition time. Upon arrival of the next acquisition time, the dissolved oxygen coupling sequence has generated a corresponding coupling record for that time. This record contains the coverage rate of *Azolla officinalis*, edge aggregation degree, and dissolved oxygen value of the water body corresponding to the next acquisition time. Using the next acquisition time as the search key, the coupling record corresponding to the next acquisition time is located in the dissolved oxygen coupling sequence, and the dissolved oxygen value and *Azolla officinalis* coverage rate corresponding to the next acquisition time are read from the coupling record. Simultaneously, using the acquisition time of the current triggering step S6 as the search key, the coupling record corresponding to the current acquisition time is located in the dissolved oxygen coupling sequence, and the dissolved oxygen value and *Azolla officinalis* coverage rate corresponding to the current acquisition time are read from the coupling record. In the context of step S6, the current acquisition time is the previous acquisition time.

[0115] The specific method for comparing dissolved oxygen in water is as follows: subtract the dissolved oxygen value of the previous collection time from the dissolved oxygen value of the next collection time to obtain the change in dissolved oxygen, expressed in milligrams per liter, rounded to two decimal places. A positive change in dissolved oxygen indicates that the dissolved oxygen in the next collection time has increased compared to the previous collection time; a negative change indicates that the dissolved oxygen in the next collection time continues to decrease compared to the previous collection time; and a change of 0 indicates that there is no change in dissolved oxygen.

[0116] The specific method for comparing the coverage rate of duckweed is as follows: The change in duckweed coverage rate is calculated by subtracting the duckweed coverage rate of the previous collection time from the duckweed coverage rate of the next collection time. The change is a dimensionless ratio, rounded to four decimal places. A negative change indicates that the duckweed coverage rate at the next collection time has decreased compared to the previous collection time, meaning the harvesting operation achieved the expected effect. A positive change indicates that the duckweed coverage rate at the next collection time has increased compared to the previous collection time, meaning the duckweed coverage is still expanding after the field-based coordinated control operation. A change of 0 indicates no change in duckweed coverage. The changes in dissolved oxygen in the water and the changes in duckweed coverage rate together constitute the effect feedback data of this field-based coordinated control operation. This effect feedback data is correlated with the critical transition level of duckweed at the previous collection time and is used to adjust the operation priority table.

[0117] The goal of adjusting the task priority table is to modify the task arrangement relationship and the execution quantity range of each task item in the task priority table corresponding to the critical conversion level of red duckweed at the same collection time as the previous collection time, based on the actual implementation effect of the field coordinated regulation operation, so that the task priority table can more accurately guide the execution of the field coordinated regulation operation under the same triggering conditions.

[0118] The adjustment rules for the operation arrangement are as follows: When the change in dissolved oxygen in the water is positive and the absolute value of the change is not lower than the preset threshold for sufficient dissolved oxygen recovery, it indicates that the implementation of the field coordinated regulation operation has resulted in a sufficient recovery of dissolved oxygen in the water. The current operation arrangement has a significant effect on improving dissolved oxygen in the water, and the operation arrangement does not need to be adjusted; the original execution order and numbering of each operation item remain unchanged. When the change in dissolved oxygen in the water is negative, or when the change in dissolved oxygen in the water is positive but the absolute value of the change in red duckweed coverage is lower than the preset threshold for sufficient dissolved oxygen recovery, it indicates that the implementation of the field coordinated regulation operation has failed to result in a sufficient recovery of dissolved oxygen in the water. The current operational arrangement is insufficient to improve dissolved oxygen in the water body, and the operational arrangement needs to be adjusted. The adjustment method is as follows: in the field coordinated regulation operation combination corresponding to the current critical conversion level of duckweed, the execution order number of the oxygenation operation and the water replenishment operation will be moved forward by 1 position. That is, the priority of the oxygenation operation and the water replenishment operation in the execution order will be increased by 1 position relative to the current arrangement. At the same time, the positions originally occupied by the oxygenation operation and the water replenishment operation will be filled by the duckweed harvesting operation or the feeding operation. The adjusted operational arrangement will be written back to the operational arrangement column corresponding to the critical conversion level of duckweed in the operation priority table. The method for setting the sufficient dissolved oxygen recovery threshold is as follows: Based on historical field test data, the minimum change in dissolved oxygen in the water body required for a stable recovery in the next sampling time after performing field coordinated regulation operations at the same critical conversion level of paddy field is statistically analyzed. The minimum change in dissolved oxygen in the water body is used as the sufficient dissolved oxygen recovery threshold. For example, the sufficient dissolved oxygen recovery threshold is set to 0.30 mg / L, that is, when the dissolved oxygen in the water body at the next sampling time recovers by no less than 0.30 mg / L compared to the previous sampling time, it is considered to have recovered sufficiently. The above value is an example. The actual value of the sufficient dissolved oxygen recovery threshold is determined based on the historical measured data of a specific paddy field.

[0119] The adjustment rules for the execution quantity value range are as follows. The execution quantity value range refers to the interval formed by the upper limit and lower limit of the execution quantity of each job item under the corresponding Hongping critical conversion level in the job priority table. The execution quantity value range provides a reference range when determining the execution quantity of each job item in step S5. When the change in red duckweed coverage is negative and the absolute value of the change is not lower than the preset threshold for sufficient red duckweed coverage reduction, it indicates that the red duckweed harvesting operation is effective and the range of red duckweed harvesting execution volume does not need to be adjusted. When the change in red duckweed coverage is positive or negative but the absolute value of the change is lower than the preset threshold for sufficient red duckweed coverage reduction, it indicates that the execution volume of red duckweed harvesting operation is insufficient to effectively control the expansion of red duckweed coverage. It is necessary to raise the lower limit of the range of red duckweed harvesting execution volume corresponding to the current critical red duckweed conversion level in the operation priority table. The increase is determined based on the difference between the change in red duckweed coverage and the threshold for sufficient red duckweed coverage reduction. For example, when the change in red duckweed coverage is positive, the lower limit of the range of red duckweed harvesting execution volume is increased by 0.05 on the current basis. That is, when triggered at the same level in the future, the minimum value of red duckweed harvesting execution volume is increased by 0.05 compared to the previous time. The method for setting the threshold for sufficient reduction of duckweed coverage is as follows: Based on historical field test data, the absolute value of the minimum change in duckweed coverage required to effectively reduce duckweed coverage in the next collection time after duckweed harvesting is statistically analyzed under the same critical conversion level. The absolute value of the minimum change in duckweed coverage is used as the threshold for sufficient reduction of duckweed coverage. For example, the threshold for sufficient reduction of duckweed coverage is set to 0.08, that is, when the duckweed coverage in the next collection time decreases by no less than 0.08 compared to the previous collection time, it is considered to have decreased sufficiently. The above value is an example. The actual value of the threshold for sufficient reduction of duckweed coverage is determined based on the historical measured data of a specific rice-duckweed-fish field. The adjustment range of the oxygenation execution amount is determined based on the difference between the change in dissolved oxygen in the water and the threshold for sufficient dissolved oxygen recovery. When the change in dissolved oxygen in the water is lower than the threshold for sufficient dissolved oxygen recovery, the lower limit of the oxygenation execution amount range will be increased by 5 minutes from the current level to provide more sufficient oxygenation time when triggered at the same level in the future. The above adjustment range is just an example. The actual adjustment range of the execution amount range for each operation item is determined based on the historical response data of the specific rice paddy fish field.

[0120] After the task priority table is adjusted, the adjusted task arrangement and execution range are written back to the corresponding column of the critical conversion level of the red duckweed in the task priority table. The updated task priority table is used as the basis for retrieval and calculation in step S5 of the subsequent data collection time. This allows the task priority table to continuously accumulate field control experience as the rice-duckweed-fish ecological farming management cycle progresses, and gradually improve the pertinence and effectiveness of field collaborative control operations.

[0121] S7. Based on the ecological farming management data table, establish a regression prediction model. When the same critical transition level of duckweed reappears, use the regression prediction model to determine the execution quantity range that will keep the expected dissolved oxygen in the water body within the ecological gain range, and update the operation priority table, including:

[0122] In this embodiment, the specific implementation process of step S7 is as follows: Extracting the accumulated dissolved oxygen, duckweed coverage, fish load, meteorological data, and field collaborative control operation data from the ecological farming management data table for at least two collection cycles. Specifically, a collection cycle refers to the complete rice-duckweed-fish ecological farming management time span from rice transplanting to rice harvest. All valid records in the ecological farming management data table arranged in chronological order within a collection cycle constitute a complete dataset for that collection cycle. Step S7 is executed after at least two collection cycles of data accumulation are completed. The execution timing is determined by checking the number of valid collection cycles that have been written into the operation execution record field in the ecological farming management data table. When the number of valid collection cycles is not less than 2, step S7 is triggered; when the number of valid collection cycles is less than 2, step S7 is not executed, and the process continues to wait for the data accumulation of the next collection cycle. The data requirement of at least two collection periods is set based on the following: the number of times the same critical transition level of duckweed is triggered within a single collection period is limited, and the sample size is insufficient to support the robust fitting of the regression prediction model. The cumulative data of at least two collection periods can cover multiple trigger records under different rice growth stages, different meteorological conditions, and different fish load combinations, thereby ensuring that the fitting sample of the regression prediction model has sufficient coverage. For example, when the collection interval between the tillering stage and the jointing stage is twice a day, the number of times the single critical transition level of duckweed is triggered within two collection periods can usually reach 10 to 30 times, which can support the minimum sample size requirement for multiple linear regression fitting.

[0123] Using the critical transition level field of Aucklandia lappa as the filtering condition, all valid records of the critical transition level field (i.e., records with a critical transition level of level 1, 2, or 3) were retrieved from the ecological farming management data table. The filtering results were then grouped according to the critical transition level, with records of the same critical transition level grouped together. For each group, the execution values ​​of the dissolved oxygen, Aucklandia lappa coverage, fish load, air temperature, relative humidity, wind speed, light intensity, rainfall, and operation execution record fields were extracted. The serialized content of the operation execution record field was then parsed to extract the values ​​of each operation. The execution volume values ​​for each operation project are parsed as follows: the serialized content is split according to a predefined field separator, and the values ​​of the operation project name field and the execution volume field are extracted from each record. The execution volume of duckweed harvesting, water replenishment, oxygenation, feeding, and fertilization are organized into numerical sequences using the operation project name as the index. After extraction, each duckweed critical conversion level corresponds to a set of multi-dimensional numerical matrices. Each row of the matrix corresponds to a trigger record, and the columns of the matrix correspond to dissolved oxygen in the water, duckweed coverage, fish load, air temperature, relative humidity, wind speed, light intensity, rainfall, and the execution volume of each operation project, respectively.

[0124] The regression prediction model, fitted using the execution volume of field-coordinated regulation operations as the independent variable and dissolved oxygen in the water as the dependent variable, is specifically designed to be a linear equation obtained by fitting historical data through multiple linear regression. This model uses the execution volume of each item in the field-coordinated regulation operation as the input variable and the dissolved oxygen value in the water at the next sampling time after the operation as the output variable. The regression prediction model is constructed independently for each critical transition level of *Agrostis pilosa*, meaning each critical transition level corresponds to a dedicated regression prediction model, and the regression prediction models for different critical transition levels are independent of each other.

[0125] Taking the fitting process of the regression prediction model corresponding to a certain critical transition level of duckweed as an example, from the multidimensional numerical matrix corresponding to the critical transition level of duckweed, the execution volume column of field coordinated regulation operations is used to construct the independent variable matrix. The number of columns in the independent variable matrix is ​​equal to the number of operation items in the field coordinated regulation operation combination corresponding to the current critical transition level of duckweed. Each column in the independent variable matrix corresponds to the execution volume of operation items related to the current critical transition level of duckweed, including duckweed harvesting, water replenishment, oxygenation, feeding, and fertilization. The dissolved oxygen value of the water body at the next collection time corresponding to each trigger record is used to construct the dependent variable vector. The method for obtaining the dissolved oxygen value of the water body at the next collection time is as follows: taking the collection time of each trigger record as a reference, the dissolved oxygen value of the water body contained in the next coupled record with the closest time sequence is retrieved in the dissolved oxygen coupling sequence. The unit of the dissolved oxygen value of the water body at the next collection time is milligrams per liter, rounded to two decimal places. The fitting equation of the regression prediction model is as follows:

[0126] ;

[0127] in, The expected dissolved oxygen value in the water body is the output of the regression prediction model, in milligrams per liter. This is the regression intercept term, expressed in milligrams per liter. The regression coefficients are given for the amount of duckweed harvested, in milligrams per liter per unit of duckweed harvested. For the amount of watermelon harvested; The regression coefficients are given for the amount of water replenishment implemented, expressed in milligrams per liter per unit of water replenishment implemented. The water replenishment volume is a dimensionless ratio. The regression coefficient is the oxygenation execution rate, expressed in milligrams per liter per minute. The oxygenation rate is measured in minutes. The regression coefficient corresponds to the feeding execution rate, expressed in milligrams per liter per unit feeding execution rate. The feeding dosage is expressed in grams per gram per square meter. The regression coefficient corresponds to the amount of fertilizer applied, expressed in milligrams per liter per gram per square meter. The fertilizer application rate is expressed in grams per square meter. When a certain application item is not included in the field coordinated control operation combination corresponding to the current critical conversion level of Aucklandia lappa, the corresponding regression coefficient and application rate term are set to 0 in the fitted equation. Regression coefficient to The solution is obtained using the least squares method. The goal of the least squares method is to minimize the sum of squares of the differences between the expected dissolved oxygen value and the actual dissolved oxygen value at the next collection time in all sample records. After fitting, the goodness of fit of the regression prediction model is tested. The goodness of fit is expressed by the coefficient of determination. When the coefficient of determination is not lower than 0.65, the regression prediction model is considered to have an acceptable fit quality and can be used to predict the expected dissolved oxygen in the water. When the coefficient of determination is lower than 0.65, if the sample size is insufficient, data is accumulated and the model is refitted. If the sample size is sufficient, abnormal records are checked in the data, and abnormal records are removed before refitting. The actual acceptable threshold is determined based on the data quality of the specific rice-fish field.

[0128] When the same critical transition level of duckweed reappears, multiple candidate field coordinated regulation operation execution quantities are input into the regression prediction model to obtain the expected dissolved oxygen in the water body corresponding to each candidate execution quantity. Specifically, the candidate field coordinated regulation operation execution quantity refers to a set of candidate numerical sequences generated at equal intervals according to a preset step size, based on the duckweed coverage, fish load, and dissolved oxygen status in the water body at the current collection time, within the value range of each operation item execution quantity determined in step S5, under the current triggering critical transition level of duckweed. The candidate numerical sequence is generated as follows: For each operation item, candidate execution quantity values ​​are generated at equal intervals from the lower limit to the upper limit of the corresponding execution quantity value range, with a step size of 10% of the value range (the minimum precision is used if it is less than the minimum precision). At least five candidate execution quantity values ​​are generated. For example, when the water replenishment execution quantity value range is 0.10 to 0.30 and the step size is 0.04, six candidate water replenishment execution quantity values ​​are generated: 0.10, 0.14, 0.18, 0.22, 0.26, and 0.30. The candidate execution quantity values ​​of all operation items in the field coordinated regulation operation combination are combined using a Cartesian product to generate all candidate execution quantity combinations. Each candidate execution quantity combination is a vector containing the execution quantity values ​​of all operation items. The candidate execution quantity values ​​of each operation item in each candidate execution quantity combination are then sequentially assigned to the corresponding values ​​in the regression prediction model. , , , and Substitute the values ​​into the regression prediction model formula after fitting to calculate the expected dissolved oxygen value of the water body corresponding to the current candidate execution quantity combination. The expected dissolved oxygen value of the water body is retained to two decimal places and the unit is milligrams per liter.

[0129] The execution quantity value range is determined by selecting execution quantities from the candidate execution quantities that are expected to have dissolved oxygen in the water within the ecological gain state range. Specifically, the ecological gain state range refers to the range of dissolved oxygen in the water above the upper limit of the dissolved oxygen threshold obtained from the two-dimensional lookup table based on the rice plant growth stage corresponding to the current collection time. The lower limit of the ecological gain state range is the upper limit of the dissolved oxygen threshold, and the upper limit of the ecological gain state range is the saturated dissolved oxygen concentration in the water of the current rice-fish paddy field under the current temperature conditions. The saturated dissolved oxygen concentration is obtained from the pre-stored temperature and saturated dissolved oxygen comparison table based on the temperature field value corresponding to the current collection time. The temperature and saturated dissolved oxygen comparison table records the saturated dissolved oxygen concentration of pure water under standard atmospheric pressure for every 1 degree Celsius within the range of 0 degrees Celsius to 40 degrees Celsius, in milligrams per liter. For all candidate execution quantity combinations, determine whether the expected dissolved oxygen value is not lower than the upper limit of the dissolved oxygen threshold and not higher than the saturated dissolved oxygen concentration. Collect candidate execution quantity combinations that meet the above conditions into a valid candidate set. For the execution quantity values ​​of each operation item in the valid candidate set, calculate the minimum and maximum values ​​respectively. Use the minimum value as the lower limit of the execution quantity value interval and the maximum value as the upper limit of the execution quantity value interval to form the execution quantity value interval for each operation item. When the valid candidate set is empty (i.e., there are no candidate execution quantity combinations that make the expected dissolved oxygen value of the water body within the ecological gain state range), the execution quantity value interval is the execution quantity value corresponding to the candidate execution quantity combination with the highest expected dissolved oxygen value in the valid candidate set as a single point interval, and record this situation in the ecological aquaculture management data table for manual review.

[0130] The specific method of replacing the execution quantity value intervals corresponding to the same critical conversion level of duckweed in the operation priority table with execution quantity value intervals is as follows: using the current critical conversion level of duckweed as the search key, locate the corresponding row in the operation priority table, and replace the original value intervals in the duckweed harvesting execution quantity value interval column, water replenishment execution quantity value interval column, oxygenation execution quantity value interval column, feeding execution quantity value interval column, and fertilization execution quantity value interval column of the corresponding row in the operation priority table with the lower limit and upper limit of the execution quantity value interval of each operation item obtained from the effective candidate set. The replacement operation is performed in the overwrite write mode. After the replacement is completed, the execution quantity value interval columns of the corresponding row in the operation priority table are updated to the execution quantity value intervals derived by the regression prediction model. When the same critical conversion level of duckweed triggers step S5 again, the calculation of the execution quantity of each operation item in step S5 is based on the updated execution quantity value interval as the reference range, thereby realizing the continuous correction of the execution quantity value interval of the operation priority table by the regression prediction model, so that the determination of the execution quantity of field coordinated regulation operations gradually transitions from the initial setting based on historical experience to the quantitative prediction based on the fitting of measured data.

[0131] Example 2

[0132] The difference between Embodiment 2 and Embodiment 1 is that this embodiment introduces a rice-fish ecological farming management system.

[0133] Figure 2 A schematic diagram of the structure of a rice-fish ecological farming management system according to the present invention is provided. The rice-fish ecological farming management system includes:

[0134] Data collection and table creation module: Acquires rice plant growth period, red duckweed cover image, dissolved oxygen in water, fish load and meteorological data for the same rice-duckweed-fish field, and generates an ecological farming management data table according to the collection time;

[0135] Coverage recognition module: performs grid-based recognition on the duckweed coverage image to obtain the duckweed coverage rate and edge aggregation degree, and forms a coverage dissolved oxygen coupling sequence with the dissolved oxygen in the water body at the same acquisition time;

[0136] State discrimination module: Based on the coupled sequence of rice plant growth period and dissolved oxygen under cover, the threshold discrimination method is used to mark the ecological gain state, critical transition state and ecological stress state corresponding to the red duckweed cover state;

[0137] Trend grading module: When the coverage state of duckweed is in the critical transition state and the ecological stress state, the sliding difference method is used in combination with fish load and meteorological data to calculate the dissolved oxygen decline trend and generate the critical transition level of duckweed;

[0138] Operation control module: Based on the critical conversion level of duckweed, the operation priority table is called to determine the execution order and amount of field coordinated control operations;

[0139] Feedback Update Module: Writes the execution order and execution volume of field collaborative regulation operations into the ecological farming management data table, and updates the operation priority table based on the dissolved oxygen in the water and the coverage rate of red duckweed at the next collection time;

[0140] Interval Update Module: Based on the ecological farming management data table, a regression prediction model is established. When the same critical conversion level of duckweed occurs again, the regression prediction model is used to determine the range of execution quantity values ​​that will keep the expected dissolved oxygen in the water body within the ecological gain state range, and the operation priority table is updated.

[0141] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0142] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0143] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0144] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0145] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0146] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0147] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0148] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0149] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for the ecological farming and management of rice-fish, characterized in that, Includes the following steps: S1. Obtain rice plant growth period, red duckweed cover image, dissolved oxygen in water, fish load and meteorological data for the same rice-duckweed-fish field, and generate an ecological farming management data table according to the collection time. S2. Perform grid-based recognition on the duckweed-covered image to obtain the duckweed coverage rate and edge aggregation degree, and form a coverage dissolved oxygen coupling sequence with the dissolved oxygen in the water body at the same collection time. S3. Based on the coupled sequence of rice plant growth period and dissolved oxygen under cover, the threshold discrimination method is used to mark the ecological gain state, critical transition state and ecological stress state corresponding to the red duckweed cover state; S4. When the coverage state of Duckweed is in a critical transition state and an ecological stress state, the sliding difference method is used in combination with fish load and meteorological data to calculate the dissolved oxygen decline trend and generate the critical transition level of Duckweed. S5. Based on the critical conversion level of the red duckweed, call the operation priority table to determine the execution order and amount of field coordinated regulation operations; S6. Write the execution order and execution volume of field coordinated regulation operations into the ecological planting and breeding management data table, and update the operation priority table according to the dissolved oxygen in the water and the coverage rate of red duckweed at the next collection time. S7. Based on the ecological farming management data table, establish a regression prediction model. When the same critical conversion level of duckweed occurs again, use the regression prediction model to determine the range of execution values ​​that will keep the dissolved oxygen in the water body within the ecological gain range, and update the operation priority table.

2. The rice-fish ecological farming management method according to claim 1, characterized in that, S1, specifically: Using the same rice-duckweed-fish field as the data collection object, the rice plant growth period in the field management record was obtained according to the collection time, images of red duckweed coverage were obtained by fixed-point shooting, dissolved oxygen in the water was obtained by dissolved oxygen detection, fish load was obtained by stocking records and sampling weighing records, and meteorological data was obtained by meteorological records. The rice plant growth period, images of duckweed cover, dissolved oxygen in the water, fish load, and meteorological data were entered into the ecological farming management data table according to the collection time.

3. The rice-fish ecological farming management method according to claim 2, characterized in that, S2, specifically: Images of duckweed cover and dissolved oxygen in water collected at the same time were retrieved from the ecological farming management data table. The field boundaries in the duckweed cover images were used as the identification range. The identification range was divided into equal-area grids, and the duckweed grids and non-duckweed grids were marked according to the color characteristics of duckweed. The coverage rate of Hongping grid is obtained by statistically analyzing the proportion of Hongping grids among all grids. The edge clustering degree is obtained by calculating the proportion of the number of adjacencies between red-ping grids to the total number of adjacencies in the red-ping grid. The coverage rate of duckweed, the edge aggregation degree, and the dissolved oxygen in the water were used to form a coverage-dissolved oxygen coupling sequence according to the collection time.

4. The rice-fish ecological farming management method according to claim 3, characterized in that, S3, specifically: The growth period of rice plants was read from the ecological farming management data table, and the coverage rate, edge aggregation degree and dissolved oxygen of duckweed at the same collection time were read from the coverage dissolved oxygen coupling sequence. According to the rice plant growth period, the red duckweed coverage threshold, the edge aggregation threshold, and the dissolved oxygen threshold of the water body are matched; The coverage rate, edge aggregation degree, and dissolved oxygen in the water were compared with the corresponding thresholds, and the coverage status of duckweed was marked as ecological gain state, critical transition state, or ecological stress state.

5. The rice-fish ecological farming management method according to claim 4, characterized in that, S4, specifically: When the coverage status of duckweed is marked as a critical transitional state or an ecological stress state, fish load and meteorological data at the same collection time are read from the ecological farming management data table, and dissolved oxygen in water bodies at adjacent collection times is extracted from the coverage dissolved oxygen coupling sequence according to the collection time order. The sliding difference method was used to calculate the difference in dissolved oxygen in water between adjacent sampling times, and the decreasing trend of dissolved oxygen was determined by combining fish load and meteorological data. The critical conversion level of red duckweed is generated according to the decreasing trend of dissolved oxygen.

6. The rice-fish ecological farming management method according to claim 5, characterized in that, S5, specifically: Based on the critical conversion level of duckweed, the corresponding field coordinated regulation operation combination is retrieved from the operation priority table; the field coordinated regulation operation combination includes the operation content corresponding to the critical conversion level of duckweed among duckweed harvesting, watering, feeding, fertilization and oxygenation; The execution order of field coordinated regulation operations is determined according to the operation arrangement relationship recorded in the operation priority table, and the execution amount of field coordinated regulation operations is determined in combination with the coverage rate of duckweed, fish load and dissolved oxygen in the water.

7. The rice-fish ecological farming management method according to claim 6, characterized in that, S6, specifically: The execution sequence and amount of field coordinated regulation operations are entered into the ecological farming management data table according to the collection time; At the next acquisition time, dissolved oxygen and duckweed coverage in the water body were read from the coverage-dissolved oxygen coupling sequence. The dissolved oxygen in the water at the next sampling time was compared with that at the previous sampling time, and the coverage rate of duckweed at the next sampling time was compared with that at the previous sampling time. Based on the comparison results, adjust the job arrangement and execution range for jobs with the same critical conversion level in the job priority table.

8. The rice-fish ecological farming management method according to claim 7, characterized in that, S7, specifically: Extract the cumulative dissolved oxygen in the water, duckweed coverage, fish load, meteorological data, and the execution volume of field collaborative regulation operations from the ecological farming management data table for at least two collection periods; Using the amount of field coordinated regulation operations as the independent variable and dissolved oxygen in water as the dependent variable, a regression prediction model was obtained by fitting. When the same critical transition level of duckweed appears again, multiple candidate field coordinated regulation operation execution volumes are input into the regression prediction model to obtain the expected dissolved oxygen in the water body corresponding to each candidate execution volume. The execution quantities are selected from the candidate execution quantities to determine the range of execution quantities where the dissolved oxygen in the water body is expected to be within the range of ecological gain. Replace the execution value range corresponding to the same critical conversion level in the job priority table with the execution value range.

9. A rice-fish ecological farming management system, used to implement the rice-fish ecological farming management method according to any one of claims 1-8, characterized in that, include: Data collection and table creation module: Acquires rice plant growth period, red duckweed cover image, dissolved oxygen in water, fish load and meteorological data for the same rice-duckweed-fish field, and generates an ecological farming management data table according to the collection time; Coverage recognition module: performs grid-based recognition on the duckweed coverage image to obtain the duckweed coverage rate and edge aggregation degree, and forms a coverage dissolved oxygen coupling sequence with the dissolved oxygen in the water body at the same acquisition time; State discrimination module: Based on the coupled sequence of rice plant growth period and dissolved oxygen under cover, the threshold discrimination method is used to mark the ecological gain state, critical transition state and ecological stress state corresponding to the red duckweed cover state; Trend grading module: When the coverage state of duckweed is in the critical transition state and the ecological stress state, the sliding difference method is used in combination with fish load and meteorological data to calculate the dissolved oxygen decline trend and generate the critical transition level of duckweed; Operation control module: Based on the critical conversion level of duckweed, the operation priority table is called to determine the execution order and amount of field coordinated control operations; Feedback Update Module: Writes the execution order and execution volume of field collaborative regulation operations into the ecological farming management data table, and updates the operation priority table based on the dissolved oxygen in the water and the coverage rate of red duckweed at the next collection time; Interval Update Module: Based on the ecological farming management data table, a regression prediction model is established. When the same critical conversion level of duckweed occurs again, the regression prediction model is used to determine the range of execution quantity values ​​that will keep the expected dissolved oxygen in the water body within the ecological gain state range, and the operation priority table is updated.

Images