Water and fertilizer integrated feedback system based on environmental perception data fusion

Abstract

The invention discloses a water and fertilizer integrated feedback system based on environmental perception data fusion, relates to the technical field of water and fertilizer integrated feedback, and is used for solving the problems that the execution effect of a water and fertilizer regulation strategy is unstable and the soil structure is degraded. Collecting the soil surface reflection state of each region, calling soil conductivity data, analyzing the change trend, calculating a salinization risk coefficient, screening and marking a target region, obtaining the water hydrogen sulfide concentration and cyanobacteria cell density of the marked region, judging the water load risk, and setting a response period; executing an irrigation regulation or drainage optimization strategy in a period, collecting a current water and fertilizer irrigation ratio, obtaining a marked area soil expansion coefficient and an earth surface temperature difference, calculating soil water and fertilizer characteristics, correcting the water and fertilizer irrigation ratio to obtain an optimized ratio, and storing the optimized ratio in a water and fertilizer management database; the water and fertilizer utilization efficiency and the land environment protection level are improved through multi-dimensional environment sensing data feedback control.

Description

Technical Field

[0001] This invention relates to the field of integrated water and fertilizer feedback technology, and more specifically, to an integrated water and fertilizer feedback system based on the fusion of environmental perception data. Background Technology

[0002] Integrated water and fertilizer management technology combines irrigation and fertilization. Through the irrigation system, dissolved fertilizer is delivered evenly, appropriately, and at regular intervals to the crop root zone, achieving efficient use of water and nutrients. This technology can significantly improve water and fertilizer utilization, reduce resource waste, and lower the risk of non-point source pollution caused by excessive fertilization.

[0003] The existing technology has the following shortcomings:

[0004] Currently, existing integrated water and fertilizer control systems mostly rely on soil moisture sensor data or single water quality monitoring results to adjust the irrigation and fertilization ratio. However, under the interaction of factors such as soil salinization trend, water load risk, and temperature difference changes, the system response is often lagging or deviating from the actual needs, resulting in unstable implementation of water and fertilizer regulation strategies, soil structure deterioration, and aggravated water eutrophication. Therefore, an integrated water and fertilizer feedback system based on environmental perception data fusion is proposed.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a water and fertilizer integrated feedback system based on environmental perception data fusion, which solves the problems mentioned in the background art by employing multi-source environmental perception data fusion analysis, regional risk intelligent screening and labeling, and dynamic correction technology for water and fertilizer ratio.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a water and fertilizer integration feedback system based on environmental perception data fusion, comprising a salinity acquisition module, a screening and labeling module, a strategy response module, and a proportion correction module, the functions of each module being as follows:

[0008] The salinity acquisition module is used to divide the land to be tested into regions, collect the soil surface reflectance of each region, retrieve soil electrical conductivity data of each region through the water and fertilizer management database, and analyze the trend of soil electrical conductivity change.

[0009] The screening and labeling module is used to comprehensively consider the soil surface reflection state and the soil electrical conductivity change trend, calculate the salinization risk coefficient of each divided area, screen the divided areas for labeling, and obtain the hydrogen sulfide concentration and cyanobacterial cell density of the water in the labeled area.

[0010] The strategy response module is used to comprehensively consider the concentration of hydrogen sulfide in the water and the density of cyanobacteria cells to determine whether there is a risk of water load in the marked area, set a response period, and then execute irrigation regulation strategy or drainage optimization strategy within the response period based on the judgment results and collect the current water and fertilizer irrigation ratio.

[0011] The proportion correction module is used to obtain the soil swelling coefficient and surface temperature difference of the marked area, calculate the soil water and fertilizer characteristics, correct the current water and fertilizer irrigation proportion based on the soil water and fertilizer characteristics, obtain the optimized water and fertilizer proportion, and store it in the water and fertilizer management database.

[0012] In a preferred embodiment, in the salinity acquisition module, the land to be tested is divided into regions according to a preset grid area;

[0013] The intensity of soil surface reflection of incident light under illumination is obtained using environmental sensors to determine the soil surface reflection state of the divided areas.

[0014] The time window is preset and divided into multiple time periods. Soil electrical conductivity data for each area within each time period is retrieved from the water and fertilizer management database.

[0015] The average value of soil electrical conductivity data obtained in each time period for the divided area is obtained by averaging the data.

[0016] In a preferred embodiment, in the salinization acquisition module, the average conductivity values ​​of each time period are combined in chronological order to form a conductivity sequence.

[0017] The mean conductivity value of the sliding window length is selected sequentially in the conductivity sequence as the moving average value;

[0018] The trend of soil electrical conductivity change is obtained by subtracting the last value of the moving average from the first value.

[0019] The soil surface reflection state and soil electrical conductivity change trend are transmitted to the screening and labeling module.

[0020] In a preferred embodiment, in the screening and marking module, the soil surface reflection state and soil electrical conductivity variation trend are standardized and then the salinization risk coefficient of each divided area is calculated by a weighted algorithm.

[0021] If the salinization risk coefficient is greater than the preset risk coefficient threshold, the divided area will be marked.

[0022] Conversely, the region is not marked.

[0023] In a preferred embodiment, the hydrogen sulfide concentration and cyanobacterial cell density of the water in the marked area are obtained through a water and fertilizer management database in the screening and marking module.

[0024] The concentration of hydrogen sulfide in water is obtained by detecting the content of hydrogen sulfide molecules in water using an electrochemical sensor and stored in a water and fertilizer management database;

[0025] Trace samples were extracted from the water in the labeled area using flow cytometry. The average number of cells per milliliter was used as the cyanobacterial cell density and stored in the water and fertilizer management database.

[0026] The concentration of hydrogen sulfide in the water and the density of cyanobacteria cells are transmitted to the strategy response module.

[0027] In a preferred embodiment, in the strategy response module, the concentration of hydrogen sulfide in the water and the density of cyanobacteria cells are jointly modeled by a nonlinear fusion function to calculate the water load score.

[0028] The mean of the water load scores for all marked areas is calculated as the water load threshold.

[0029] If the water load score is greater than or equal to the water load threshold, the marked area is determined to have a water load risk.

[0030] If the water load score is less than the water load threshold, it is determined that there is no water load risk in the marked area.

[0031] In a preferred embodiment, the strategy response module sets a response period, which is the time period for executing different strategies;

[0032] If the assessment result indicates that there is a risk of water load in the marked area, then the drainage optimization strategy will be implemented.

[0033] If the assessment result indicates that there is no water load risk in the marked area, then the irrigation regulation strategy will be implemented;

[0034] Calculate the ratio of water resource volume to total water and fertilizer input volume, obtain the current water and fertilizer irrigation ratio, and transmit it to the ratio correction module.

[0035] In a preferred embodiment, the soil swelling coefficient and surface temperature difference of the corresponding marked area are obtained from the water and fertilizer management database in the proportion correction module.

[0036] The soil swelling coefficient is the rate of change in soil volume caused by a unit change in soil moisture content;

[0037] The surface temperature difference represents the difference between the surface temperature of the marked area and the reference temperature, which is the historical average surface temperature of the marked area for the same period.

[0038] In a preferred embodiment, the soil swelling coefficient and surface temperature difference are input into a feature function, and the soil water and fertilizer characteristics are output. The feature function is defined as follows: ;

[0039] in, Soil water and fertilizer characteristics, The soil swelling coefficient, For surface temperature difference, It is a natural constant. These are the preset fitting coefficients;

[0040] The product of the soil water and fertilizer characteristics multiplied by the preset correction coefficient and then added by 1, and the current water and fertilizer irrigation ratio, is taken as the water and fertilizer optimization ratio.

[0041] The optimized water and fertilizer ratio is stored in the water and fertilizer management database.

[0042] The technical effects and advantages of this invention are as follows:

[0043] This invention divides the land to be tested into regions, collects the soil surface reflection status of each region using environmental sensors, retrieves soil conductivity data from a water and fertilizer management database, analyzes the trend of soil conductivity changes, calculates the salinization risk coefficient of each region by combining soil surface reflection status and soil conductivity trends, screens and marks regions, obtains hydrogen sulfide concentration and cyanobacterial cell density in the marked regions to determine whether there is water load risk in the marked regions, sets a response period, and executes irrigation regulation strategies or drainage optimization strategies within the response period based on the judgment results. It then collects the current water and fertilizer irrigation ratio, obtains the soil swelling coefficient and surface temperature difference of the marked regions to calculate soil water and fertilizer characteristics, corrects the current water and fertilizer irrigation ratio based on the soil water and fertilizer characteristics, obtains the optimized water and fertilizer ratio, and stores it in the water and fertilizer management database. Based on intelligent feedback control using multi-dimensional environmental perception data, this invention improves water and fertilizer utilization efficiency and land environmental protection levels, reduces the risk of soil salinization and water eutrophication, and ensures the sustainability of agricultural production. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating the implementation of the integrated water and fertilizer feedback system based on environmental perception data fusion, as described in this invention.

[0045] Figure 2 This is a schematic diagram of the water and fertilizer integration feedback system based on environmental perception data fusion according to the present invention. Detailed Implementation

[0046] 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] This invention provides a water and fertilizer integration feedback system based on environmental perception data fusion, such as... Figures 1 to 2 As shown, it includes a salinization acquisition module, a screening and marking module, a strategy response module, and a proportion correction module. The functions of each module are as follows:

[0048] The salinity acquisition module is used to divide the land to be tested into regions. It collects the soil surface reflection status of each region through environmental sensors, retrieves soil conductivity data of each region through the water and fertilizer management database, analyzes the trend of soil conductivity change, and transmits the soil surface reflection status and soil conductivity change trend to the screening and labeling module.

[0049] The screening and labeling module is used to comprehensively consider the soil surface reflection state and the soil electrical conductivity change trend, calculate the salinization risk coefficient of each divided area, screen and label the divided areas according to the salinization risk coefficient, obtain the hydrogen sulfide concentration and cyanobacterial cell density of the water in the labeled area and transmit them to the strategy response module.

[0050] The strategy response module is used to comprehensively consider the hydrogen sulfide concentration and cyanobacterial cell density in the water body to determine whether there is a water load risk in the marked area. Based on the judgment result, a response period is set, and irrigation regulation strategy or drainage optimization strategy is executed within the response period. After the strategy is executed, the current water and fertilizer irrigation ratio is collected and transmitted to the ratio correction module.

[0051] The proportion correction module is used to receive the current water and fertilizer irrigation proportion, obtain the soil expansion coefficient and surface temperature difference of the marked area, calculate the soil water and fertilizer characteristics, correct the current water and fertilizer irrigation proportion according to the soil water and fertilizer characteristics, obtain the optimized water and fertilizer proportion, and store the optimized water and fertilizer proportion in the water and fertilizer management database.

[0052] The specific implementation is as follows:

[0053] In the salinization acquisition module, the land to be tested is divided into regions according to a preset grid area. Environmental sensors deployed in each region are used to conduct optical observations of the soil in the region and collect the surface reflection status of the soil in the region.

[0054] Soil surface reflectance refers to the intensity of soil surface reflection of incident light obtained by environmental sensors under illumination conditions, reflecting the salt deposition status of the soil surface.

[0055] It should be explained that the environmental sensor is a soil surface observation device installed in each divided area. It has automatic illumination compensation and acquisition angle correction functions to reduce the impact of ambient light changes on the data and can convert the acquired optical signal into reflection intensity. The preset grid area refers to a single divided area set according to the monitoring accuracy requirements and sensor deployment density when dividing the land to be measured. For example, when the land to be measured is 10 hectares, the land can be divided into divided areas with a side length of 10 meters, and each divided area is 100 square meters.

[0056] A preset time window is divided into multiple time periods. Soil electrical conductivity data for each region within each time period is retrieved from the water and fertilizer management database. Soil electrical conductivity data is used to reflect the total concentration of dissolved salt ions in the soil solution. The higher the value, the greater the soil salinity.

[0057] The average value of soil electrical conductivity data obtained in each time period for the divided area is taken to obtain the average electrical conductivity value for the corresponding time period. The average electrical conductivity values ​​of each time period are combined in chronological order to form an electrical conductivity sequence.

[0058] The conductivity sequence is processed by moving average by setting a sliding window length. The mean conductivity of the sliding window length is selected in the conductivity sequence as the moving average value. The difference between the last value and the first value of the moving average value is used to obtain the trend of soil conductivity change.

[0059] The trend of soil electrical conductivity change is obtained by subtracting the last value of the moving average from the first value, which preserves the overall direction and magnitude of change while reducing the interference of short-term fluctuations.

[0060] If the change trend of electrical conductivity is greater than 0, it indicates that the soil electrical conductivity data is on an upward trend, indicating that the soil salinity is accumulating. If the change trend of electrical conductivity is less than 0, it indicates that the soil electrical conductivity data is on a downward trend, indicating that the soil surface salinity is being diluted.

[0061] It needs to be explained that the water and fertilizer management database refers to a structured information system specifically used to store, manage, and maintain various environmental data, monitoring data, and management parameters related to farmland water and fertilizer management. The data covers multiple dimensions, including but not limited to soil electrical conductivity, soil surface reflectance, soil expansion coefficient, surface temperature difference, hydrogen sulfide concentration in water bodies, cyanobacterial cell density, and the proportion of water and fertilizer irrigation. It comes from real-time data collected by environmental sensors and historical monitoring records. The preset time window refers to the continuous time range used to analyze the trend of soil electrical conductivity changes. Its length can be determined according to the irrigation cycle or monitoring accuracy requirements. For example, it can be set to the last 30 days, dividing the time window into multiple consecutive time periods, such as dividing 30 days into 10 consecutive 3-day time periods. The preset sliding window length is the number of time periods participating in a single moving average processing. For example, when the sliding window length is 3, it means that the average conductivity of 3 adjacent time periods is taken each time to calculate the moving average.

[0062] The soil surface reflection state and soil electrical conductivity change trend are transmitted to the screening and labeling module.

[0063] In the screening and labeling module, after standardizing the soil surface reflectance and soil electrical conductivity trends, a weighted algorithm is used to calculate the salinization risk coefficient for each zone. The formula for calculating the salinization risk coefficient is as follows: , This refers to the saltification risk factor. This is the standardized value of the soil surface reflectance. The value is the standardized value after considering the trend of soil electrical conductivity changes. , These are the preset weighting coefficients.

[0064] The salting risk coefficient is compared with a preset risk coefficient threshold to filter, divide, and mark the regions:

[0065] If the salinization risk coefficient is greater than the risk coefficient threshold, the divided area is marked.

[0066] Conversely, the region is not marked.

[0067] It should be explained that the standardization methods include, but are not limited to, standard linear transformation based on interval scaling, statistical Z-score standardization, or normalization based on nonlinear mapping functions. The specific methods used for standardization will not be elaborated upon here. The preset weighting coefficients, used to reflect the contribution of soil surface reflectance and soil conductivity trends, can be set using historical monitoring data or expert experience. For example, The value is set to 0.4. The value is set to 0.6; the preset risk coefficient threshold is the judgment boundary value when classifying and marking the salinization risk coefficient of each divided area. The threshold can be set based on statistical distribution characteristics. For example, the 75th percentile of the historical salinization risk coefficient distribution can be taken as the risk coefficient threshold.

[0068] In the screening and labeling module, the concentration of hydrogen sulfide and the density of cyanobacteria cells in the water body of the labeled area are obtained through the water and fertilizer management database;

[0069] The concentration of hydrogen sulfide in water is detected by an electrochemical sensor. The electrochemical sensor is based on the principle of electrode reaction. It uses the current signal generated by the oxidation-reduction reaction of hydrogen sulfide on the surface of the working electrode to calculate the concentration of hydrogen sulfide in water and store it in the water and fertilizer management database.

[0070] Cyanobacterial cell density was determined by extracting trace samples from the water body in the labeled area using flow cytometry. The samples were then rapidly counted using laser scattering and fluorescence labeling techniques. The average number of cells per milliliter was used as the cyanobacterial cell density and stored in the water and fertilizer management database.

[0071] It should be noted that an electrochemical sensor is an analytical instrument based on the principle of electrochemical reaction, used to detect the concentration of specific chemical substances; the electrode reaction principle refers to the redox reaction process that occurs on the surface of the working electrode in an electrochemical sensor; a flow cytometer is a high-throughput cell analysis device that uses fluid dynamics to arrange cells individually and irradiate them with a laser beam; laser scattering technology refers to the technique of obtaining cell size and structural characteristics based on the scattering angle and intensity information by irradiating flowing cells with a laser; fluorescent labeling technology uses fluorescent proteins to label target cells, which emit fluorescent signals of specific wavelengths after laser excitation, helping to distinguish different cell types.

[0072] The concentration of hydrogen sulfide in the water and the density of cyanobacteria cells are transmitted to the strategy response module.

[0073] The strategy response module receives the concentration of hydrogen sulfide in the water and the density of cyanobacteria cells transmitted from the screening and labeling module.

[0074] A nonlinear fusion function is used to jointly model the hydrogen sulfide concentration and cyanobacterial cell density in the water body, and to calculate the water body load score. The nonlinear fusion function adopts the form of a bivariate logistic function and is defined as follows:

[0075] ;

[0076] in, The water body load score has a range of values. The closer the value is to 1, the higher the risk. The concentration of hydrogen sulfide in the water of the marked area; The density of cyanobacterial cells in the marked area; and These are environmental safety reference benchmarks, representing the normal environmental levels of hydrogen sulfide concentration and cyanobacterial cell density in the water body, respectively. The coefficients of the fusion function were obtained by fitting historical data and environmental characteristics using a nonlinear least squares method, and satisfy the following conditions: It is used to characterize the nonlinear impact and cross-coupling effect of indicator changes on risk;

[0077] It should be noted that the logistic function is a monotonic nonlinear function that smoothly maps any real number input to a range between 0 and 1. In this embodiment, it is used to fuse and map the hydrogen sulfide concentration and cyanobacterial cell density in the water body into a water load score. The nonlinear least squares method is a numerical optimization method used to minimize the sum of squared residuals in the parameter estimation of a nonlinear model, which will not be elaborated here.

[0078] The mean water load score of all marked areas is calculated as the water load threshold, and the water load score of each marked area is compared with the water load threshold.

[0079] If the water load score is greater than or equal to the water load threshold, the marked area is determined to have a water load risk.

[0080] If the water load score is less than the water load threshold, it is determined that there is no water load risk in the marked area.

[0081] Set the response period, which is the time period for executing different strategies, and set it according to the agricultural irrigation cycle;

[0082] In the strategy response module, different strategies are executed based on the water load risk determination results within the response period. If the above determination results indicate that there is a water load risk in the marked area, the drainage optimization strategy is executed. The drainage optimization strategy discharges part of the water in the marked area by controlling the drainage channel and drainage duration, thereby reducing the overall pollutant concentration and eutrophication level of the water body, inhibiting the growth of cyanobacteria and the accumulation of harmful gases, and improving the water environment quality.

[0083] If the assessment result indicates that there is no water load risk in the marked area, an irrigation control strategy is implemented. This strategy increases the input of clean water to replenish the water body in the marked area, thereby increasing the total water volume and diluting the concentration of pollutants. In other words, by adding water to dilute the water, the potential content of harmful substances in the local water body is reduced, improving water resource utilization efficiency and avoiding resource waste and secondary environmental risks caused by excessive fertilization or over-irrigation.

[0084] After the strategy is implemented, the current water and fertilizer irrigation ratio in the marked area is collected. The current water and fertilizer irrigation ratio is the ratio of water resource volume to the total water and fertilizer input volume. The specific calculation formula is as follows:

[0085] ;

[0086] in, The current proportion of water and fertilizer irrigation, For the volume of water resources input, The current water-fertilizer irrigation ratio reflects the current proportion of water and fertilizer irrigation, representing the volume of fertilizer applied.

[0087] The current water and fertilizer irrigation ratio is transmitted to the ratio correction module for subsequent optimization of the water and fertilizer irrigation ratio based on soil water and fertilizer characteristics.

[0088] In the proportion correction module, the current water and fertilizer irrigation proportion of the marked area is received, and the soil expansion coefficient and surface temperature difference of the corresponding marked area are obtained through the water and fertilizer management database.

[0089] The soil swelling coefficient represents the soil's ability to expand in volume under the influence of changes in moisture, that is, the rate of change in soil volume caused by a unit change in soil moisture content. By deploying soil moisture sensors and soil swelling meters in the marked area for a long period of time, the soil moisture content and corresponding volume values ​​are recorded at different time periods. The difference between the corresponding volume values ​​during the change in soil moisture content is divided by the product of the initial soil volume and the soil moisture content per unit volume to obtain the soil swelling coefficient, which is then stored in the water and fertilizer management database.

[0090] The surface temperature difference represents the difference between the surface temperature of the marked area and the reference temperature, which is the historical average surface temperature of the marked area for the same period. The surface temperature is collected in real time by a surface temperature sensor and recorded in the water and fertilizer management database.

[0091] It should be noted that a soil moisture sensor is a detection device used to measure the volumetric water content of soil at a specific depth. It achieves real-time monitoring of moisture content by determining the relationship between the soil dielectric constant and water content. A soil dilatometer is a displacement monitoring device used to measure changes in soil volume. An internal measuring probe is inserted into the soil layer to be measured. When the soil expands due to water absorption or shrinks due to water loss, the position of the measuring probe changes accordingly. The mechanical displacement is converted into an electrical signal, and the corresponding volume change value is calculated. A surface temperature sensor is a measuring device used to detect surface temperature. It achieves real-time monitoring of soil or surface cover temperature based on infrared thermometry technology.

[0092] The soil swelling coefficient and surface temperature difference are input into a feature function, which outputs soil water and fertilizer characteristics. The feature function is defined as follows:

[0093] ;

[0094] in, Soil water and fertilizer characteristics, The soil swelling coefficient, For surface temperature difference, It is a natural constant. The fitting coefficients are obtained from historical data using the nonlinear least squares method; Describe the saturated relationship between soil swelling coefficient and water retention capacity; Characterizing the attenuation effect of surface temperature difference on soil fertility retention capacity; This reflects the impact of the interaction between soil swelling coefficient and surface temperature difference on water and fertilizer balance.

[0095] The current water and fertilizer irrigation ratio is adjusted based on soil water and fertilizer characteristics, and the optimal water and fertilizer ratio is calculated using the following formula:

[0096] ;

[0097] in, To optimize the water-to-fertilizer ratio, The current proportion of water and fertilizer irrigation, Soil water and fertilizer characteristics, The correction coefficient is determined by fitting the optimal irrigation effect in historical operating data. If the soil water and fertilizer characteristics are positive, it means that the soil has a higher water absorption capacity under the current conditions, and the proportion of water should be increased; if the soil water and fertilizer characteristics are negative, it means that the soil has a relatively higher demand for fertilizer, and the proportion of water should be reduced.

[0098] The calculated optimal water and fertilizer ratio is stored in the water and fertilizer management database for subsequent irrigation decisions and long-term operation optimization, realizing dynamic adjustment of the water and fertilizer ratio based on soil characteristics and environmental conditions.

[0099] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0100] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0101] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0102] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0103] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A water and fertilizer integrated feedback system based on environmental perception data fusion, characterized in that: It includes a salinization acquisition module, a screening and marking module, a strategy response module, and a proportion correction module. The functions of each module are as follows: The salinity acquisition module is used to divide the land to be tested into regions, collect the soil surface reflectance of each region, retrieve soil electrical conductivity data of each region through the water and fertilizer management database, and analyze the trend of soil electrical conductivity change. The screening and labeling module is used to comprehensively consider the soil surface reflection state and the soil electrical conductivity change trend, calculate the salinization risk coefficient of each divided area, screen the divided areas for labeling, and obtain the hydrogen sulfide concentration and cyanobacterial cell density of the water in the labeled area. The strategy response module is used to comprehensively consider the concentration of hydrogen sulfide in the water and the density of cyanobacteria cells to determine whether there is a risk of water load in the marked area, set a response period, and then execute irrigation regulation strategy or drainage optimization strategy within the response period based on the judgment results and collect the current water and fertilizer irrigation ratio. The proportion correction module is used to obtain the soil swelling coefficient and surface temperature difference of the marked area, calculate the soil water and fertilizer characteristics, correct the current water and fertilizer irrigation proportion based on the soil water and fertilizer characteristics, obtain the optimized water and fertilizer proportion, and store it in the water and fertilizer management database.

2. The water and fertilizer integrated feedback system based on environmental perception data fusion according to claim 1, characterized in that: In the salinity acquisition module, the land to be tested is divided into regions according to the preset grid area; The intensity of soil surface reflection of incident light under illumination is obtained using environmental sensors to determine the soil surface reflection state of the divided areas. The time window is preset and divided into multiple time periods. Soil electrical conductivity data for each area within each time period is retrieved from the water and fertilizer management database. The average value of soil electrical conductivity data obtained in each time period for the divided area is obtained by averaging the data.

3. The water and fertilizer integrated feedback system based on environmental perception data fusion according to claim 2, characterized in that: In the salinization acquisition module, the average conductivity values ​​of each time period are combined in chronological order to form a conductivity sequence; The mean conductivity value of the sliding window length is selected sequentially in the conductivity sequence as the moving average value; The trend of soil electrical conductivity change is obtained by subtracting the last value of the moving average from the first value. The soil surface reflection state and soil electrical conductivity change trend are transmitted to the screening and labeling module.

4. The water and fertilizer integrated feedback system based on environmental perception data fusion according to claim 1, characterized in that: In the screening and labeling module, the soil surface reflection state and soil electrical conductivity variation trend are standardized and then the salinization risk coefficient of each division area is calculated by weighted algorithm. If the salinization risk coefficient is greater than the preset risk coefficient threshold, the divided area will be marked. Conversely, the region is not marked.

5. The water and fertilizer integrated feedback system based on environmental perception data fusion according to claim 1, characterized in that: In the screening and labeling module, the concentration of hydrogen sulfide and the density of cyanobacteria cells in the water body of the labeled area are obtained through the water and fertilizer management database; The concentration of hydrogen sulfide in water is obtained by detecting the content of hydrogen sulfide molecules in water using an electrochemical sensor and stored in a water and fertilizer management database; Trace samples were extracted from the water in the labeled area using flow cytometry. The average number of cells per milliliter was used as the cyanobacterial cell density and stored in the water and fertilizer management database. The concentration of hydrogen sulfide in the water and the density of cyanobacteria cells are transmitted to the strategy response module.

6. The water and fertilizer integrated feedback system based on environmental perception data fusion according to claim 1, characterized in that: In the strategy response module, the concentration of hydrogen sulfide in the water and the density of cyanobacteria cells are jointly modeled by a nonlinear fusion function to calculate the water load score. The mean of the water load scores for all marked areas is calculated as the water load threshold. If the water load score is greater than or equal to the water load threshold, the marked area is determined to have a water load risk. If the water load score is less than the water load threshold, it is determined that there is no water load risk in the marked area.

7. The water and fertilizer integrated feedback system based on environmental perception data fusion according to claim 1, characterized in that: In the strategy response module, set the response period, which is the time period for executing different strategies; If the assessment result indicates that there is a risk of water load in the marked area, then the drainage optimization strategy will be implemented. If the assessment result indicates that there is no water load risk in the marked area, then the irrigation regulation strategy will be implemented; Calculate the ratio of water resource volume to total water and fertilizer input volume, obtain the current water and fertilizer irrigation ratio, and transmit it to the ratio correction module.

8. The water and fertilizer integrated feedback system based on environmental perception data fusion according to claim 1, characterized in that: In the proportion correction module, the soil swelling coefficient and surface temperature difference of the corresponding marked area are obtained through the water and fertilizer management database; The soil swelling coefficient is the rate of change in soil volume caused by a unit change in soil moisture content; The surface temperature difference represents the difference between the surface temperature of the marked area and the reference temperature, which is the historical average surface temperature of the marked area for the same period.

9. The water and fertilizer integrated feedback system based on environmental perception data fusion according to claim 8, characterized in that: The soil swelling coefficient and surface temperature difference are input into the feature function, and the soil water and fertilizer characteristics are output. The characteristic function is defined as ; in, Soil water and fertilizer characteristics, The soil swelling coefficient, For surface temperature difference, It is a natural constant. These are the preset fitting coefficients; The product of the soil water and fertilizer characteristics multiplied by the preset correction coefficient and then added by 1, and the current water and fertilizer irrigation ratio, is taken as the water and fertilizer optimization ratio. The optimized water and fertilizer ratio is stored in the water and fertilizer management database.

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