A precise water-saving irrigation method for leafy vegetables and root crops

Abstract

The present invention discloses a precise water-saving irrigation method for leafy vegetables and root crops, which relates to the technical field of precise crop irrigation. An environmental anomaly degree is generated from the obtained monitoring data. If it exceeds the environmental anomaly threshold, predictions are made on the planting conditions and crop water requirement rules data. Irrigation characteristics are extracted from the obtained prediction data, and the irrigation scheme library matches a corresponding water-saving irrigation system for the crop planting area according to the irrigation characteristics. A crop water-saving irrigation digital twin model is used to test the water-saving irrigation scheme. A feasibility is constructed from the obtained test data, and the feasibility of the irrigation scheme is verified based on the feasibility. Corresponding response measures are taken according to the verification results. A drainage anomaly degree is constructed from the obtained drainage state data. If the drainage anomaly degree exceeds the expectation, drainage emergency treatment is carried out in the crop planting area. Due to the differences in water requirement characteristics and growth periods of different crops, a water-saving and high-yield irrigation system is provided for the refined management of various crops.

Description

Technical Field

[0001] The present invention relates to the technical field of precise irrigation for crops, and particularly to a precise water-saving irrigation method for leafy vegetables and root vegetables. Background Art

[0002] Leafy vegetables and root vegetables are two major categories of vegetables, each with its own characteristics in growth habits, edible parts, and nutritional values. Leafy vegetables mainly use young leaves or leaf stalks as the edible parts. Common leafy vegetables include spinach, rape, pakchoi, lettuce, and crown daisy. These vegetables are rich in chlorophyll, vitamin C, vitamin K, and various minerals, and are important sources of vitamins and minerals in the diet. They usually prefer a moist soil environment, have a short growth cycle, rapid changes in different growth stages, and different water requirements. The irrigation amount in different growth periods has a great impact on the quality of the final harvest. During the growth process, they need sufficient light and appropriate moisture to ensure the tenderness of the leaves and the richness of nutrients. Root vegetables mainly use thickened fleshy roots or stems as the edible parts, such as carrots and white radishes. These vegetables are rich in dietary fiber, vitamin C, potassium and other nutrients, which help to promote intestinal peristalsis and maintain heart health. Root vegetables usually have strong drought resistance, but they also need appropriate amounts of water and nutrients during the growth process to support the growth and development of their roots. Excessive or insufficient irrigation water will cause fruit cracking, mildew or hollowness. At the same time, they have high requirements for the soil and need a loose, fertile and well-drained soil environment.

[0003] Precise irrigation of leafy vegetables and root vegetables needs to be carried out according to the growth characteristics and requirements of the crops. For leafy vegetables such as lettuce and Chinese cabbage, drip irrigation, micro-spraying belts or inverted micro-spraying are usually used to ensure uniform water supply to the vicinity of the roots, while keeping the soil moist but not overly wet to promote tender leaves and high yields; when irrigating, the principle of "less but frequent" should be followed, and the irrigation amount and frequency should be adjusted according to the growth stage and weather changes. For root vegetables such as carrots and white radishes, the soil humidity should be ensured to be appropriate during irrigation, which not only meets the growth needs of the roots but also avoids the occurrence of diseases caused by excessive water; drip irrigation or sub-surface irrigation is preferred for irrigation methods to reduce the risk of water evaporation and disease transmission.

[0004] In the Chinese invention patent with the authorization announcement number CN105494033B, an intelligent water-saving irrigation method based on crop requirements is disclosed. The method includes the following steps: First, according to the type of cultivated crops, determine the mechanism parameters r and Sp of the internal growth and development of the crops; Second, construct a growth model for the growth cycle i of the crops, and quantitatively determine the biomass yield of the crops in different growth cycles according to the mechanism parameters of the internal growth and development of the crops; Third, construct a water demand model for the growth cycle i of the crops, and calculate the water demand of the crops in different growth cycles according to the crop biomass yield obtained in the second step and the soil water content data obtained by the environmental monitoring equipment; Fourth, according to the water demand of the crops obtained in the third step, formulate an irrigation plan for the entire life cycle of the crops.

[0005] Combined with the above application and the content in the prior art:

[0006] When irrigation is required in the planting area, in order to save labor costs during irrigation and achieve precise irrigation, an intelligent irrigation and drainage system is usually installed in the crop planting area. When there is no rain for a long time or continuous rainfall in the area where the planting area is located, through automatic control, irrigation or drainage is carried out on the planting area to ensure that environmental conditions such as soil water content and air humidity in the planting area can meet the growth of leafy vegetables and root vegetables.

[0007] Existing intelligent irrigation and drainage systems usually collect various planting environment data based on a sensor network, and judge whether irrigation is needed by the collected data. If irrigation is needed, the irrigation process is launched. However, when the environmental conditions in the crop planting area, such as soil humidity and air humidity, change frequently, due to the inability to accurately obtain the actual irrigation demand, it is easy to cause a certain degree of waste of water resources when controlling the irrigation and drainage system, and thus affect the growth of crops in the planting area to a certain extent.

[0008] Therefore, the present invention provides a precise water-saving irrigation method for leafy vegetables and root vegetables. Summary of the Invention

[0009] (I) Technical problems to be solved

[0010] In view of the deficiencies of the prior art, the present invention provides a precise water-saving irrigation method for leafy vegetables and root crops. By predicting based on planting conditions and crop water requirement rules data, irrigation characteristics are extracted from the obtained prediction data, and the irrigation plan library matches corresponding water-saving irrigation plans for the crop planting areas according to the irrigation characteristics. The crop water-saving irrigation digital twin model is used to test the water-saving irrigation plan, a feasibility degree is constructed from the obtained test data, the feasibility of the irrigation plan is verified by the feasibility degree, and corresponding countermeasures are taken according to the verification results. A drainage abnormality degree is constructed from the obtained drainage state data. If the drainage abnormality degree exceeds the expectation, drainage emergency treatment is carried out in the crop planting area. Considering the differences in water requirement characteristics and growth periods of different crops, personalized irrigation plans are provided for the refined management of various crops, thus solving the technical problems recorded in the background art.

[0011] Through long-term cumulative experiments, this method observes the growth rules, water requirement rules of crops at different growth stages during planting in different seasons, and the planned wetting layer of irrigation, reasonably controls irrigation, constructs a mathematical model of crop water requirement, scientifically analyzes the water-saving potential, and thus formulates a relatively water-saving irrigation system. It can be used for precise water-saving irrigation in field and facility agricultural planting areas, provides technical support for the automatic switch control of intelligent agricultural irrigation equipment and irrigation water use, and achieves the goal of maximizing water use efficiency and ensuring water-saving and high-yield.

[0012] (2) Technical solution

[0013] To achieve the above objectives, the present invention is realized through the following technical solutions: A precise water-saving irrigation method for leafy vegetables and root crops, including monitoring the meteorological and soil environmental conditions in the crop planting area by the arranged sensor network, and generating corresponding environmental abnormality degrees from the obtained monitoring data , if the environmental abnormality degree exceeds the environmental abnormality threshold, a prediction instruction is sent to the outside; among them, the environmental data collected by the sensor network in the crop planting area, including soil humidity, rainfall, air temperature and humidity, are summarized to construct a planting environment data set;

[0014] Using the trained planting area environment prediction model to predict the planting conditions and crop water requirement rules data, extracting irrigation characteristics from the prediction data, and the irrigation plan library matches corresponding water-saving irrigation plans for the crop planting area according to the irrigation characteristics;

[0015] Using the crop water-saving irrigation digital twin model to test the water-saving irrigation plan, constructing a feasibility degree from the obtained test data , by the feasibility degree verifying the feasibility of the irrigation plan, and taking corresponding countermeasures according to the verification results;

[0016] Select monitoring points within the coverage area of the drainage system, monitor the drainage status data in the planting area at the monitoring points, and construct the drainage abnormality degree from the obtained drainage status data If the drainage abnormality degree exceeds the expectation, perform drainage emergency treatment in the crop planting area;

[0017] Query the feedback data after implementing the water-saving irrigation plan within the feedback period, and generate the satisfaction coefficient for implementing the water-saving irrigation task in the planting area from the feedback data If the satisfaction coefficient is lower than the expectation, send an inspection instruction to the outside, and orderly overhaul and maintain the irrigation system and related equipment in the planting area.

[0018] Furthermore, generate the environmental abnormality degree from the planting environment data set Among them, perform linear normalization processing on the soil humidity and the air humidity and map the corresponding data values to the interval as follows:

[0019]

[0020] Among them, , is the total number of data acquisition sub-cycles, and the weight coefficient: , , and ; is the soil humidity in the i-th data acquisition sub-cycle, is the corresponding soil humidity reference target value, is the air humidity in the i-th data acquisition sub-cycle, is the corresponding air humidity reference target value.

[0021] Furthermore, after receiving the alarm instruction, obtain the corresponding prediction data from the trained planting area environment prediction model, and summarize and construct the environmental prediction data set; extract the features of the obtained prediction data and the current crop growth status, obtain the corresponding irrigation features, obtain several water-saving irrigation plans, and summarize and pre-construct the irrigation plan library;

[0022] According to the correspondence between the irrigation features and the irrigation plans, match the corresponding water-saving irrigation plan for the crop planting area from the irrigation plan library, and send a test instruction to the outside.

[0023] Further, after receiving the test instruction, train to obtain the digital twin model for crop water-saving irrigation, use the digital twin model for crop water-saving irrigation to test the water-saving irrigation plan and obtain test data, and summarize the test data to construct the corresponding test data set; construct the corresponding feasibility from the test data set , if the obtained feasibility exceeds the feasibility threshold, send an execution instruction to the outside; if the feasibility does not exceed the feasibility threshold, send an optimization instruction to the outside.

[0024] Further, after linearly normalizing the water infiltration rate and the surface runoff , map the corresponding data values to the interval and construct the feasibility according to the following formula:

[0025]

[0026] Weight coefficient, , , and , is the average value of the water infiltration rate in the sub-region, is the reference target value of the water infiltration rate; is the average value of the surface runoff in the sub-region, is the reference target value of the surface runoff.

[0027] Further, install an irrigation system in the crop planting area. After receiving the execution instruction, the irrigation system executes the output water-saving irrigation plan. After executing the water-saving irrigation plan, send an observation instruction to the outside;

[0028] Select several non-adjacent monitoring points in the coverage area of the drainage system, monitor the working status of the drainage system in real time at the monitoring points, obtain the real-time drainage status data, summarize it and construct the drainage status data set, and construct the drainage abnormality from the drainage status data in the drainage status data set .

[0029] Further, after linearly normalizing the groundwater level and the ponding water level , map the corresponding data values to the interval and then construct the drainage abnormality according to the following formula:

[0030]

[0031] Among them, , is the number of monitoring points; weight coefficient: , and ; is the groundwater level of the i-th monitoring point, is the reference target value of the groundwater level; is the ponding water level of the monitoring point, is the reference target value of the ponding water level.

[0032] Furthermore, during the feedback period, the feedback data after implementing the irrigation plan is queried, and the improvement degree is constructed from the feedback data after each implementation of the irrigation plan , where the biological accumulation and the water use efficiency are linearly normalized, and the corresponding data values are mapped to the interval according to the following formula:

[0033]

[0034] weight coefficient, , .

[0035] Furthermore, after continuously obtaining several improvement degrees , the satisfaction coefficient during the feedback period when implementing the irrigation plan in the planting area is analyzed and obtained. If the satisfaction coefficient is lower than the satisfaction threshold, an inspection instruction is sent to the outside; the construction method of the satisfaction coefficient is as follows:

[0036]

[0037] where n, n is the number of irrigation times during the feedback period, is the improvement degree after the i-th implementation of the irrigation plan, is the average value of the improvement degrees, weight coefficient: , , and .

[0038] Furthermore, an electronic map covering the crop planting area is constructed, and the irrigation system, drainage system, and sensor network are marked on the electronic map; after receiving the inspection instruction, the sensor network, irrigation system, and drainage system are inspected within the preset inspection period. If there are operating faults, the locations with faults are marked on the electronic map;

[0039] Combined with the fault location data, path planning is performed on the electronic map by the path planning algorithm, and the obtained path is used as the maintenance path and marked on the electronic map.

[0040] (III) Beneficial effects

[0041] The present invention provides a precise water-saving irrigation method for leafy vegetables and root crops, having the following beneficial effects:

[0042] 1. Construct an environmental anomaly degree based on the fluctuations of various environmental conditions , determine whether there is an anomaly in the environmental conditions in the planting area, and be able to promptly handle the anomaly when it exists, ensuring the normal growth of leafy vegetables and root crops in the planting area.

[0043] 2. Predict various environmental data in the planting area by the planting area environmental prediction model, determine whether there is an anomaly in the next environmental condition data, and if there is an anomaly, be able to promptly send an alarm to the outside; taking the growth state of the crop and the determined irrigation demand standard as a reference, quickly match a water-saving irrigation plan, which can save the formulation time of the water-saving irrigation plan.

[0044] 3. Use the trained digital twin model of crop water-saving irrigation to test the water-saving irrigation plan, construct a corresponding feasibility based on the test data , and evaluate the effectiveness of the water-saving irrigation plan based on the feasibility . If it is effective, it can be directly implemented. If the effectiveness is insufficient, the water-saving irrigation plan can be optimized, which can ensure the reliability of the constructed water-saving irrigation plan.

[0045] 4. Control and respond to the irrigation system in the planting area, play a role in water saving while meeting the expected irrigation effect, and facilitate timely adjustment of the current irrigation effect.

[0046] 5. Through the calculation and analysis combining the water balance formula and the Penman formula, determine the irrigation critical value at different growth stages, determine the wetting layer depth according to the root distribution during the crop growth period, ensure the effectiveness of water absorption, reduce water resource waste, formulate the irrigation cycle and wetting layer depth according to the requirements of different growth periods, improve the water resource utilization efficiency in agricultural production, and achieve the dual effects of water saving and yield increase; provide personalized irrigation plans for the water demand characteristics and growth period differences of different crops, realize the refined management of various crops, and improve the quality and yield of crops.

[0047] 6. Judge whether there is an anomaly in the drainage state in the planting area based on the drainage anomaly degree . If there is an anomaly, send an alarm instruction to the outside and make emergency treatment for the current drainage state, gradually normalize the drainage state, prevent rainwater accumulation, and avoid negative impacts on the planting in the planting area caused by excessive rainfall.

[0048] 7. According to the improvement degree Evaluate the irrigation effect for each irrigation execution; based on the improvement degree Construct the corresponding satisfaction coefficient , evaluate the irrigation effect. If the irrigation effect fails to meet the expectation, the current irrigation plan or irrigation plan can be adjusted in a timely manner, judge whether there are faults in the irrigation system, etc., and verify the availability of the irrigation system.

[0049] 8. After detecting faults in the irrigation system, drainage system and sensor network and obtaining the corresponding fault locations, the path planning algorithm outputs the corresponding maintenance path. When maintaining and repairing each fault in turn according to the maintenance path, the efficiency of maintenance and repair can be improved, and the irrigation effect in the planting area can be guaranteed during the irrigation of the planting area. Brief Description of the Drawings

[0050] Figure 1 It is a schematic structural diagram of the precise water-saving irrigation method for leafy vegetables and root vegetables of the present invention. Detailed Embodiment

[0051] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0052] Please refer to Figure 1 , the present invention provides a precise water-saving irrigation method for leafy vegetables and root vegetables, including

[0053] Step 1. The deployed sensor network monitors the environmental conditions in the crop planting area, and generates the corresponding environmental abnormality degree from the obtained monitoring data , if the environmental abnormality degree exceeds the environmental abnormality threshold, send a prediction instruction to the outside;

[0054] The content of the above Step 1 includes:

[0055] Step 101. Deploy a sensor network in the crop planting area, including soil moisture sensors, temperature sensors, humidity sensors, rain gauges, etc., ensure that the sensor network covers all key areas, and use the environmental data collected by the sensor network in the crop planting area. The environmental data includes at least soil moisture, rainfall, air temperature and humidity, and summarize the collected environmental data to construct a planting environment data set;

[0056] Step 102. Generate the corresponding environmental abnormality degree from the planting environment data set , wherein, for soil humidity and air humidity perform linear normalization processing, and map the corresponding data values to the interval as follows:

[0057]

[0058] wherein, , is the total number of data acquisition sub - cycles, weight coefficient: , , and ; The weight coefficient can be obtained by referring to the analytic hierarchy process, is the soil humidity of the i - th data acquisition sub - cycle, is the corresponding soil humidity reference target value, is the air humidity of the i - th data acquisition sub - cycle, is the corresponding air humidity reference target value;

[0059] According to historical data and the environmental management expectations during crop planting, preset the environmental anomaly threshold;

[0060] If the obtained environmental anomaly degree exceeds the environmental anomaly threshold, it indicates that there is a certain anomaly in the environment within the current crop planting area. Different weather conditions vary greatly, which may have a certain negative impact on planting. At this time, send a prediction instruction to the outside, and it is necessary to predict the next environmental conditions in the planting area;

[0061] When in use, combine the content in steps 101 and 102:

[0062] Collect various data through installing a sensor network in the planting area, and construct the environmental anomaly degree based on the fluctuations of various environmental conditions, so as to judge whether there is an anomaly in the environmental conditions in the planting area, and be able to handle the anomaly situation in a timely manner when there is an anomaly, ensuring the normal growth of crops in the planting area, especially leafy vegetables and root vegetables.

[0063] Existing intelligent irrigation and drainage systems usually collect various planting environment data based on a sensor network, judge whether irrigation is needed through the collected data, and if so, start the irrigation process. However, when the environmental conditions in the crop planting area, such as soil humidity and air humidity, change frequently, due to the inability to accurately obtain the actual irrigation demand, when controlling the irrigation and drainage system, it is easy to cause a certain degree of waste of water resources, and then affect the growth of crops in the planting area to a certain extent.

[0064] Step 2: Use the trained planting area environment prediction model to predict the planting conditions and crop water requirement patterns data. Based on the accumulated crop irrigation data, analyze the water requirement patterns and planned wetting layers of the crops at different stages. Combine the performance levels of meteorological environment factors, extract irrigation features from the prediction data, and match the corresponding water-saving irrigation plan for the crop planting area by the irrigation plan library according to the irrigation features;

[0065] The above Step 2 includes the following contents:

[0066] Step 201: After receiving the alarm instruction, collect sample data to train the convolutional neural network, obtain the corresponding planting area environment prediction model. Use the trained planting area environment prediction model to predict the rainfall data and soil humidity in the planting area, and obtain the corresponding prediction data, including rainfall amount data, soil humidity data, air humidity data, light humidity, light conditions, etc. After summarization, construct an environmental prediction data set;

[0067] When in use, by constructing a planting area environment prediction model, after setting it to the prediction node, the planting area environment prediction model predicts various environmental data in the planting area, judges whether there are abnormalities in the next environmental condition data. If there are abnormalities, it can send an alarm to the outside in time;

[0068] Step 202: Extract features from the obtained prediction data and the current crop growth status to obtain the corresponding irrigation water requirement features; Through online retrieval and offline formulation, obtain several water-saving irrigation plans, and construct an irrigation plan library in advance after summarization; Use the trained matching model, based on the correspondence between irrigation features and irrigation plans, match the corresponding water-saving irrigation plan for the crop planting area by the pre-constructed irrigation plan library, and send a test instruction to the outside;

[0069] Among them, based on the farmland water balance formula and the Penman formula, calculate the daily water requirement of the crops at different growth stages, and formulate the corresponding water-saving irrigation plan accordingly. Specifically, as follows, through calculation and analysis, obtain the upper and lower limits of soil moisture of different crops at different times. For example, the planned wetting layer of Chinese cabbage at the seedling stage is 20 cm, and the relative soil moisture should be maintained at 70 - 80%. The planned wetting layer at the rosette stage is 40 cm, and the relative soil moisture is maintained at 80 - 90% to ensure its growth quality. Determine the wetting layer depth and irrigation cycle at different growth stages to ensure the effective water absorption of the roots. For example, by measuring the field water holding capacity of the soil and observing whether the 0 - 40 cm soil layer of the soil moisture meter reaches the formulated relative soil moisture, estimate the single irrigation water volume. For example, during the rosette stage of Chinese cabbage, when the relative soil moisture of the 0 - 40 cm soil layer reaches 70% - 90%, it is the appropriate irrigation volume, while at the seedling stage, adjust the planned wetting layer depth and irrigation volume according to the root distribution range.

[0070] For example, during the seedling stage: quantitatively irrigate the crops and control the relative soil moisture content at 70 - 80% to avoid over - irrigation. During the growth stage: increase the irrigation frequency and control the soil moisture content within the range of 80 - 90% through a soil moisture monitor. During the maturity stage: appropriately reduce the irrigation volume according to the water requirements of the crops to prevent excessive water from affecting the quality.

[0071] When in use, combine the content in Steps 201 and 202:

[0072] After predicting and obtaining the next environmental condition data, when irrigation is required in the crop planting area, based on the obtained prediction data, using the growth state of the crops and the determined irrigation requirement standards as references, extract the corresponding irrigation characteristics. According to the irrigation characteristics, the corresponding water - saving irrigation plan can be quickly matched, which can save the time for formulating the water - saving irrigation plan.

[0073] Step Three: Use the crop water - saving irrigation digital twin model to test the water - saving irrigation plan and construct the feasibility degree from the obtained test data , from the feasibility degree Verify the feasibility of the irrigation plan and take corresponding countermeasures according to the verification results;

[0074] The above - mentioned Step Three includes the following content:

[0075] Step 301: After receiving the test instruction, construct an initial model by a machine - learning algorithm. Collect topographic data, soil data, water evaporation data, etc. in the crop planting area as sample data. Use the sample data to train the initial model, and train to obtain the crop water - saving irrigation digital twin model. Use the crop water - saving irrigation digital twin model to test the water - saving irrigation plan and obtain test data, including the data of the soil moisture change over time, water infiltration rate, surface runoff, etc. in each sub - area within the crop planting area after performing the irrigation task. After summarizing the test data, construct the corresponding test data set;

[0076] Step 302: Construct the corresponding feasibility degree from the test data in the test data set to verify the feasibility of the water - saving irrigation plan. The method is as follows: After linearly normalizing the water infiltration rate and the surface runoff , map the corresponding data values to the interval according to the following formula:

[0077]

[0078] Weight coefficient, , , and , the weight coefficient can be obtained by referring to the analytic hierarchy process. is the average value of the water infiltration rate in the sub-region. is the reference target value of the water infiltration rate. is the average value of the surface runoff in the sub-region. is the reference target value of the surface runoff.

[0079] According to historical data and the management expectations for the irrigation effect of the water-saving plan, a feasible threshold is set in advance.

[0080] If the obtained feasibility exceeds the feasible threshold, it indicates that the output water-saving irrigation plan is feasible. At this time, an execution instruction is sent to the outside; if the feasibility does not exceed the feasible threshold, it means that the current water-saving irrigation plan is not feasible and the irrigation plan needs to be optimized to improve the execution effect of the irrigation plan. At this time, an optimization instruction is sent to the outside.

[0081] When in use, after obtaining the output water-saving irrigation plan, use the trained digital twin model of crop water-saving irrigation to test the irrigation plan and obtain the corresponding test data. The corresponding feasibility is constructed from the test data. According to the feasibility

[0082] Evaluate whether the water-saving irrigation plan is effective. If it is effective, it can be directly executed. If the effectiveness is insufficient, the water-saving irrigation plan can be optimized, which can ensure the reliability of the constructed water-saving irrigation plan.

[0083] When in use, combine the content in steps 301 and 303:

[0084] After obtaining the irrigation plan, control and respond to the irrigation system in the planting area to achieve precise irrigation and water-saving irrigation in the crop planting area, play a role in water conservation while meeting the expected irrigation effect, and observe the execution status of the water-saving irrigation plan after executing the irrigation plan. If there is a large difference between the actual effect and the expectation after executing the water-saving irrigation plan, an alarm instruction is sent to the outside to facilitate timely adjustment of the current irrigation effect.

[0085] Based on the calculation and analysis by combining the water balance formula and the Penman formula, the irrigation critical values at different growth stages are determined. The wetting layer depth is determined according to the root distribution during the crop growth period. In this way, it is judged that the amount of irrigation water and the wetting layer depth each time can ensure the effectiveness of water absorption and reduce water resource waste. The irrigation cycle and wetting layer depth are formulated according to the requirements of different growth periods, improving the water use efficiency in agricultural production and achieving the dual effects of water conservation and yield increase.

[0086] For the water demand characteristics and growth period differences of different crops, personalized irrigation plans are provided, realizing the refined management of various crops and improving the quality and yield of crops.

[0087] Step Four: Select monitoring points within the coverage area of the drainage system, monitor the drainage status data in the planting area at the monitoring points, and construct the drainage anomaly degree from the obtained drainage status data , if the drainage anomaly degree exceeds the expectation, perform drainage emergency treatment in the crop planting area;

[0088] The above Step Four includes the following contents:

[0089] Step 401: If the irrigation water volume in the current irrigation area is large or the continuous rainfall is excessive, drainage is required for the crop planting area. At this time, after determining the coverage area of the drainage system, select several non-adjacent monitoring points within the coverage area, install monitoring devices such as water level sensors and flow meters at the monitoring points, and monitor the working status of the drainage system in real time to obtain real-time drainage status data, including cumulative drainage volume, groundwater level, and water level in the waterlogging area, etc. After summarization, construct a drainage status data set;

[0090] Step 402: Construct the drainage anomaly degree from the drainage status data in the drainage status data set, where

[0091] After linearly normalizing the groundwater level and the waterlogging water level , map the corresponding data values to the interval , and then according to the following formula:

[0092]

[0093] where , is the number of monitoring points; weight coefficient: , and ; The weight coefficient can be obtained by referring to the analytic hierarchy process; is the groundwater level of the i-th monitoring point, is the reference target value of the groundwater level; For the accumulated water level at the monitoring point, is the reference target value of the accumulated water level;

[0094] According to historical data and the management expectation of the drainage state in the planting area, a drainage anomaly threshold is preset in advance;

[0095] If the drainage anomaly degree exceeds the drainage anomaly threshold, it indicates that the current drainage state may be abnormal. For example, when the soil humidity is too high or the rainfall exceeds the standard, an alarm instruction is sent to the outside;

[0096] After receiving the alarm instruction, emergency treatment is carried out according to the drainage anomaly degree , including using temporary drainage equipment, covering to protect crops, opening temporary drainage ditches, etc.;

[0097] When in use, combine the content in steps 401 and 402:

[0098] When it is necessary to drain water in the crop planting area, monitor the drainage state in each area covered by the drainage system, and construct the corresponding drainage anomaly degree from the monitoring data , and judge whether there is an abnormality in the drainage state in the planting area according to the drainage anomaly degree . If there is an abnormality, an alarm instruction is sent to the outside, and emergency treatment is carried out on the current drainage state to gradually normalize the drainage state, prevent rainwater from accumulating, and avoid negative impacts on crop planting in the planting area caused by excessive rainfall.

[0099] Step Five: Query the feedback data after implementing the water-saving irrigation plan within the feedback period, and generate a satisfaction coefficient for the implementation of the water-saving irrigation task in the planting area from the feedback data , if the satisfaction coefficient is lower than the expectation, send an inspection instruction to the outside, and orderly repair and maintain the irrigation system and related equipment in the planting area;

[0100] The said Step Five includes the following content:

[0101] Step 501: Preset the feedback period in advance, query the feedback data after implementing the irrigation plan within the feedback period, including the humidity retention time, biological accumulation amount, and water use efficiency in the irrigation area, etc., and construct an improvement degree from the feedback data after each implementation of the irrigation plan , where

[0102] For the biological accumulation amount and the water use efficiency perform linear normalization processing, and map the corresponding data values to the interval , according to the following formula:

[0103]

[0104] Weight coefficient , ; The value of the weight coefficient can be defined by referring to the analytic hierarchy process;

[0105] After continuously obtaining several improvement degrees , analyze and obtain the satisfaction coefficient when implementing the irrigation plan in the planting area within the feedback period, , the method is as follows:

[0106] Among them, n, where n is the number of irrigation times within the feedback period, is the improvement degree after the i-th implementation of the irrigation plan, is the average value of the improvement degree, weight coefficient: , , and , the value of the weight coefficient remains consistent with the previous value;

[0107] According to historical data and the expected effect management during irrigation in the planting area, preset the satisfaction threshold;

[0108] If the satisfaction coefficient is lower than the satisfaction threshold, it indicates that when implementing the water-saving irrigation task for the planting area within the feedback period, the probability of failing to achieve the expected effect is relatively high, and this may be due to faults in the irrigation system, drainage system, or sensor network. At this time, send an inspection instruction to the outside;

[0109] When in use, after implementing the water-saving irrigation plan, collect the corresponding feedback data, and construct the improvement degree of each implementation of the irrigation plan from the obtained feedback data , and evaluate the irrigation effect of each implementation according to the improvement degree . Further, after several consecutive times, construct the corresponding satisfaction coefficient from the improvement degree , and then comprehensively evaluate the irrigation effect, judge the irrigation effect on the planting area within the entire feedback period. If the irrigation effect does not meet the expectation, the current irrigation plan or irrigation plan can be adjusted in a timely manner. At the same time, if the expected effect cannot be achieved for several consecutive times, it is possible to judge whether there are faults in the irrigation system, etc., and verify the availability of the irrigation system.

[0110] Step 502: Construct an electronic map covering the crop planting area, and mark the irrigation system, drainage system, and sensor network on the electronic map; after receiving the inspection instruction, check the sensor network, irrigation system, and drainage system within the preset inspection period. If there are operating faults, mark the faulty locations on the electronic map;

[0111] Combined with the fault location data, a path planning algorithm is used to perform path planning on the electronic map, and the obtained planned path is used as the maintenance path, and the maintenance path is marked on the electronic map.

[0112] During use, combine the content in steps 501 and 502:

[0113] After detecting faults in the irrigation system, drainage system and sensor network and obtaining the corresponding fault locations, the path planning algorithm outputs the corresponding maintenance path. When maintaining and repairing each fault in sequence according to the maintenance path, the efficiency of maintenance and repair can be improved, and the irrigation effect of the planting area can be guaranteed during irrigation of the planting area.

[0114] Among them, the analytic hierarchy process is an analysis method that combines qualitative and quantitative methods. It can decompose complex problems into multiple levels. By comparing the importance of factors at each level, it can help decision-makers make decisions on complex problems and determine the final decision-making plan. In this process, the analytic hierarchy process can be used to determine the weight coefficients of these indicators.

[0115] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but this implementation should not be considered to exceed the scope of this application.

[0116] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only for some logical function divisions. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0118] The unit described as a separation component may or may not be physically separated. The component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed across multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] As described above, the above are only specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claimed rights.

Claims

1. A precise water-saving irrigation method for leafy vegetables and root crops, characterized in that: include, The environmental conditions in the crop planting area are monitored by the arranged sensor network, and the corresponding environmental anomaly degree is generated from the acquired monitoring data. If the environmental anomaly degree exceeds the environmental anomaly threshold, a prediction instruction is issued to the outside. The environmental data collected by the sensor network in the crop planting area, including soil moisture, rainfall, air temperature and humidity, are summarized to construct a planting environment data set. Use the trained planting area environment prediction model to predict the planting condition data in the planting area, extract irrigation features from the predicted data, and use the irrigation plan library to match the corresponding water-saving irrigation plan for the crop planting area based on the irrigation features; Use the crop water-saving irrigation digital twin model to test the water-saving irrigation plan. Construct the feasibility of the irrigation plan based on the test data of water infiltration rate and surface runoff. Use the feasibility to verify the feasibility of the irrigation plan and take corresponding measures based on the verification results. Select monitoring points within the coverage area of ​​the drainage system, monitor the drainage status data in the planting area at the monitoring points, and construct drainage anomaly from the acquired drainage status data. If the drainage anomaly exceeds expectations, emergency drainage treatment is performed in the crop planting area. The feedback data after the implementation of the water-saving irrigation plan is queried within the feedback cycle. The improvement degree is constructed from the feedback data including bioaccumulation and water use efficiency after each irrigation plan is implemented. After obtaining several improvement degrees in succession, the satisfaction coefficient of the irrigation plan implemented in the planting area within the feedback cycle is calculated by analysis. , if the satisfaction coefficient Lower than expected, an inspection order was issued to the outside to carry out repair and maintenance of the irrigation system and related equipment in the planting area in an orderly manner; among them, the satisfaction coefficient The construction is as follows: ;in, n , n is the number of irrigations within the feedback cycle, is the improvement degree after the i-th irrigation scheme is implemented, is the mean of the improvement, weight coefficient: , ,and ; Bioaccumulation and water use efficiency Perform linear normalization and map the corresponding data values ​​to the interval The improvement degree is constructed based on the feedback data according to the following formula : ; Weight coefficient, , .

2. The precise water-saving irrigation method for crops according to claim 1, characterized in that: Generate environmental anomaly from planting environment data set , among which, soil moisture and air humidity Perform linear normalization and map the corresponding data values ​​to the interval According to the following method: ;in, , is the total number of data collection sub-cycles, and the weight coefficient is: ， ,and ; is the soil moisture of the ith data collection sub-period, is the corresponding soil moisture reference target value, is the air humidity of the ith data collection sub-cycle, is the corresponding reference target value of air humidity.

3. The precise water-saving irrigation method for crops according to claim 2, characterized in that: After receiving the alarm command, the trained planting area environment prediction model obtains the corresponding prediction data, which are summarized to build an environmental prediction data set; feature extraction is performed on the obtained prediction data and the current crop growth status, and the corresponding irrigation features are obtained to obtain several water-saving irrigation plans, which are summarized to pre-build an irrigation plan library; According to the correspondence between irrigation characteristics and irrigation plans, the irrigation plan library matches the corresponding water-saving irrigation plan for the crop planting area and issues test instructions to the outside.

4. The precise water-saving irrigation method for crops according to claim 3, characterized in that: After receiving the test instruction, the digital twin model of crop water-saving irrigation is trained and obtained, and the water-saving irrigation scheme is tested using the digital twin model of crop water-saving irrigation and test data is obtained. The test data is aggregated to construct the corresponding test data set; the corresponding feasibility , if the feasibility of obtaining If the feasibility threshold is exceeded, an execution instruction is issued to the outside. If the feasible threshold is not exceeded, optimization instructions are issued to the outside.

5. The precise water-saving irrigation method for crops according to claim 4, characterized in that: Water infiltration rate and surface runoff After linear normalization, the corresponding data values ​​are mapped to the interval According to the following formula, the feasibility is constructed : ; Weight coefficient, , ,and , is the average water infiltration rate in the sub-area, is the reference target value of water infiltration rate; is the mean surface runoff in the sub-area, It is the reference target value of surface runoff.

6. The precise water-saving irrigation method for crops according to claim 5, characterized in that: An irrigation system is installed in the crop planting area. After receiving the execution instruction, the irrigation system executes the output water-saving irrigation plan. After executing the water-saving irrigation plan, an observation instruction is issued to the outside. Select several non-adjacent monitoring points in the coverage area of ​​the drainage system, monitor the working status of the drainage system in real time at the monitoring points, obtain real-time drainage status data, and build a drainage status data set after aggregation. The drainage anomaly degree is constructed from the drainage status data in the drainage status data set. .

7. The precise water-saving irrigation method for crops according to claim 6, characterized in that: Groundwater level And water level After linear normalization, the corresponding data values ​​are mapped to the interval Then, the drainage anomaly degree is constructed according to the following formula : ;in, , is the number of monitoring points; weight coefficient: , and ; For the i The groundwater level at each monitoring point, is the reference target value of groundwater level; is the water level at the monitoring point, It is the reference target value of the accumulated water level.

8. The precise water-saving irrigation method for crops according to claim 7, characterized in that: Construct an electronic map covering the crop planting area and mark the irrigation system, drainage system and sensor network on the electronic map; after receiving the inspection instruction, inspect the sensor network, irrigation system and drainage system within the preset inspection cycle, and if there is an operational fault, mark the location of the fault on the electronic map; In combination with the fault location data, a path planning algorithm is used to perform path planning on an electronic map, and the path obtained by planning is used as a maintenance path, and the maintenance path is marked on the electronic map.

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