Water-fertilizer integrated irrigation control method based on wheat growth cycle

Abstract

The present invention relates to the field of irrigation control technology, specifically to a water-fertilizer integrated irrigation control method based on the wheat growth cycle, comprising the following steps: collecting soil moisture and wheat growth status data, using a random forest algorithm to screen key soil and biological parameters that affect wheat growth, and predicting wheat's water and nutrient requirements at different growth stages based on the key parameters. In the present invention, the water and nutrient requirements of wheat at different growth stages are accurately predicted by using a random forest algorithm, and resources are directly allocated according to the actual needs of the plants, effectively avoiding the waste of resources and insufficient supply problems in traditional irrigation systems, and the dynamic adjustment strategy is not only based on the current soil and plant status, but also uses historical and predicted data to optimize the water and fertilizer supply plan, enhance the responsiveness to environmental changes, and the real-time feedback loop is combined with a PID controller to finely adjust the irrigation and fertilization parameters, further ensuring the accuracy and effectiveness of each irrigation and fertilization.

Description

Technical Field

[0001] The invention relates to the technical field of irrigation control, and in particular to a water-fertilizer integrated irrigation control method based on the wheat growth cycle. Background Art

[0002] Irrigation control technology involves the management and utilization of agricultural water resources, focusing on effectively controlling water supply to meet the needs of plant growth while reducing water waste. It ensures that crops receive a balanced water supply by utilizing various sensor technologies and control systems to monitor soil moisture, weather conditions, and the moisture status of plants. Through automatic or semi-automatic irrigation, water distribution can be adjusted based on real-time data to improve irrigation accuracy and efficiency.

[0003] Among them, the integrated water-fertilizer irrigation control method during the wheat growth cycle involves adjusting the growth environment of wheat through an irrigation system that integrates water and fertilizer management during the wheat growth cycle. Its main purpose is to increase wheat yield and quality while reducing the use of water resources and fertilizers. By precisely controlling the timing and amount of irrigation and fertilization, it can ensure that wheat obtains appropriate nutrition and water at each growth stage, thereby improving the crop's stress resistance and reducing the environmental burden.

[0004] Existing technologies mainly rely on basic sensors and control systems, lacking the ability to conduct in-depth analysis and prediction of complex data, making it impossible for irrigation systems to effectively adapt to changing environmental conditions or accurately meet the specific needs of crops, resulting in low water and fertilizer utilization and failure to fully realize crop growth potential. In terms of resource management, traditional technologies use relatively static irrigation strategies that are difficult to adjust in real time to cope with sudden climate changes, resulting in excessive or insufficient irrigation, affecting crop health and exacerbating the ineffective use of water resources. For example, inaccurate water-fertilizer ratios and timing selection lead to fertilizer loss and soil salinization, which not only increases agricultural input costs, but also has a negative impact on the ecological environment. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and propose a water-fertilizer integrated irrigation control method based on the wheat growth cycle.

[0006] In order to achieve the above object, the present invention adopts the following technical scheme: a water-fertilizer integrated irrigation control method based on the wheat growth cycle, comprising the following steps:

[0007] S1: Collect soil moisture and wheat growth status data, use random forest algorithm to screen key soil and biological parameters that affect wheat growth, and predict wheat's demand for water and nutrition at different growth stages based on key parameters to obtain demand prediction indicators;

[0008] S2: Based on the demand prediction index, according to the current growth stage of wheat and real-time soil data, dynamically adjust the valve opening degree of the irrigation system and the operating efficiency of the fertilizer pump to match the water and nutrient supply with the wheat demand, and refine the adjustment accuracy through the feedback control loop to obtain the parameter control configuration;

[0009] S3: Based on the parameter control configuration, perform irrigation and fertilization, monitor soil moisture and wheat growth response in real time, adjust irrigation and fertilization parameters according to real-time feedback data, optimize water and fertilizer distribution, and generate real-time adjustment feedback information;

[0010] S4: Based on the real-time adjustment feedback information, the water and fertilizer supply is continuously adjusted through the PID controller, the changes in water, fertilizer and soil conditions caused by wheat growth are monitored, the optimal supply time of water and fertilizer is determined, and the optimal supply plan is generated.

[0011] The present invention is improved in that the steps of screening the key soil and biological parameters are specifically as follows:

[0012] S111: Collect soil moisture and wheat growth status data and organize them into a time series dataset covering the entire growth cycle;

[0013] S112: Based on the time series data set, complete data points are screened, and noise and outliers are removed by using moving average and median filtering methods to obtain a processed data set;

[0014] S113: Based on the processed data set, a random forest algorithm is used to perform feature criticality assessment using the formula:

[0015] ;

[0016] Screen the key soil and biological parameters that affect wheat growth and obtain a list of key parameters, among which: Representation characteristics The information gain of Is a node The proportion of samples of a certain type in yes The complement of Includes features The number of tree nodes.

[0017] The present invention is improved in that the step of obtaining the demand forecasting index is specifically as follows:

[0018] S121: performing correlation analysis on the key parameters, wheat growth cycle data and environmental factors to determine the impact of multiple factors on water and nutrient requirements, and obtaining a prediction basic data set;

[0019] S122: Perform prediction evaluation on the prediction basic data set by calculating the contribution of each factor to the prediction result using the formula:

[0020] ;

[0021] Calculate the average proportion of forecast errors , and get the adjusted prediction parameters, where represents the sample size, is the current observation value, is the predicted value;

[0022] S123: Based on the adjusted prediction parameters and in combination with real-time monitoring data, including current soil moisture and weather conditions, the demand of the current wheat growth stage is re-analyzed to obtain a demand prediction index.

[0023] The present invention is improved in that the adjustment steps of the valve opening degree and the operating efficiency of the fertilizer pump are specifically as follows:

[0024] S211: Based on the demand prediction index, according to the soil moisture, temperature and nutrient content data monitored in real time by the sensor, assess the immediate water and nutrient requirements of the crop to obtain supply demand data;

[0025] S212: Based on the supply and demand data, the formula is used:

[0026] ;

[0027] Calculate irrigation and fertilization parameters, where represents the adjusted flow rate, represents the crop coverage area, is the crop demand concentration, is the current soil concentration, is the efficiency coefficient;

[0028] S213: Dynamically adjust the valve opening degree of the irrigation system and the operating efficiency of the fertilization pump according to the irrigation and fertilization parameters to obtain adjusted operating parameters.

[0029] The present invention is improved in that the step of obtaining the parameter control configuration is specifically as follows:

[0030] S221: According to the feedback control loop, the formula is used:

[0031] ;

[0032] Determine the magnitude of the adjustment needed to reduce the difference between the target and the current situation, including: is the adjustment amount, is the proportional gain, is the target parameter value, is the current parameter value collected from the sensor;

[0033] S222: Based on the amplitude required for adjustment, the crop growth status and environmental data are continuously monitored, and the valve opening degree and the fertilizer pump speed are optimized in real time according to the feedback control loop to obtain the parameter control configuration.

[0034] The present invention is improved in that the monitoring steps of soil moisture and wheat growth response are specifically as follows:

[0035] S311: Based on the parameter control configuration, the soil moisture value and wheat growth rate of each measuring point are recorded in real time to obtain real-time growth data;

[0036] S312: Based on the real-time growth data, the formula is used:

[0037] ;

[0038] Evaluate soil and wheat growth data to obtain real-time monitoring information, including: Represents the health index, Represents the current soil moisture value, Represents the growth rate of wheat. and is the weight parameter.

[0039] The present invention is improved in that the step of obtaining the real-time adjustment feedback information is specifically as follows:

[0040] S321: Automatically analyze the real-time feedback data and perform preliminary processing using the formula:

[0041] ;

[0042] Estimate irrigation and fertilization needs to obtain overall regulation requirements ,in, and are the weight coefficients of soil moisture and wheat growth rate, represents the target soil moisture, represents the current measured soil moisture, represents the target wheat growth rate, Represents the currently measured wheat growth rate;

[0043] S322: Automatically adjust parameter settings of the irrigation and fertilization controllers according to the overall regulation requirements, and generate real-time regulation feedback information.

[0044] The present invention is improved in that the step of obtaining the optimal supply timing is specifically as follows:

[0045] S411: Based on the real-time adjustment feedback information, the real-time data of irrigation and fertilization, including water volume, fertilizer flow rate and corresponding timestamps, are collected through the PID controller, and the current water and fertilizer use efficiency is calculated to generate real-time water and fertilizer use information;

[0046] S412: Based on the real-time water and fertilizer usage information, the formula is used:

[0047] ;

[0048] Calculate the sensitivity index of crop growth to water and fertilizer supply , determine the adjustment needs of water and fertilizer supply, among which, Indicates that during the target time period The amount of fertilizer applied, Indicates the time period Crop growth index within

[0049] S413: Automatically adjust the settings of the PID controller according to the sensitivity index, optimize the supply process of irrigation and fertilization, and obtain the optimal supply plan.

[0050] Compared with the prior art, the advantages and positive effects of the present invention are:

[0051] In the present invention, a random forest algorithm is used to accurately predict the water and nutrient requirements of wheat at different growth stages, and resources are allocated directly according to the actual needs of the plants, effectively avoiding the waste of resources and insufficient supply problems in traditional irrigation systems. The dynamic adjustment strategy is not only based on the current soil and plant status, but also uses historical and predicted data to optimize the water and fertilizer supply plan, enhance the ability to respond to environmental changes, and the real-time feedback loop is combined with the PID controller to fine-tune the irrigation and fertilization parameters, further ensuring the accuracy and effectiveness of each irrigation and fertilization, and reducing the burden on the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The present invention proposes a flow chart of a water-fertilizer integrated irrigation control method based on the wheat growth cycle;

[0053] Figure 2 The present invention is a flowchart for screening key soil and biological parameters;

[0054] Figure 3 A flow chart for obtaining demand forecast indicators in the present invention;

[0055] Figure 4 It is a flow chart for adjusting the valve opening degree and the operating efficiency of the fertilizer pump in the present invention;

[0056] Figure 5 A flowchart for obtaining parameter control configuration in the present invention;

[0057] Figure 6 It is a flow chart for monitoring soil moisture and wheat growth response in the present invention;

[0058] Figure 7 A flowchart for obtaining real-time adjustment feedback information in the present invention;

[0059] Figure 8 This is a flow chart for obtaining the optimal supply timing in the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0061] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0062] Example:

[0063] See also Figure 1 The present invention provides a technical solution: a water-fertilizer integrated irrigation control method based on the wheat growth cycle, comprising the following steps:

[0064] S1: Collect soil moisture and wheat growth status data, use random forest algorithm to screen key soil and biological parameters that affect wheat growth, and predict wheat's demand for water and nutrition at different growth stages based on key parameters to obtain demand prediction indicators;

[0065] S2: Based on demand prediction indicators, according to the current growth stage of wheat and real-time soil data, dynamically adjust the valve opening degree of the irrigation system and the operating efficiency of the fertilizer pump to match the water and nutrient supply with wheat demand, and refine the adjustment accuracy through feedback control loops to obtain parameter control configuration;

[0066] S3: Based on parameter control configuration, execute irrigation and fertilization, monitor soil moisture and wheat growth response in real time, adjust irrigation and fertilization parameters according to real-time feedback data, optimize water and fertilizer distribution, and generate real-time adjustment feedback information;

[0067] For parameter adjustment, if the real-time feedback data shows that the soil moisture is lower than the ideal level of the current growth stage of wheat, the irrigation amount will be increased. For example, when wheat enters the jointing stage, the ideal soil moisture should be maintained at a certain level. If the soil moisture is monitored to be lower than this standard, the irrigation system will automatically increase the amount of water for the next irrigation, or shorten the irrigation interval to ensure that the soil moisture can quickly return to the ideal state;

[0068] Adjust the type and proportion of fertilizers based on the growth status of crops and feedback data on soil nutrient content. For example, if feedback data indicates that the nitrogen content in the soil is low and wheat is in its prime growth period, the system will increase the proportion of nitrogen-containing fertilizers to promote plant growth and development.

[0069] The frequency and timing of fertilization are adjusted based on the needs of wheat and real-time monitoring data of nutrients in the soil. For example, if the data shows that the soil can better retain moisture when the temperature is lower at night, the system will optimize the fertilization plan and apply fertilizer during specific periods to improve fertilizer utilization and reduce evaporation losses.

[0070] S4: Based on real-time adjustment feedback information, the PID controller continuously adjusts the water and fertilizer supply, monitors the changes in water, fertilizer and soil conditions for wheat growth, determines the optimal time for water and fertilizer supply, and generates the optimal supply plan.

[0071] Demand prediction indicators include plant water absorption rate, nutrient demand level, and growth stage demand. Parameter control configuration includes valve adjustment parameters, pump speed adjustment parameters, and feedback control information. Real-time adjustment feedback information includes soil moisture feedback information, plant growth response information, and control parameter adjustment effects. The optimal supply plan includes irrigation scheduling plan, fertilization scheduling plan, and nutrient allocation efficiency.

[0072] See also Figure 2 , the screening steps for key soil and biological parameters are as follows:

[0073] S111: Collect soil moisture and wheat growth status data and organize them into a time series dataset covering the entire growth cycle;

[0074] In the process of collecting soil moisture and wheat growth status data, sensors are set to collect data at regular intervals and transmit the data wirelessly to the central database. Through data preprocessing, such as null value processing and outlier elimination, statistical analysis methods are used to determine the statistical characteristics of the data, such as the mean and standard deviation, to ensure the integrity and accuracy of the data set and obtain a time series data set.

[0075] S112: Based on the time series data set, complete data points are screened, and noise and outliers are removed using moving average and median filtering methods to obtain a processed data set;

[0076] Complete data points are filtered from the time series data set. Data noise and outliers are removed by using moving average and median filtering methods. Trends and periodic changes in the data are identified. Moving averages are calculated using sliding window techniques. Median filtering is used to reduce the impact of prominent peaks, thereby improving data consistency. The processed data set obtained will provide a more stable basis for feature selection.

[0077] S113: Based on the processed data set, the random forest algorithm is used to evaluate the criticality of features using the formula:

[0078] ;

[0079] Screen the key soil and biological parameters that affect wheat growth and obtain a list of key parameters, among which: Representation characteristics The information gain of Is a node The proportion of samples of a certain type in yes The complement of represents the proportion of samples of other categories besides the main category. Includes features The number of tree nodes;

[0080] There is a tree, characteristic Appearing in 3 nodes, the sample ratio of each node The number of samples per node is 0.2, 0.5 and 0.3 respectively. are 100, 150 and 120 respectively, then:

[0081] ;

[0082] ;

[0083] ;

[0084] This result shows that the characteristics The information gain of is 78.7, reflecting the feature The ability to distinguish different categories in the data set. High information gain means that the feature It is of high importance and helps to predict the growing requirements of wheat more accurately.

[0085] See also Figure 3 , the specific steps for obtaining demand forecast indicators are:

[0086] S121: Based on key parameters, correlation analysis is performed with wheat growth cycle data and environmental factors to determine the impact of multiple factors on water and nutrient requirements and obtain a prediction basic data set;

[0087] The key soil and biological parameters are correlated with wheat growth cycle data and environmental factors. This involves collecting soil samples and measuring their components such as nitrogen, phosphorus, potassium content and microbial activity. At the same time, climate data including rainfall, temperature and humidity are collected, and a preliminary correlation analysis is conducted on the collected data. By calculating the correlation coefficient between each factor and the wheat growth rate, data with low correlation is excluded, and factors with significant impact on wheat growth are retained and organized into a basic data set for predictive analysis.

[0088] S122: Perform prediction evaluation on the prediction basic data set by calculating the contribution of each factor to the prediction result using the formula:

[0089] ;

[0090] Calculate the average proportion of forecast errors , and get the adjusted prediction parameters, where represents the sample size, is the current observation value, is the predicted value;

[0091] There are 5 sample data, the current observation value and predicted values They are:

[0092] ;

[0093] ;

[0094] Each item in the calculation formula is:

[0095] ;

[0096] ;

[0097] ;

[0098] ;

[0099] ;

[0100] ;

[0101] The results show that the average error rate of the prediction is about 0.306%, which means that the prediction is very close to the actual observation value, and after adjustment, it can better predict the moisture and nutritional requirements of wheat.

[0102] S123: Based on the adjusted forecast parameters and combined with real-time monitoring data, including current soil moisture and weather conditions, reanalyze the demand of the current wheat growth stage to obtain demand forecast indicators;

[0103] In the process of re-analyzing the specific needs of the current wheat growth stage using the adjusted parameters in combination with the latest real-time monitoring data, it is necessary to monitor the data output of soil moisture sensors and climate monitoring stations in real time, including current rainfall, soil temperature and humidity and other information, and quickly calculate through verified parameter settings to determine the optimal moisture and nutrient levels of wheat at the current stage. The output data is displayed graphically for application in irrigation and fertilization plans. The analysis results can directly affect crop management decisions and improve the efficiency and yield of crop production.

[0104] See also Figure 4 The specific steps for adjusting the valve opening degree and the operating efficiency of the fertilizer pump are as follows:

[0105] S211: Based on demand prediction indicators, the immediate water and nutrient requirements of crops are evaluated according to the soil moisture, temperature and nutrient content data monitored in real time by sensors to obtain supply demand data;

[0106] Real-time soil moisture, temperature and nutrient content monitoring data are collected through multiple sensors installed in the field. The sensors send data regularly, and then immediately evaluate the input data to calculate the current moisture and nutrient levels. In addition, weather conditions data such as rainfall and temperature provided by the meteorological station are combined to ensure the comprehensiveness of the information, thereby generating a comprehensive crop demand analysis report, which will be directly used to determine the basic strategy for irrigation and fertilization.

[0107] S212: Based on supply and demand data, use the formula:

[0108] ;

[0109] Calculate irrigation and fertilization parameters, where Indicates the adjusted flow rate (liters or grams), represents the crop cover area (square meters), is the crop demand concentration, is the current soil concentration, is the efficiency factor, taking into account losses such as evaporation and leakage;

[0110] Suppose a wheat field has a coverage area of For 5000 square meters, the ideal moisture concentration is The current soil concentration is 0.2 g / L. is 0.15 g / L, the efficiency factor The value is 0.95 to take into account some losses in the system and substitute the value into the formula:

[0111] ;

[0112] ;

[0113] It is calculated that water supply or fertilization needs to be adjusted to provide an additional 237.5 grams of water-soluble nutrients to fill the current gap and ensure an optimal crop growth environment.

[0114] S213: dynamically adjusting the valve opening degree of the irrigation system and the operating efficiency of the fertilization pump according to the irrigation and fertilization parameters to obtain adjusted operating parameters;

[0115] Based on the calculated valve opening degree and fertilizer pump efficiency parameters, real-time feedback control adjustments are implemented to ensure accurate matching of wheat's moisture and nutrient requirements. Operating parameters are automatically adjusted based on the latest soil moisture and nutrient data collected from sensors. Real-time monitoring ensures that each adjustment is based on the latest soil and environmental conditions. The output operating parameters are the result of continuous optimization, ensuring the accuracy of irrigation and fertilization.

[0116] See also Figure 5 , the specific steps for obtaining parameter control configuration are:

[0117] S221: According to the feedback control loop, the formula is used:

[0118] ;

[0119] Determine the magnitude of the adjustment needed to reduce the difference between the target and the current situation, including: is the adjustment amount, is the proportional gain, is the target parameter value, such as ideal soil moisture or nutrient concentration, is the current parameter value collected from the sensor;

[0120] At a specific detection point, the target soil moisture is 50%RH, and the real-time sensor reading is 45%RH, and the proportional gain is set is 0.1. Then, the adjustment amount It can be obtained by the following calculation:

[0121] ;

[0122] The results show that in order to achieve the target humidity, the adjustment amount that needs to be increased is 0.5%RH to make the actual soil moisture closer to the target setting, helping the irrigation system to continuously maintain the optimal crop growth environment, reduce resource waste, and improve the efficiency and effectiveness of the entire irrigation system.

[0123] S222: Based on the magnitude of adjustment required, the crop growth status and environmental data are continuously monitored, and the valve opening degree and the fertilizer pump speed are optimized in real time according to the feedback control loop to obtain the parameter control configuration;

[0124] Collect wheat growth data and environmental conditions in real time, regularly calculate deviations in soil moisture and nutrient levels, and adjust the operating parameters of the irrigation and fertilization systems through feedback control algorithms, including collecting data from soil moisture sensors and chlorophyll content monitors. The data is sent via a wireless network. Based on the feedback control algorithm, the operating status of valves and pumps is refined according to real-time data on crop growth stages and environmental variables to ensure that each plant obtains the optimal amount of water and nutrients it needs, taking into account soil type, weather conditions and crop types to optimize the distribution and utilization efficiency of water and fertilizer.

[0125] See also Figure 6 , the specific steps for monitoring soil moisture and wheat growth response are:

[0126] S311: Based on the parameter control configuration, the soil moisture value and wheat growth rate of each measuring point are recorded in real time to obtain real-time growth data;

[0127] Based on the parameter control configuration, soil moisture values ​​and wheat growth rates are recorded in real time. The data at each measurement point is coded and identified to maintain its uniqueness and traceability. The data includes specific soil moisture percentage and plant growth rate, allowing real-time reception and monitoring of data streams to ensure the accuracy and timeliness of each data point. The generated real-time growth data provides a basis for subsequent irrigation and fertilization decisions, ensuring real-time data updates and accurate feedback.

[0128] S312: Based on real-time growth data, the formula is:

[0129] ;

[0130] Evaluate soil and wheat growth data to obtain real-time monitoring information, including: Represents the health index, Represents the current soil moisture value, Represents the growth rate of wheat. and is the weight parameter used to adjust the influence of soil moisture and wheat growth rate in the comprehensive health index;

[0131] If the current soil moisture is 40%, the growth rate of wheat 1.2cm per week, weight and Set them to 0.6 and 0.4 respectively, and substitute them into the formula to calculate:

[0132] ;

[0133] ;

[0134] The calculated health index is 24.48, reflecting the current crop growth conditions, so as to understand the crop growth status and soil moisture in real time, and facilitate rapid adjustment of irrigation or fertilization strategies to adapt to the current growth conditions.

[0135] See also Figure 7 ,The specific steps for obtaining real-time adjustment feedback information are:

[0136] S321: Automatically analyze the real-time feedback data and perform preliminary processing using the formula:

[0137] ;

[0138] Estimate irrigation and fertilization needs to obtain overall regulation requirements ,in, and are the weight coefficients of soil moisture and wheat growth rate, represents the target soil moisture, Represents the current measured soil moisture, represents the target wheat growth rate, Represents the currently measured wheat growth rate;

[0139] Target soil moisture The actual measured value is 75%. The adjustment coefficient is 70%. Set to 1.0; target growth rate 2.5cm / week, actual measured value The adjustment coefficient is 2.0cm / week. Set it to 0.8 and substitute it into the formula:

[0140] ;

[0141] ;

[0142] Calculated The value indicates that water or nutrition needs to be increased accordingly to meet the growth needs of crops. This result shows that by adjusting the amount of irrigation and fertilization in real time, we can effectively respond to environmental changes, maintain soil moisture and crop growth rate in the optimal state, and thus improve the growth efficiency and quality of crops.

[0143] S322: Automatically adjust parameter settings of irrigation and fertilization controllers according to overall regulation requirements, and generate real-time regulation feedback information;

[0144] According to the overall regulation needs, the soil moisture and wheat growth response of each irrigation area are continuously measured. According to the preset target parameters and actual readings, it is determined whether the amount of irrigation and fertilization needs to be adjusted. The adjustment process is based on historical data and real-time data, and the optimal adjustment parameters are automatically calculated. Then, the controller adjusts the settings of the water valve and fertilizer distribution mechanism according to the calculation results to keep the soil moisture and nutrient supply matched with the needs of wheat. The real-time regulation feedback information generated includes the soil moisture adjustment amount and fertilization rate adjustment amount for each area, ensuring the optimization of the entire irrigation and fertilization process to maximize crop yield and healthy growth.

[0145] See also Figure 8 , the specific steps to obtain the optimal supply timing are:

[0146] S411: Based on the real-time adjustment feedback information, the real-time data of irrigation and fertilization, including water volume, fertilizer flow rate and corresponding timestamps, are collected through the PID controller, and the current water and fertilizer use efficiency is calculated to generate real-time water and fertilizer use information;

[0147] Through the analysis of real-time feedback information, the PID controller collects data on water volume, fertilizer flow rate and corresponding timestamps involved in the irrigation and fertilization process. The data comes from the direct monitoring results of each sensor. After collecting the data, preliminary data processing is performed to determine the flow rate of water and fertilizer and their consumption efficiency. The current water and fertilizer utilization efficiency can be calculated through the information, realizing real-time monitoring and adjustment of irrigation and fertilization parameters, ensuring the efficient operation of the irrigation system, and the generated real-time water and fertilizer utilization information provides a basis for further adjustment.

[0148] S412: Based on real-time water and fertilizer usage information, use the formula:

[0149] ;

[0150] Calculate the sensitivity index of crop growth to water and fertilizer supply , determine the adjustment needs of water and fertilizer supply, among which, Indicates that during the target time period The amount of fertilizer applied, Indicates the time period Crop growth index within

[0151] During a specific evaluation period, the amount of fertilizer applied The corresponding crop growth index is 20, 25 and 30 respectively. They are 0.5, 0.8 and 0.7 respectively, and the calculation process is as follows:

[0152] ;

[0153] ;

[0154] The results show that the current fertilization strategy has an overall efficiency of 0.68 in improving the crop growth index, which provides guidance on how to optimize the water and fertilizer supply strategy in the next step to ensure that crops can get the best growth conditions.

[0155] S413: Automatically adjust the settings of the PID controller according to the sensitivity index, optimize the supply process of irrigation and fertilization, and obtain the optimal supply plan;

[0156] According to the sensitivity index collected through the irrigation and fertilization process, the relevant settings of the PID controller are automatically adjusted. The adjustment process involves analyzing the deviation between real-time data and preset targets and optimizing the control parameters accordingly. The automated adjustment is not only based on current operating data, but also responds to real-time feedback on crop growth and soil conditions. Through this dynamic adjustment, the system accurately controls the supply of water and fertilizer, thereby providing the best growth environment for crops. The generated optimal supply plan ensures the rational use of resources and maximizes crop growth.

[0157] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A water-fertilizer integrated irrigation control method based on the wheat growth cycle, characterized in that: The following steps are involved: Collect soil moisture and wheat growth status data, use the random forest algorithm to screen the key soil and biological parameters that affect wheat growth, and predict the water and nutrient requirements of wheat at different growth stages based on the key parameters to obtain demand prediction indicators; Based on the demand prediction index, according to the current growth stage of wheat and real-time soil data, the valve opening degree of the irrigation system and the operating efficiency of the fertilizer pump are dynamically adjusted to match the water and nutrient supply with the wheat demand, and the adjustment accuracy is refined through a feedback control loop to obtain a parameter control configuration; Based on the parameter control configuration, irrigation and fertilization are performed, soil moisture and wheat growth response are monitored in real time, irrigation and fertilization parameters are adjusted according to real-time feedback data, water and fertilizer distribution is optimized, and real-time adjustment feedback information is generated; Based on the real-time adjustment feedback information, the water and fertilizer supply is continuously adjusted through the PID controller, the changes in water, fertilizer and soil conditions caused by wheat growth are monitored, the optimal supply time of water and fertilizer is determined, and the optimal supply plan is generated.

2. The water-fertilizer integrated irrigation control method based on the wheat growth cycle according to claim 1 is characterized in that: The screening steps of the key soil and biological parameters are specifically as follows: Collect soil moisture and wheat growth status data and organize them into a time series dataset covering the entire growth cycle; Based on the time series data set, complete data points are screened, and noise and outliers are removed using moving average and median filtering methods to obtain a processed data set; Based on the processed data set, the random forest algorithm is used to evaluate the criticality of features using the formula: ； Screen the key soil and biological parameters that affect wheat growth and obtain a list of key parameters, among which: Representation characteristics The information gain of Is a node The proportion of samples of a certain type in yes The complement of Includes features The number of tree nodes.

3. The water-fertilizer integrated irrigation control method based on the wheat growth cycle according to claim 1 is characterized in that: The steps for obtaining the demand forecasting index are specifically as follows: According to the key parameters, correlation analysis is performed with wheat growth cycle data and environmental factors to determine the impact of multiple factors on water and nutrient requirements, and obtain a prediction basic data set; The prediction basic data set is used for prediction evaluation, and the contribution of each factor to the prediction result is calculated using the formula: ； Calculate the average proportion of forecast errors , and get the adjusted prediction parameters, where represents the sample size, is the current observation value, is the predicted value; Based on the adjusted forecast parameters, combined with real-time monitoring data, including current soil moisture and weather conditions, the demand of the current wheat growth stage is re-analyzed to obtain demand forecast indicators.

4. The water-fertilizer integrated irrigation control method based on the wheat growth cycle according to claim 1 is characterized in that: The adjustment steps of the valve opening degree and the operating efficiency of the fertilizer pump are specifically as follows: Based on the demand prediction indicators, the immediate water and nutrient requirements of crops are evaluated according to the soil moisture, temperature and nutrient content data monitored in real time by sensors to obtain supply demand data; Based on the supply and demand data, the formula is adopted: ； Calculate irrigation and fertilization parameters, where represents the adjusted flow rate, represents the crop coverage area, is the crop demand concentration, is the current soil concentration, is the efficiency coefficient; According to the irrigation and fertilization parameters, the valve opening degree of the irrigation system and the operating efficiency of the fertilization pump are dynamically adjusted to obtain adjusted operating parameters.

5. The water-fertilizer integrated irrigation control method based on the wheat growth cycle according to claim 1 is characterized in that: The steps for obtaining the parameter control configuration are specifically as follows: According to the feedback control loop, the formula is adopted: ； Determine the magnitude of the adjustment needed to reduce the difference between the target and the current situation, including: is the adjustment amount, is the proportional gain, is the target parameter value, is the current parameter value collected from the sensor; Based on the amplitude required for adjustment, the crop growth status and environmental data are continuously monitored, and the valve opening degree and the fertilizer pump speed are optimized in real time according to the feedback control loop to obtain the parameter control configuration.

6. The water-fertilizer integrated irrigation control method based on the wheat growth cycle according to claim 1 is characterized in that: The monitoring steps of soil moisture and wheat growth response are specifically as follows: Based on the parameter control configuration, the soil moisture value and wheat growth rate of each measuring point are recorded in real time to obtain real-time growth data; Based on the real-time growth data, the formula is adopted: ； Evaluate soil and wheat growth data to obtain real-time monitoring information, including: Represents the health index, Represents the current soil moisture value, Represents the growth rate of wheat. and is the weight parameter.

7. The water-fertilizer integrated irrigation control method based on the wheat growth cycle according to claim 1, characterized in that: The step of obtaining the real-time adjustment feedback information is specifically as follows: Automatically analyze the real-time feedback data and perform preliminary processing using the formula: ； Estimate irrigation and fertilization needs to obtain overall regulation requirements ,in, and are the weight coefficients of soil moisture and wheat growth rate, represents the target soil moisture, represents the current measured soil moisture, represents the target wheat growth rate, Represents the currently measured wheat growth rate; According to the overall regulation requirements, parameter settings of the irrigation and fertilization controllers are automatically adjusted to generate real-time regulation feedback information.

8. The water-fertilizer integrated irrigation control method based on the wheat growth cycle according to claim 1, characterized in that: The steps for obtaining the optimal supply timing are specifically as follows: Based on the real-time adjustment feedback information, the real-time data of irrigation and fertilization, including water volume, fertilizer flow rate and corresponding timestamps, are collected through the PID controller, and the current water and fertilizer use efficiency is calculated to generate real-time water and fertilizer use information; Based on the real-time water and fertilizer usage information, the formula is used: ； Calculate the sensitivity index of crop growth to water and fertilizer supply , determine the adjustment needs of water and fertilizer supply, among which, Indicates that during the target time period The amount of fertilizer applied, Indicates the time period Crop growth index within According to the sensitivity index, the settings of the PID controller are automatically adjusted to optimize the supply process of irrigation and fertilization to obtain the optimal supply plan.

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