Tidal seedling bed intelligent control method and system
By using real-time monitoring and feedback to regulate the irrigation system of the tidal seedling bed, the problems of inaccurate irrigation timing and insufficient monitoring of the rhizosphere environment were solved, achieving precise irrigation control and optimization of the rhizosphere environment, thereby improving seedling quality and production efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-19
- Publication Date
- 2026-03-31
AI Technical Summary
The existing tidal seedling bed irrigation control system cannot correct model parameters and adjust control strategies based on real-time feedback information during the irrigation process, resulting in inaccurate irrigation timing, inability to monitor and regulate the rhizosphere environment in real time, and affecting seedling quality and production costs.
By acquiring photosynthetic radiation, air temperature and humidity, and leaf area index, the comprehensive water evapotranspiration rate is calculated. Combined with liquid level height and matrix impedance phase angle, the irrigation trigger threshold and liquid supply are adjusted in real time. The evapotranspiration model parameters are corrected based on conductivity feedback. The rhizosphere environment is monitored using complex impedance, and low-concentration nutrient solution is flushed.
It enables real-time optimization of irrigation control, improves model prediction accuracy, ensures substrate saturation and rhizosphere health, and enhances seedling growth quality and production efficiency.
Smart Images
Figure CN121753700A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of control, and in particular relates to an intelligent control method and system for tidal seedling beds. Background Technology
[0002] The irrigation control method for tidal seedling beds affects seedling quality and production costs. Irrigation control methods using a timed control mode, where irrigation is initiated at fixed intervals, cannot match the crop's water requirements according to different growth stages, weather changes, and fluctuations in environmental temperature and humidity. While substrate moisture sensors or weighing methods can be used to determine irrigation timing, moisture sensors suffer from poor contact, measurement drift, and poor representativeness of single-point measurements, while weighing methods are expensive and difficult to implement in large-scale production.
[0003] Control methods based on crop evapotranspiration models estimate the total amount of water evaporated and transpired by crops by monitoring environmental parameters such as light, air temperature, and humidity. Irrigation is triggered when the cumulative evapotranspiration reaches a certain threshold. However, key parameters in the model, such as the crop coefficient, cannot be adjusted according to the growth stage, failing to reflect changes in the water-fertilizer absorption ratio caused by crop growth and development and changes in the external environment. When determining the liquid supply for a single irrigation, the changes in the characteristics of the seedling substrate due to root growth and changes in aggregate structure are ignored, making it difficult to ensure that the substrate reaches the appropriate saturation state each time. In addition, existing control systems lack real-time monitoring and regulation of the crop rhizosphere stress state, making it impossible to take intervention measures when the rhizosphere environment deteriorates. Therefore, how to construct a closed-loop intelligent control system that can correct model parameters and adjust control strategies based on real-time feedback information from the irrigation process is a technical problem that urgently needs to be solved in this field. Summary of the Invention
[0004] This invention proposes an intelligent control method for tidal seedbeds to address the problem that existing technologies cannot correct model parameters and adjust control strategies based on real-time feedback information from the irrigation process. The method includes:
[0005] Acquire photosynthetic radiation, air temperature and humidity, and leaf area index; calculate the comprehensive water evapotranspiration rate through a preset evapotranspiration weight matrix; and obtain the cumulative water deficit value by integrating the rate over time.
[0006] When the cumulative water deficit reaches the irrigation trigger threshold, the nutrient solution supply process is initiated. During the nutrient solution supply, the liquid level height data in the bed is collected in real time and the first derivative of the data with respect to time is calculated. When the first derivative value exceeds the inflection point value of the substrate saturation flow rate, the nutrient solution supply is stopped and the duration of this nutrient solution supply is recorded. During the nutrient solution retention period, the complex impedance phase angle of the seedling substrate is measured. After the nutrient solution retention period ends, the nutrient solution is drained, and the conductivity of the returned nutrient solution is measured and the substrate water holding capacity is calculated.
[0007] Based on the comparison between the conductivity measured after drainage and the conductivity of the nutrient solution before irrigation, the crop transpiration coefficient in the evapotranspiration weight matrix is adjusted to reflect the actual water and fertilizer absorption ratio of the crop; the inflection point value of the substrate saturation velocity is updated according to the calculated substrate water holding capacity to adapt to changes in substrate properties.
[0008] By utilizing the statistical deviation between the current nutrient solution supply duration and the historical nutrient solution supply duration, the irrigation trigger threshold for the next irrigation cycle is corrected; when the phase angle deviates from the healthy growth baseline by a preset amount, a low-concentration nutrient solution flushing process is initiated in the next irrigation cycle to improve the rhizosphere stress environment.
[0009] Furthermore, this invention also relates to an intelligent control system for tidal seedling beds, comprising the following modules:
[0010] The calculation module is used to obtain photosynthetic radiation, air temperature and humidity and leaf area index, calculate the comprehensive water evapotranspiration rate through a preset evapotranspiration weight matrix, and obtain the cumulative water deficit value by time integration of the rate.
[0011] The measurement module is used to initiate the nutrient solution supply process when the cumulative water deficit value reaches the irrigation trigger threshold; during the nutrient solution supply, the liquid level height data in the bed is collected in real time and the first derivative of the data with respect to time is calculated; when the first derivative value exceeds the inflection point value of the substrate saturation flow rate, the nutrient solution supply is stopped and the duration of this nutrient solution supply is recorded; during the liquid retention period, the complex impedance phase angle of the seedling substrate is measured; after the liquid retention period ends, the liquid is drained and the conductivity of the returned nutrient solution is measured and the water holding capacity of the substrate is calculated.
[0012] The update module is used to adjust the crop transpiration coefficient in the evapotranspiration weight matrix based on the comparison between the conductivity measured after drainage and the conductivity of the nutrient solution before irrigation, so as to reflect the actual water and fertilizer absorption ratio of the crop; and to update the inflection point value of the substrate saturation velocity according to the calculated substrate water holding capacity, so as to adapt to the changes in substrate properties.
[0013] The improvement module is used to correct the irrigation trigger threshold for the next irrigation cycle by utilizing the statistical deviation between the current nutrient supply duration and the historical nutrient supply duration; when the phase angle deviates from the healthy growth baseline by a preset amount, a low-concentration nutrient solution flushing process is initiated in the next irrigation cycle to improve the rhizosphere stress environment.
[0014] This invention calculates water deficit and determines irrigation timing by integrating environmental and crop growth parameters. It also controls the amount of liquid supplied per cycle by utilizing the characteristic points of the liquid level change rate during the supply process, ensuring coordinated optimization of irrigation initiation and termination. Based on the change in conductivity of the return liquid after irrigation, the crop coefficient in the evapotranspiration model is corrected, and the criteria for determining liquid saturation are updated according to the substrate water holding capacity calculation. This allows the control strategy to follow the evolution of crop water and fertilizer absorption characteristics and substrate physical properties, improving the model's long-term prediction accuracy. Furthermore, by monitoring root complex impedance, rhizosphere environmental stress can be identified in advance, and proactive flushing measures can be taken to improve the root growth environment and ensure robust seedling growth. Attached Figure Description
[0015] Figure 1 A flowchart of the first embodiment;
[0016] Figure 2 This is a schematic diagram for calculating cumulative water deficit.
[0017] Figure 3 This is a schematic diagram illustrating the adjustment of the evaporation coefficient based on conductivity feedback.
[0018] Figure 4 This is a schematic diagram of initiating rhizosphere flushing based on phase angle monitoring. Detailed Implementation
[0019] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.
[0020] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.
[0021] In the first embodiment, the present invention proposes an intelligent control method for tidal seedling beds, such as... Figure 1 ,include:
[0022] S1. Acquire photosynthetic radiation, air temperature and humidity, and leaf area index. Calculate the comprehensive water evapotranspiration rate through a preset evapotranspiration weight matrix and perform time integration on the rate to obtain the cumulative water deficit value.
[0023] The leaf area index is periodically measured by quantum light sensors, air temperature and humidity sensors deployed in the seedling environment, and by multi-angle imaging technology combined with image recognition algorithms. The real-time data is input into an evapotranspiration model based on the Penman-Montes formula, which is the preset evapotranspiration weight matrix. The model comprehensively considers the influence of energy balance terms and aerodynamic terms on water evaporation. The controller calculates the current evapotranspiration rate at a frequency of, for example, once per minute, and accumulates the evapotranspiration amount every minute to form a cumulative water deficit value counted from the end of the last irrigation.
[0024] In an optional embodiment, the steps of acquiring photosynthetic radiation, air temperature and humidity, and leaf area index, calculating the comprehensive water evapotranspiration rate through a preset evapotranspiration weighting matrix, and integrating the rate over time to obtain the cumulative water deficit value include:
[0025] Using a photosynthetic effective radiation sensor, an air temperature and humidity sensor, and a hyperspectral camera placed 1m above the canopy of the seedling bed, photosynthetic radiation, air temperature and humidity, and leaf area index were collected with a sampling cycle of 10 minutes.
[0026] Using formula Calculate the overall water evapotranspiration rate V, where R is the normalized photosynthetic radiation, T is the normalized air temperature, H is the normalized relative humidity, L is the normalized leaf area index, and the coefficient is... This is a preset value for the evaporation weight matrix;
[0027] The calculated comprehensive water evaporation rate is accumulated in 10-minute time steps to obtain the cumulative water deficit value.
[0028] Specifically, environmental data is periodically collected using a sensor array. For example, at 10:00 AM, a photosynthetically active radiation sensor located above the crop canopy measures photosynthetic radiation at 850 μmol / m² / s, an air temperature and humidity sensor measures a temperature of 26℃ and a relative humidity of 65%, and a hyperspectral camera captures canopy images. The leaf area index (LAI) is calculated to be 3.2 using a normalized vegetation index (NVI) algorithm. Based on preset extreme values for parameters such as full-scale photosynthetic radiation (1000 μmol / m² / s), upper temperature reference limit of 40℃, upper humidity limit of 100%, and maximum LVI reference value of 8.0, the raw data is linearly normalized, resulting in: normalized photosynthetic radiation R = 0.85, normalized temperature T = 0.65, normalized relative humidity H = 0.65, and normalized LVI L = 0.4. A preset evapotranspiration weighting model is then used for calculation, employing normalized input to eliminate dimensional influences. The preset weight matrix coefficients are assumed to be: photosynthetic radiation weight. Temperature weight is 10. Humidity weight is 10. The leaf area index weight is 5. The value is 20. Based on the collected data, the instantaneous comprehensive water evapotranspiration rate was calculated using the formula, resulting in 19.75. This value represents the water evapotranspiration intensity under the current environmental and crop conditions. Taking the rate of 19.75 calculated at 10:00 AM as an example, the estimated water deficit increment within the next 10-minute sampling step is 11850. If the cumulative water deficit value before this calculation was 80000, the updated cumulative deficit value becomes 91850. This process is repeated every 10 minutes, continuously updating the cumulative water deficit value until the preset irrigation trigger threshold is reached, such as... Figure 2 Since the effects of temperature and humidity on evapotranspiration are usually not independent, in one embodiment, the saturated vapor pressure difference VPD is calculated using temperature and humidity, and the combined moisture evapotranspiration rate V is obtained by normalizing R, T and VPD respectively and then weighting and summing them.
[0029] S2, When the cumulative water deficit value reaches the irrigation trigger threshold, the liquid supply process is started; during the liquid supply period, the liquid level height data in the bed is collected in real time and the first derivative of the data with respect to time is calculated. When the first derivative value exceeds the inflection point value of the substrate saturation flow rate, the liquid supply is stopped and the duration of this liquid supply is recorded; during the liquid retention period, the complex impedance phase angle of the seedling substrate is measured; after the liquid retention is completed, the liquid is drained and the conductivity of the returned nutrient solution is measured and the substrate water holding capacity is calculated;
[0030] The controller continuously compares the calculated cumulative water deficit with a preset irrigation trigger threshold, such as 350 ml per square meter. Once the deficit is greater than or equal to this threshold, the controller activates the water pump relay to start the water supply. After the water supply begins, the ultrasonic level sensor installed in the seedling bed sends the water level data to the controller once per second. The controller calculates the rate of water level rise, i.e., the first derivative, by dividing the height difference between two adjacent sampling points by the time interval. Because the water level rises slowly when the substrate absorbs water, once the substrate reaches saturation, it cannot quickly absorb the subsequent incoming liquid, and the water level will rise rapidly. The first derivative value will show a significant jump, and this jump point is the substrate saturation flow rate inflection point, for example, a sudden increase from 0.5 cm / s to 2 cm / s. Once the controller detects that this derivative value exceeds the set inflection point value, such as 1.5 cm / s, it immediately disconnects the water pump relay, stops the water supply, and records the total time from pump start to stop.
[0031] Healthy cell membranes possess good integrity and polarity, typically exhibiting a large phase angle. However, if the root system is damaged, aging, or subjected to abiotic stress, cell membrane integrity declines, leading to significant changes in the phase angle. During the nutrient retention phase, from the cessation of nutrient supply to the commencement of drainage, a weak, multi-frequency AC excitation signal is applied through a four-electrode probe inserted into the root zone. The phase difference between the response signal and the excitation signal, known as the complex impedance phase angle, is measured using an impedance spectroscopy analyzer. This value reflects the physiological activity of the roots and the physicochemical properties of the rhizosphere environment. After nutrient retention is complete, the controller opens the electromagnetic drain valve, allowing the nutrient solution to flow back to the storage tank. A conductivity sensor installed in the return pipe measures the conductivity of the returned solution in real time. Simultaneously, the total nutrient supply volume is obtained by multiplying the rated flow rate of the supply pump by the duration of this supply, and then subtracting the total return flow rate measured by the flow meter in the return pipe. The difference between these two values represents the actual water holding capacity of the substrate after this irrigation.
[0032] In an optional embodiment, during the liquid supply, the liquid level height data in the bed is collected in real time and the first derivative of the data with respect to time is calculated. When the value of the first derivative exceeds the inflection point value of the matrix saturation flow rate, the liquid supply is stopped, including:
[0033] The liquid level height data is continuously collected at a sampling frequency of 1 second by an ultrasonic liquid level sensor installed at the bottom of the seedling bed.
[0034] The first derivative of the liquid level height with respect to time is calculated using the backward difference method, i.e. Where H(t) is the liquid level at the current moment, and H(t-1) is the liquid level at the previous moment. The sampling time interval;
[0035] When all three continuously monitored first derivative values are greater than the matrix saturation flow rate inflection point value, the liquid supply solenoid valve is immediately closed to stop the liquid supply.
[0036] After the liquid supply is started, the ultrasonic liquid level sensor located at the bottom of the seedling bed begins to operate at a frequency of 1 second. For example, at the 30th second of the liquid supply, the sensor measures a liquid level height H(30) of 45 mm, while at the 29th second, the recorded height H(29) is 43 mm, with a time interval of [missing information]. The time interval is 1 second. Immediately, the backward difference method is used to calculate the liquid level rise rate v(30) = 2 mm / s at this moment. The calculation process is performed in real time every second, generating a time series data of the liquid level rise rate.
[0037] An internally preset inflection point value for the substrate saturation flow rate is defined. This value represents the critical point at which the liquid permeation rate begins to slow down when the substrate transitions from an unsaturated to a saturated state. For example, this value is set to 1.5 mm / s. The real-time calculated liquid level rise rate is compared with this inflection point value. Assuming that at 35s, the calculated rate v(35) is 1.6 mm / s, which is greater than 1.5. At 36s, the rate v(36) is 1.7 mm / s, which is also greater than 1.5. At 37s, the rate v(37) is 1.8 mm / s, which is still greater than 1.5. At this point, it is detected that three consecutive calculated rate values have exceeded the set inflection point value, indicating that the substrate is close to saturation and excess liquid begins to accumulate rapidly. It is determined that irrigation is sufficient, and an immediate command is issued to close the liquid supply solenoid valve to stop the liquid supply and avoid over-supply.
[0038] S3. Based on the comparison between the conductivity measured after drainage and the conductivity of the nutrient solution before irrigation, the crop transpiration coefficient in the evapotranspiration weight matrix is adjusted to reflect the actual water and fertilizer absorption ratio of the crop; the substrate saturation velocity inflection point value is updated according to the calculated substrate water holding capacity to adapt to changes in substrate properties.
[0039] The controller compares the average conductivity of the returned nutrient solution measured in this study with the initial conductivity of the nutrient solution in the storage tank before irrigation. If the conductivity of the returned solution is higher than the initial value, it indicates that the proportion of water absorbed by the crop is greater than the proportion of nutrients absorbed, suggesting that the actual transpiration is stronger than the model estimate. The controller then uses the crop transpiration coefficient from the evapotranspiration model. The value is increased by a fixed step size, for example, by 2%. Conversely, if the conductivity of the reflux liquid decreases, it indicates that the crop absorbs nutrients at a higher rate, and the actual transpiration is weaker than the model estimate, so the value is decreased. Value. If the two are basically equal, then maintain. The value remains unchanged.
[0040] The controller compares and analyzes the calculated substrate water holding capacity with historical data. As crop roots grow and the substrate structure naturally evolves, the substrate's porosity and water-holding capacity change. For example, when the controller detects a continuous increasing trend in substrate water holding capacity over time, it indicates an increase in the substrate's water storage space, potentially leading to a longer time required for the substrate to reach saturation. This can cause a shift in the inflection point characteristic of the liquid level rise rate. The controller will then fine-tune the substrate saturation flow rate inflection point value used to determine when to stop liquid supply, based on a preset functional relationship or lookup table. For example, it might lower the value from 1.5 cm / s to 1.4 cm / s to ensure that the liquid supply matches the changing substrate conditions.
[0041] In an optional embodiment, adjusting the crop transpiration coefficient in the evapotranspiration weighting matrix based on a comparison between the conductivity measured after drainage and the conductivity of the nutrient solution before irrigation includes:
[0042] If the conductivity measured after drainage is higher than the upper limit of the standard conductivity range, it indicates that the crop's water absorption rate is greater than its nutrient absorption rate. Therefore, in the next irrigation cycle, the weighting coefficients corresponding to the leaf area index in the evapotranspiration weighting matrix will be adjusted. Increased by 5%;
[0043] If the conductivity measured after drainage is lower than the lower limit of the standard conductivity range, it indicates that the crop's nutrient absorption rate is greater than its water absorption rate. Therefore, the weighting coefficient will be adjusted accordingly. Reduced by 5%.
[0044] Specifically, the standard conductivity range is set to 95% to 105% of the nutrient solution conductivity value before irrigation. Before the start of an irrigation cycle, the conductivity of the nutrient solution to be supplied in the storage tank is measured, for example, if the measured value is 2.0 millisiemens per centimeter. Based on this, the reasonable conductivity range for the drained solution after this irrigation is set to 1.9 to 2.1 millisiemens per centimeter. After the irrigation, solution retention, and draining processes are all completed, the conductivity sensor located at the drain outlet measures the conductivity of the collected residual nutrient solution.
[0045] Assuming the measured conductivity of the drained solution is 2.2 millisiemens per centimeter, which is higher than the upper limit of the 2.1 range, this indicates that the crop absorbs more water than nutrients from the nutrient solution, leading to an increased salt concentration in the remaining liquid. This phenomenon suggests that the previous evapotranspiration model may have underestimated the actual transpiration water consumption of the crop. To correct this bias, the weighting coefficient of the leaf area index, which is related to crop transpiration, in the evapotranspiration weighting matrix was adjusted. If currently The value is 1.8, so the value is increased by 5%. The value will become 1.89.
[0046] Conversely, if the measured evaporation conductivity is 1.8 mSiemens per centimeter, below the lower limit of the 1.9 range, it indicates that the rate of nutrient absorption by the crop exceeds the rate of water absorption. This suggests that the evapotranspiration model overestimates actual water consumption. In this case, the weighting coefficients should be adjusted. Reduced by 5%, new The value will become 1.71. Through the closed-loop feedback adjustment, the evapotranspiration model can adapt to the water and fertilizer absorption characteristics of crops at different growth stages, and realize irrigation decisions, such as... Figure 3 .
[0047] In an optional embodiment, updating the substrate saturation velocity inflection point value based on the calculated substrate water holding capacity includes:
[0048] The total supply volume is recorded by the flow meter of the supply pump, and the total return volume is recorded by the flow meter of the return port. The difference between the two is the substrate water holding capacity.
[0049] Compare the currently calculated substrate water holding capacity with the average substrate water holding capacity over 20 historical irrigation cycles;
[0050] If the current water holding capacity of the substrate is lower than 98% of the historical average, the inflection point value of the substrate saturation velocity will be lowered by 2% to adapt to the change in permeation rate caused by the decrease in substrate porosity.
[0051] During a complete irrigation cycle, water volume is measured using two flow meters. For example, the flow meter at the supply pump outlet records a total supply of 6.0 liters, while the flow meter at the return outlet records a total return volume of 2.5 liters during the drainage phase. This calculates the actual water holding capacity of the substrate to be 3.5 liters. This value reflects the total amount of water that the substrate and roots can retain under the current conditions.
[0052] The calculated water holding capacity of 3.5 liters was compared with historical water holding capacity data from the most recent 20 irrigation cycles stored in the database. The average historical value was assumed to be 3.7 liters. The ratio of the current value to the historical average was calculated to be 94.6%. This ratio is lower than a preset threshold of 98%, indicating a decrease in the substrate's water holding capacity due to substrate compaction or root growth occupying pore space. Decreased substrate porosity slows down water infiltration.
[0053] To adapt to these changes and avoid premature saturation and cessation of liquid supply due to slower infiltration, the substrate saturation flow rate inflection point is adjusted. Assuming the current inflection point is 1.5 mm / s, lowering it by 2% will result in a new inflection point of 1.47 mm / s. This new, lower inflection point is used as the basis for determining substrate saturation, thereby ensuring adequate irrigation even with slower infiltration rates.
[0054] S4. By utilizing the statistical deviation between the current nutrient solution supply duration and the historical nutrient solution supply duration, the irrigation trigger threshold for the next irrigation cycle is corrected to compensate for the cumulative error of the evapotranspiration model. When the phase angle deviates from the healthy growth baseline by a preset amount, a low-concentration nutrient solution flushing process is initiated in the next irrigation cycle to improve the rhizosphere stress environment.
[0055] The controller maintains a moving average of the duration of the last ten irrigations. The current irrigation duration is compared to this moving average. If the current duration is longer than the average, it indicates that the actual water requirement of the crop exceeded the evapotranspiration model's prediction during the time interval between the last irrigation and the current irrigation trigger, resulting in a longer wait before the trigger condition is met. To correct this bias, the controller lowers the trigger threshold for the next irrigation from 350 ml / m² to 340 ml / m², causing the next irrigation to occur earlier. Conversely, if the current duration is shorter than the average, the irrigation trigger threshold is increased to calibrate the irrigation timing.
[0056] During the early seedling stage or when the crop is healthy, a set of curves representing the optimal root growth state—the complex impedance phase angle versus frequency—is recorded as a healthy growth baseline. In each irrigation cycle, the controller compares the newly measured phase angle curve with this baseline model and calculates the deviation. If the deviation exceeds a preset tolerance range, such as a phase angle shift exceeding 20° at a certain characteristic frequency, excessive salt accumulation in the rhizosphere, or hypoxia stress, the controller will execute a flushing procedure in the next irrigation cycle. This involves irrigating and draining a low-conductivity nutrient solution or clean water from a storage tank to rinse the rhizosphere and restore a healthy growth environment.
[0057] In an optional embodiment, the step of adjusting the irrigation trigger threshold for the next irrigation cycle by utilizing the statistical deviation between the current irrigation duration and historical irrigation duration includes:
[0058] Calculate the average duration of liquid supply for the most recent 30 irrigation cycles. with standard deviation ;
[0059] If the duration of this fluid supply is greater than If this indicates that the evapotranspiration model has a positive cumulative error, then the irrigation trigger threshold for the next irrigation cycle will be reduced by 3% from the current value.
[0060] If the duration of this fluid supply is less than If the evapotranspiration model has a negative cumulative error, then the irrigation trigger threshold for the next irrigation cycle will be increased by 3% based on the current value.
[0061] Specifically, a database containing the duration of the most recent 30 irrigations is maintained. Based on this data, statistical analysis is performed to calculate the average duration of the irrigation. and standard deviation For example, the average liquid supply time can be calculated. 240 seconds, standard deviation The duration is 12 seconds. Based on the aforementioned statistics, a normal infusion duration range is established, with a statistically significant upper and lower limit of 258 seconds and 222 seconds, respectively.
[0062] After this irrigation cycle ends, the actual water supply duration is recorded, assumed to be 265 seconds. This duration exceeds the statistical upper limit of 258 seconds, and is therefore considered an abnormally long water supply event. From the end of the last irrigation to the triggering of this irrigation, the actual accumulated water deficit is greater than calculated by the evapotranspiration model, resulting in a longer time required to replenish water to substrate saturation. The evapotranspiration model exhibits a positive cumulative error, meaning it underestimates water consumption. To correct this trend, the irrigation trigger threshold for the next irrigation cycle will be adjusted. If the current threshold is a cumulative water deficit of 90,000, the new threshold will be reduced by 3%, becoming 87,300.
[0063] Conversely, if the duration of this irrigation supply is 215 seconds, which is less than the statistical lower limit of 222 seconds, it indicates that the model has overestimated water consumption, causing irrigation to be triggered too early. In this case, the irrigation trigger threshold is increased by 3% from the current value, and the new threshold becomes 92700. Through the statistical feedback based on irrigation behavior, the cumulative error of the water deficit model can be calibrated over a long period.
[0064] In an optional embodiment, when the phase angle deviates from the healthy growth baseline by a preset amount, a low-concentration nutrient solution flushing process is initiated in the next irrigation cycle, including:
[0065] The healthy growth baseline is the arithmetic mean of the complex impedance phase angles measured at noon each day from day 7 to day 14 under standard management.
[0066] The preset amplitude is defined as a negative deviation of 20% from the baseline model value.
[0067] When the phase angle is detected to meet the above conditions, the flushing process is started. The process uses a low-concentration nutrient solution with 50% conductivity as the main nutrient solution to perform a complete irrigation-liquid retention-liquid drainage process.
[0068] To establish a baseline for root impedance phase angle under healthy crop growth conditions, a period of vigorous and stable physiological activity is observed from day 7 to day 14 after crop transplanting. Complex impedance in the root zone is measured daily at noon using electrodes implanted in the substrate, and the phase angle is recorded. For example, the phase angles measured over eight consecutive days are -18.2°, -18.5°, -18.3°, -18.6°, -18.4°, -18.7°, -18.5°, and -18.3°. The arithmetic mean of these values is calculated to obtain the healthy growth baseline value, which is -18.44°. Alternatively, a correspondence can be established between time intervals and the arithmetic mean of complex impedance phase angles, such as the arithmetic mean of complex impedance phase angles from 6-8 AM and from 8-10 AM. The healthy growth baseline is determined based on the current irrigation time, and the phase angles measured during the water retention period are compared with the corresponding healthy growth baseline.
[0069] A warning threshold was set: a 20% negative deviation of the phase angle from the baseline model value. The calculated trigger threshold was -22.13°. The phase angle was measured daily at noon. For example, on day 35, the measured phase angle was -22.5°. This value was more negative than -22.13°, meeting the trigger condition. A negative deviation of the phase angle usually indicates excessively high ion concentration in the rhizosphere environment, i.e., salt stress, which affects the normal physiological functions of the roots.
[0070] Once a phase angle meeting the required conditions is detected, it is marked in the control program, and a special flushing process is planned for the next irrigation cycle. When the next irrigation cycle starts as planned, instead of using the standard nutrient solution, the solution preparation system is instructed to prepare and supply a low-concentration nutrient solution. This nutrient solution has a conductivity only half that of the standard formulation, for example, reduced from 2.0 mSiemens per centimeter to 1.0 mSiemens per centimeter. A complete irrigation, retention, and drainage process is performed using this low-concentration nutrient solution, thoroughly rinsing the substrate with the lower osmotic pressure liquid, dissolving and draining excess salt accumulated in the root zone, thereby alleviating salt stress in the crop. Figure 4 .
[0071] In the second embodiment, the present invention also proposes an intelligent control system for tidal seedling beds, comprising the following modules:
[0072] The calculation module is used to obtain photosynthetic radiation, air temperature and humidity and leaf area index, calculate the comprehensive water evapotranspiration rate through a preset evapotranspiration weight matrix, and obtain the cumulative water deficit value by time integration of the rate.
[0073] The measurement module is used to initiate the nutrient solution supply process when the cumulative water deficit value reaches the irrigation trigger threshold; during the nutrient solution supply, the liquid level height data in the bed is collected in real time and the first derivative of the data with respect to time is calculated; when the first derivative value exceeds the inflection point value of the substrate saturation flow rate, the nutrient solution supply is stopped and the duration of this nutrient solution supply is recorded; during the liquid retention period, the complex impedance phase angle of the seedling substrate is measured; after the liquid retention period ends, the liquid is drained and the conductivity of the returned nutrient solution is measured and the water holding capacity of the substrate is calculated.
[0074] The update module is used to adjust the crop transpiration coefficient in the evapotranspiration weight matrix based on the comparison between the conductivity measured after drainage and the conductivity of the nutrient solution before irrigation, so as to reflect the actual water and fertilizer absorption ratio of the crop; and to update the inflection point value of the substrate saturation velocity according to the calculated substrate water holding capacity, so as to adapt to the changes in substrate properties.
[0075] The improvement module is used to correct the irrigation trigger threshold of the next irrigation cycle by utilizing the statistical deviation between the current nutrient supply duration and the historical nutrient supply duration, and to compensate for the cumulative error of the evapotranspiration model; when the phase angle deviates from the healthy growth baseline by a preset amount, a low-concentration nutrient solution flushing process is started in the next irrigation cycle to improve the rhizosphere stress environment.
[0076] In an optional embodiment, the steps of acquiring photosynthetic radiation, air temperature and humidity, and leaf area index, calculating the comprehensive water evapotranspiration rate through a preset evapotranspiration weighting matrix, and integrating the rate over time to obtain the cumulative water deficit value include:
[0077] Using a photosynthetic effective radiation sensor, an air temperature and humidity sensor, and a hyperspectral camera placed 1m above the canopy of the seedling bed, photosynthetic radiation, air temperature and humidity, and leaf area index were collected with a sampling cycle of 10 minutes.
[0078] Using formula Calculate the overall water evapotranspiration rate V, where R is the normalized photosynthetic radiation, T is the normalized air temperature, H is the normalized relative humidity, L is the normalized leaf area index, and the coefficient is... This is a preset value for the evaporation weight matrix;
[0079] The calculated comprehensive water evaporation rate is accumulated in 10-minute time steps to obtain the cumulative water deficit value.
[0080] In an optional embodiment, during the liquid supply, the liquid level height data in the bed is collected in real time and the first derivative of the data with respect to time is calculated. When the value of the first derivative exceeds the inflection point value of the matrix saturation flow rate, the liquid supply is stopped, including:
[0081] The liquid level height data is continuously collected at a sampling frequency of 1 second by an ultrasonic liquid level sensor installed at the bottom of the seedling bed.
[0082] The first derivative of the liquid level height with respect to time is calculated using the backward difference method, i.e. Where H(t) is the liquid level at the current moment, and H(t-1) is the liquid level at the previous moment. The sampling time interval;
[0083] When all three continuously monitored first derivative values are greater than the matrix saturation flow rate inflection point value, the liquid supply solenoid valve is immediately closed to stop the liquid supply.
[0084] In an optional embodiment, adjusting the crop transpiration coefficient in the evapotranspiration weighting matrix based on a comparison between the conductivity measured after drainage and the conductivity of the nutrient solution before irrigation includes:
[0085] If the conductivity measured after drainage is higher than the upper limit of the standard conductivity range, it indicates that the crop's water absorption rate is greater than its nutrient absorption rate. Therefore, in the next irrigation cycle, the weighting coefficients corresponding to the leaf area index in the evapotranspiration weighting matrix will be adjusted. Increased by 5%;
[0086] If the conductivity measured after drainage is lower than the lower limit of the standard conductivity range, it indicates that the crop's nutrient absorption rate is greater than its water absorption rate. Therefore, the weighting coefficient will be adjusted accordingly. Reduced by 5%.
[0087] In an optional embodiment, updating the substrate saturation velocity inflection point value based on the calculated substrate water holding capacity includes:
[0088] The total supply volume is recorded by the flow meter of the supply pump, and the total return volume is recorded by the flow meter of the return port. The difference between the two is the substrate water holding capacity.
[0089] Compare the currently calculated substrate water holding capacity with the average substrate water holding capacity over 20 historical irrigation cycles;
[0090] If the current water holding capacity of the substrate is lower than 98% of the historical average, the inflection point value of the substrate saturation velocity will be lowered by 2% to adapt to the change in permeation rate caused by the decrease in substrate porosity.
[0091] In an optional embodiment, the step of adjusting the irrigation trigger threshold for the next irrigation cycle by utilizing the statistical deviation between the current irrigation duration and historical irrigation duration includes:
[0092] Calculate the average duration of liquid supply for the most recent 30 irrigation cycles. with standard deviation ;
[0093] If the duration of this fluid supply is greater than If this indicates that the evapotranspiration model has a positive cumulative error, then the irrigation trigger threshold for the next irrigation cycle will be reduced by 3% from the current value.
[0094] If the duration of this fluid supply is less than If the evapotranspiration model has a negative cumulative error, then the irrigation trigger threshold for the next irrigation cycle will be increased by 3% based on the current value.
[0095] In an optional embodiment, when the phase angle deviates from the healthy growth baseline by a preset amount, a low-concentration nutrient solution flushing process is initiated in the next irrigation cycle, including:
[0096] The healthy growth baseline is the arithmetic mean of the complex impedance phase angles measured at noon each day from day 7 to day 14 under standard management.
[0097] The preset amplitude is defined as a negative deviation of 20% from the baseline model value.
[0098] When the phase angle is detected to meet the above conditions, the flushing process is started. The process uses a low-concentration nutrient solution with 50% conductivity as the main nutrient solution to perform a complete irrigation-liquid retention-liquid drainage process.
[0099] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.
[0100] The functional modules shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.
[0101] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.
[0102] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.
[0103] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.
Claims
1. A tidal type seedling bed intelligent control method, characterized in that, The method comprises the following steps: obtaining photosynthetic radiation, air temperature and humidity, and leaf area index, calculating the comprehensive water evapotranspiration rate through a preset evapotranspiration weight matrix, and time-integrating the rate to obtain cumulative water deficit values; when the cumulative water deficit values reach an irrigation triggering threshold, starting the liquid supply process; during the liquid supply, collecting the liquid level height data in the bed in real time and calculating the first-order derivative of the data with respect to time, when the first-order derivative value exceeds the matrix saturated flow rate inflection point value, stopping the liquid supply and recording the current liquid supply duration; during the liquid retention, measuring the complex impedance phase angle of the nursery substrate; after the liquid retention ends, performing liquid drainage and measuring the conductivity of the backflow nutrient solution and calculating the matrix water holding capacity; based on the comparison result of the conductivity measured after the liquid drainage and the conductivity of the nutrient solution before the irrigation, adjusting the crop transpiration coefficient in the evapotranspiration weight matrix to reflect the actual water and fertilizer absorption ratio of the crop; according to the calculated matrix water holding capacity, updating the matrix saturated flow rate inflection point value to adapt to the change of the matrix properties; using the statistical deviation of the current liquid supply duration and the historical liquid supply duration to correct the irrigation triggering threshold of the next irrigation cycle; when the phase angle deviates from the healthy growth baseline by a preset amplitude, starting the low-concentration nutrient solution flushing process in the next irrigation cycle to improve the rhizosphere stress environment.
2. The method of claim 1, wherein, The method for obtaining photosynthetic radiation, air temperature and humidity, and leaf area index, calculating the comprehensive water evapotranspiration rate through a preset evapotranspiration weight matrix, and time-integrating the rate to obtain cumulative water deficit values comprises: through the photosynthetic active radiation sensor, the air temperature and humidity sensor, and the hyperspectral camera arranged 1m above the canopy of the nursery bed, collecting the photosynthetic radiation, air temperature and humidity, and leaf area index at a sampling period of 10 minutes; The integrated water evapotranspiration rate V is calculated using the formula where R is the normalized photosynthetic radiation, T is the normalized air temperature, H is the normalized air relative humidity, L is the normalized leaf area index, and the coefficients are preset values for the evapotranspiration weight matrix; at a time step of 10 minutes, accumulating the calculated comprehensive water evapotranspiration rate to obtain the cumulative water deficit values.
3. The method of claim 1, wherein, The method for collecting the liquid level height data in the bed in real time during the liquid supply and calculating the first-order derivative of the data with respect to time, when the first-order derivative value exceeds the matrix saturated flow rate inflection point value, stopping the liquid supply comprises: through the ultrasonic liquid level sensor installed at the bottom of the nursery bed, continuously collecting the liquid level height data at a sampling frequency of 1s; using the backward difference method to calculate the first-order derivative of the liquid level height with respect to time; when the three continuously monitored first-order derivative values are all greater than the matrix saturated flow rate inflection point value, immediately closing the liquid supply electromagnetic valve to stop the liquid supply.
4. The method of claim 1, wherein, The method for adjusting the crop transpiration coefficient in the evapotranspiration weight matrix based on the comparison result of the conductivity measured after the liquid drainage and the conductivity of the nutrient solution before the irrigation comprises: If the conductivity measured after drainage is higher than the upper limit of the standard conductivity interval, it indicates that the water absorption rate of the crop is greater than the nutrient absorption rate, and in the next irrigation cycle, the weight coefficient corresponding to the leaf area index in the evapotranspiration weight matrix up-regulation 5%; If the conductivity measured after draining is lower than the lower limit of the standard conductivity interval, it indicates that the crop nutrient uptake rate is greater than the water uptake rate, and the weight coefficient Down 5%.
5. The method of claim 1, wherein, The method for updating the matrix saturated flow rate inflection point value according to the calculated matrix water holding capacity comprises: recording the total liquid supply amount through the flowmeter of the liquid supply pump, and recording the total backflow amount through the flowmeter of the backflow port, and the difference between the two is the matrix water holding capacity; comparing the currently calculated matrix water holding capacity with the average value of the matrix water holding capacity in the last 20 irrigation cycles; if the current matrix water holding capacity is lower than 98% of the historical average value, then the matrix saturated flow rate inflection point value is lowered by 2% to adapt to the change of the infiltration rate caused by the decrease of the matrix porosity.
6. The method of claim 1, wherein, The irrigation trigger threshold of the next irrigation cycle is corrected by using the statistical deviation of the current liquid supply duration and the historical liquid supply duration, including: Calculate the average of the length of the supply of liquid for the last 30 irrigation cycles with the standard deviation ; If the current liquid supply time is greater than , it indicates that the evapotranspiration model has a positive cumulative error, and the irrigation trigger threshold for the next irrigation cycle is reduced by 3% based on the current value. If the current liquid supply duration is less than , it indicates that there is a negative cumulative error in the evapotranspiration model, and the irrigation trigger threshold for the next irrigation cycle is increased by 3% based on the current value.
7. The method of claim 1, wherein, When the phase angle deviates from the healthy growth baseline by a preset amplitude, a low-concentration nutrient liquid flushing process is started in the next irrigation cycle, including: The healthy growth baseline is the arithmetic mean of the phase angle of the complex impedance measured at 12:00 noon every day during the 7th to 14th day under standard management; The preset amplitude is a negative deviation of 20% from the baseline model value; When the phase angle meets the above conditions, the flushing process is started, which uses a low-concentration nutrient liquid with a conductivity of 50% of the main nutrient liquid formula to perform a complete irrigation-liquid preservation-liquid discharge process.
8. A tidal type seedling bed intelligent control system, characterized in that, The following modules are included: A calculation module is used to obtain photosynthetic radiation, air temperature and humidity, and leaf area index, calculate the comprehensive water evaporation rate through a preset evaporation weight matrix, and time-integrate the rate to obtain the cumulative water deficit value; A measurement module is used to start the liquid supply process when the cumulative water deficit value reaches the irrigation trigger threshold; During the liquid supply, the liquid level height data in the bed is collected in real time and the first-order derivative of the data with respect to time is calculated, and when the first-order derivative value exceeds the matrix saturation flow rate inflection point value, the liquid supply is stopped and the current liquid supply duration is recorded; During the liquid preservation, the phase angle of the complex impedance of the nursery substrate is measured; After the liquid preservation is completed, the liquid is discharged, and the conductivity of the backflow nutrient liquid and the matrix water holding capacity are measured; An update module is used to adjust the crop transpiration coefficient in the evaporation weight matrix based on the comparison result of the conductivity measured after the liquid discharge and the conductivity of the nutrient liquid before irrigation, to reflect the actual water and fertilizer absorption ratio of the crop; and update the matrix saturation flow rate inflection point value according to the calculated matrix water holding capacity, to adapt to the change of the matrix properties; An improvement module is used to correct the irrigation trigger threshold of the next irrigation cycle by using the statistical deviation of the current liquid supply duration and the historical liquid supply duration; When the phase angle deviates from the healthy growth baseline by a preset amplitude, a low-concentration nutrient liquid flushing process is started in the next irrigation cycle, to improve the rhizosphere stress environment.
9. The system of claim 8, wherein, The photosynthetic radiation, air temperature and humidity, and leaf area index are obtained, the comprehensive water evaporation rate is calculated through a preset evaporation weight matrix, and the rate is time-integrated to obtain the cumulative water deficit value, including: The photosynthetic radiation, air temperature and humidity, and leaf area index are collected by a photosynthetically active radiation sensor, an air temperature and humidity sensor, and a hyperspectral camera arranged 1m above the canopy of the nursery bed, with a sampling period of 10 minutes; The integrated water evapotranspiration rate V is calculated using the formula where R is the normalized photosynthetic radiation, T is the normalized air temperature, H is the normalized air relative humidity, L is the normalized leaf area index, and the coefficients are preset values for the evapotranspiration weight matrix; The calculated comprehensive water evaporation rate is accumulated in steps of 10 minutes to obtain the cumulative water deficit value.
10. The system of claim 8, wherein, During the liquid supply, the liquid level height data in the bed is collected in real time and the first-order derivative of the data with respect to time is calculated, and when the first-order derivative value exceeds the matrix saturation flow rate inflection point value, the liquid supply is stopped, including: The liquid level height data is continuously collected by an ultrasonic liquid level sensor installed at the bottom of the nursery bed, with a sampling frequency of 1s; The first-order derivative of the liquid level height with respect to time is calculated by using the backward difference method; When the three first derivative values monitored continuously are all greater than the matrix saturation flow rate inflection point value, immediately close the liquid supply solenoid valve and stop supplying liquid.