A cooperative myrica rubra fungus fertilizer irrigation operation system

Abstract

The application discloses a kind of collaborative waxberry bacterial fertilizer irrigation operation systems, including cultivation area inspection mechanism, intelligent collaborative fermentation and modulation center and central host computer system.Patrol mechanism carries out two-dimensional translation and vertical lifting inspection under the control of main control system with soil detection needle and water injection hole.Main control system virtually divides cultivation area into multiple grid areas, constructs second-order polynomial regression model using continuously rolling collected historical humidity data, and forecasts soil moisture consumption trend in advance.Modulation center includes composite microbial fermentation tank and servo variable frequency proportional mixing valve, which is used to dynamically adjust dilution ratio and output corresponding concentration of bacterial fertilizer liquid to each grid.Main control system automatically calculates the historical interval that makes the absolute difference between average humidity after irrigation and constant target value minimum as the irrigation time interval of next cycle through the subgroup matching self-learning algorithm of historical irrigation record.

Description

Technical Field

[0001] This invention relates to the field of agricultural equipment technology, specifically a collaborative bayberry microbial fertilizer irrigation system. Background Technology

[0002] As a characteristic subtropical evergreen fruit tree in southern my country, the waxberry possesses extremely unique physiological characteristics. On the one hand, waxberries are extremely sensitive to water conditions, preferring moist conditions but being severely susceptible to waterlogging. Prolonged excessive soil moisture or poor drainage can easily lead to root suffocation and rot, resulting in severe fruit cracking during ripening. Conversely, periods of drought can cause poor fruit development, reduced quality, and even widespread fruit drop. Therefore, maintaining a dynamic balance of rhizosphere soil moisture and implementing precise, grid-based regulation are crucial for achieving high yields and quality waxberries. On the other hand, waxberries are a species highly dependent on mycorrhizal fungi for symbiosis. Their root development, stress resistance, and absorption of insoluble phosphorus, potassium, and other minerals from the soil are deeply dependent on the activity of beneficial microbial communities in the rhizosphere. In modern cultivation, the application of compound microbial fertilizers has become a core method for improving the soil structure of waxberry orchards and enhancing the quality of waxberry fruit.

[0003] Traditional irrigation equipment often uses timed and quantitative control or on / off control based on soil moisture thresholds at a single point in time. Because soil moisture movement and plant transpiration exhibit significant lag and spatial heterogeneity, this simple threshold feedback control cannot predict soil moisture consumption trends in advance based on weather changes and the real-time physiological needs of the waxberry plant. This often results in soil moisture continuing to rise after irrigation stops, or the soil becoming excessively dry before irrigation resumes, failing to meet the waxberry's demanding requirement for a constant humidity environment.

[0004] In summary, the present invention provides a collaborative bayberry microbial fertilizer irrigation system to solve the above-mentioned problems. Summary of the Invention

[0005] This invention provides a collaborative bayberry microbial fertilizer irrigation system. By constructing a gridded spatiotemporal trend prediction model of the cultivation area and conducting strong collaborative adjustment with the on-site live microbial fertilizer high-density fermentation and multi-gradient frequency conversion dilution center, it solves the problems in the prior art where automatic irrigation feedback lag easily leads to bayberry root rot or fruit cracking, factory pre-made microbial fertilizer is easily deactivated during long-distance transportation, and the measurement and control system and microbial fertilizer modulation center are isolated from each other and cannot achieve spatiotemporal deep self-learning collaboration.

[0006] The specific technical solution of this invention is as follows:

[0007] A collaborative bayberry microbial fertilizer irrigation system includes a cultivation area inspection mechanism, an intelligent collaborative fermentation and modulation center, and a central control microcomputer system.

[0008] The cultivation area inspection mechanism carries a soil detection needle and a water injection hole, and moves horizontally and vertically within the cultivation area under the control of the central main control microcomputer system.

[0009] The intelligent collaborative fermentation and modulation center includes a composite microbial fermenter and a servo frequency conversion proportional mixing valve connected to the liquid outlet of the fermenter. The servo frequency conversion proportional mixing valve is connected to the water injection hole through a liquid delivery pipeline.

[0010] The central control microcomputer system is electrically connected to the cultivation area inspection mechanism, soil probe and servo frequency conversion proportional mixing valve respectively. It virtually divides the cultivation area into multiple grid areas and controls the cultivation area inspection mechanism to periodically collect the current soil moisture of each grid area.

[0011] The central control microcomputer system constructs a second-order polynomial regression model based on the historical humidity data continuously collected from each grid area to predict the soil moisture consumption trend, and dynamically adjusts the dilution ratio of the servo frequency conversion proportional mixing valve accordingly, so as to output the corresponding concentration of diluted bacterial fertilizer solution to the corresponding grid area.

[0012] As a further preferred embodiment of the above technical solution, the system relies on a three-dimensional truss structure for spatial inspection. Its base features planting frames to accommodate bayberry cultivation units, with an overall support frame extending upwards around the planting frames. In the two-dimensional horizontal plane at the top of the support frame, horizontal slide rails are fixedly arranged laterally, and a longitudinal optical axis is arranged parallel to the longitudinal direction. A drive motor, via a belt, drives a slider to move laterally along the horizontal slide rails, simultaneously causing the longitudinal optical axis to move laterally as well. A sliding irrigation platform is supported on the longitudinal optical axis. Driven by the belt of the longitudinal drive motor, the irrigation platform moves longitudinally along the longitudinal optical axis, thereby achieving precise translational inspection of the entire cultivation area within the two-dimensional horizontal and vertical planes.

[0013] The irrigation platform further integrates a vertical lifting mechanism responsible for vertical movement. This mechanism includes a vertical stepper motor, whose output shaft drives a central gear. Two sliding rods, symmetrically meshed on either side of the central gear, slide vertically in opposite directions. One sliding rod's bottom end connects to the soil probe, and the other connects to the water injection hole. By rotating the stepper motor left or right, the central gear is driven, allowing the two sliding rods to move vertically in opposite directions synchronously, thus achieving self-balancing lifting of the vertical axis. A fixed horizontal distance is maintained between the soil probe and the water injection hole. The soil probe includes two fixed-diameter stainless steel probes as resistive probes, with their roots sealed by a 3D-printed shell for rapid impedance sensing of soil moisture at specific soil depths.

[0014] At the levels of system control, process fermentation, and self-learning algorithms, the above system further includes the following preferred features:

[0015] The composite microbial fermenter is equipped with a heating and temperature control device and an air pump aeration device. The heating and temperature control device maintains the temperature inside the fermenter at 26 to 30 degrees Celsius.

[0016] The composite microbial fermenter is also equipped with an online pH meter and an alkaline solution titration pump. The central main control microcomputer system dynamically controls the alkaline solution titration pump to drip alkaline solution according to the real-time reading of the online pH meter, so as to maintain the pH of the microbial fertilizer fermentation liquid between 6.5 and 7.0.

[0017] The composite microbial fermenter is also equipped with an automatic dynamic feeder, which performs quantitative six-stage batch feeding on days 0, 2, 4, 6, 8 and 10 of the microbial fertilizer fermentation cycle, and the raw material ratio for microbial fertilizer fermentation in the fermenter adopts a ten-fold culture medium ratio.

[0018] The central control microcomputer system runs a main control program and is connected to a microcontroller development board; the main control program has a graphical user interface, which reflects the soil moisture level of each grid area in real time through the color depth of the matrix area.

[0019] The central control microcomputer system is equipped with an irrigation counter for each grid area. The initial value of the irrigation counter is calculated by dividing the preset single irrigation interval by the inspection and sensing interval. Each time the cultivation area inspection mechanism performs a sensing operation on the corresponding grid area, the irrigation counter automatically decrements by one until it decreases to zero, at which point an irrigation command is triggered.

[0020] The central control microcomputer system records the current timestamp, current irrigation interval, and pre-irrigation humidity value each time an irrigation command is triggered. During the next pre-irrigation inspection after the irrigation interval, it collects the current soil humidity of each grid area as the end-of-irrigation humidity. The above data are stored together in the central database as associated data to generate historical irrigation record items.

[0021] When the irrigation counter in the grid area reaches zero and triggers the adjustment decision for the next irrigation cycle, the central control microcomputer system reads the current soil moisture and searches the central database for all historical irrigation records whose pre-irrigation moisture values ​​match the current soil moisture. The searched records are then grouped and categorized according to their corresponding historical irrigation intervals to obtain multiple historical record sets.

[0022] The central control microcomputer system calculates the average end-of-irrigation humidity corresponding to each historical record set, compares the absolute difference between the preset target value of constant humidity in the rhizosphere of the bayberry and the average end-of-irrigation humidity, selects the historical record set that minimizes the absolute difference, and uses the historical irrigation interval time corresponding to the set as the next irrigation interval time for the grid area.

[0023] When the central control microcomputer system detects that the current soil moisture is higher than the preset safe high threshold through the soil probe, it automatically extends the next irrigation interval. Furthermore, during the initial stage of system operation when there is no matching record in the central database, the central control microcomputer system directly calls the second-order polynomial regression model to calculate and determine the irrigation interval.

[0024] In this invention, when the future soil moisture consumption trend predicted by the second-order polynomial regression model is lower than the dry safety red line within a set time period, the central main control microcomputer system sends a strong intervention signal to control the cultivation area inspection agency to move to the corresponding grid area in real time to perform targeted microbial fertilizer spraying.

[0025] In this invention, "matching" means that the absolute difference between the historical humidity value before irrigation and the current soil humidity is within a preset allowable error range, thereby improving the reuse rate of historical records and the stability of grouping and classification.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. This invention achieves forward-looking, full-grid soil constant humidity control by constructing a second-order polynomial regression trend prediction model. It effectively eliminates the severe sensor hysteresis effect caused by drastic environmental fluctuations or irrigation actions, maintaining constant humidity in the rhizosphere soil of bayberry trees with extremely high precision. This effectively alleviates the problems of root rot or large-scale fruit cracking and drop caused by the untimely traditional single-point threshold feedback control.

[0028] 2. This invention achieves high-viability on-site maturation of functional microbial fertilizer specifically for bayberries by integrating temperature control, aeration, closed-loop pH response, and a six-stage batch feeding process at the on-site conditioning center. It successfully overcomes the problems of metabolite accumulation and large-scale lysis and death of bacteria caused by long-distance transportation of traditional industrial pre-made microbial fertilizers. At the bayberry application terminal, it ensures extremely high viable and total bacterial counts, greatly promoting the dominant symbiotic relationship and colonization efficiency of microorganisms in the bayberry rhizosphere.

[0029] 3. This invention achieves a strong collaborative closed loop of water, fertilizer, and microorganisms in the spatiotemporal dimensions through a cluster matching self-learning algorithm based on historical irrigation records. The system can deeply bind the actual soil water absorption performance of each spatial zone with the variable frequency mixing valve in the central modulation center. Through minimum difference convergence calculation, it automatically and dynamically configures the optimal dilution and physicochemical concentration for different grid points, realizing precision management in modern agriculture. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the overall structure of the present invention.

[0031] Figure 2 This is a top view of the structure of the present invention.

[0032] The attached diagram is labeled as follows: 1. Planting frame; 2. Support frame; 3. Irrigation platform; 4. Drive motor; 5. Slider; 6. Optical axis; 7. Slide rail. Detailed Implementation

[0033] The embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0034] like Figures 1-2 As shown, this invention provides a collaborative bayberry microbial fertilizer irrigation system, including a planting frame 1 for accommodating bayberry trees and their cultivation soil. An integral support frame 2 extends upwards from the outside of the planting frame 1. A three-axis truss translation mechanism is mounted on the top of the support frame 2, serving as the physical movement body for the cultivation area inspection mechanism. A horizontally parallel slide rail 7 is fixed at the top of the support frame 2, and a slider 5 is slidably connected to the slide rail 7. The slider 5 is connected to a horizontally positioned drive motor 4 via a belt drive, enabling the drive motor 4 to drive the slider 5 to perform horizontal translation along the slide rail 7. A longitudinally extending optical axis 6 is fixedly connected to the horizontally sliding slider 5, allowing the optical axis 6 to move horizontally synchronously with the slider 5. An irrigation platform 3 slides on the optical axis 6, driven by another longitudinally positioned motor and a belt, allowing it to move longitudinally along the optical axis 6. Thus, by utilizing the cooperation of two sets of drive motors 4 (horizontal and longitudinal), the irrigation platform 3 can perform arbitrary two-dimensional translational inspection within the horizontal plane above the planting frame 1.

[0035] A vertical lifting mechanism is further integrated into the irrigation platform 3. Internally, it includes a vertically oriented stepper motor and a central gear. Two sliding rods, symmetrically meshed on either side of the central gear, slide vertically in opposite directions. The bottom ends of the two sliding rods are vertically fixed with soil probes and water injection holes, respectively, maintaining a fixed horizontal distance of 3 cm between the soil probes and the water injection holes. The soil probes utilize two 0.2 cm diameter stainless steel probes as resistance probes, with their roots sealed using a 3D-printed shell.

[0036] This system also includes an intelligent collaborative fermentation and modulation center, which consists of a 50-liter high-density fermenter for functional microorganisms and a servo-controlled variable frequency proportional mixing valve connected to its bottom outlet. This mixing valve is connected to a water injection hole that moves synchronously with the irrigation platform 3 via a highly flexible infusion pipeline. The core command of the system is a central main control microcomputer system, which is electrically connected to the drive motor 4, the stepper motor in the vertical lifting mechanism, the soil probe, and the servo-controlled variable frequency proportional mixing valve.

[0037] Example: The high-density fermentation tank of the intelligent collaborative fermentation and modulation center contains a specific ratio of bayberry-specific compound microbial fertilizer culture medium. The raw materials mainly include whole milk powder culture medium and molasses carbon source, and it is inoculated with 11 kinds of compound microbial agents, including endomycorrhizal fungi, ectomycorrhizal fungi, nitrogen-fixing bacteria, phosphate-solubilizing bacteria, and actinomycetes. The fermentation tank uses a 10:1 ratio of culture medium. The built-in heating and temperature control device maintains the internal temperature at a constant 28±2℃, and the air pump aeration device continuously oxygenates the tank at an equivalent disturbance rate of 120 rpm. An online pH meter is installed on the side wall of the fermentation tank. The central main control microcomputer system reads the pH meter reading in real time and controls the alkali titration pump to automatically add 1.0M sodium hydroxide solution into the tank, strictly locking the pH of the microbial fertilizer fermentation liquid between 6.5 and 7.0. To significantly extend the logarithmic growth phase of microorganisms and inhibit lysis and death of bacteria, the configured automatic dynamic feeder automatically performs quantitative six-stage batch feeding on days 0, 2, 4, 6, 8, and 10 of the microbial fertilizer fermentation cycle. On day 12, when fermentation is complete and the maximum bacterial count level is reached, on-site collaborative irrigation is initiated.

[0038] The central control microcomputer system uses a main control program written in C# and interacts with an Arduino Mega2560 microcontroller development board in real time via serial communication. The main control program virtually divides the cultivation area within the planting frame 1 into nine virtual grid zones (Zone 0 to Zone 8) in a 3x3 matrix format. The graphical user interface dynamically reflects the soil moisture level of each zone through color variations. Each virtual grid zone has an independent irrigation counter (Counter). In this embodiment, the preset historical optimal irrigation interval is set to 240 minutes, while the interval for the system's horizontal and vertical drive motors 4 to periodically inspect and sense the irrigation platform 3 is set to 30 minutes. Therefore, the initial setting value of the irrigation counter (Counter) is calculated to be 8.

[0039] After the system starts, the drive motor 4 controls the irrigation platform 3 to move sequentially to the center above each virtual grid partition. The stepper motor of the vertical lifting mechanism rotates, driving the central gear, and the sliding rod on one side extends downward, allowing the soil probe to insert into the cultivated soil at the appropriate depth to collect the current soil moisture. After each inspection and sensing operation, the irrigation counter Counter for that partition automatically decrements by one. When the Counter for that partition reaches 0, the main control program immediately triggers the irrigation command. Before the microbial fertilizer solution is sprayed from the water injection hole, the soil probe first collects the current soil moisture at that point and uses it as the pre-irrigation moisture value h_p. At the same time, the main control program records the current system timestamp t and combines it with the current irrigation interval time T. After this irrigation interval time has elapsed and the next inspection node before irrigation is reached, the probe measures the soil moisture at that point again and uses it as the end-of-irrigation moisture h_c. These data are automatically stored in the central database in a four-tuple record format of (t, T, h_p, h_c), generating historical irrigation record items.

[0040] During continuous system operation, each time the central control microcomputer system collects the current soil moisture h_i of a certain grid area, it automatically extracts the most recent 8 historical moisture data continuously collected from the central database for that area. It then calls upon a mathematical function library to construct a high-precision second-order polynomial regression model, thereby fitting a quadratic polynomial curve within the software to proactively predict the soil moisture consumption trend line for that specific area in the next 2 to 4 hours. When the irrigation counter reaches zero and a decision adjustment for the next irrigation cycle is needed, the microcomputer system reads the current soil moisture measured by the probe and searches the central database for all historical irrigation records whose pre-irrigation moisture values ​​h_p match the current soil moisture. The main control program groups all the searched records according to their corresponding historical irrigation interval time T, dividing them into multiple independent historical record sets G_1, G_2, ..., G_n. Subsequently, the system calculates the arithmetic mean of the end-of-irrigation moisture of each historical record set, obtaining the average end-of-irrigation moisture H_avg for each set. The system pre-sets the target value H_target, which is the most suitable constant humidity target value for the root development of bayberry. In this embodiment, it is set to an equivalent simulation value of 600. The main control program compares the constant humidity target value with the average humidity at the end of the irrigation cycle of each set by subtraction. Through the absolute value minimization function, the system selects the historical data set that minimizes the absolute difference between the two, |H_target-H_avg|, and directly extracts the historical irrigation interval time T corresponding to the set as the optimal irrigation interval time for the next time in the grid area. This realizes the self-learning and adaptive adjustment of the irrigation cycle.

[0041] When the second-order polynomial regression model predicts that a virtual grid zone, such as Zone 2, will experience a sharp decline in water consumption due to strong local sunlight and rapid transpiration, and that it will exceed the set dryness safety threshold within the next 2 hours, the system will automatically issue a strong intervention signal. This signal will control the servo frequency conversion proportional mixing valve to adjust the valve opening, preparing the mature high-bacterial-count microbial fertilizer stock solution in the fermentation tank into a 5-fold diluted high-concentration functional microbial fertilizer solution. The system will then instruct the translation mechanism to quickly and precisely spray 15 ml onto the point to activate the rhizosphere drought-resistant symbiotic mechanism. After executing the strong intervention precise spraying, the central main control microcomputer system will reinitialize and reset the irrigation counter for the corresponding grid zone to avoid repeated irrigation. Conversely, when the central main control microcomputer system detects that the current soil moisture in a certain grid area is too high and exceeds the preset safety high threshold, in order to prevent the waxberry roots from rotting, the system will automatically cut off the microbial fertilizer supply plan for that point and forcibly extend the next irrigation interval to 8 hours, stopping irrigation and maintaining water control with a long-term water and fertilizer suspension. If, during the initial startup phase of the system, there are no historical records available for cluster matching in the central database, the central control microcomputer system will directly call the aforementioned second-order polynomial regression model to calculate the predicted number of hours required for the current soil moisture to reach the target constant moisture value, thereby quickly initializing the irrigation counter (Counter) corresponding to that partition. In this embodiment, during continuous testing over several weeks, the system's control error for soil moisture at specific depths in each grid area within planting frame 1 was strictly locked within a minimal error threshold of ±5% for over 85% of the total experimental time. Furthermore, the compound microbial fertilizer solution, continuously and dynamically replenished on-site, maintained an extremely high viable bacteria count of over 10^9 CFU / mL, significantly improving the fruit setting rate and fruit sugar content of the bayberries.

[0042] The embodiments of the present invention are given for the purposes of illustration and description. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A collaborative bayberry microbial fertilizer irrigation system, comprising a cultivation area inspection mechanism, an intelligent collaborative fermentation and modulation center, and a central control microcomputer system, characterized in that: The cultivation area inspection mechanism carries a soil detection needle and a water injection hole, and moves horizontally and vertically within the cultivation area under the control of the central main control microcomputer system. The intelligent collaborative fermentation and modulation center includes a composite microbial fermenter and a servo frequency conversion proportional mixing valve connected to the liquid outlet of the fermenter. The servo frequency conversion proportional mixing valve is connected to the water injection hole through a liquid delivery pipeline. The central control microcomputer system is electrically connected to the cultivation area inspection mechanism, soil probe and servo frequency conversion proportional mixing valve respectively. It virtually divides the cultivation area into multiple grid areas and controls the cultivation area inspection mechanism to periodically collect the current soil moisture of each grid area. The central control microcomputer system constructs a second-order polynomial regression model based on the historical humidity data continuously collected from each grid area to predict the soil moisture consumption trend, and dynamically adjusts the dilution ratio of the servo frequency conversion proportional mixing valve accordingly, so as to output the corresponding concentration of diluted bacterial fertilizer solution to the corresponding grid area.

2. The collaborative bayberry microbial fertilizer irrigation system according to claim 1, characterized in that, The composite microbial fermenter is equipped with a heating and temperature control device and an air pump aeration device; the heating and temperature control device maintains the temperature inside the fermenter at 26 to 30 degrees Celsius.

3. The collaborative bayberry microbial fertilizer irrigation system according to claim 2, characterized in that, The composite microbial fermenter is also equipped with an online pH meter and an alkaline solution titration pump; the central main control microcomputer system dynamically controls the alkaline solution titration pump to drip alkaline solution according to the real-time reading of the online pH meter, so as to maintain the pH of the microbial fertilizer fermentation liquid between 6.5 and 7.

0.

4. The collaborative bayberry microbial fertilizer irrigation system according to claim 3, characterized in that, The composite microbial fermenter is also equipped with an automatic dynamic feeder; the automatic dynamic feeder performs quantitative six-stage batch feeding on days 0, 2, 4, 6, 8 and 10 of the microbial fertilizer fermentation cycle, and the raw material ratio for microbial fertilizer fermentation in the fermenter adopts a ten-fold culture medium ratio.

5. The collaborative bayberry microbial fertilizer irrigation system according to claim 1, characterized in that, The central control microcomputer system runs a main control program and is connected to a microcontroller development board; the main control program has a graphical user interface, which reflects the soil moisture level of each grid area in real time through the color depth of the matrix area.

6. The collaborative bayberry microbial fertilizer irrigation system according to claim 1, characterized in that, The central control microcomputer system is equipped with an irrigation counter for each grid area; the initial value of the irrigation counter is calculated by dividing the preset single irrigation interval by the inspection and sensing interval; each time the cultivation area inspection mechanism performs a sensing operation on the grid area, the irrigation counter automatically decrements by one until it decreases to zero, triggering an irrigation command.

7. The collaborative bayberry microbial fertilizer irrigation system according to claim 6, characterized in that, The central control microcomputer system records the current timestamp, current irrigation interval, and pre-irrigation humidity value each time an irrigation command is triggered; and during the next pre-irrigation inspection after the irrigation interval, it collects the current soil humidity of each grid area as the end-of-irrigation humidity, and stores the above data as associated data in the central database to generate historical irrigation record items.

8. The collaborative bayberry microbial fertilizer irrigation system according to claim 7, characterized in that, When the irrigation counter in the grid area reaches zero and triggers the adjustment decision for the next irrigation cycle, the central control microcomputer system reads the current soil moisture and searches the central database for all historical irrigation records whose pre-irrigation moisture values ​​match the current soil moisture. The searched records are then grouped and categorized according to their corresponding historical irrigation intervals to obtain multiple historical record sets.

9. The collaborative bayberry microbial fertilizer irrigation system according to claim 8, characterized in that, The central control microcomputer system calculates the average end-of-irrigation humidity corresponding to each historical record set, compares the absolute difference between the preset target value of constant humidity in the rhizosphere of the bayberry and the average end-of-irrigation humidity, selects the historical record set that minimizes the absolute difference, and uses the historical irrigation interval time corresponding to the set as the next irrigation interval time for the grid area.

10. The collaborative bayberry microbial fertilizer irrigation system according to claim 9, characterized in that, When the central control microcomputer system detects that the current soil moisture is higher than the preset safe high threshold through the soil probe, it automatically extends the next irrigation interval. Furthermore, during the initial stage of system operation when there is no matching record in the central database, the central control microcomputer system directly calls the second-order polynomial regression model to calculate and determine the irrigation interval.

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