Crop irrigation control method and monitoring device

Abstract

This invention provides a crop irrigation control method and monitoring device. It acquires crop canopy images and canopy leaf surface temperatures, and processes the canopy images to obtain the current leaf area index (LAI) value. Based on the canopy leaf surface temperature, it dynamically adjusts a preset irrigation threshold and / or decision delay time to obtain adjusted irrigation decision parameters. Based on the adjusted irrigation decision parameters and the current LAI value, it generates irrigation control commands and controls the irrigation system to start or stop irrigation operations. By acquiring crop canopy images and calculating the LAI, it achieves a shift from irrigating soil to irrigating crops, accurately capturing the critical point of crop physiological water demand. By dynamically adjusting irrigation decision parameters through canopy leaf surface temperature, the irrigation strategy adapts to changes in ambient temperature, effectively avoiding irrigation lag or false triggering caused by fixed thresholds. This allows for precise control of crop water stress while significantly saving irrigation water and improving crop quality.

Description

Technical Field

[0001] This invention relates to the field of smart agriculture and precision irrigation technology, and in particular to a crop irrigation control method and monitoring device. Background Technology

[0002] Irrigation is a crucial aspect of agricultural production, and a rational irrigation strategy is essential for ensuring crop yields, improving fruit quality, and conserving water resources. With the development of the Internet of Things, sensor technology, and machine vision technology, automated irrigation systems have been widely applied in greenhouses and field planting scenarios. These systems aim to replace traditional manual, experience-based irrigation with intelligent methods, thereby achieving refined management of agricultural production.

[0003] Existing irrigation control technologies primarily rely on soil moisture sensors, weather station data, or fixed schedules for decision-making. Some advanced systems are beginning to utilize machine vision technology to monitor crop growth, but these often employ preset, fixed thresholds for judgment. When monitored environmental parameters or growth indicators reach preset values, the system activates or deactivates the irrigation equipment. These methods can, to some extent, automate irrigation and reduce the cost of manual intervention.

[0004] However, existing technological solutions still have limitations and cannot meet the development needs of precision agriculture for water conservation, quality improvement, and high efficiency. First, relying on soil moisture or meteorological data is an indirect monitoring method and cannot directly reflect the crop's physiological water requirements. This can easily lead to misjudgments such as soil being moist but the crop being water-deficient, or soil being too wet causing excessive vegetative growth. Second, existing irrigation decision parameters are mostly preset fixed thresholds. Under extreme weather conditions such as high or low temperatures, the intensity of crop transpiration changes significantly, making it difficult to accurately capture the crop's critical water requirement. Furthermore, existing irrigation methods mostly employ fixed-duration timed irrigation strategies or threshold irrigation strategies based on soil moisture. The timing and amount of irrigation are set based on ensuring the crop's basic growth water needs. Crops are often kept in a state of sufficient water for extended periods, making it difficult to create appropriate water stress conditions, thus limiting fruit quality improvement and requiring further improvement in irrigation water efficiency. Summary of the Invention

[0005] This invention provides a crop irrigation control method and monitoring device to solve the technical problem that existing irrigation control methods, which rely on indirect environmental parameters and static decision logic, cannot accurately respond to the physiological water demand of crops and are difficult to adapt to changes in environmental temperature.

[0006] This invention provides a crop irrigation control method, comprising: Acquire canopy images and canopy leaf surface temperatures of the crop, process the canopy images, and obtain the current value of the leaf area index of the crop; The preset irrigation threshold and / or decision delay time are dynamically adjusted based on the canopy leaf temperature to obtain the adjusted irrigation decision parameters; Based on the adjusted irrigation decision parameters and the current value of the leaf area index, an irrigation control command is generated, which enables the irrigation system actuator to start or stop irrigation operations according to the irrigation control command.

[0007] According to the crop irrigation control method provided by the present invention, the step of dynamically adjusting the preset irrigation threshold and / or decision delay time based on the canopy leaf temperature includes: A correction factor is calculated based on the difference between the canopy leaf temperature and the crop's growth baseline temperature, and the correction factor is used to dynamically adjust the irrigation threshold and / or the decision delay time.

[0008] According to the crop irrigation control method provided by the present invention, the step of dynamically adjusting the irrigation threshold and / or the decision delay time using the correction factor includes: The irrigation upper and lower thresholds are scaled based on the correction factor; and / or The decision delay time is set to be inversely proportional to the correction factor.

[0009] According to the crop irrigation control method provided by the present invention, the step of generating irrigation control instructions based on the adjusted irrigation decision parameters and the current value of the leaf area index includes: When the current value of the leaf area index continues to decrease to below or equal to the lower limit threshold of the adjusted irrigation decision parameters, an irrigation start command is generated. During irrigation, when the current value of the leaf area index rises to a level higher than or equal to the upper limit threshold of the adjusted irrigation decision parameters, a stop irrigation command is generated.

[0010] According to the crop irrigation control method provided by the present invention, the step of processing the canopy image to obtain the current value of the leaf area index of the crop includes: The canopy image is subjected to pixel recognition and segmentation to obtain the canopy gap ratio; The current value of the leaf area index is calculated based on the gap ratio model and the canopy gap ratio.

[0011] According to the crop irrigation control method provided by the present invention, the irrigation control command further includes an irrigation duration parameter, and the method further includes: The irrigation duration parameter is generated based on the difference between the upper limit threshold and the current value of the leaf area index in the adjusted irrigation decision parameters, the water use efficiency coefficient, the leaf area per plant, and the average flow rate of the irrigation system.

[0012] The present invention also provides a crop irrigation monitoring device for implementing any of the above-described crop irrigation control methods, the device comprising: Image acquisition unit, used to acquire images of the crop canopy; A temperature acquisition unit is used to acquire the canopy leaf surface temperature of the crop; The main control unit is used to process the canopy image to obtain the current value of the leaf area index of the crop, dynamically adjust the preset irrigation threshold and / or decision delay time according to the canopy leaf temperature to obtain the adjusted irrigation decision parameters, and generate irrigation control instructions based on the adjusted irrigation decision parameters and the current value of the leaf area index. A communication unit, connected to the main control unit, is used to transmit the irrigation control command to the irrigation system actuator, so that the irrigation system actuator can start or stop the irrigation operation according to the irrigation control command.

[0013] According to the crop irrigation control device provided by the present invention, the image acquisition unit is a high-definition digital camera deployed above the canopy of the crop; the communication unit is a wireless communication module.

[0014] According to the crop irrigation control device provided by the present invention, the device further includes: a power module, which is a solar power supply system, including a solar panel, an energy storage battery and a charging management module; and a temperature acquisition unit including a non-contact infrared temperature sensor.

[0015] According to the crop irrigation control device provided by the present invention, the device further includes: a waterproof and dustproof housing, wherein the image acquisition unit, the temperature acquisition unit, the main control unit and the communication unit are encapsulated within the waterproof and dustproof housing.

[0016] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the crop irrigation control method as described above.

[0017] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the crop irrigation control method as described above.

[0018] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the crop irrigation control method as described above.

[0019] The crop irrigation control method and monitoring device provided by this invention first acquires crop canopy images and canopy leaf surface temperatures, and processes the canopy images to obtain the current value of the crop's leaf area index (LAI). Then, based on the canopy leaf surface temperature, a preset irrigation threshold and / or decision delay time are dynamically adjusted to obtain adjusted irrigation decision parameters. Finally, based on the adjusted irrigation decision parameters and the current LAI value, an irrigation control command is generated, and the irrigation system is controlled to start or stop irrigation operations according to the irrigation control command. This invention realizes the transformation from irrigating soil to irrigating crops by acquiring crop canopy images, and can accurately capture the critical point of crop physiological water demand. Simultaneously, by dynamically adjusting irrigation decision parameters through canopy leaf surface temperature, the irrigation strategy can adapt to changes in ambient temperature, effectively avoiding irrigation lag or false triggering caused by fixed thresholds. Therefore, while accurately controlling crop water stress, it can also significantly save irrigation water and improve crop quality. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a schematic flowchart of the crop irrigation control method provided by the present invention.

[0022] Figure 2 This is a structural block diagram of the crop irrigation monitoring device provided by the present invention.

[0023] Figure 3 This is a flowchart illustrating the crop irrigation control method provided by the present invention in a tomato greenhouse planting scenario.

[0024] Figure 4 A dynamic comparison chart of leaf area index in tomato greenhouse cultivation scenarios.

[0025] Figure 5 A schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0027] Existing irrigation control technologies mainly rely on indirect monitoring of environmental parameters such as soil moisture and meteorological data, or, while incorporating machine vision, still use preset fixed thresholds for decision-making. These solutions can achieve irrigation automation to some extent and reduce the cost of manual intervention. However, they still have shortcomings: First, indirect monitoring cannot directly reflect the physiological water requirements of crops, which can easily lead to misjudgments of supply and demand; second, fixed thresholds cannot adapt to fluctuations in crop transpiration patterns caused by changes in ambient temperature, resulting in delayed irrigation during high temperatures or false triggering during low temperatures; third, traditional strategies focus on ensuring basic water needs and are difficult to create conditions of moderate water stress, which in turn limits the improvement of crop quality and further optimization of water use efficiency.

[0028] To address the aforementioned problems in existing technologies, this invention provides a crop irrigation control method and monitoring device. The inventive concept of this crop irrigation control method and monitoring device lies in proposing a precise irrigation control scheme based on the feedback linkage between the crop's physiological state and environmental temperature. Specifically, canopy images are collected to calculate the current leaf area index as the core basis for irrigation decisions. Simultaneously, canopy leaf surface temperature is introduced to dynamically adjust irrigation decision parameters to adapt to environmental changes. Finally, irrigation control commands are generated based on the adjusted irrigation decision parameters and the current leaf area index value, achieving precise regulation of moderate water stress on crops and simultaneously achieving the dual goals of water conservation and quality improvement while ensuring yield.

[0029] The following is combined Figures 1 to 5 This invention describes the crop irrigation control method and monitoring device provided by the present invention.

[0030] Figure 1 This is a schematic flowchart of the crop irrigation control method provided by the present invention, as shown below. Figure 1 As shown, the method includes: S101. Obtain the canopy image and canopy leaf surface temperature of the crop, and process the canopy image to obtain the current value of the crop's leaf area index.

[0031] For example, an image acquisition unit can be vertically deployed above the crop canopy to acquire high-definition digital images of the crop canopy covering the monitoring area at a preset cycle, such as once per hour. This ensures that the images clearly capture the morphology of crop leaves and the density of the canopy, thus obtaining a canopy image. Simultaneously, a temperature acquisition unit, such as a non-contact infrared thermometer, can be used to measure the average leaf surface temperature (T_leaf) of the crop canopy, i.e., the canopy leaf surface temperature.

[0032] In some embodiments, the image acquisition unit can be deployed at a height of, for example, 1.2-1.8 meters above the crop canopy to ensure that the lens of the image acquisition unit can completely cover the monitoring area.

[0033] In some embodiments, while collecting the canopy image and the canopy leaf surface temperature, the ambient air temperature (T_air) and the wet-bulb temperature (T_wet) are synchronously collected to provide data support for subsequent correction calculations.

[0034] Furthermore, all the collected data such as the canopy image, the canopy leaf surface temperature, the ambient air temperature, the wet-bulb temperature, etc. can be transmitted from the corresponding collection units to the main control unit in real time through the communication unit, and the main control unit performs subsequent calculations and decision-making judgments based on the collected data.

[0035] For example, the main control unit processes the canopy image to obtain the current value of the leaf area index of the crop.

[0036] In some embodiments, the main control unit processes the canopy image to obtain the current value of the leaf area index of the crop, which may include: The main control unit first performs pixel recognition and segmentation on the canopy image to obtain the canopy gap ratio, and then based on the gap ratio model, calculates the current value of the leaf area index according to the canopy gap ratio.

[0037] Specifically, the main control unit preprocesses the collected high-definition digital image, that is, the canopy image, such as denoising, enhancement, grayscale conversion, etc., and then through the pixel recognition and segmentation algorithm, distinguishes the leaf pixels and background pixels in the canopy image, and calculates the canopy gap ratio (P), that is, the proportion of sky pixels in the total pixels. Then, based on the Beer-Lambert law, the gap ratio model is used to measure the current value of the leaf area index (LAI_m) of the crop in the monitoring area. The gap ratio model is shown in the following formula (1): LAI=-(1 / K) ln(P) (1) Where, LAI is the current value of the leaf area index, without unit; P is the canopy gap ratio (0 < P < 1); K is the extinction coefficient, and its value is related to the crop type and leaf angle, and can be preset through preliminary experiments. For example, the extinction coefficient of tomatoes is 0.7 to 0.9, and the extinction coefficient of wheat is 0.6 to 0.8, etc. The value of K needs to ensure that the measurement accuracy error of LAI_m does not exceed the corresponding threshold, such as 5%. In addition, the denser the leaves, the smaller the canopy gap ratio P, ln(P) is negative, and the calculated LAI value is larger, and vice versa. The current value of the leaf area index can accurately reflect the canopy density and physiological growth state of the crop.

[0038] S102. Dynamically adjust the preset irrigation threshold and / or decision delay time according to the canopy leaf surface temperature to obtain the adjusted irrigation decision parameters.

[0039] This step uses the canopy leaf surface temperature that reflects the crop transpiration intensity and the water stress state as the feedback basis. The main control unit can adaptively correct the preset static irrigation threshold and / or decision delay time, so that the irrigation decision parameters can dynamically adjust the response sensitivity according to the environmental temperature change. Thus, adjusted irrigation decision parameters that can eliminate environmental interference and match the current physiological water demand state of the crop are obtained, and a dynamic benchmark is provided for generating accurate irrigation control instructions in combination with the current value of the leaf area index in the subsequent stage.

[0040] In some embodiments, dynamically adjusting the irrigation threshold and / or decision delay time according to the canopy leaf surface temperature may include: Calculating a correction factor based on the difference between the canopy leaf surface temperature and the crop growth benchmark temperature, and then dynamically adjusting the preset irrigation threshold and / or decision delay time by using the correction factor to eliminate the influence of environmental temperature on the judgment of the crop water demand state and improve the decision accuracy.

[0041] For example, the correction factor can be calculated using the following formula (2): Correction factor = 1 + K1 (T_leaf - T_base) (2) Where, the correction factor is a dimensionless coefficient; T_leaf is the currently collected average canopy leaf surface temperature (°C), that is, the current value of the canopy leaf surface temperature; T_base is the crop growth benchmark temperature (°C), which can be preset according to the crop variety; K1 is an empirical coefficient, and it can take positive or negative values according to the size relationship between T_leaf and T_base. For example, when T_leaf > T_base, K1 takes 0.01 - 0.03 / °C, and when T_leaf < T_base, K1 takes -0.01 to -0.03 / °C.

[0042] It can be seen from formula (2) that at high temperatures (T_leaf > T_base), the crop transpiration is strong, and the irrigation response speed needs to be accelerated. The correction factor is greater than 1, and the irrigation threshold can be appropriately increased to start irrigation in advance; at low temperatures (T_leaf < T_base), the transpiration is weak, the correction factor is less than 1, and the irrigation threshold can be appropriately decreased to avoid mis-irrigation and achieve adaptive adjustment.

[0043] After calculating the correction factor, the preset irrigation threshold and / or decision delay time are dynamically adjusted accordingly.

[0044] Adjusting preset irrigation thresholds using correction factors can be achieved by scaling the upper and lower limits of the preset irrigation thresholds. Specifically, preset irrigation thresholds such as LAI_lower_base and LAI_upper_base can be multiplied by the correction factor to obtain temperature-corrected dynamic upper and lower limit thresholds (LAI_lower_adj and LAI_upper_adj). The temperature-corrected dynamic upper limit threshold (LAI_upper_adj) is the adjusted upper limit threshold in the irrigation decision parameters, and the temperature-corrected dynamic lower limit threshold (LAI_lower_base) is the adjusted lower limit threshold in the irrigation decision parameters.

[0045] Dynamically adjusting the decision delay time using a correction factor can be achieved by setting the decision delay time inversely proportional to the correction factor. Specifically, when judging the trend of the current value of leaf area index (LAI_m), a decision delay time is introduced. The decision delay time is inversely proportional to the correction factor; that is, the higher the T_leaf, the stronger the transpiration, and the shorter the decision delay time (e.g., 5-10 minutes), thus avoiding irrigation lag; the lower the T_leaf, the weaker the transpiration, and the longer the decision delay time (e.g., 15-20 minutes), thus avoiding accidental irrigation triggering.

[0046] It should be noted that the adjusted irrigation decision parameters include the upper and lower irrigation thresholds scaled based on the correction factor, and / or the decision delay time adjusted based on the correction factor.

[0047] S103. Based on the adjusted irrigation decision parameters and the current value of the leaf area index, an irrigation control command is generated, which enables the irrigation system actuator to start or stop irrigation operations according to the irrigation control command.

[0048] The real-time calculated leaf area index is compared and analyzed with irrigation decision parameters corrected for canopy leaf temperature. The timing of irrigation is determined based on the matching relationship between crop physiological state and decision parameters. Irrigation control commands containing start or stop actions are generated and transmitted to the irrigation system actuator via a wireless communication unit. The irrigation system actuator responds to the irrigation control command to start or stop the irrigation operation, thereby completing the closed-loop control from physiological state monitoring to irrigation action execution, and realizing automated irrigation operation based on the actual water demand of the crop.

[0049] In some embodiments, generating irrigation control instructions based on the adjusted irrigation decision parameters and the current leaf area index in step S103 may include: When the current value of the leaf area index (LAI) continuously decreases to below or equal to the lower irrigation threshold in the adjusted irrigation decision parameters—for example, when LAI_m continuously decreases, such as when it decreases in two consecutive measurements and is below or equal to the adjusted lower irrigation threshold (LAI_lower_base)—it can be preliminarily determined that the crop has entered the water demand critical point, and thus an irrigation start command is generated. During irrigation, when the current value of the leaf area index rises to above or equal to the upper irrigation threshold in the adjusted irrigation decision parameters—for example, during irrigation, if the change in LAI_m is continuously monitored and LAI_m rises to above or equal to the upper irrigation threshold (LAI_upper_base)—it is preliminarily determined that the crop has sufficient water, and an irrigation stop command is generated.

[0050] As can be seen from the above description, the crop irrigation control method provided by the present invention generates corresponding start or stop irrigation commands based on the lower and upper irrigation thresholds in the adjusted irrigation decision parameters and the current value of the calculated leaf area index. This ensures that the timing of irrigation start and stop is accurate, avoids irrigation response lag or false triggering, and thus keeps the crop water status within a moderate water stress range, which is conducive to saving irrigation water and improving crop quality.

[0051] In some embodiments, the irrigation control command further includes an irrigation duration parameter, which can be generated based on the difference between the upper limit threshold and the current value of the leaf area index in the adjusted irrigation decision parameters, the water use efficiency coefficient, the leaf area per plant, and the average flow rate of the irrigation system.

[0052] In some embodiments, the irrigation duration parameter can be calculated using the following formula (3): T_irrigate=[(LAI_upper_adj-LAI_m) WUE A] / F (3) Where T_irrigate is the ideal irrigation duration parameter, in minutes; LAI_upper_adj is the upper limit threshold of the irrigation decision parameters after adjustment; LAI_m is the current value of leaf area index at the start of irrigation; and WUE is the water use efficiency coefficient (g·L). -1 A represents the leaf area per plant (m²). 2F represents the average flow rate of the irrigation system (L / min). The larger the difference between the upper limit of irrigation and the current value of the leaf area index (LAI), the more severe the crop water shortage, and the longer the required irrigation time. Furthermore, by combining water use efficiency with the average flow rate of the irrigation system, the physiological needs of the crop can be converted into specific irrigation durations, achieving quantitative irrigation and avoiding over-irrigation or under-irrigation caused by fixed durations. This ensures that the crop recovers to a suitable water state while further saving irrigation water and improving water use efficiency.

[0053] It should be noted that the steps of the crop irrigation control method provided by this invention are not executed once, but rather form a closed-loop control process that is cyclically executed according to a preset acquisition cycle throughout the entire crop growth period. The steps of acquiring canopy images and canopy leaf surface temperature, calculating the current value of the leaf area index, dynamically adjusting irrigation decision parameters, and generating irrigation control commands can be continuously and repeatedly executed until the end of the growth period or a stop command is received. This cyclical operation mechanism ensures that irrigation decisions can respond in real time to the dynamic changes in crop physiological state and ambient temperature, achieving fully unattended automated control of the entire process.

[0054] The crop irrigation control method provided by this invention first acquires crop canopy images and canopy leaf surface temperatures, and processes the canopy images to obtain the current value of the crop's leaf area index (LAI). Then, based on the canopy leaf surface temperature, it dynamically adjusts a preset irrigation threshold and / or decision delay time to obtain adjusted irrigation decision parameters. Finally, based on the adjusted irrigation decision parameters and the current LAI value, it generates irrigation control commands, and controls the irrigation system to start or stop irrigation operations according to the irrigation control commands. By acquiring crop canopy images and calculating the LAI, it achieves a shift from irrigating soil to irrigating crops, accurately capturing the critical point of crop physiological water demand. Simultaneously, by dynamically adjusting irrigation decision parameters through canopy leaf surface temperature, the irrigation strategy can adapt to changes in ambient temperature, effectively avoiding irrigation lag or false triggering caused by fixed thresholds. Therefore, while accurately controlling crop water stress, it can also significantly save irrigation water and improve crop quality.

[0055] Figure 2 This is a structural block diagram of the crop irrigation monitoring device provided by the present invention. This crop irrigation monitoring device can implement the crop irrigation control method provided in the above embodiments. Figure 2 As shown, the crop irrigation monitoring device 200 includes: Image acquisition unit 201 is used to acquire images of the crop canopy; Temperature acquisition unit 202 is used to acquire the temperature of the crop canopy leaves; The main control unit 203 is used to process the canopy image to obtain the current value of the leaf area index of the crop, dynamically adjust the preset irrigation threshold and / or decision delay time according to the canopy leaf temperature, obtain the adjusted irrigation decision parameters, and generate irrigation control instructions based on the adjusted irrigation decision parameters and the current value of the leaf area index. The communication unit 204 is connected to the main control unit 203 and is used to transmit irrigation control commands to the irrigation system actuator, so that the irrigation system actuator can start or stop irrigation operations according to the irrigation control commands.

[0056] In some embodiments, the image acquisition unit 201 may be, for example, a high-definition digital camera, vertically mounted 1.2-1.8 meters above the crop canopy, with the lens facing the canopy and fixed on the same horizontal plane to ensure complete coverage of the monitoring area, which may refer to a canopy radius of 1-3 meters. The high-definition digital camera may also support autofocus and timed shooting, thereby acquiring high-definition digital images, i.e., canopy images, at a preset cycle. The image resolution is no less than 1080P, ensuring accurate leaf pixel recognition. The image acquisition unit 201 and the main control unit 203 are connected via, for example, a data cable or wirelessly, for real-time transmission of the acquired canopy images.

[0057] In some embodiments, the temperature acquisition unit 202 may be, for example, a non-contact infrared temperature sensor, which can be deployed synchronously with the image acquisition unit 201 to measure the leaf surface temperature of the crop canopy. The measurement range can be 0-50℃, and the measurement accuracy is ±0.5℃, thereby effectively capturing leaf temperature changes caused by crop water stress. The temperature acquisition unit 202 is communicatively connected to the main control unit 203, which can transmit temperature measurement data in real time, providing core data support for leaf temperature feedback correction.

[0058] In some embodiments, the main control unit 203, as the core control module, can adopt a high-performance microcontroller or embedded chip, integrating functions such as data processing, algorithm operation, and logic control. It is used to receive data transmitted by the image acquisition unit 201 and the temperature acquisition unit 202, calculate the current value of the leaf area index and run irrigation decision logic, calculate correction factors and dynamically adjust irrigation thresholds, thereby generating start / stop irrigation commands and controlling the communication unit 204 to transmit commands, etc.

[0059] Optionally, the main control unit 203 may also integrate a storage module to store collected data, preset parameters such as preset irrigation thresholds and parameters in the response formula, as well as irrigation logs, for easy subsequent querying and data analysis.

[0060] In some embodiments, the communication unit 204 can be, for example, a 4G / 5G or LoRa wireless communication module, which is communicatively connected to the main control unit 203. It transmits irrigation control commands generated by the main control unit 203 to irrigation system actuators such as solenoid valves and water pump controllers. It also supports reverse communication, for example, receiving feedback signals from the actuators to confirm the execution status of the irrigation control commands. The communication unit 204 has a transmission distance of at least 100 meters, which can adapt to the long-distance control requirements of field planting scenarios, and it has anti-interference capabilities to ensure stable command transmission.

[0061] In some embodiments, the crop irrigation monitoring device 200 provided by the present invention further includes a power module 205. The power module 205 can employ a solar power system, consisting of a solar panel, an energy storage battery, and a charging management module, providing a stable and continuous power supply for the entire crop irrigation monitoring device 200, adaptable to environments in the field without mains power. Optionally, the solar panel power is not less than 20W, capable of efficiently converting solar energy into electrical energy. The energy storage battery capacity is not less than 12V / 20Ah, capable of storing excess electrical energy to ensure normal operation of the device on cloudy days and at night. The charging management module is used to protect the battery, preventing overcharging and over-discharging, and extending the battery's lifespan.

[0062] In some embodiments, the crop irrigation monitoring device 200 can be entirely encapsulated in a waterproof and dustproof housing with a protection rating of not less than IP65, capable of withstanding harsh field environments characterized by high temperatures, heavy rainfall, and dust. Components such as the image acquisition unit, temperature acquisition unit, main control unit, and communication unit can be modularly designed and encapsulated within the waterproof and dustproof housing for easy installation, debugging, and maintenance. In actual operating conditions, the components included in the crop irrigation monitoring device 200 include, but are not limited to, those such as… Figure 2 The components shown can be flexibly adjusted and deployed according to the scale of crop planting.

[0063] As can be seen from the description of the above embodiments, the crop irrigation control method and monitoring device provided by the present invention have at least the following beneficial effects compared with the prior art: 1. This invention enables precise perception and adaptive decision-making based on crop physiological status. Specifically, it abandons the traditional indirect monitoring mode that relies on environmental parameters such as soil moisture, and directly calculates the current value of leaf area index through canopy images, which can accurately reflect the transpiration water consumption and physiological water demand of the crop population. Simultaneously, it introduces canopy leaf temperature as a feedback variable, dynamically adjusting the preset irrigation threshold and / or decision delay time to obtain adjusted irrigation decision parameters, thereby eliminating the interference of environmental temperature changes on the decision logic. This dual mechanism of physiological perception and dynamic correction effectively solves the problems of delayed response in high-temperature environments and easy false triggering in low-temperature environments caused by traditional fixed threshold methods, significantly improving the accuracy and environmental adaptability of irrigation decisions.

[0064] 2. This invention can significantly improve crop quality and enhance water resource utilization efficiency. Based on adjusted irrigation decision parameters and the current leaf area index, it generates irrigation control commands, precisely controlling crops within a moderate water stress range. This avoids yield reduction risks caused by excessive stress and utilizes water stress to induce the accumulation of secondary metabolites, contributing to improved fruit sugar content, color, and other quality indicators. Furthermore, by combining quantitative calculations of irrigation duration parameters, it enables on-demand, quantitative irrigation, avoiding water waste caused by traditional timed irrigation. Experiments show that the crop irrigation control method provided by this invention can effectively save irrigation water and improve crop quality while ensuring yield, achieving the dual goals of water conservation and quality improvement.

[0065] 3. High integration, strong environmental adaptability and practicality. The crop irrigation monitoring device provided by this invention adopts a modular design, integrating image acquisition, temperature acquisition, main control and communication units, with a simple structure and convenient installation and maintenance. Equipped with a solar power supply system and a waterproof and dustproof casing, it can operate stably for a long time in harsh field environments without relying on mains power. The wireless communication module also ensures stable transmission of long-distance control signals. The entire device can achieve fully unattended automated monitoring and control, reducing manual intervention costs, and is suitable for various planting scenarios such as greenhouses and open fields.

[0066] 4. The technical solution has strong compatibility and wide applicability. This invention integrates image recognition, crop physiology, and automatic control technologies to form a complete intelligent irrigation technology system. The system's preset parameters (such as growth reference temperature, extinction coefficient, and water use efficiency coefficient) can be flexibly adjusted according to the growth characteristics of different crops (such as tomatoes, cucumbers, and wheat). It can adapt to the planting needs of various crops without changing the hardware structure, and has good prospects for industrialization and promotion.

[0067] The following embodiments are exemplary illustrations of the application of the crop irrigation control method and monitoring device provided by the present invention in a tomato greenhouse planting scenario. It should be understood that the embodiments described herein are merely for explaining the present invention and are not intended to limit the scope of protection of the present invention.

[0068] In this embodiment, the crop irrigation monitoring device is deployed as follows: The crop irrigation monitoring device is fixed 1.5 meters above the tomato greenhouse canopy, ensuring that the field of view of the image acquisition unit (high-definition digital camera) completely covers the target monitoring area. The temperature acquisition unit, a non-contact infrared temperature sensor, is deployed synchronously with the camera, with the sensor probe facing the center of the tomato canopy to measure the leaf surface temperature. The communication unit uses a 4G wireless communication module to establish a wireless connection with the solenoid valve controller of the greenhouse irrigation system, ensuring stable transmission of irrigation control commands. The power module uses a 20W solar panel paired with a 12V / 20Ah energy storage battery and charging management module, fixed in an unobstructed area on the greenhouse roof to ensure continuous power supply. The entire crop irrigation monitoring device is encased in a waterproof and dustproof shell with a protection rating of at least IP65. The main control unit integrates a storage module for storing collected data, preset parameters, and irrigation logs.

[0069] Before implementing the crop irrigation control method, relevant parameters were preset in the main control unit based on the growth characteristics of tomatoes during the flowering and fruit-setting period. The preset irrigation thresholds were set as a lower limit of 3.0 and an upper limit of 3.5. In the correction factor calculation, the crop growth baseline temperature (T_base) was set to 25℃ and the empirical coefficient (K1) to 0.02 / ℃. In the LAI calculation parameters, the extinction coefficient (K) was set to 0.8. In the estimated irrigation duration parameters, the water use efficiency coefficient (WUE) was set to 0.5 g·L⁻¹. -1 The leaf area (A) of a single tomato plant within the monitoring area was set at 0.3 m². 2 The average flow rate (F) of the irrigation system was set to 1 L / min. The data acquisition cycle was set to once per hour.

[0070] Figure 3 This is a flowchart illustrating the crop irrigation control method provided by the present invention in a tomato greenhouse cultivation scenario, as shown below. Figure 3 As shown, the specific operation steps of the crop irrigation control method in this embodiment are as follows: S1. Data Acquisition. The device acquires high-definition images of the tomato canopy through the image acquisition unit at preset intervals, and measures the canopy leaf surface temperature through the temperature acquisition unit. All data is transmitted to the main control unit in real time.

[0071] S2. Leaf Area Index (LAI) Calculation. The main control unit preprocesses the acquired images, identifies the proportion of sky pixels in the images to determine the canopy gap ratio, and calculates the current LAI value based on the gap ratio model. An example of the gap ratio model formula is: LAI = -(1 / K_ext) ln(P), where P is the canopy gap ratio and K_ext is the extinction coefficient. For example, data collected on a certain day shows that the current leaf area index is 2.95, and the canopy leaf surface temperature is measured to be 30℃.

[0072] S3. Dynamic Adjustment of Decision Parameters. The main control unit calculates a correction factor based on the difference between the canopy leaf temperature and the crop growth baseline temperature. In this embodiment, a threshold correction method is used. The formula for calculating the correction factor is as follows: Correction factor = 1 + K1 (T_leaf-T_base). Substitute the data to calculate the correction factor, which is 1.1. Use this correction factor to scale the preset irrigation threshold to obtain the adjusted irrigation decision parameters, namely the lower irrigation threshold, also known as the dynamic lower threshold, which is 3.3, and the upper irrigation threshold, also known as the dynamic upper threshold, which is 3.85.

[0073] S4. Initiate irrigation decision. The main control unit compares the current leaf area index (LAI) value with the adjusted irrigation lower limit threshold in the irrigation decision parameters. Since the current LAI value continues to drop below the adjusted irrigation lower limit threshold, it determines that the crop has entered the water demand critical point and generates an irrigation initiation command.

[0074] S5. Irrigation Duration Estimation and Execution. After irrigation is initiated, the main control unit generates irrigation duration parameters based on the difference between the adjusted irrigation decision parameters (the upper limit threshold of irrigation) and the current value of the leaf area index, combined with the water use efficiency coefficient, single-plant leaf area, and the average flow rate of the irrigation system. An example of the duration estimation formula is: T_irrigate=[(LAI_upper_adj-LAI_m)] WUE A] / F. Substituting the data, the estimated ideal irrigation duration is approximately 8.1 minutes. The main control unit generates an irrigation control command containing this duration, which is transmitted to the solenoid valve controller via the communication unit. The solenoid valve is activated, and quantitative irrigation begins.

[0075] S6. Stop Irrigation Decision. During irrigation, the current leaf area index (LAI) and canopy leaf temperature are continuously monitored. When the LAI rises to 3.9 and the canopy leaf temperature reaches 28°C, the correction factor is recalculated and the dynamic upper limit threshold is updated to 3.71. Since the current LAI has risen above the adjusted irrigation upper limit threshold, the main control unit generates a stop irrigation command, the solenoid valve closes, and one irrigation cycle is completed.

[0076] S7. Cyclic Operation. The device returns to the initial data collection stage and continues monitoring according to the preset cycle, repeating the above process to achieve precise irrigation control throughout the entire tomato growth period.

[0077] As can be seen from this embodiment, the present invention directly characterizes the physiological state of crops by leaf area index and dynamically adjusts irrigation decision parameters by combining leaf temperature feedback, which effectively solves the problem that the traditional fixed threshold method cannot adapt to changes in environmental temperature, and can achieve synergistic optimization of water saving and quality improvement.

[0078] To further verify the practical application effect of this embodiment, a control group was set up for comparative experiment. The control group used the traditional timed irrigation method, irrigating twice a day for 3 minutes each time; the experimental group used the crop irrigation control method of this embodiment. The experimental period was from the flowering and fruit setting period of tomatoes to the ripening period, a total of 60 days.

[0079] The comparative test results show that, in terms of water saving, the total irrigation water volume of this embodiment is 860L, while that of the control group is 1320L, resulting in a water saving rate of approximately 34.8%. In terms of quality improvement, the average soluble solids content of tomatoes in this embodiment group is 11.2°, while that of the control group is 9.7°, representing an improvement of approximately 15.5%. In terms of yield assurance, there is no significant difference in the yield per tomato plant between the two groups. The average yield per plant in this embodiment group is 2.8kg, while that in the control group is 2.7kg, achieving water saving and quality improvement without reducing yield. In terms of automation, the device in this embodiment achieves unattended operation throughout the entire process, eliminating the need for manual intervention in irrigation timing and volume, saving more than 60% of labor costs compared to the control group.

[0080] In the comparative test results, the water-saving rate is calculated using the following formula (4): WSR=(W_conventional-W_LAI) / W_conventional 100% (4) Wherein, WSR represents the water-saving rate (%); W_conventional represents the total water consumption of the traditional irrigation method (L); and W_LAI represents the total water consumption of the method of this invention (L). By calculating the water-saving rate, the water-saving benefits of this invention can be directly quantified, providing data support for technology promotion.

[0081] The above data shows that this embodiment can effectively solve the problems of large water waste and limited crop quality improvement in traditional irrigation methods. By directly characterizing the physiological state of crops through leaf area index and dynamically adjusting irrigation decision parameters in combination with leaf temperature feedback, it effectively solves the problem that traditional fixed threshold methods cannot adapt to changes in environmental temperature, and achieves synergistic optimization of water conservation and quality improvement, which has significant promotion and application value.

[0082] in addition, Figure 4 This figure shows a dynamic comparison of leaf area index (LAI) in a tomato greenhouse cultivation scenario. The purpose of this figure is to visually compare, through simulated experimental data, the significant differences between the method provided in this invention (based on LAI feedback) and traditional timed irrigation methods in terms of crop canopy dynamics and irrigation effects during the mid-to-late stages of tomato growth (the period of coexistence of vegetative and reproductive growth). (Refer to...) Figure 4As shown in the curve illustrating the dynamic changes in leaf area index (LAI) obtained using traditional timed irrigation control, the curve is smooth and changes slowly. The LAI value remains at a high level for most of the growth cycle, exceeding the upper threshold, indicating that the crop has been consistently well-watered and has not experienced effective water stress. While biomass accumulation may be significant, this can easily lead to excessive vegetative growth, with too much nutrient being used for leaf and branch growth rather than fruit development, while also resulting in substantial water loss through evaporation.

[0083] Reference Figure 4 As shown in the curve illustrating the dynamic change of leaf area index (LAI) obtained through irrigation control using the method of this invention, the curve exhibits a distinct sawtooth-like fluctuation, regularly varying within a preset upper and lower threshold. Each sawtooth represents a complete irrigation cycle. During the LAI decline phase, irrigation is stopped. The crop consumes water through transpiration, initiating mild water stress, and the leaf area index (e.g., slight wilting and leaf angle closure) decreases. When the lower threshold is reached (e.g., LAI approaches 3.0), the critical water requirement point is considered reached, and irrigation is initiated. During the LAI recovery phase, water is replenished, the crop returns to its normal physiological state, leaves unfold, and LAI recovers. When the upper threshold is reached (e.g., LAI approaches 3.5), the water requirement is considered met, and irrigation is stopped. This initiates the next cycle. The threshold region represents the ideal mild water stress range set to pursue optimal fruit quality (e.g., high sugar content) and water use efficiency. The crop irrigation control method provided by this invention, through precise control, allows the crop's physiological state (manifested as LAI) to continuously fluctuate within this ideal range.

[0084] contrast Figure 4 The curves showing the dynamic changes in leaf area index under irrigation control using the method of this invention and traditional timed irrigation control, as shown in Table 1 below, yield the following comparison results: Table 1

[0085] Figure 5 A schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 5As shown, the electronic device may include a processor 510, a communications interface 520, a memory 530, and a communication bus 540, wherein the processor 510, communications interface 520, and memory 530 communicate with each other via the communication bus 540. The processor 510 can call logical instructions in the memory 530 to execute a crop irrigation control method, which includes: acquiring a canopy image and canopy leaf surface temperature of the crop, processing the canopy image to obtain the current value of the crop's leaf area index; dynamically adjusting a preset irrigation threshold and / or decision delay time based on the canopy leaf surface temperature to obtain adjusted irrigation decision parameters; and generating irrigation control instructions based on the adjusted irrigation decision parameters and the current value of the leaf area index, causing the irrigation system actuator to start or stop irrigation operations according to the irrigation control instructions.

[0086] Furthermore, the logical instructions in the aforementioned memory 530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0087] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the crop irrigation control method provided by the above methods. The method includes: acquiring a canopy image and canopy leaf surface temperature of the crop, and processing the canopy image to obtain the current value of the crop's leaf area index; dynamically adjusting a preset irrigation threshold and / or decision delay time according to the canopy leaf surface temperature to obtain adjusted irrigation decision parameters; and generating an irrigation control command based on the adjusted irrigation decision parameters and the current value of the leaf area index, so that the irrigation system actuator starts or stops the irrigation operation according to the irrigation control command.

[0088] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the crop irrigation control method provided by the above methods. The method includes: acquiring a canopy image and canopy leaf surface temperature of the crop, and processing the canopy image to obtain the current value of the leaf area index of the crop; dynamically adjusting a preset irrigation threshold and / or decision delay time according to the canopy leaf surface temperature to obtain adjusted irrigation decision parameters; and generating an irrigation control command based on the adjusted irrigation decision parameters and the current value of the leaf area index, so that the irrigation system actuator starts or stops the irrigation operation according to the irrigation control command.

[0089] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0090] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling crop irrigation, characterized in that, include: Acquire canopy images and canopy leaf surface temperatures of the crop, and process the canopy images to obtain the current value of the leaf area index of the crop; The preset irrigation threshold and / or decision delay time are dynamically adjusted based on the canopy leaf temperature to obtain the adjusted irrigation decision parameters; Based on the adjusted irrigation decision parameters and the current value of the leaf area index, an irrigation control command is generated, which enables the irrigation system actuator to start or stop irrigation operations according to the irrigation control command.

2. The method according to claim 1, characterized in that, The dynamic adjustment of the preset irrigation threshold and / or decision delay time based on the canopy leaf temperature includes: A correction factor is calculated based on the difference between the canopy leaf temperature and the crop's growth baseline temperature, and the correction factor is used to dynamically adjust the irrigation threshold and / or the decision delay time.

3. The method according to claim 2, characterized in that, The step of dynamically adjusting the irrigation threshold and / or the decision delay time using the correction factor includes: The irrigation upper and lower thresholds are scaled based on the correction factor; and / or The decision delay time is set to be inversely proportional to the correction factor.

4. The method according to claim 1, characterized in that, The step of generating irrigation control instructions based on the adjusted irrigation decision parameters and the current value of the leaf area index includes: When the current value of the leaf area index continues to decrease to below or equal to the lower limit threshold of the adjusted irrigation decision parameters, an irrigation start command is generated. During irrigation, when the current value of the leaf area index rises to a level higher than or equal to the upper limit threshold of the adjusted irrigation decision parameters, a stop irrigation command is generated.

5. The method according to claim 1, characterized in that, The process of processing the canopy image to obtain the current value of the leaf area index of the crop includes: The canopy image is subjected to pixel recognition and segmentation to obtain the canopy gap ratio; The current value of the leaf area index is calculated based on the gap ratio model and the canopy gap ratio.

6. The method according to claim 1, characterized in that, The irrigation control command also includes an irrigation duration parameter, and the method further includes: The irrigation duration parameter is generated based on the difference between the upper limit threshold and the current value of the leaf area index in the adjusted irrigation decision parameters, the water use efficiency coefficient, the leaf area per plant, and the average flow rate of the irrigation system.

7. A crop irrigation monitoring device, characterized in that, The apparatus for implementing the crop irrigation control method as described in any one of claims 1-6, comprising: Image acquisition unit, used to acquire images of the crop canopy; A temperature acquisition unit is used to acquire the canopy leaf surface temperature of the crop; The main control unit is used to process the canopy image to obtain the current value of the leaf area index of the crop, dynamically adjust the preset irrigation threshold and / or decision delay time according to the canopy leaf temperature to obtain the adjusted irrigation decision parameters, and generate irrigation control instructions based on the adjusted irrigation decision parameters and the current value of the leaf area index. A communication unit, connected to the main control unit, is used to transmit the irrigation control command to the irrigation system actuator, so that the irrigation system actuator can start or stop the irrigation operation according to the irrigation control command.

8. The apparatus according to claim 7, characterized in that, The image acquisition unit is a high-definition digital camera, deployed above the canopy of the crop; the communication unit is a wireless communication module.

9. The apparatus according to claim 7, characterized in that, The device further includes: a power module, which is a solar power system, including a solar panel, an energy storage battery, and a charging management module; and a temperature acquisition unit, including a non-contact infrared temperature sensor.

10. The apparatus according to claim 7, characterized in that, The device further includes a waterproof and dustproof housing, in which the image acquisition unit, the temperature acquisition unit, the main control unit, and the communication unit are encapsulated.

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