Greenhouse rose water and soil conservation control method and system based on internet of things

Abstract

The present application relates to the technical field of greenhouse planting control, and provides a greenhouse Chinese rose water and soil conservation control method and system based on the Internet of Things, which comprises the following steps: according to the cause classification result, performing irrigation adjustment operation to obtain irrigation adjustment result; wherein, the irrigation adjustment operation comprises adjusting the water supply parameter of the irrigation branch or adjusting the micro-pulse irrigation; the micro-pulse irrigation refers to an intermittent water supply irrigation mode of the irrigation branch according to the pulse length, pulse interval and single water volume; based on the irrigation adjustment result, monitoring the updated water supply uniformity judgment result after the irrigation adjustment operation is performed; when the updated water supply uniformity judgment result still indicates that the preset standard is not met, generating a maintenance prompt according to the irrigation adjustment result and the substrate state. The present application has the effect of improving the water and fertilizer utilization efficiency and the overall quality of the Chinese rose.

Description

Technical Field

[0001] This invention relates to the technical field of greenhouse planting control, specifically to an Internet of Things-based method and system for controlling water and moisture retention in greenhouse roses. Background Technology

[0002] In modern greenhouses, IoT-based automated water and fertilizer management systems have been widely applied to the commercial production of high-end cut roses. This system uses sensors deployed in the rose planting bed soil to monitor soil moisture and electrical conductivity in real time. Based on preset ideal ranges, a central controller instructs the drip irrigation system to precisely replenish water and apply nutrient solutions, significantly improving water and fertilizer utilization efficiency and ensuring a stable basic environment for rose growth.

[0003] However, with the expansion of production scale and the increasing demands for rose quality, the existing system has revealed limitations in terms of refined management. Although the system has been upgraded to zoned management, with independent irrigation and fertilization programs set for roses at different growth stages, differences in rose quality still exist within the same management zone. This is mainly due to differences in the microenvironment within the zone and the inherent unevenness of the drip irrigation system itself.

[0004] The existing control logic relies excessively on readings from a few representative soil sensors. When the soil moisture at these representative points remains within the ideal range, the system determines that irrigation is unnecessary. However, in reality, rose bushes in microenvironments with rapid water loss or those supplied by semi-blocked drippers may already be experiencing water stress, manifesting as physiological changes such as increased leaf temperature or stomatal closure. These early symptoms are difficult for the existing soil sensor network to detect. By the time localized drought becomes severe enough to affect soil sensor readings, irreversible damage to plant growth and flower bud differentiation has occurred, leading to a decline in final quality.

[0005] Therefore, the current system cannot directly sense and respond to the true "thirst" state of individual rose bushes, resulting in a delay and deviation between the control basis and the control target. This deviation is amplified, especially when faced with differences in the microenvironment and equipment operating conditions within the plot, making true "on-demand irrigation" difficult to achieve. This leads to significant differences in key quality indicators such as flower size, color, and shelf life among the same batch of roses.

[0006] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0007] This application discloses an IoT-based method and system for controlling water and moisture retention in greenhouse roses, aiming to address the limitations of existing greenhouse rose water and fertilizer management systems in terms of refined management, particularly the inability to directly perceive and respond to the actual water stress state of individual rose plants, and the problem of rose quality differences caused by the unevenness of drip irrigation systems.

[0008] The technical solution of this application is as follows:

[0009] In a first aspect, this application discloses a method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things, comprising the following steps:

[0010] Obtain information on the growth stage and preset water requirements of the rose plants, and determine the target water supply flow rate for each irrigation branch based on the growth stage and preset water requirements.

[0011] Obtain the actual water supply flow rate of each irrigation branch, the leaf temperature information of the rose plants, and the substrate moisture information;

[0012] Based on the comparison between the actual water supply flow and the target water supply flow, leaf temperature information, and substrate moisture information, the water supply uniformity of the irrigation branch is judged, and the water supply uniformity judgment result is obtained.

[0013] When the water supply uniformity judgment result does not meet the preset standard, the cause is distinguished as dripper blockage or decreased substrate permeability based on the actual water supply flow, leaf temperature information and substrate moisture information, and the cause is distinguished. Among them, substrate moisture information includes shallow substrate moisture data and deep substrate moisture data. Decreased substrate permeability indicates that the substrate in the rose root zone has reduced ability to infiltrate irrigation water, resulting in an abnormal difference in the change between shallow substrate moisture and deep substrate moisture.

[0014] Based on the cause, the result is distinguished, and irrigation adjustment operations are performed to obtain the irrigation adjustment result; among them, irrigation adjustment operations include adjusting the water supply parameters of irrigation branches or adjusting micro-pulse irrigation; micro-pulse irrigation refers to an irrigation method that intermittently supplies water to irrigation branches according to pulse duration, pulse interval and single water output volume;

[0015] Based on the irrigation adjustment results, monitor the updated water supply uniformity judgment results obtained after the irrigation adjustment operation is performed;

[0016] If the updated water supply uniformity assessment result still indicates that it does not meet the preset standard, a maintenance prompt will be generated based on the irrigation adjustment results and substrate status.

[0017] Secondly, this application also discloses an IoT-based greenhouse rose water and moisture conservation control system, used to perform IoT-based greenhouse rose water and moisture conservation control, including:

[0018] The target flow determination module is used to obtain information on the growth stage of the rose plant and the preset water demand information, and to determine the target water supply flow for each irrigation branch based on the growth stage information and the preset water demand information.

[0019] The data information acquisition module is used to acquire the actual water supply flow of each irrigation branch, the leaf temperature information of the rose plants, and the substrate moisture information.

[0020] The water supply uniformity judgment module is used to judge the water supply uniformity of irrigation branches based on the comparison results of the actual water supply flow and the target water supply flow, leaf temperature information and substrate moisture information, and obtain the water supply uniformity judgment result.

[0021] The cause differentiation module is used to differentiate the cause as dripper blockage or decreased substrate permeability based on the actual water supply flow rate, blade temperature information and substrate humidity information when the water supply uniformity judgment result does not meet the preset standard, and obtain the cause differentiation result.

[0022] The irrigation adjustment execution module is used to distinguish the result based on the cause, perform irrigation adjustment operations, and obtain the irrigation adjustment result.

[0023] The result monitoring module is used to monitor the water supply uniformity judgment result updated after the irrigation adjustment operation is performed, based on the irrigation adjustment result.

[0024] The maintenance prompt generation module is used to generate maintenance prompts based on irrigation adjustment results and substrate status when the updated water supply uniformity judgment result still indicates that it does not meet the preset standard.

[0025] Beneficial Effects: The IoT-based greenhouse rose water retention and moisture control method disclosed in this application determines the target water supply flow rate by acquiring information on the rose plant's growth stage and preset water demand, and acquires real-time information on actual water supply flow rate, leaf temperature, and substrate moisture. This method can comprehensively judge the water supply uniformity of irrigation branches based on multi-dimensional data and intelligently distinguish specific causes such as dripper blockage or decreased substrate permeability. For different causes, the system can perform corresponding irrigation adjustment operations, such as adjusting water supply parameters or performing micro-pulse irrigation. After irrigation adjustments, the system continuously monitors water supply uniformity and generates maintenance prompts if it still does not meet standards.

[0026] Through the above technical solution, this application effectively solves the problems of existing technologies that over-rely on readings from a few soil sensors, making it impossible to directly perceive the true water stress state of individual rose plants, and the unevenness of drip irrigation systems leading to differences in rose quality. Specifically, by introducing leaf temperature information and moisture data from both shallow and deep substrate layers, the system can perceive the initial symptoms of water stress in rose plants and changes in substrate permeability earlier and more accurately, overcoming the delay and deviation between the control basis and control target in traditional systems. By accurately distinguishing between dripper clogging and decreased substrate permeability, this application can provide targeted solutions, avoiding blind irrigation or ineffective maintenance, thereby significantly improving water and fertilizer utilization efficiency, ensuring the optimal environment for rose growth, and ultimately enhancing the overall quality of roses, achieving true "on-demand irrigation." Attached Figure Description

[0027] Figure 1 This is a flowchart of a method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things, according to one embodiment of the present invention.

[0028] Figure 2 This is a flowchart of a method for controlling water and moisture retention in greenhouse roses based on the Internet of Things, according to another embodiment of the present invention.

[0029] Figure 3 This is a system block diagram of an IoT-based greenhouse rose water retention and moisture conservation control system according to another embodiment of the present invention;

[0030] Explanation of reference numerals in the attached figures:

[0031] 1. IoT-based greenhouse rose water conservation and moisture retention control system; 11. Target flow determination module; 12. Data information acquisition module; 13. Water supply uniformity judgment module; 14. Cause differentiation module; 15. Irrigation adjustment execution module; 16. Result monitoring module; 17. Maintenance prompt generation module. Detailed Implementation

[0032] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0033] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0034] This application proposes an IoT-based method for controlling water and moisture retention in greenhouse rose cultivation, combining... Figure 1 As shown, it includes:

[0035] S1, obtain the growth stage information and preset water demand information of the rose plant, and determine the target water supply flow rate of each irrigation branch based on the growth stage information and preset water demand information.

[0036] In one possible implementation, the target water supply flow rate for each irrigation branch is determined based on the baseline water requirement per plant, the number of rose plants corresponding to each irrigation branch, the irrigation duration, and environmental correction results. The baseline water requirement per plant is compiled into a growth stage water requirement table based on historical irrigation records, transpiration monitoring records, substrate moisture recovery records, and manual calibration results for the same rose variety at different growth stages. The central control unit retrieves the corresponding baseline water requirement per plant from the growth stage water requirement table based on the rose plant's growth stage information and corrects it according to greenhouse environmental information. The preset water requirement information can be stored in the form of a growth stage water requirement table, which includes the baseline water requirement per plant for different growth stages. The greenhouse environmental information refers to specific collected information on greenhouse environmental parameters, including temperature, light intensity, air humidity, and ventilation speed.

[0037] ;

[0038] in, Indicates the first The target water supply flow rate for each irrigation branch can be expressed in L / min. Indicates the first The number of rose plants corresponding to each irrigation branch; This indicates the baseline water requirement per plant corresponding to the current growth stage, and the unit can be L / plant. The environmental correction factor represents the target water supply flow rate; Indicates the first The irrigation duration for each irrigation branch can be expressed in minutes. The environmental correction factor can be determined based on greenhouse temperature, light intensity, air humidity, and ventilation speed. To avoid extreme environmental data causing abnormal increases or decreases in the target water supply flow, the environmental correction factor can be limited to a preset environmental correction range.

[0039] ;

[0040] ;

[0041] in, Indicates intermediate quantities for environmental correction; This indicates the lower limit of the environmental correction factor; This indicates the upper limit of the environmental correction factor; Indicates greenhouse temperature; This indicates the reference temperature corresponding to the current growth stage; Indicates light intensity; This indicates the baseline light intensity corresponding to the current growth stage; Indicates air humidity; This indicates the baseline air humidity corresponding to the current growth stage; Indicates ventilation speed; This indicates the baseline ventilation speed corresponding to the current growth stage; These represent the target flow correction weights corresponding to temperature, light intensity, air humidity, and ventilation speed, respectively; the correction weights are determined by the correspondence between changes in environmental parameters and changes in monthly rose water demand in historical irrigation samples.

[0042] S2, obtain the actual water supply flow of each irrigation branch, the leaf temperature information of the rose plants, and the substrate moisture information;

[0043] In one possible implementation, each irrigation branch is equipped with at least one flow sensor and one branch pressure sensor. The flow sensor is used to collect the actual water supply flow rate, and the branch pressure sensor is used to collect the branch inlet pressure status. A main water supply pipeline is equipped with a main pipe pressure sensor, differential pressure sensors are installed at both ends of the filter, valves are equipped with valve opening feedback units, and branch pipelines are equipped with leakage detection units and venting status detection units. These sensors collectively generate water supply system status information, used to eliminate pump pressure abnormalities, filter blockages, pipeline leaks, valve malfunctions, and localized airlocks before dripper blockage is detected.

[0044] Shallow and deep substrate moisture sensors are positioned within the same dripper wetting front coverage area and arranged vertically along the rose root zone. The shallow substrate moisture sensor is not limited to a fixed depth and can be positioned within the upper third of the rose root zone; the deep substrate moisture sensor is not limited to a fixed depth and can be positioned within the lower middle part of the rose root zone. For cultivation substrates with shallow root zones, the burial depth can be reduced accordingly; for cultivation substrates with deeper root zones, the burial depth can be increased accordingly.

[0045] Leaf temperature information can be collected using infrared temperature sensors, thermal imaging equipment, or mobile temperature measurement devices. During collection, priority should be given to functional leaves within the corresponding area of ​​the irrigation branch, avoiding areas with strong direct sunlight and reflection, diseased or pest-infested leaves, and mechanically damaged leaves. Multiple leaf temperature measurement points can be selected for each irrigation branch, and the mean or median of the leaf temperatures from these points can be calculated to obtain the leaf temperature information corresponding to that irrigation branch.

[0046] All sensor data are aligned using a unified timestamp. Under normal monitoring conditions, actual water supply flow, branch pressure, substrate humidity, leaf temperature, and greenhouse environmental information can be collected at sampling intervals of 1 to 5 minutes; after micro-pulse irrigation is triggered, sampling intervals of 5 to 30 seconds can be used. The central control unit only includes data with completed timestamp alignment within the same sampling period in the water supply uniformity assessment and water infiltration response analysis.

[0047] Before formal operation, the flow sensor can be calibrated using a standard flow meter, the pressure sensor using a standard pressure source, the substrate moisture sensor using a standard substrate sample with known moisture content, and the leaf temperature acquisition device using a blackbody thermometric reference source. During operation, when sensor data exceeds the measurement range, the amplitude of continuous sampling abrupt changes exceeds the preset abrupt change threshold, or the data deviation between adjacent sensors in the same irrigation branch exceeds the preset consistency threshold, the corresponding data will be marked as abnormal data and removed or suspended from participation in the judgment.

[0048] S3. Based on the comparison between the actual water supply flow and the target water supply flow, the leaf temperature information and the substrate moisture information, the water supply uniformity of the irrigation branch is judged, and the water supply uniformity judgment result is obtained.

[0049] In one possible implementation, the water supply uniformity judgment result is determined by a combination of abnormal flow rate markers, abnormal blade temperature markers, and abnormal humidity change markers.

[0050] ;

[0051] in, Indicates the first Flow deviation of each irrigation branch; Indicates the first The actual water supply flow of each irrigation branch; Indicates the first The target water supply flow rate for each irrigation branch. This represents the preset flow deviation threshold, which can be determined by the mean and standard deviation of the flow deviation in normal irrigation samples.

[0052] when Greater than If the traffic is abnormal, mark it as abnormal; otherwise, mark it as normal.

[0053] Furthermore, the leaf temperature information is corrected based on the greenhouse environment information to obtain the corrected leaf temperature information. This corrected leaf temperature information is the result of environmental compensation of the original leaf temperature information and is not an independently added data source.

[0054] ;

[0055] in, Indicates the first Environmentally corrected blade temperature information for each irrigation branch; Indicates the first Original blade temperature information corresponding to each irrigation branch; These represent the blade temperature correction coefficients corresponding to temperature, light intensity, air humidity, and ventilation speed, respectively; the blade temperature correction coefficients are calibrated from historical samples of blade temperature changes with environmental parameters under normal water supply conditions.

[0056] when If the leaf temperature is higher than the upper limit of the normal leaf temperature corresponding to the current growth stage, the leaf temperature is identified as abnormal and marked as abnormal; otherwise, the leaf temperature is identified as abnormal and marked as normal.

[0057] ;

[0058] in, Indicates the first Differences in humidity variation among irrigation branches; Indicates the rate of change in moisture content of the shallow matrix; Indicates the rate of change in moisture content of the deep matrix; This indicates a preset small quantity used to avoid a denominator of zero; The threshold representing the difference in humidity change can be determined by statistical results of the difference between the humidity change rate of shallow matrix and the humidity change rate of deep matrix in normal infiltration samples.

[0059] when Greater than If the humidity variation difference is abnormal, it is marked as abnormal; otherwise, it is marked as normal. When at least two of the abnormal flow rate, abnormal blade temperature, and abnormal humidity variation are abnormal, the water supply uniformity judgment result is determined to be non-compliant with the preset standard; when fewer than two of the above abnormal markers are abnormal, the water supply uniformity judgment result is determined to be compliant with the preset standard.

[0060] S4. When the water supply uniformity judgment result does not meet the preset standard, the cause is distinguished as dripper blockage or decreased substrate permeability based on the actual water supply flow, leaf temperature information and substrate moisture information, and the cause distinction result is obtained. Among them, substrate moisture information includes shallow substrate moisture data and deep substrate moisture data. Decreased substrate permeability indicates that the substrate in the rose root zone has reduced ability to infiltrate irrigation water, resulting in an abnormal difference in the change between shallow substrate moisture and deep substrate moisture.

[0061] In one possible implementation, before determining the cause as dripper blockage, the central control unit first reads the water supply system status information. If the main pipe pressure is abnormal, a pump pressure abnormality alert is generated; if the filter differential pressure is abnormal, a filter blockage alert is generated; if the branch inlet pressure is abnormal, a branch pressure abnormality alert is generated; if the valve opening status is inconsistent with the control command, a valve abnormality alert is generated; if the pipeline leakage status indicates a leak, a pipeline leakage alert is generated; if the venting status is abnormal, an air lock alert is generated.

[0062] Only when all the above-mentioned water supply system status information is normal, and the actual water supply flow is lower than the target water supply flow or the flow deviation is considered normal. Exceeding the preset flow deviation threshold Only then was the cause determined to be dripper blockage.

[0063] Before determining that the cause was a decrease in substrate permeability, the central control unit first performed environmental correction on the leaf temperature information based on greenhouse environmental data. If the corrected leaf temperature information... The readings still show increased blade temperature, and a flow deviation between the actual and target water supply flow rates. The preset flow deviation threshold was not exceeded. If there is an abnormal difference between the moisture change rate of the shallow substrate and the moisture change rate of the deep substrate, micro-pulse irrigation is triggered, and water infiltration response analysis is performed after micro-pulse irrigation.

[0064] If, after micropulse irrigation, the rate of change in shallow substrate humidity is significantly higher than that in deep substrate humidity, the increase in deep substrate humidity is lower than the low permeability threshold, and the rate of decrease in leaf temperature after environmental correction is lower than the leaf temperature decrease rate judgment standard, then the water infiltration response analysis result is determined to be insufficient infiltration, and the cause judgment result is determined to be decreased substrate permeability. The low permeability threshold can be determined by the statistical results of the increase in deep substrate humidity in low-permeability samples; the low-permeability samples refer to historical samples where the water supply system is in normal condition and the shallow substrate humidity has increased, but the deep substrate humidity has not increased sufficiently within the preset sampling time window. If neither the shallow nor deep substrate humidity data shows a reasonable change, and the leaf temperature change differs significantly from that of adjacent plants on the same branch, then a sensor placement or sensor response check prompt is generated, and the cause distinction result is paused, directly determining it as decreased substrate permeability.

[0065] S5, distinguish the result based on the cause, perform irrigation adjustment operation, and obtain the irrigation adjustment result; among which, irrigation adjustment operation includes adjusting the water supply parameters of irrigation branch or adjusting micro-pulse irrigation; micro-pulse irrigation refers to the irrigation method of intermittently supplying water to irrigation branch according to pulse duration, pulse interval and single water output volume;

[0066] S6, Based on the irrigation adjustment results, monitor the updated water supply uniformity judgment results obtained after the irrigation adjustment operation is performed;

[0067] S7. When the updated water supply uniformity judgment result still indicates that it does not meet the preset standard, a maintenance prompt is generated based on the irrigation adjustment result and substrate status.

[0068] "Growth stage information" refers to the growth status of the rose plant at different growth stages, such as the vegetative growth stage, flower bud differentiation stage, and flowering stage. Because the transpiration rate, root water absorption capacity, and flower bud development requirements of roses differ at different growth stages, their water requirements also vary. Therefore, growth stage information is an important basis for determining the irrigation needs of roses. "Preset water requirement information" refers to the water requirement information pre-set based on the rose's growth stage, variety characteristics, greenhouse environmental parameters, and historical irrigation experience. The greenhouse environmental parameters may include temperature, humidity, and light intensity. The preset water requirement information provides a benchmark for subsequently determining the target water supply flow rate for irrigation branches.

[0069] "Target water supply flow rate" refers to the ideal water flow rate that each irrigation branch should provide to meet the water requirements of roses at a specific growth stage. "Actual water supply flow rate" refers to the actual water flow rate output by each irrigation branch, monitored in real time by flow sensors. By comparing the target and actual water supply flow rates, it is possible to determine whether there are problems such as insufficient, excessive, or uneven water distribution in the irrigation branches. "Leaf temperature information" refers to the surface temperature data of rose leaves obtained through infrared temperature sensors, thermal imaging equipment, or other non-contact temperature measurement devices. Leaf temperature reflects the water stress state of the rose; when the rose is short of water, transpiration weakens, the leaf's heat dissipation capacity decreases, and the leaf temperature usually rises. "Substrate moisture information" refers to the moisture content data of the rose root zone substrate, including shallow and deep substrate moisture data. Shallow substrate moisture data usually reflects the moisture content of the surface layer of the substrate, while deep substrate moisture data usually reflects the moisture content of the main root distribution area. By comparing the shallow and deep substrate moisture data, it is possible to determine whether irrigation water can effectively infiltrate into the root zone.

[0070] "Water supply uniformity" refers to the evenness of water supply from the irrigation system to different irrigation branches, different planting areas, or different rose bushes. If the water supply uniformity does not meet the preset standards, some rose bushes may experience water shortages while others experience waterlogging. "Drip emitter clogging" refers to the phenomenon where irrigation drippers are partially or completely blocked at the outlet due to scale, sediment, microbial films, or other impurities, resulting in the actual water flow rate of the corresponding irrigation branch being lower than the target water flow rate. "Decreased substrate permeability" refers to a reduced ability of the rose root zone substrate to infiltrate irrigation water, causing abnormal differences between shallow and deep substrate moisture data. This condition may be caused by substrate compaction, organic matter decomposition, dense root growth, or changes in pore structure due to long-term irrigation. "Irrigation adjustment operations" refer to parameter adjustments performed on the irrigation system based on the cause of the water supply uniformity problem. This may include adjusting irrigation duration, irrigation frequency, water pressure, and other water supply parameters for irrigation branches, or adjusting micro-pulse irrigation. "Micro-pulse irrigation" refers to an irrigation method that intermittently supplies water to irrigation branches according to pulse duration, pulse interval, and single water output volume. It can promote the gradual infiltration of irrigation water with small flow and multiple times, which is beneficial to improving the problem of uneven water supply in the root zone caused by decreased substrate permeability.

[0071] This application achieves refined water and moisture control for greenhouse roses through a series of steps. First, it acquires information on the rose plant's growth stage and preset water requirements. Specifically, growth stage information can be obtained through manual input, planting plan calculations, or image recognition. For example, based on the rose's planting date, pruning date, and a preset growth cycle model, the system can automatically determine whether the rose is currently in its vegetative growth stage, flower bud differentiation stage, or flowering stage. Alternatively, it can determine the current growth stage by acquiring images of the rose plant and identifying the number of branches and leaves, flower bud status, or flowering status. Preset water requirements can be set based on the rose variety, current growth stage, greenhouse temperature, humidity, light intensity, historical irrigation data, and expert experience. For example, roses in their flower bud differentiation or flowering stage typically require higher water supply stability, and their preset water requirements can be higher than those in the vegetative growth stage. Based on the growth stage information and preset water requirements, the system determines the target water flow rate for each irrigation branch, ensuring that roses in different areas or under different growth conditions receive water supply targets that match their water requirements.

[0072] Secondly, the actual water flow rate of each irrigation branch, the leaf temperature information of the rose plants, and the substrate moisture information are obtained. The actual water flow rate can be obtained in real time through flow sensors installed on each irrigation branch, reflecting the current actual water output of each branch. Leaf temperature information can be obtained through an array of infrared temperature sensors, thermal imaging cameras, or mobile temperature measuring devices deployed in the greenhouse. These devices can periodically scan the surface temperature of the rose leaves and send the collected results to the central control unit. Substrate moisture information can be obtained through moisture sensors deployed in the root zone of the rose, generating shallow substrate moisture data and deep substrate moisture data respectively. For example, shallow moisture sensors can be installed 5 to 10 cm below the substrate surface, and deep moisture sensors can be installed 20 to 30 cm below the substrate surface, thus reflecting the water content of the surface substrate and the main water absorption area of ​​the roots, respectively.

[0073] Next, based on the comparison between the actual and target water supply flow rates, leaf temperature information, and substrate moisture information, the system assesses the water supply uniformity of the irrigation branches, obtaining the water supply uniformity assessment result. Specifically, the system first compares the deviation between the actual and target water supply flow rates of each irrigation branch to determine if there are cases of insufficient branch flow, excessive branch flow, or excessive flow differences between branches. Simultaneously, the system combines rose leaf temperature information to determine if the plant exhibits a water stress tendency, and combines shallow and deep substrate moisture data to determine the distribution of irrigation water in the substrate. For example, if the actual water supply flow rate of a certain irrigation branch is lower than the target water supply flow rate, and the corresponding area of ​​rose leaf temperature continues to rise, it can be determined that there is a risk of insufficient water supply in that area; if the actual water supply flow rate is close to the target water supply flow rate, but the shallow substrate moisture data is high, the deep substrate moisture data is low, and the leaf temperature is still rising, it can be determined that the irrigation water has not effectively infiltrated into the root zone, and the water supply uniformity may not meet the preset standards.

[0074] When the water supply uniformity assessment result does not meet the preset standard, the cause is determined based on the actual water supply flow, leaf temperature information, and substrate moisture information, identifying either dripper blockage or decreased substrate permeability. In practice, if the actual water supply flow of a certain irrigation branch is significantly lower than the target flow, and the corresponding area shows increased rose leaf temperature and generally low substrate moisture, then the uneven water supply is more likely caused by dripper blockage. Dripper blockage directly reduces the water output of the irrigation branch, making it difficult for both shallow and deep substrate moisture data in the corresponding area to reach the expected levels. If the actual water supply flow is close to the target flow, but there is an abnormal difference between shallow and deep substrate moisture data—for example, higher shallow substrate moisture while persistently lower deep substrate moisture, coupled with increased leaf temperature—the uneven water supply is more likely caused by decreased substrate permeability. Decreased substrate permeability indicates that although irrigation water has been output from the irrigation branch, it has not adequately entered the main root distribution area, resulting in water stress symptoms in the rose.

[0075] After determining the cause, irrigation adjustment operations are performed based on the results. If the cause indicates dripper blockage, the adjustment operations may include increasing the water supply pressure of the corresponding irrigation branch, extending the irrigation duration, initiating a flushing procedure, or adjusting the irrigation frequency to attempt to flush out the blockage and restore the actual water supply flow. If the cause indicates decreased substrate permeability, the adjustment operations may include adjusting the pulse duration, pulse interval, and single-volume output volume of the micro-pulse irrigation. For example, the pulse duration can be shortened, the pulse interval increased, or the single-volume output volume reduced to allow irrigation water to enter the substrate in small flows and multiple times, reducing the risk of surface water accumulation and promoting slow infiltration of water into deeper substrate layers. By performing different irrigation adjustment operations for different causes, dripper blockage can be avoided from being mistakenly treated as decreased substrate permeability, and surface water accumulation can be avoided simply by increasing the water supply when substrate permeability is decreased.

[0076] Subsequently, based on the irrigation adjustment results, the system monitors the updated water supply uniformity assessment results obtained after the irrigation adjustment operation. Specifically, after adjusting the water supply parameters of the irrigation branch or implementing micro-pulse irrigation, the system re-acquires the actual water supply flow rate of the corresponding irrigation branch, the leaf temperature information of the rose plants, and the substrate moisture information. It then again assesses the water supply uniformity based on the comparison between the actual and target water supply flow rates, leaf temperature information, and substrate moisture information. If the adjusted actual water supply flow rate returns to near the target flow rate, the leaf temperature drops to a reasonable range, and the difference between shallow and deep substrate moisture data decreases, an updated assessment result indicating that the water supply uniformity meets the preset standards can be obtained. If the above indicators still do not improve, it indicates that the irrigation adjustment operation has not adequately resolved the current water supply uniformity problem and further processing is required.

[0077] Finally, if the updated water supply uniformity assessment result still indicates that it does not meet the preset standard, maintenance prompts are generated based on the irrigation adjustment results and substrate condition. Specifically, if the actual water supply flow rate is still lower than the target water supply flow rate after repeatedly increasing the water supply pressure, extending the irrigation duration, or performing a flushing procedure, maintenance prompts such as "check and replace the drippers," "clean the filter," or "check for blockages in the irrigation branches" can be generated. If, after performing micro-pulse irrigation adjustments, the shallow substrate humidity data is still significantly higher than the deep substrate humidity data, and the leaf temperature is still high, maintenance prompts such as "perform substrate improvement," "check the substrate compaction status," or "adjust the root zone substrate structure" can be generated. Through the above methods, this application can set water supply targets according to the rose's growth stage and water requirement status, and identify water supply uniformity problems by combining actual water supply flow rate, leaf temperature information, and shallow and deep substrate humidity information. It can further distinguish between dripper blockage and decreased substrate permeability, and generate corresponding irrigation adjustment operations and maintenance prompts, thereby improving the accuracy and stability of water retention and moisture control for greenhouse roses.

[0078] Optionally, the steps for obtaining substrate moisture information include:

[0079] Shallow substrate humidity sensors and deep substrate humidity sensors are deployed in the root zone of the rose corresponding to the irrigation branch, and the corresponding shallow substrate humidity data and deep substrate humidity data are acquired.

[0080] The step of determining the water supply uniformity of the irrigation branch based on the comparison result of the actual water supply flow rate and the target water supply flow rate, the leaf temperature information, and the substrate moisture information, and obtaining the water supply uniformity determination result, includes:

[0081] The flow deviation is calculated based on the comparison between the actual water supply flow and the target water supply flow.

[0082] Based on the flow deviation, the blade temperature information, the shallow substrate moisture data, and the deep substrate moisture data, the water supply uniformity of the irrigation branch is determined, and the water supply uniformity judgment result is obtained.

[0083] When the water supply uniformity judgment result does not meet the preset standard, the step of distinguishing the cause as dripper blockage or decreased substrate permeability based on the actual water supply flow rate, the blade temperature information, and the substrate humidity information, and obtaining the cause distinction result includes:

[0084] When the water supply uniformity judgment result does not meet the preset standard, and the actual water supply flow is lower than the target water supply flow, and the flow deviation exceeds the preset flow deviation threshold, the cause differentiation result is determined to be dripper blockage;

[0085] When the water supply uniformity judgment result does not meet the preset standard, the flow deviation does not exceed the preset flow deviation threshold, and the blade temperature information shows that the blade temperature is rising, micro-pulse irrigation is triggered.

[0086] Within a preset time after the micro-pulse irrigation is triggered, shallow substrate humidity data, deep substrate humidity data, and leaf temperature information are collected after the pulse. The shallow substrate humidity data in the substrate humidity information is updated to the shallow substrate humidity data after the pulse, and the deep substrate humidity data in the substrate humidity information is updated to the deep substrate humidity data after the pulse.

[0087] Based on the shallow substrate humidity data, deep substrate humidity data, and leaf temperature information after the pulse, a water infiltration response analysis is performed to obtain the water infiltration response analysis results. The water infiltration response analysis results represent the water infiltration response to the deep substrate determined based on the shallow substrate humidity data, deep substrate humidity data, and leaf temperature information after the micro-pulse irrigation is triggered.

[0088] Based on the water infiltration response analysis results, determine whether the reason why the water supply uniformity judgment result does not meet the preset standard is due to the decrease in matrix permeability, and obtain the reason judgment result;

[0089] When the cause determination result indicates that the cause is decreased matrix permeability, the cause differentiation result is determined to be decreased matrix permeability.

[0090] Specifically, to obtain more refined substrate moisture information, shallow and deep substrate moisture sensors can be deployed in the rose root zone corresponding to the irrigation branches. Shallow substrate moisture sensors are typically placed a few centimeters below the substrate surface to monitor immediate moisture changes after irrigation water enters the substrate; deep substrate moisture sensors are placed in deeper areas where the rose roots are mainly distributed to monitor water infiltration and root absorption. These two sensors at different depths can acquire both shallow and deep substrate moisture data, providing a more comprehensive understanding of the moisture distribution and dynamic changes within the substrate.

[0091] When determining the water supply uniformity of irrigation branches, the flow deviation is first calculated by comparing the actual water supply flow rate with the target flow rate. Flow deviation is a key indicator measuring the difference between the actual and expected water supply, directly reflecting whether the irrigation system is experiencing insufficient or excessive water supply. Subsequently, this flow deviation, leaf temperature information, shallow substrate moisture data, and deep substrate moisture data are combined to comprehensively assess the water supply uniformity of the irrigation branches. For example, if the flow deviation is large, leaf temperature is elevated (indicating plant water shortage), and the changes in shallow and deep substrate moisture are inconsistent, it can be determined that the water supply uniformity does not meet the preset standard.

[0092] In practical applications, when the water supply uniformity assessment result does not meet the preset standard, it is necessary to further distinguish the specific reasons. Specifically, when the water supply uniformity assessment result does not meet the preset standard, and the actual water supply flow is lower than the target water supply flow, while the flow deviation exceeds the preset flow deviation threshold, the cause can be clearly identified as dripper blockage. This indicates that there is a physical obstacle in the irrigation system, leading to insufficient actual water supply.

[0093] However, when the water supply uniformity assessment result does not meet the preset standard, but the flow deviation does not exceed the preset flow deviation threshold, and the leaf temperature information shows that the leaf temperature is rising, this may mean that the total water supply appears normal, but the water has not effectively reached the roots or been absorbed by the plant. In this case, micro-pulse irrigation will be triggered. Micro-pulse irrigation is an intermittent, low-flow irrigation method. Its purpose is to simulate natural rainfall or improve the permeability of the substrate through short-term, multiple water supply, and it also serves as a diagnostic tool.

[0094] Within a preset timeframe following the triggering of micro-pulse irrigation, the system collects shallow substrate humidity data, deep substrate humidity data, and leaf temperature information. This data is used to update the existing substrate humidity information for subsequent analysis. Subsequently, based on this updated data, a water infiltration response analysis is performed. This analysis aims to assess the response of water infiltration into the deep substrate after micro-pulse irrigation is triggered. For example, if shallow substrate humidity increases rapidly while deep substrate humidity remains relatively unchanged, or if leaf temperature fails to decrease effectively, it may indicate that water infiltration is obstructed.

[0095] Finally, based on the water infiltration response analysis results, it is determined whether the reason for the water supply uniformity judgment result not meeting the preset standard is a decrease in matrix permeability. When the water infiltration response analysis results clearly indicate a decrease in water infiltration capacity, the cause can be identified as a decrease in matrix permeability. A decrease in matrix permeability is usually manifested as an abnormal difference in the change between the moisture content of the shallow matrix and the moisture content of the deep matrix, that is, water stays in the shallow layer for too long and is unable to effectively penetrate to the deeper layers.

[0096] Optional, combined Figure 2 As shown, the steps for conducting water infiltration response analysis and obtaining the results include: based on the shallow substrate humidity data, deep substrate humidity data, and leaf temperature information after the pulse, the water infiltration response analysis is performed.

[0097] A1, reads the growth stage information of the rose plant, as well as the temperature and light intensity information of the greenhouse environment;

[0098] A2, Based on the aforementioned growth stage information, retrieve the transpiration rate range and water absorption characteristics of the rose.

[0099] A3. Calculate the transpiration correction coefficient based on the temperature information and the light intensity information;

[0100] A4. Based on the transpiration rate range, the water absorption characteristics, and the transpiration correction coefficient, adjust the threshold for the difference in humidity change between the shallow substrate humidity change rate and the deep substrate humidity change rate, as well as the criterion for judging the rate of leaf temperature decrease.

[0101] A5. Based on the adjusted humidity change difference threshold and the leaf temperature drop rate judgment standard, the moisture infiltration response analysis is performed on the shallow matrix humidity data, the deep matrix humidity data, and the leaf temperature information after the pulse, and the moisture infiltration response analysis results are obtained.

[0102] In one possible implementation, the evapotranspiration correction coefficient is determined based on temperature information, light intensity information, air humidity information, and ventilation speed information, and is limited to a preset evapotranspiration correction range.

[0103] ;

[0104] ;

[0105] in, Indicates the transpiration correction factor; This indicates the intermediate amount of transpiration correction; This indicates the lower limit of the transpiration correction factor; This indicates the upper limit of the transpiration correction factor; These represent the influence coefficients of temperature, light intensity, air humidity, and ventilation speed on the transpiration of roses; the influence coefficients are obtained by calibrating the correspondence between rose transpiration rate samples under normal water supply conditions and greenhouse environmental parameter samples.

[0106] The baseline humidity variation threshold is determined using normal infiltration samples. These normal infiltration samples refer to shallow and deep substrate humidity variation rate samples collected during historical irrigation processes where the water supply system, substrate condition, and leaf temperature have returned to normal. The mean of the difference between the shallow and deep substrate humidity variation rates in the normal infiltration samples, plus a preset standard deviation, can be used as the baseline humidity variation threshold.

[0107] ;

[0108] in, This indicates the threshold for the difference in humidity after adjustment; Indicates the threshold for difference in baseline humidity; This represents the correction coefficient for the growth stage, which can be calibrated based on the rose's root water absorption capacity and sensitivity to changes in substrate moisture at different growth stages.

[0109] The criterion for judging the rate of decrease in baseline leaf temperature was determined using normal micropulse irrigation samples. These normal micropulse irrigation samples refer to historical samples where the deep substrate humidity increased and the leaf temperature returned to normal after micropulse irrigation.

[0110] ;

[0111] in, This indicates the criteria for judging the rate of temperature decrease of the adjusted blades; This indicates the standard for judging the rate of temperature decrease of the reference blade.

[0112] When performing water infiltration response analysis, the rate of change in shallow matrix moisture after the pulse is calculated. , rate of change in deep matrix humidity after pulse and the rate of temperature decrease of the blades after environmental correction. .when Greater than the adjusted humidity change difference threshold ,and The rate of temperature drop below the adjusted blade temperature threshold is the judgment standard. If the water infiltration response analysis result is negative, it is determined to be insufficient infiltration; otherwise, it is determined to be normal infiltration. Insufficient infiltration means that after micropulse irrigation, water is mainly retained in the shallow substrate and does not form a deep substrate humidity rise response that matches the changes in shallow substrate humidity within the preset sampling time window.

[0113] Specifically, before conducting water infiltration response analysis, it is necessary to first obtain information on the growth stage of the rose plants, as well as the temperature and light intensity information of the greenhouse environment. Growth stage information can include the rose's budding stage, growth stage, and flowering stage, which can be obtained through pre-set planting plans, image recognition technology, or manual input. The temperature and light intensity information of the greenhouse environment can be collected in real time by environmental sensors deployed within the greenhouse. Based on the obtained growth stage information, the system will retrieve the transpiration rate range and water absorption characteristics of the rose corresponding to that growth stage. For example, roses in their rapid growth or flowering stage typically have higher transpiration rates and water absorption than those in dormancy or seedling stages. This biological characteristic data can be pre-stored in a database and managed in a refined manner according to rose varieties and growth models.

[0114] In practical applications, based on the collected greenhouse temperature and light intensity information, the system calculates a transpiration correction coefficient. This correction coefficient quantifies the impact of current environmental conditions on the rose's transpiration rate. For example, under high temperature and high light conditions, the transpiration correction coefficient will increase accordingly to reflect higher transpiration potential. Furthermore, based on the retrieved transpiration rate range, water absorption characteristics, and the calculated transpiration correction coefficient, the system dynamically adjusts the humidity change difference threshold between the shallow and deep substrate humidity change rates, as well as the leaf temperature drop rate judgment criteria. For example, when the rose is in a high transpiration period and environmental conditions promote transpiration, the judgment criteria for water infiltration may be more stringent, requiring a faster increase in deep substrate humidity or a more significant decrease in leaf temperature to be considered normal infiltration. Therefore, based on these dynamically adjusted humidity change difference thresholds and leaf temperature drop rate judgment criteria, water infiltration response analysis is performed on the shallow substrate humidity data, deep substrate humidity data, and leaf temperature information collected after micro-pulse irrigation triggering, resulting in more accurate water infiltration response analysis results.

[0115] Optionally, when the cause differentiation result indicates a decrease in substrate permeability, the specific steps for performing irrigation adjustment operations based on the cause differentiation result to obtain the irrigation adjustment result include:

[0116] To determine the degree of difference between the moisture change rate of the shallow matrix and the moisture change rate of the deep matrix;

[0117] Based on the degree of difference, determine the level of decrease in matrix permeability;

[0118] Based on the substrate permeability degradation level, determine the pulse duration, pulse interval, and single water output volume of the micro-pulse irrigation.

[0119] Micro-pulse irrigation is carried out based on the determined pulse duration, pulse interval, and single water output volume of micro-pulse irrigation.

[0120] During micropulse irrigation, shallow substrate humidity data, deep substrate humidity data, and leaf temperature information are monitored to obtain micropulse irrigation monitoring results.

[0121] Based on the micropulse irrigation monitoring results, the pulse duration, the pulse interval, or the single water output volume are adjusted to obtain the micropulse irrigation parameters.

[0122] The micropulse irrigation parameters are used as the corresponding irrigation adjustment results.

[0123] Specifically, when the cause differentiation clearly indicates a decrease in matrix permeability, the system first obtains the degree of difference between the moisture change rate of the shallow matrix and the moisture change rate of the deep matrix. The moisture change rate of the shallow matrix refers to the magnitude of change in moisture within a certain time period, while the moisture change rate of the deep matrix refers to the magnitude of change in moisture within the same time period. The degree of difference between these two rates directly reflects the efficiency of vertical infiltration of water into the matrix. For example, if the moisture change rate of the shallow matrix is ​​high while that of the deep matrix is ​​low, it indicates that water is retained in the shallow layer, and infiltration is hindered.

[0124] In one possible implementation, the degree of difference between the moisture change rate of the shallow matrix and the moisture change rate of the deep matrix is ​​determined according to the following formula.

[0125] ;

[0126] in, This indicates the degree of difference between the rate of change of moisture in the shallow matrix and the rate of change of moisture in the deep matrix. Indicates the rate of change in moisture content of the shallow matrix; This indicates the rate of change in moisture content of the deep matrix.

[0127] according to The comparison results with preset threshold levels can classify the decline in matrix permeability into mild, moderate, and severe declines. The preset threshold levels can be determined by statistical results from normal and low-permeability samples. For example, when... When the permeability is above the upper limit of normal infiltration samples but below the threshold of the first low permeability level, it is defined as a slight decrease; when... A moderate decrease is defined as when the first low permeability threshold is reached but below the second low permeability threshold; when... When the second low permeability threshold is reached, it is determined to be a severe decrease.

[0128] Furthermore, based on the degree of difference obtained, the system can determine the level of substrate permeability decline. This level can be mild, moderate, or severe, and its purpose is to provide a quantitative basis for subsequent irrigation adjustments. For example, the greater the degree of difference, the higher the level of substrate permeability decline. Based on this permeability decline level, the system will determine the pulse duration, pulse interval, and single-pump volume of micro-pulse irrigation. Micro-pulse irrigation is an intermittent water supply method that effectively avoids surface runoff and deep leakage caused by a large amount of water supplied at once through short-duration, multiple pulses, and is particularly suitable for substrates with decreased permeability. Pulse duration, pulse interval, and single-pump volume are key parameters of micro-pulse irrigation, and their proper setting is crucial for restoring substrate permeability and improving water use efficiency. For example, for substrates with severe permeability decline, shorter pulse durations, longer pulse intervals, and smaller single-pump volumes may be required to give the substrate sufficient time to absorb water.

[0129] After determining the initial micro-pulse irrigation parameters, the system will perform micro-pulse irrigation based on these parameters. During this process, to ensure irrigation effectiveness and perform real-time optimization, the system continuously monitors shallow substrate moisture data, deep substrate moisture data, and leaf temperature information, and generates micro-pulse irrigation monitoring results based on this data. The shallow and deep substrate moisture data reflect the distribution and infiltration of water in the substrate, while leaf temperature information serves as an indicator of the degree of water stress in the rose plant. For example, excessively high leaf temperature may indicate that the plant is still in a state of water shortage.

[0130] Based on the micropulse irrigation monitoring results, the system will adaptively adjust the pulse duration, pulse interval, or single-pump water volume to obtain optimized micropulse irrigation parameters. For example, if the monitoring results show that the shallow layer humidity is too high while the deep layer humidity is insufficient, it may be necessary to extend the pulse interval or reduce the single-pump water volume to promote more uniform downward water penetration. Conversely, if the leaf temperature continues to rise, it may be necessary to increase the single-pump water volume or shorten the pulse interval. Ultimately, these adjusted and optimized micropulse irrigation parameters will be used as the corresponding irrigation adjustment results to guide subsequent irrigation operations.

[0131] Optionally, during micropulse irrigation, the steps for monitoring shallow substrate moisture data, deep substrate moisture data, and leaf temperature information to obtain micropulse irrigation monitoring results include:

[0132] At preset time points before and after the micropulse valve is opened, shallow matrix humidity data, deep matrix humidity data, and leaf temperature information are collected.

[0133] The collected shallow and deep matrix humidity data were averaged and outliers were removed to obtain the processed humidity data.

[0134] Based on the growth stage information of the rose plants and the greenhouse environmental parameters, the saturation threshold of the humidity sensor was adjusted to obtain the adjusted saturation threshold.

[0135] Based on the processed humidity data, the aforementioned leaf temperature information, and the adjusted saturation threshold, micro-pulse irrigation monitoring results are generated.

[0136] The system collects data at preset time points before and after the micro-pulse valve opens and closes to capture instantaneous changes in substrate humidity and leaf temperature before and after irrigation, thereby more accurately assessing the effectiveness of micro-pulse irrigation. These preset time points can be set according to the response speed and data acquisition frequency of the actual irrigation system; for example, 5 seconds before valve opening and 10 seconds after valve closing. Furthermore, averaging and outlier removal are performed on the collected shallow and deep substrate humidity data to improve data accuracy and reliability. Averaging smooths data fluctuations and reduces random errors; outlier removal eliminates erroneous data caused by sensor malfunctions or environmental interference, ensuring the validity of subsequent analysis. In addition, adjusting the humidity sensor's saturation threshold based on the rose plant's growth stage and greenhouse environmental parameters ensures that humidity monitoring results better reflect reality. Rose plants at different growth stages have different water requirements and absorption capacities, and greenhouse environmental parameters (such as temperature and light) also affect water evaporation and plant transpiration. Dynamically adjusting the saturation threshold allows for more accurate judgment of substrate moisture levels, avoiding misjudgments. For example, during the rose seedling stage, the sensitivity to substrate moisture may be higher, and the saturation threshold can be appropriately lowered; while during the full bloom stage, the water requirement is high, and the saturation threshold can be appropriately raised. Finally, based on the processed humidity data, the aforementioned leaf temperature information, and the adjusted saturation threshold, micropulse irrigation monitoring results are generated. These results comprehensively reflect the impact of micropulse irrigation on substrate moisture and the physiological state of rose plants, providing a crucial basis for subsequent adjustments to irrigation parameters.

[0137] In one possible implementation, the saturation threshold of the humidity sensor is determined based on substrate type, rose growth stage, and greenhouse environmental information. First, a baseline saturation threshold is obtained by calibration using standard saturated substrate samples under the same substrate type. Then, a growth stage correction coefficient is determined based on the rose plant's growth stage information. Next, an environmental correction coefficient is determined based on greenhouse temperature, light intensity, air humidity, and ventilation speed. Finally, the adjusted saturation threshold is obtained.

[0138] ;

[0139] in, This represents the adjusted saturation threshold; Indicates the baseline saturation threshold; The growth stage correction coefficient can be determined based on the rose root water absorption capacity and substrate moisture sensitivity range at different growth stages. This represents the environmental correction coefficient for the saturation threshold, which can be calibrated based on the impact of the greenhouse environment on substrate evaporation and plant transpiration.

[0140] When the processed humidity data reaches the adjusted saturation threshold At this time, the central control unit stops increasing the volume of water discharged at one time to avoid water accumulation on the surface substrate.

[0141] Outlier removal includes range rejection, abrupt change rejection, and consistency rejection. Range rejection removes data that exceeds the effective range of the corresponding sensor; abrupt change rejection removes data where the change in adjacent sampling points exceeds a preset abrupt change threshold; consistency rejection removes data where the deviation from the data of adjacent sensors in the same irrigation branch exceeds a preset consistency threshold. For rejected data, the median of adjacent sensors within the same sampling period can be used as a substitute. When outliers occur in multiple consecutive sampling periods for the same irrigation branch, a sensor check prompt is generated.

[0142] Optionally, the steps for adjusting the pulse duration, pulse interval, or single water output volume based on the micropulse irrigation monitoring results to obtain micropulse irrigation parameters include:

[0143] The trends of shallow substrate humidity, deep substrate humidity, and leaf temperature were extracted from the micropulse irrigation monitoring results.

[0144] When both the shallow and deep substrate moisture trends indicate insufficient water infiltration, and the leaf temperature trend indicates a decrease in leaf temperature, a short observation period should be initiated.

[0145] During a short observation period, shallow substrate humidity data, deep substrate humidity data, and leaf temperature information were continuously collected.

[0146] After the short observation period ends, determine whether there is a continuous upward trend in the moisture data of shallow and deep substrates after the micropulse irrigation stops, and determine whether the decrease in leaf temperature is stable.

[0147] When both shallow and deep substrate moisture data show a continuous upward trend after micro-pulse irrigation stops and leaf temperature stabilizes, maintain the current pulse duration and pulse interval, and extend the interval of the next micro-pulse irrigation. The results of the maintenance and extension treatments are then compiled.

[0148] When at least one of the shallow substrate moisture data and deep substrate moisture data does not show a continuous upward trend after micro-pulse irrigation stops, but the leaf temperature drops steadily, the single outflow volume is increased and the interval between the next micro-pulse irrigation is shortened, and the results of the increased treatment are obtained.

[0149] When the shallow and deep substrate moisture data rise after the micro-pulse irrigation stops, but the rise is below the low permeability threshold, and the leaf temperature drop has not stabilized, a substrate permeability anomaly verification command is generated, and the command processing result is obtained.

[0150] Micropulse irrigation parameters are obtained based on the results of maintaining and extending the treatment, increasing the treatment, and the results of instruction processing.

[0151] Specifically, extracting the trends in shallow substrate humidity, deep substrate humidity, and leaf temperature from micropulse irrigation monitoring results involves performing time-series analysis on continuously collected shallow substrate humidity data, deep substrate humidity data, and leaf temperature information. Methods such as moving averages, difference calculations, or regression analysis are used to determine the rising, falling, or stable trends of these parameters during and after micropulse irrigation. Both shallow and deep substrate humidity trends indicate insufficient water infiltration. This can be understood as a significant increase in shallow substrate humidity after irrigation, but a less significant or slow increase in deep substrate humidity, indicating that water mainly remains on the surface and fails to effectively penetrate downwards. A decrease in leaf temperature typically indicates that after the plant receives sufficient water, transpiration returns to normal, and the leaves cool down through transpiration.

[0152] When the above conditions are met—namely, insufficient water infiltration and a drop in leaf temperature—the system will initiate a preset short observation period. This short observation period aims to further confirm the effectiveness of micropulse irrigation and the true infiltration status of the substrate. During this period, the system will continuously and frequently collect shallow substrate moisture data, deep substrate moisture data, and leaf temperature information to more accurately capture dynamic changes after irrigation stops.

[0153] After the short observation period ends, the system will make key judgments. It will determine whether there is a continuous upward trend in the shallow and deep substrate moisture data after the micro-pulse irrigation stops, aiming to assess whether the irrigation water is still slowly infiltrating and being absorbed by the substrate, or whether there is a rebound. It will also determine whether the decrease in leaf temperature has stabilized, in order to assess whether the plant's water stress has been effectively alleviated and has reached a stable state.

[0154] Based on these judgment results, the system will adopt different adjustment strategies:

[0155] 1. When both shallow and deep substrate moisture data show a continuous upward trend after micro-pulse irrigation stops, and leaf temperature stabilizes, this indicates that the current irrigation amount and infiltration rate are appropriate, and the plants have received sufficient water. At this point, to avoid over-irrigation and conserve water resources, the system will maintain the current pulse duration and interval, but will extend the interval between the next micro-pulse irrigation.

[0156] 2. When, after micropulse irrigation stops, at least one of the shallow and deep substrate moisture data no longer shows a sustained upward trend, but the leaf temperature stabilizes, this may indicate that although the plant's water stress has been alleviated, the overall water-holding capacity or penetration depth of the substrate remains insufficient, or the water distribution is uneven. To ensure that deeper substrates also receive sufficient moisture, the system increases the single outflow volume and shortens the interval between the next micropulse irrigation, aiming to improve deep penetration through more concentrated water supply.

[0157] 3. When the moisture data of both shallow and deep substrates rise after micro-pulse irrigation stops, but the increase is below the low permeability threshold, and the leaf temperature has not stabilized, this strongly indicates a serious problem with substrate permeability, preventing water from effectively infiltrating and leaving the plant under water stress. At this point, the system will generate a substrate permeability anomaly verification command, triggering further diagnostic procedures to determine the specific cause of the decreased substrate permeability.

[0158] Finally, based on the above three processing results (maintaining and extending the processing results, increasing the processing results, and command processing results), the system will obtain the final micro-pulse irrigation parameters to guide subsequent irrigation operations.

[0159] In one possible implementation, the micropulse irrigation parameters are not adjusted indefinitely, but rather an initial parameter table is invoked based on the level of substrate permeability decline. The initial parameter table includes the initial pulse duration, initial pulse interval, initial single-cycle water volume, parameter adjustment step size, and upper and lower limits of the parameters corresponding to mild, moderate, and severe declines.

[0160] For mild water drop, a longer initial pulse duration, a shorter initial pulse interval, and a larger initial single outflow volume can be used; for moderate water drop, a medium initial pulse duration, a medium initial pulse interval, and a medium initial single outflow volume can be used; for severe water drop, a shorter initial pulse duration, a longer initial pulse interval, and a smaller initial single outflow volume can be used to reduce the risk of surface water accumulation and prolong the time for water to infiltrate into the deeper matrix.

[0161] During each adjustment, the central control unit adjusts the pulse duration, pulse interval, or single-output water volume according to the parameter adjustment step size. The parameter adjustment step size can be a preset number of seconds for the pulse duration, a preset number of minutes for the pulse interval, or a preset proportion of the single-output water volume. The upper and lower limits of the parameters are used to restrict the maximum and minimum values ​​of the pulse duration, pulse interval, and single-output water volume. When any parameter reaches its corresponding upper or lower limit, further adjustment in that direction stops.

[0162] After each micro-pulse irrigation adjustment, the central control unit calculates the amount of improvement.

[0163] ;

[0164] in, Indicates the amount of adjustment and improvement; Indicates the increase in moisture content of the deep matrix; This indicates the degree to which the difference between the moisture content of the shallow and deep substrates has narrowed. This indicates the degree of temperature reduction in the blades after environmental correction; These represent the weights of the corresponding indicators, which can be determined based on the rose's growth stage and historical control effects.

[0165] When the updated water supply uniformity assessment result meets the preset standard, stop adjusting the micro-pulse irrigation parameters; when the improvement amount is adjusted twice consecutively... When the temperature falls below the preset convergence threshold, micro-pulse irrigation parameter adjustment stops, and the maintenance prompt generation process begins; when the number of micro-pulse irrigation adjustments reaches the preset upper limit, micro-pulse irrigation parameter adjustment stops; when the shallow substrate moisture data reaches the adjusted saturation threshold... When the adjustment stops, the increase in single-output volume is stopped. The pulse duration, pulse interval, and single-output volume corresponding to the stop adjustment are taken as the irrigation adjustment result. The preset convergence threshold can be determined based on the change range of adjustment improvement in historical micro-pulse irrigation adjustment samples; when the adjustment improvement after continuous adjustment is lower than the preset convergence threshold, it indicates that continuing to adjust the pulse duration, pulse interval, or single-output volume has limited effect on improving the uniformity of water supply.

[0166] Optionally, when the shallow and deep substrate moisture data rise after micro-pulse irrigation stops, but the rise is below the low permeability threshold, and the leaf temperature has not stabilized, the steps to generate a substrate permeability anomaly verification command and obtain the command processing result include:

[0167] When the moisture data of shallow and deep substrates rise after micro-pulse irrigation stops, but the rise is below the low permeability threshold, and the leaf temperature drops and does not stabilize, the substrate permeability anomaly verification trigger condition is confirmed to be met.

[0168] Obtain information on substrate type, substrate service life, greenhouse temperature, and light intensity;

[0169] Based on the substrate type information, the substrate service life information, the greenhouse temperature information, and the light intensity information, calculate the permeability correction coefficient;

[0170] The verification pulse parameters are determined based on the matrix permeability anomaly verification triggering conditions and the permeability efficiency correction coefficient; the verification pulse parameters include the verification pulse duration, verification pulse outflow rate, verification sampling time window, and verification sampling object;

[0171] Based on the verification pulse parameters, a corresponding matrix permeability anomaly verification command is generated, and the command processing result is obtained.

[0172] Specifically, after micro-pulse irrigation stops, if both shallow and deep substrate moisture data show an upward trend, but the increase is below the preset low permeability threshold, and the leaf temperature decline trend has not yet stabilized, the system will confirm that the triggering conditions for substrate permeability anomaly verification have been met. This indicates a potential problem of decreased substrate permeability, requiring further verification.

[0173] Based on this, the system acquires multiple pieces of information to more accurately assess substrate permeability. Substrate type information refers to the type of substrate currently used in the greenhouse, such as peat moss, coconut coir, or a mixed substrate. Different types of substrates have different initial permeability characteristics. Substrate usage years information refers to the length of time the substrate has been in use; substrate permeability typically changes with age, such as aging or compaction. Greenhouse temperature and light intensity information reflect the current greenhouse environment. These environmental factors affect the transpiration of rose plants and the evaporation rate of substrate moisture, thus indirectly affecting substrate permeability.

[0174] Furthermore, based on the acquired information on substrate type, substrate service life, greenhouse temperature, and light intensity, the system calculates a permeability correction factor. This correction factor quantifies the extent to which substrate permeability may deviate from the standard value under current substrate and environmental conditions. For example, for specific types of substrates with longer service lives and operating in high-temperature, high-light environments, the permeability correction factor may be adjusted to be higher to reflect the risk of a potential decrease in permeability.

[0175] Subsequently, based on the confirmed substrate permeability anomaly verification triggering conditions and the calculated permeability efficiency correction coefficient, the system determines the specific verification pulse parameters. Specifically, the verification pulse parameters include the verification pulse duration, i.e., the duration of the verification irrigation pulse; the verification pulse water output, i.e., the amount of water provided by a single verification pulse; the verification sampling time window, i.e., the specific time period before and after the verification pulse during which data needs to be collected; and the verification sampling objects, i.e., the sensor data that needs to be monitored, such as shallow substrate moisture data, deep substrate moisture data, and leaf temperature information.

[0176] Finally, based on these customized verification pulse parameters, the system generates a corresponding substrate permeability anomaly verification command and obtains the command processing result. This command is then sent to the irrigation control unit to trigger a targeted verification irrigation, thereby obtaining more accurate substrate permeability data.

[0177] In one possible implementation, the permeability correction factor is determined based on the substrate type, the substrate's service life, and greenhouse environment information.

[0178] ;

[0179] in, This represents the permeability efficiency correction factor; This represents the baseline permeability corresponding to the matrix type information; This represents the service life degradation coefficient corresponding to the substrate's service life information; This represents the environmental correction factor corresponding to greenhouse environment information.

[0180] Benchmark permeability The infiltration rate can be determined through infiltration calibration experiments of different substrate types under standard irrigation conditions. The substrate types may include coconut coir substrate, peat substrate, perlite mixed substrate, or other rose greenhouse cultivation substrates. An attenuation coefficient is used. It can be determined based on the service life of the substrate; the longer the service life of the substrate, the better. The lower the value, the more it reflects the decreased infiltration capacity caused by matrix compaction, organic matter decomposition, and changes in pore structure. Environmental correction factor. It can be determined based on greenhouse temperature, light intensity, air humidity, and ventilation speed, and used to correct for the effects of substrate evaporation and plant transpiration on the verification results.

[0181] After obtaining the permeability efficiency correction coefficient Subsequently, the central control unit determines the verification pulse parameters from a preset verification pulse parameter table. This preset verification pulse parameter table can be generated based on historical verification samples under different substrate types, substrate service life, and permeability efficiency levels. The verification pulse parameters include the verification pulse duration, verification pulse water output, verification sampling time window, and verification sampling objects. The verification sampling objects include at least shallow substrate humidity data, deep substrate humidity data, and environmentally corrected leaf temperature information.

[0182] Optionally, after the steps of generating the corresponding matrix permeability anomaly verification command based on the verification pulse parameters and obtaining the command processing result, the method further includes:

[0183] The irrigation control unit triggers the matrix permeability anomaly verification pulse according to the verification pulse parameters in the matrix permeability anomaly verification instruction;

[0184] The sensor acquisition unit collects shallow matrix humidity data, deep matrix humidity data, and leaf temperature information according to the verification sampling time window and verification sampling object in the matrix permeability anomaly verification instruction.

[0185] Based on the shallow matrix humidity data and the deep matrix humidity data, determine whether there is a difference in vertical humidity change after triggering the matrix permeability anomaly verification pulse;

[0186] Based on the blade temperature information, determine whether the blade temperature drops rapidly after the verification pulse;

[0187] When there are differences in vertical humidity and the leaf temperature does not drop rapidly, it is determined that the substrate permeability has decreased.

[0188] When there is no difference in vertical humidity and the leaf temperature does not drop rapidly, the humidity sensor is deemed to be under-responsive.

[0189] Based on the determined decrease in matrix permeability or insufficient response of the humidity sensor, a matrix permeability anomaly verification result is generated.

[0190] Based on the matrix permeability anomaly verification results, update the maintenance prompt.

[0191] Specifically, after generating the substrate permeability anomaly verification command and obtaining the command processing result, the irrigation control unit is configured to trigger a substrate permeability anomaly verification pulse according to the preset verification pulse parameters in the command. This verification pulse is a controlled, short-duration irrigation designed to simulate actual irrigation conditions in order to observe the response of the substrate and plants. The verification pulse parameters may include the verification pulse duration, verification pulse water output, verification sampling time window, and verification sampling objects, all of which are calculated based on factors such as substrate type, service life, and greenhouse environment.

[0192] After the verification pulse is triggered, the sensor acquisition unit will collect shallow substrate humidity data, deep substrate humidity data, and leaf temperature information in real time according to the verification sampling time window and verification sampling object specified in the verification instruction. The shallow and deep substrate humidity data are used to monitor the vertical infiltration of water in the substrate, while the leaf temperature information is used to reflect the water absorption status and transpiration response of the rose plant.

[0193] Subsequently, the system analyzes the collected shallow and deep substrate moisture data to determine if there are significant differences in vertical moisture changes in the substrate after the verification pulse. These differences refer to abnormalities in the magnitude or rate of change between shallow and deep substrate moisture after the verification pulse; for example, a significant increase in shallow moisture while deep moisture changes little, typically indicating impaired water infiltration. Simultaneously, the system also uses leaf temperature information to determine if a rapid decrease in leaf temperature occurs after the verification pulse. A rapid decrease in leaf temperature is usually a physiological response to increased water absorption and transpiration in the plant.

[0194] Based on this, the system will make a comprehensive judgment: when there is a difference in vertical humidity (i.e., poor water infiltration) and the leaf temperature does not drop rapidly (i.e., the plant is not effectively absorbing water), the cause is determined to be decreased substrate permeability. This indicates that there may be a problem with the physical structure of the substrate, preventing water from effectively reaching the root zone. Conversely, when there is no difference in vertical humidity (i.e., normal water infiltration), but the leaf temperature still does not drop rapidly, the cause is determined to be insufficient response from the humidity sensor.

[0195] Ultimately, based on the above judgment results, the system will generate a clear matrix permeability anomaly verification result, which clearly indicates whether the problem lies in the matrix permeability or the sensor response.

[0196] It is important to note that when determining whether the leaf temperature drops rapidly after the verification pulse, the central control unit does not directly use the original leaf temperature information. Instead, it first performs environmental correction on the leaf temperature information based on greenhouse environmental information, and then uses the environmentally corrected leaf temperature information to determine whether the leaf temperature drop rate meets the leaf temperature drop rate judgment standard. This process can reduce the interference of changes in light intensity, greenhouse temperature, air humidity, and ventilation speed on the verification pulse judgment results.

[0197] When the micro-pulse irrigation parameters are stopped, if the water supply uniformity judgment result still does not meet the preset standard, and the matrix permeability abnormality verification result indicates that the matrix permeability has decreased, the central control unit further collects matrix electrical impedance data and matrix surface and shallow layer image data to identify the key factors of the decreased matrix permeability.

[0198] Optionally, based on the matrix permeability anomaly verification results, the steps for updating maintenance prompts include:

[0199] When the matrix permeability anomaly verification results indicate a decrease in matrix permeability, obtain matrix electrical impedance data of the rose root region as well as surface and shallow matrix image data;

[0200] Based on the matrix electrical impedance data, the uniformity of the matrix pore structure is analyzed to obtain the pore structure analysis results.

[0201] Based on the surface and shallow layer image data of the matrix, the root growth density of roses is identified, and the root density identification result is obtained.

[0202] Based on the pore structure analysis results and the root density identification results, the key factors causing the decrease in matrix permeability are determined; the key factors include local matrix compaction, decreased water absorption due to organic matter decomposition, or physical obstruction caused by dense root growth;

[0203] When the key factor is localized substrate compaction or decreased water absorption due to organic matter decomposition, suggestions for substrate improvement measures are generated.

[0204] When the key factor is physical obstruction caused by dense root growth, a root pruning prompt is generated;

[0205] When the matrix permeation anomaly verification result indicates that the humidity sensor response is insufficient, a humidity sensor check prompt is generated.

[0206] Update the maintenance prompts based on the substrate improvement measures prompts, the root pruning prompts, or the humidity sensor check prompts.

[0207] Acquiring matrix electrical impedance data from the rose root zone involves collecting data using impedance sensors deployed within the rose root region. This data reflects the electrical properties of the matrix, indirectly characterizing its physicochemical properties such as pore structure, water content, and ion concentration. Analyzing changes in impedance data allows for the assessment of matrix uniformity and compaction. Surface and shallow matrix image data can be acquired using miniature cameras or image sensors, providing a direct view of the matrix surface condition and root distribution within the shallow matrix.

[0208] Furthermore, the uniformity of the matrix pore structure is analyzed based on matrix electrical impedance data, yielding pore structure analysis results. These results are based on matrix electrical impedance data and evaluated using specific algorithm models to assess the size, distribution, and connectivity of pores within the matrix. For example, electrical impedance tomography can be used to construct a three-dimensional electrical impedance distribution map within the matrix, thereby analyzing the uniformity of the pore structure. The root growth density of roses is identified based on surface and shallow matrix image data, yielding root density identification results. These results are based on surface and shallow matrix image data and quantify the density of rose root growth within specific areas using image processing and pattern recognition techniques. For example, the pixel proportion occupied by roots in an image can be calculated, or the number of root intersections can be identified to assess density.

[0209] Specifically, key factors contributing to decreased substrate permeability include localized substrate compaction, decreased water absorption due to organic matter decomposition, and physical obstruction caused by dense root growth. Localized substrate compaction refers to the formation of dense clumps of substrate particles under long-term irrigation and compaction, leading to reduced porosity and hindered water permeation. Decreased water absorption due to organic matter decomposition refers to the decomposition of organic matter in the substrate by microorganisms, resulting in a decrease in the substrate's water retention capacity and granular structure stability, thus affecting water permeation and retention. Physical obstruction caused by dense root growth refers to the excessive growth of rose roots, forming a dense network in the root zone, physically hindering the downward infiltration of water.

[0210] When the key factor is localized substrate compaction or decreased water absorption due to organic matter decomposition, the system will generate substrate improvement prompts. For example, it may suggest loosening the soil, adding new organic substrate, adjusting the substrate ratio, or using biological amendments to improve the substrate's physical structure and water absorption performance. When the key factor is physical obstruction caused by dense root growth, the system will generate root pruning prompts. For example, it may suggest appropriately pruning the rose plant's roots to reduce physical obstruction of water infiltration and promote new root growth. When the substrate permeability abnormality verification result indicates insufficient humidity sensor response, the system will generate humidity sensor check prompts. For example, it may suggest checking the humidity sensor's installation location, ensuring proper wiring, or calibrating or replacing the sensor to ensure accurate data acquisition.

[0211] This application also discloses an IoT-based greenhouse rose water and moisture conservation control system, used to perform IoT-based greenhouse rose water and moisture conservation control, combined with... Figure 3 As shown, the IoT-based greenhouse rose water retention and moisture conservation control system 1 includes:

[0212] The target flow determination module 11 is used to obtain the growth stage information and preset water demand information of the rose plant, and determine the target water supply flow of each irrigation branch based on the growth stage information and preset water demand information.

[0213] The data information acquisition module 12 is used to acquire the actual water supply flow of each irrigation branch, the leaf temperature information of the rose plants, and the substrate moisture information.

[0214] The water supply uniformity judgment module 13 is used to judge the water supply uniformity of the irrigation branch based on the comparison results of the actual water supply flow and the target water supply flow, the leaf temperature information and the substrate moisture information, and to obtain the water supply uniformity judgment result.

[0215] The cause differentiation module 14 is used to differentiate the cause as dripper blockage or decreased substrate permeability based on the actual water supply flow rate, blade temperature information and substrate humidity information when the water supply uniformity judgment result does not meet the preset standard, and obtain the cause differentiation result.

[0216] The irrigation adjustment execution module 15 is used to distinguish the result based on the cause, perform irrigation adjustment operations, and obtain the irrigation adjustment result.

[0217] The result monitoring module 16 is used to monitor the water supply uniformity judgment result updated after the irrigation adjustment operation is performed, based on the irrigation adjustment result.

[0218] The maintenance prompt generation module 17 is used to generate maintenance prompts based on irrigation adjustment results and substrate status when the updated water supply uniformity judgment result still indicates that it does not meet the preset standard.

[0219] The data acquisition module can consist of a series of sensors and data acquisition units. For example, the actual water flow rate can be measured in real time by a flow meter installed on the irrigation branch; leaf temperature information can be acquired non-contactly by an infrared thermal imager or a point-type infrared temperature sensor array deployed in the greenhouse; and substrate moisture information can be acquired by dielectric constant sensors or resistive humidity sensors buried at different depths (e.g., shallow and deep) in the rose root zone. The data from these sensors can be transmitted to the central processing unit via wired or wireless communication networks (such as LoRa, ZigBee, or Wi-Fi).

[0220] The water supply uniformity assessment module can be implemented as a software algorithm unit that receives data from the data acquisition module and compares it with the target water supply flow rate output by the target flow rate determination module. This module can employ a preset mathematical model or statistical method, such as calculating the coefficient of variation or uniformity index, to evaluate the water supply uniformity.

[0221] The cause differentiation module can be designed as an intelligent diagnostic unit. When the water supply uniformity judgment module outputs a result that does not meet preset standards, this module will further analyze the actual water supply flow rate, blade temperature information, and substrate moisture information. For example, if the actual water supply flow rate is significantly lower than the target flow rate and the blade temperature is elevated, the module tends to identify the cause as dripper blockage. If the actual water supply flow rate is close to the target flow rate, but the blade temperature is elevated and the shallow substrate moisture is high while the deep substrate moisture is low, the module tends to identify the cause as decreased substrate permeability. This module can make decisions based on an expert rule base, fuzzy logic, or machine learning models.

[0222] The irrigation adjustment execution module can be a control unit connected to an irrigation controller or actuator. After the cause differentiation module outputs the cause differentiation results, this module will perform corresponding irrigation adjustment operations according to different causes. For example, if the cause is dripper blockage, this module can instruct the irrigation system to increase the water supply pressure or extend the irrigation duration; if the cause is decreased substrate permeability, this module can adjust the parameters of micro-pulse irrigation, such as pulse duration, pulse interval, and single water output volume, to optimize water infiltration.

[0223] The results monitoring module can be implemented as a continuously running feedback unit. After the irrigation adjustment execution module completes its operation, it will again invoke the functions of the data acquisition module and the water supply uniformity judgment module to obtain and analyze the adjusted water supply uniformity judgment results. This module can perform periodic monitoring to evaluate the long-term effects of the irrigation adjustment operation.

[0224] The maintenance prompt generation module can be a user interface or a notification system. When the result monitoring module finds that the water supply uniformity judgment result still does not meet the preset standard even after irrigation adjustments, this module will generate corresponding maintenance prompts based on the irrigation adjustment results and substrate status. For example, it can generate prompts such as "Check drippers," "Perform substrate improvement," or "Check humidity sensor," and notify management personnel for manual intervention via display screen, SMS, or email.

[0225] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things, characterized in that, include: Obtain information on the growth stage and preset water requirements of the rose plants, and determine the target water supply flow rate for each irrigation branch based on the growth stage and preset water requirements. Obtain the actual water supply flow rate of each irrigation branch, the leaf temperature information of the rose plants, and the substrate moisture information; Based on the comparison between the actual water supply flow rate and the target water supply flow rate, the leaf temperature information, and the substrate moisture information, the water supply uniformity of the irrigation branch is determined, and the water supply uniformity determination result is obtained. When the water supply uniformity judgment result does not meet the preset standard, the cause is distinguished as dripper blockage or decreased substrate permeability based on the actual water supply flow rate, the leaf temperature information, and the substrate moisture information, thus obtaining the cause distinction result; wherein, the substrate moisture information includes shallow substrate moisture data and deep substrate moisture data; the decreased substrate permeability indicates that the substrate in the rose root zone has reduced infiltration capacity for irrigation water, resulting in an abnormal difference in the change between shallow substrate moisture and deep substrate moisture; Based on the reasons identified, irrigation adjustment operations are performed to obtain irrigation adjustment results; wherein, the irrigation adjustment operations include adjusting the water supply parameters of the irrigation branch or adjusting micro-pulse irrigation; the micro-pulse irrigation refers to an irrigation method that intermittently supplies water to the irrigation branch according to the pulse duration, pulse interval and single water output volume; Based on the irrigation adjustment results, monitor the updated water supply uniformity judgment results obtained after the irrigation adjustment operation is performed. If the updated water supply uniformity judgment result still indicates that it does not meet the preset standard, a maintenance prompt is generated based on the irrigation adjustment result and substrate status.

2. The method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things according to claim 1, characterized in that, The steps to obtain substrate moisture information include: Shallow substrate humidity sensors and deep substrate humidity sensors are deployed in the root zone of the rose corresponding to the irrigation branch, and the corresponding shallow substrate humidity data and deep substrate humidity data are acquired. The step of determining the water supply uniformity of the irrigation branch based on the comparison result of the actual water supply flow rate and the target water supply flow rate, the leaf temperature information, and the substrate moisture information, and obtaining the water supply uniformity determination result, includes: The flow deviation is calculated based on the comparison between the actual water supply flow and the target water supply flow. Based on the flow deviation, the blade temperature information, the shallow substrate moisture data, and the deep substrate moisture data, the water supply uniformity of the irrigation branch is determined, and the water supply uniformity judgment result is obtained. When the water supply uniformity judgment result does not meet the preset standard, the step of distinguishing the cause as dripper blockage or decreased substrate permeability based on the actual water supply flow rate, the blade temperature information, and the substrate humidity information, and obtaining the cause distinction result includes: When the water supply uniformity judgment result does not meet the preset standard, and the actual water supply flow is lower than the target water supply flow, and the flow deviation exceeds the preset flow deviation threshold, the cause differentiation result is determined to be dripper blockage; When the water supply uniformity judgment result does not meet the preset standard, the flow deviation does not exceed the preset flow deviation threshold, and the blade temperature information shows that the blade temperature is rising, micro-pulse irrigation is triggered. Within a preset time after the micro-pulse irrigation is triggered, shallow substrate humidity data, deep substrate humidity data, and leaf temperature information are collected after the pulse. The shallow substrate humidity data in the substrate humidity information is updated to the shallow substrate humidity data after the pulse, and the deep substrate humidity data in the substrate humidity information is updated to the deep substrate humidity data after the pulse. Based on the shallow substrate humidity data, deep substrate humidity data, and leaf temperature information after the pulse, a water infiltration response analysis is performed to obtain the water infiltration response analysis results. The water infiltration response analysis results represent the water infiltration response to the deep substrate determined based on the shallow substrate humidity data, deep substrate humidity data, and leaf temperature information after the micro-pulse irrigation is triggered. Based on the water infiltration response analysis results, determine whether the reason why the water supply uniformity judgment result does not meet the preset standard is due to the decrease in matrix permeability, and obtain the reason judgment result; When the cause determination result indicates that the cause is decreased matrix permeability, the cause differentiation result is determined to be decreased matrix permeability.

3. The method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things according to claim 2, characterized in that, The step of performing water infiltration response analysis based on the shallow substrate humidity data after the pulse, the deep substrate humidity data after the pulse, and the leaf temperature information after the pulse, and obtaining the water infiltration response analysis results includes: Read information on the growth stage of rose plants, as well as temperature and light intensity information in the greenhouse environment; Based on the aforementioned growth stage information, retrieve the transpiration rate range and water absorption characteristics of the rose. Calculate the transpiration correction factor based on the temperature information and the light intensity information; Based on the transpiration rate range, the water absorption characteristics, and the transpiration correction coefficient, adjust the threshold for the difference in humidity change between the shallow substrate humidity change rate and the deep substrate humidity change rate, as well as the criterion for judging the rate of leaf temperature decrease. Based on the adjusted humidity change difference threshold and the leaf temperature drop rate judgment standard, water infiltration response analysis was performed on the shallow matrix humidity data, deep matrix humidity data, and leaf temperature information after the pulse, and the water infiltration response analysis results were obtained.

4. The method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things according to claim 1, characterized in that, When the cause differentiation result indicates a decrease in substrate permeability, the step of performing irrigation adjustment operations based on the cause differentiation result to obtain the irrigation adjustment result includes: To determine the degree of difference between the moisture change rate of the shallow matrix and the moisture change rate of the deep matrix; Based on the degree of difference, determine the level of decrease in matrix permeability; Based on the substrate permeability degradation level, determine the pulse duration, pulse interval, and single water output volume of the micro-pulse irrigation. Micro-pulse irrigation is carried out based on the determined pulse duration, pulse interval, and single water output volume of micro-pulse irrigation. During micropulse irrigation, shallow substrate humidity data, deep substrate humidity data, and leaf temperature information are monitored to obtain micropulse irrigation monitoring results. Based on the micropulse irrigation monitoring results, the pulse duration, the pulse interval, or the single water output volume are adjusted to obtain the micropulse irrigation parameters. The micropulse irrigation parameters are used as the corresponding irrigation adjustment results.

5. A method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things, as described in claim 4, is characterized in that... The steps for monitoring shallow substrate moisture data, deep substrate moisture data, and leaf temperature information during micropulse irrigation to obtain micropulse irrigation monitoring results include: At preset time points before and after the micropulse valve is opened, shallow matrix humidity data, deep matrix humidity data, and leaf temperature information are collected. The collected shallow and deep matrix humidity data were averaged and outliers were removed to obtain the processed humidity data. Based on the growth stage information of the rose plants and the greenhouse environmental parameters, the saturation threshold of the humidity sensor was adjusted to obtain the adjusted saturation threshold. Based on the processed humidity data, the leaf temperature information, and the adjusted saturation threshold, micro-pulse irrigation monitoring results are generated.

6. The method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things according to claim 4, characterized in that, The step of adjusting the pulse duration, the pulse interval, or the single water output volume based on the micropulse irrigation monitoring results to obtain micropulse irrigation parameters includes: The trends of shallow substrate humidity, deep substrate humidity, and leaf temperature were extracted from the micropulse irrigation monitoring results. When both the shallow matrix humidity change trend and the deep matrix humidity change trend indicate insufficient water infiltration, and the leaf temperature change trend indicates a decrease in leaf temperature, a short observation period is initiated. During the short observation period, shallow substrate humidity data, deep substrate humidity data, and leaf temperature information were continuously collected. After the short observation period ends, it is determined whether the moisture data of shallow substrate and deep substrate continue to rise after the micropulse irrigation stops, and whether the leaf temperature drop is stable. When both shallow and deep substrate moisture data show a continuous upward trend after micro-pulse irrigation stops and leaf temperature stabilizes, maintain the current pulse duration and pulse interval, and extend the interval of the next micro-pulse irrigation. The results of the maintenance and extension treatments are then compiled. When at least one of the shallow substrate moisture data and deep substrate moisture data does not show a continuous upward trend after micro-pulse irrigation stops, but the leaf temperature drops steadily, the single outflow volume is increased and the interval between the next micro-pulse irrigation is shortened, and the results of the increased treatment are obtained. When the shallow and deep substrate moisture data rise after the micro-pulse irrigation stops, but the rise is below the low permeability threshold, and the leaf temperature drop has not stabilized, a substrate permeability anomaly verification command is generated, and the command processing result is obtained. The micropulse irrigation parameters are obtained based on the results of maintaining and extending the processing, increasing the processing, and the results of the instruction processing.

7. A method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things, as described in claim 6, is characterized in that... The steps for generating a substrate permeability anomaly verification command and obtaining the command processing result when the shallow substrate moisture data and deep substrate moisture data rise but the rise is below the low permeability threshold after the micropulse irrigation stops, and the leaf temperature drop has not stabilized, include: When the moisture data of shallow and deep substrates rise after micro-pulse irrigation stops, but the rise is below the low permeability threshold, and the leaf temperature drops and does not stabilize, the substrate permeability anomaly verification trigger condition is confirmed to be met. Obtain information on substrate type, substrate service life, greenhouse temperature, and light intensity; Based on the substrate type information, the substrate service life information, the greenhouse temperature information, and the light intensity information, calculate the permeability correction coefficient; The verification pulse parameters are determined based on the matrix permeability anomaly verification triggering conditions and the permeability efficiency correction coefficient; the verification pulse parameters include the verification pulse duration, verification pulse outflow rate, verification sampling time window, and verification sampling object; Based on the verification pulse parameters, a corresponding matrix permeability anomaly verification command is generated, and the command processing result is obtained.

8. A method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things, as described in claim 7, is characterized in that... After the step of generating a corresponding matrix permeability anomaly verification command based on the verification pulse parameters and obtaining the command processing result, the method further includes: The irrigation control unit triggers the matrix permeability anomaly verification pulse according to the verification pulse parameters in the matrix permeability anomaly verification instruction; The sensor acquisition unit collects shallow matrix humidity data, deep matrix humidity data, and leaf temperature information according to the verification sampling time window and verification sampling object in the matrix permeability anomaly verification instruction. Based on the shallow matrix humidity data and the deep matrix humidity data, determine whether there is a difference in vertical humidity change after triggering the matrix permeability anomaly verification pulse; Based on the blade temperature information, determine whether the blade temperature drops rapidly after the verification pulse; When there are differences in vertical humidity and the leaf temperature does not drop rapidly, it is determined that the substrate permeability has decreased. When there is no difference in vertical humidity and the leaf temperature does not drop rapidly, the humidity sensor is deemed to be under-responsive. Based on the determined decrease in matrix permeability or insufficient response of the humidity sensor, a matrix permeability anomaly verification result is generated. Based on the matrix permeability anomaly verification results, update the maintenance prompt.

9. A method for controlling water retention and moisture conservation in greenhouse roses based on the Internet of Things according to claim 8, characterized in that, The step of updating the maintenance prompt based on the matrix permeability anomaly verification result includes: When the matrix permeability anomaly verification result indicates a decrease in matrix permeability, acquire matrix electrical impedance data of the rose root region and image data of the matrix surface and shallow layer; Based on the matrix electrical impedance data, the uniformity of the matrix pore structure is analyzed to obtain the pore structure analysis results. Based on the surface and shallow layer image data of the matrix, the root growth density of roses is identified, and the root density identification result is obtained. Based on the pore structure analysis results and the root density identification results, the key factors causing the decrease in matrix permeability are determined; the key factors include local matrix compaction, decreased water absorption due to organic matter decomposition, or physical obstruction caused by dense root growth; When the key factor is localized substrate compaction or decreased water absorption due to organic matter decomposition, suggestions for substrate improvement measures are generated. When the key factor is physical obstruction caused by dense root growth, a root pruning prompt is generated; When the matrix permeation anomaly verification result indicates that the humidity sensor response is insufficient, a humidity sensor check prompt is generated. Update the maintenance prompts based on the substrate improvement measures prompts, the root pruning prompts, or the humidity sensor check prompts.

10. An IoT-based greenhouse rose water and moisture conservation control system, used to perform IoT-based greenhouse rose water and moisture conservation control, characterized in that, include: The target flow determination module is used to obtain information on the growth stage of the rose plant and the preset water demand information, and to determine the target water supply flow for each irrigation branch based on the growth stage information and the preset water demand information. The data information acquisition module is used to acquire the actual water supply flow of each irrigation branch, the leaf temperature information of the rose plants, and the substrate moisture information. The water supply uniformity judgment module is used to judge the water supply uniformity of the irrigation branch based on the comparison result of the actual water supply flow rate and the target water supply flow rate, the leaf temperature information and the substrate humidity information, and to obtain the water supply uniformity judgment result. The cause differentiation module is used to differentiate the cause as dripper blockage or decreased substrate permeability based on the actual water supply flow rate, the blade temperature information and the substrate humidity information when the water supply uniformity judgment result does not meet the preset standard, and obtain the cause differentiation result. The irrigation adjustment execution module is used to distinguish the results based on the stated reasons, perform irrigation adjustment operations, and obtain irrigation adjustment results. The result monitoring module is used to monitor the water supply uniformity judgment result updated after the irrigation adjustment operation is performed, based on the irrigation adjustment result. The maintenance prompt generation module is used to generate maintenance prompts based on the irrigation adjustment results and substrate status when the updated water supply uniformity judgment result still indicates that it does not meet the preset standard.

Images