149 results about "Water potential" patented technology

The invention discloses an intelligent farmland irrigation decision-making method based on digital twinning, and the method comprises the following steps: S1, collecting multi-source data of a farmland environment, and generating a time sequence farmland environment data set; s2, constructing a farmland digital twinborn model, and updating node and edge attribute information in real time; s3, constructing a time sequence diagram based on the updated twinborn model, and inputting the time sequence diagram to a time sequence diagram neural network; s4, optimizing structural parameters of the neural network of the time sequence diagram by applying a red-mouth blue-magpie optimization algorithm; s5, predicting the future soil water potential and the crop water demand trend by using the optimized network; s6, generating an irrigation control instruction according to the prediction result in combination with water resource supply; and S7, executing irrigation, monitoring the humidity of the land parcel and the crop state in real time, and updating the farmland digital twinborn model. According to the invention, by fusing the digital twinning, the time sequence diagram neural network and the Red-billed-blue-magpie optimization algorithm, accurate prediction and intelligent irrigation control of the future water demand trend of the farmland are realized, and the water resource utilization efficiency and the crop yield are significantly improved.

The invention relates to the technical field of intelligent control, and discloses a water-saving fertilization variable control method suitable for sandy soil, and the method comprises the steps: obtaining collection data based on a sensor; and establishing and updating an infiltration-storage-leaching loss prediction model of the sandy soil according to the collected data, performing state estimation on soil moisture and nutrient states, and calculating root layer moisture deviation, fertilizer concentration deviation and deep seepage risk. And executing model predictive control in the rolling time domain to obtain a control result. And executing water-saving fertilization operation according to the control result. In the execution process, the soil volume moisture content, the soil water potential, the soil conductivity and shallow layer leakage observation data are fused, the prediction model is corrected, the control result is dynamically adjusted according to the correction result, and when the environment wind speed exceeds a set threshold value, the spray irrigation parameters are corrected. The fine level of control is improved, deep layer leakage can be inhibited under the sandy soil condition, water and fertilizer balance of a root layer is guaranteed, and external disturbance is coped with.

The invention belongs to the technical field of agriculture, particularly relates to a cranberry water demand dynamic sensing system and a method thereof, and aims to solve the problems that an existing traditional irrigation method is often based on a fixed time table or simple soil humidity measurement, the actual water demand condition of cranberries cannot be timely and accurately reflected, and insufficient irrigation or excessive irrigation is easily caused. In order to solve the problems that in the prior art, water resources are wasted, and the growth and yield of cranberries are possibly influenced, the invention provides the following scheme: the system comprises a monitoring module, a control module and a display module, wherein the monitoring module comprises stem flow rate, leaf water potential, soil water content at different depths and positions, air temperature and humidity, illumination intensity and wind speed data; according to the cranberry water demand monitoring system, accurate monitoring, real-time evaluation and scientific prediction of the cranberry water demand condition can be achieved, then a reasonable irrigation decision and environment regulation and control are guided, and the irrigation efficiency and the water resource utilization efficiency are improved.

The invention provides a soil humidity detection method and system, and the method comprises the steps: determining the soil water potential of each horizontal sampling point through the soil moisture of each horizontal sampling point, and determining the diffusion attenuation rate of the humidity in a target soil region on the horizontal scale through all soil water potentials and the soil moisture tension on the horizontal scale in the target soil region; determining a sedimentation coefficient of moisture in the target soil area according to the soil moisture of each vertical sampling point, and determining permeation distribution of humidity in the target soil area on the depth scale according to the sedimentation coefficient; performing scale fusion on the attenuation rate of the humidity diffused on the horizontal scale and the permeation distribution on the depth scale to obtain the diffusion gradient of the humidity of the target soil area on the spatial scale; performing confidence humidity detection on the target soil area based on the diffusion gradient of the humidity to obtain a confidence humidity value of the target soil area; by adopting the scheme provided by the invention, multi-scale space detection of the soil humidity can be realized, so that the credible range of soil humidity detection is increased.

The invention relates to the field of intelligent irrigation, and discloses an intelligent irrigation system and method for a crop root system, and the system comprises a root zone sensing module which is used for collecting soil environment parameters through multi-mode soil sensor arrays disposed at soil layers of different depths, generating a sensing matrix, and transmitting the sensing matrix to a root zone sensing module; the sensing matrix is used for representing water potential, pH value, nutrient concentration and temperature information in each soil layer; and the root system density analysis module is connected with the root zone sensing module, and is used for constructing a root system density weight matrix based on root system space distribution information obtained by underground computed tomography, and multiplying the sensing matrix by the root system density weight matrix element by element to generate a root zone state vector. Accurate generation of regulation and control signals is achieved, the micro-fluidic execution module can adjust the irrigation flow and the fertilization proportion in real time according to the actual requirements of the root zone, and therefore it is guaranteed that the rhizosphere environment is always close to the optimal physiological interval.

The invention relates to the technical field of environment monitoring, in particular to an intelligent digital rural environment monitoring system and method based on big data, and the system comprises a layered water potential collection module, a gradient reverse correction module, a path inversion modeling module and a multi-dimensional diffusion modeling module, and the layered water potential collection module calculates and generates rural soil environment monitoring data; the rural soil environment monitoring data comprises layered soil water potential distribution, soil water content gradient and a soil conductivity characteristic value, and the soil water potential abnormal flow data comprises a vertical water potential difference value, an abnormal water flow direction vector and a water flow intensity grade; the moisture permeation path distribution diagram comprises a permeation path distribution structure, a soil water potential accumulation interval and a water flow propagation direction identifier, and the diffusion boundary space model comprises a pollutant diffusion boundary range, a moisture transverse migration region and multi-dimensional diffusion rate distribution. According to the scheme, the abnormal distribution range, the duration time and the development trend are quantitatively described, and the research and judgment accuracy of the abnormal penetration and diffusion process is improved.

The invention discloses an in-situ biomineralizable mineral-PHA water-based seed coating based on microphase separation and soil water potential response and a preparation method and application thereof, and belongs to the technical field of green coatings, the in-situ biomineralizable mineral-PHA water-based seed coating comprises a structural mineral skeleton, a PHA and resin composite matrix and a pore-forming disintegrating agent. According to the invention, a resin enrichment layer and island microphase structure is innovatively constructed, and the contradiction between poor wear resistance and difficult disintegration of a bio-based material is effectively solved. Compared with the prior art, the wear-resistant and dust-reducing coating has the advantages that the wear-resistant and dust-reducing performance far better than that of the traditional PHA coating is realized by utilizing an interface enhancement effect under the condition of equal or even lower polymer dosage; meanwhile, the coating is endowed with a sensitive soil water potential response'switch ', so that dry-state tough seed protection and wet-state rapid disintegration are ensured, and germination is not hindered. Organic components of the composition can be biodegraded in aerobic soil, inorganic components are natural minerals, the environmental compatibility is good, the composition has the advantages of high performance and low cost, and an excellent seed treatment scheme is provided for green agriculture.

The invention relates to a tide level obtaining method and system based on an OWC wave energy conversion device. The method comprises the following steps: constructing an energy loss prediction model in the air chamber; acquiring field incident wave energy, reflected wave energy, water potential energy increment, kinetic energy increment and pneumatic output energy at the current time period; inputting incident wave energy and reflected wave energy into the model to obtain predicted energy loss; and the tide level variation is solved based on the energy conservation relational expression, and the current tide level is calculated. The system comprises an energy loss prediction module, a wave energy acquisition module, a water body energy acquisition module, a pneumatic output acquisition module, an energy loss calculation module, a tide energy solving module and a tide level calculation module, which cooperatively realize the method. According to the scheme, an external tide gauge station is not needed, the local sea area tide level can be inversed in situ, at high frequency and with high precision, the method is suitable for an OWC-breakwater fusion scene, and cooperative operation of a port and ocean energy is supported.

The utility model discloses a mountain river water potential stratified sampler which comprises a handle, the bottom of the handle is fixedly connected with a telescopic rod, a plurality of sampling bottles are arranged below the telescopic rod, the movable end of the telescopic rod is fixedly connected with the top sampling bottle, and electromagnetic valves fixedly penetrate through the two ends of each sampling bottle; and except the bottommost sampling bottle, the bottoms of the other sampling bottles are fixedly connected with plastic shells. According to the sampling device, the telescopic rod, the sampling bottles, the electromagnetic valve, the plastic shell, the telescopic assembly, the winding wheel and the electric wire assembly are arranged, the sampling bottles are designed in a telescopic mode, the sampling device can be conveniently carried in a mountainous area, sampling of different depths of one sampling point can be completed at a time when the sampling device is used, repeated operation is not needed, and the sampling device is convenient to use; meanwhile, the plurality of sampling bottles are rigidly connected and are fixed in relative positions, so that the sampling bottles are not easy to deviate under the action of water flow after being inserted into water, and the accuracy of sampling positions is ensured.

The invention relates to the technical field of intelligent management of landscaping, in particular to an intelligent management method and system for irrigating landscaping plants, and the method comprises the following steps: 1, carrying out multi-dimensional data collection and dynamic modeling: collecting plant physiological data through a stem flow sensor, a leaf water potential sensor and a high-definition camera, the method comprises the following steps: acquiring environment and soil data through a meteorological station array and a soil sensor, and constructing a digital twinborn model containing a plant growth stage-water demand curve based on historical data; 2, water demand prediction and intelligent decision making: inputting real-time data into an LSTM neural network model to predict the water demand of the plant in the future 1-3 days, generating a dynamic irrigation scheme in combination with weather forecast data, and optimizing the irrigation amount and the time period according to the plant type, the growth stage and the soil partition; the water demand state is directly sensed through plant physiological signals, dynamic regulation and control are combined with a prediction model, water is saved by 50% or above compared with traditional regular irrigation, and the soil water accumulation rate is reduced to 5% or below.

The invention provides a crop evapotranspiration prediction method and device, equipment, a storage medium and a program product. The method comprises the steps of determining reference evapotranspiration data based on evapotranspiration input data; determining the relationship between the soil water potential and the soil moisture stress coefficient based on the evapotranspiration measured data and the reference evapotranspiration data; and based on the reference evapotranspiration data and the relationship, predicting the crop evapotranspiration of the to-be-predicted region to obtain a crop evapotranspiration prediction result. According to the method, reference evapotranspiration data is determined through evapotranspiration input data obtained from a to-be-predicted area, evapotranspiration measured data obtained from the to-be-predicted area are used for jointly determining the relation between the soil water potential and the soil moisture stress coefficient, and finally the crop evapotranspiration amount of the to-be-predicted area is predicted based on the reference evapotranspiration data and the determined relation. And obtaining a crop evapotranspiration prediction result. According to the method, the abiotic stress condition of the soil is effectively judged through the soil water potential, and the accuracy of crop evapotranspiration prediction is improved.

The invention relates to the technical field of soil monitoring, and provides a lysimeter, a soil monitoring system and a soil evapotranspiration calculation method.The lysimeter comprises a weighing barrel, a water permeable membrane and a monitoring assembly, the weighing barrel is provided with a first opening and a second opening, the first opening is formed in the upper end of the weighing barrel, and the second opening is formed in the lower end of the weighing barrel; the permeable membrane is laid at the second opening and is used for assisting moisture movement of the to-be-detected soil; the monitoring assembly is arranged on the weighing barrel and used for monitoring the weight of the to-be-measured soil, the soil water potential of the to-be-measured soil and the soil moisture of the to-be-measured soil. According to the lysimeter provided by the invention, an original closed bottom is replaced by a water permeable membrane material, so that the bottom of the weighing barrel is changed into an open design, the problem that soil to be detected is not communicated with natural soil below can be eliminated, and water can freely circulate between the soil to be detected and the natural soil; and the movement condition of field moisture can be simulated more truly.

The present invention relates to a soil tension sensor device with self-diagnosis and self-calibration, characterized in that the soil tension sensor device comprises: a fluid box, a fluid pipeline, a first solenoid valve, a second solenoid valve, a soil tension sensor, a porous ceramic medium, a pressure sensor, a liquid level sensor, a drive control unit, a data processing unit, a data storage unit, and a data sending and receiving unit; the fluid box is connected to the soil tension sensor through the fluid pipeline, the liquid in the fluid box enters the liquid cavity of the soil tension sensor, a porous ceramic medium is inserted under the liquid cavity, the porous ceramic medium contacts the soil, and the liquid in the liquid cavity exchanges water with the soil through the porous ceramic medium to achieve water potential balance; the present invention uses a local data self-checking and judging method to maintain the soil tension sensor, and the grower does not need to go to the installation site regularly to conduct a comprehensive inspection and maintenance of the sensor device.

The invention discloses a monitoring and analyzing system for root systems of plant slope protection in a mining area. According to the method, morphological enhancement and deep learning technologies are creatively fused through the root system image recognition unit, and the problem that the root system microstructure is difficult to capture in a complex soil background in a traditional method is effectively solved. The unit is based on a multi-scale feature fusion algorithm, can automatically extract key morphological parameters such as root system topology fractal dimensions and the like, remarkably improves the fine root recognition rate, and enables slope protection plant type selection and layout to better fit actual geological conditions. The root growth prediction unit integrates an environmental constraint model and biological rhythm characteristics, realizes accurate prediction of a root extension trend by dynamically coupling parameters such as soil water potential and nutrient concentration, helps managers to plan a reseeding scheme in advance, and avoids the risk of slope instability caused by lagging of root development.

The invention relates to the technical field of forestry data processing, in particular to a landscaping maintenance system and method based on big data, and the system comprises a water potential monitoring module, a block division module, a pruning adjustment module, a man-hour scheduling module and an anomaly recognition module. According to the method, by tracking the consistency of soil moisture fluctuation in real time, accurately analyzing the dynamic influence of the root system type and the soil layer structure on water absorption and combining plant evapotranspiration physiological indexes and meteorological condition differences to finely divide water demand grades, efficient matching of water supply and plant physiological statuses is achieved; the pruning period is dynamically adjusted according to the actual change of plant photosynthesis and tissue expansion, the coordination error between maintenance working hour calculation and geographic path planning is effectively reduced, the continuity and timeliness of illumination change abnormal response recognition are improved, the accuracy and refinement level of garden plant maintenance decision making are remarkably improved, and the method is suitable for popularization and application. And the scientific decision-making capability, the space adaptive capability and the intelligent response level of greening maintenance management are improved.

The invention relates to the field of data analysis, in particular to a controlled-release nitrogen fertilizer application decision optimization method in combination with soil water content change characteristics, and the method comprises the following steps: obtaining an effective infiltration potential energy optimization factor through field water capacity threshold truncation of a soil volume water content sequence and effective infiltration potential energy time window accumulation difference evaluation; obtaining a water potential lag direction optimization factor through first-order difference gradient direction consistency and trend amplitude gating coupling evaluation of the soil volume moisture content sequence; the DTW local distance is corrected through the effective infiltration potential energy optimization factor and the water potential lag direction optimization factor; and performing release curve weighted prediction on the optimal matching historical sequence corresponding to the optimized DTW distance to obtain an accurate controlled-release nitrogen fertilizer application decision suggestion so as to solve the problems of historical scene matching distortion and controlled-release nitrogen fertilizer application decision deviation caused by neglecting of an effective cumulative effect and a water potential hysteresis effect in the existing Euclidean distance measurement.

The invention discloses a method for simultaneously detecting bioavailability of adsorbed and desorbed antibiotics in soil, and belongs to the field of biotechnology application. A biosensing detection system is designed by adopting a method of combining fluorescence sensing bacteria and an agar plate, and the biosensing detection system is used for detecting the biosensing bacteria by controlling the humidity of an agar plate system based on soil-antibiotic interface behaviors and an agar diffusion principle. The system can detect and quantify the bioavailability of tetracycline adsorbed and desorbed in soil with different water potentials. The biosensing detection system designed by the invention is simple, sensitive, low in consumption and convenient, soil with the water potential range of-10.59 to-2.95 Kpa can be detected in situ, and the lowest detection limit value of tetracycline antibiotics is 1mg / kg.

The invention provides a method for simulating and quantifying physical stress of field soil based on field in-situ monitoring and a model. The method comprises the following steps: step 1, acquiring soil bulk density, water content and penetration resistance values under different water potentials; step 2, fitting the transfer equation of each limiting condition by using each measured data in the step 1, and establishing soil transfer equations of four limiting conditions of LLWR; 3, field soil bulk density dynamic measured data are obtained; 4, constructing a field soil bulk density dynamic prediction model in the implementation stage and the expansion and shrinkage stage under the influence of cultivation and rainfall; step 5, acquiring actually measured data of field rainfall and soil water content of the research area; and step 6, obtaining the LLWR range of the research area and the dynamic change of each limiting condition. The method solves the technical problems that in the prior art, seasonal dynamic of soil bulk density, which is a key transmission variable influencing LLWR, is ignored, and it is difficult to accurately estimate dynamic changes of LLWR in seasons and quantify physical stress caused by the LLWR on crop growth.

The invention relates to the field of measurement and calibration of trunk sap flow, in particular to a calibration device and method for measuring trunk sap flow based on a heat dissipation method. A stable water potential difference is formed between a water tank in the calibration device and a water containing tray under the control of a Markov bottle, and water in the closed water containing tray is pressed into a trunk section, is gathered at the top of the trunk section and enters a volumetric flask through a water passing opening; the lower end of the trunk section is hermetically connected with the water containing tray, and the section of the top end of the trunk section is inclined and is connected with the acrylic cover plate; after the test is finished, weighing the weight of water passing through the trunk section in unit time, calculating the average liquid flux density of the trunk according to the cross section area of the water-guiding xylem of the trunk, and fitting the average liquid flux density as a measured value with the temperature difference between the upper probe and the lower probe inserted into the xylem of the trunk section; and correction of the empirical relationship between the average liquid flux density of the trunk and the temperature difference of the sensor probe is realized. The method is suitable for measuring and calibrating the trunk liquid flow.

The invention provides a sewage unpowered biological ecological treatment device, and relates to the field of ecological treatment devices, the sewage unpowered biological ecological treatment device comprises a primary caisson, the back of the primary caisson is communicated with a water inlet bin, the inner side of the water inlet bin is fixedly provided with a sliding rod, and the surface of the sliding rod is sleeved with a spring. According to the sewage treatment device disclosed by the invention, a sliding rod, a spring, a base plate, a water baffle, an intercepting plate, a cam, a connecting plate A, a connecting seat, a belt wheel A, a water receiving plate A, a belt wheel B and a belt are arranged, so that large-volume impurities carried in sewage can be effectively and quickly intercepted in the process of injecting the sewage into the inner side of the water inlet bin, and the subsequent sewage treatment effect is improved; the rotating rod is driven to rotate under the action of water potential energy, so that the intercepting plate is driven to slide up and down in a reciprocating manner at high frequency along the sliding rod under the action of the transmission mechanism, the intercepted impurities can be driven to be screened, and the impurities can be accumulated in the direction of the baffle by matching with an inclined surface; and the impurities are prevented from blocking the intercepting plate and are conveniently collected and cleaned.

The invention relates to a dry slope field spring corn fertilization optimization method based on dynamic regulation and control of soil moisture, which comprises the following steps: identifying capillary water paths according to particle size distribution and pore structures of soil at different slope positions before sowing, and regulating capillary communication through tillage intervention, so that the moisture is migrated and converged to a 10-30cm target root layer; preferentially applying soluble fertilizer along the path to realize overlapping of the fertilizer efficiency area and the water holding area; after rainfall or irrigation, fertilization is delayed for 3-5 days based on soil moisture time lag, so that the fertilization time is matched with a water potential stable period and a root system absorption peak value, and zoning and staggered fertilization is implemented according to the slope direction or texture; nutrients pass through a moisture shielding layer and directly reach a target root layer by adopting local moisture conducting and film breaking or vertical fertilizer injection; setting a moisture threshold value, triggering fertilization amount redistribution when the moisture threshold value is lower than the threshold value, performing supplementary fertilization on a water-deficient area by adopting a moisture-absorbing slow-release material or adjusting a dosage form, and performing slow-release sealing control treatment on an easy-to-lose area; after harvesting, the layer sealing and soil moisture conservation of a plough layer structure are kept, and continuous and feedforward regulation of cross-season water and fertilizer regulation is achieved.

The invention belongs to the technical field of crop irrigation control, and particularly discloses a multi-modal water-saving sprinkling irrigation system based on the Internet of Things, which comprises a data acquisition module, a stress analysis module connected with the data acquisition module, a sprinkling irrigation control module connected with the stress analysis module and a fault processing module connected with the sprinkling irrigation control module, the embedded stem micro-change sensor and the thermal infrared imager are cooperated to monitor the physiological dynamic state of crops in a multi-mode manner, the occurrence of water stress can be accurately identified in an early stage, a capillary pulse spray irrigation mode is automatically started when the water stress is identified, and on-demand, accurate, small-flow and high-frequency water supply is realized; the timeliness and physiological suitability of irrigation response are remarkably improved, the appropriate water potential of the root zone can be effectively maintained, efficient absorption and utilization of water are promoted, waste of water resources is reduced, and meanwhile normal physiological metabolism of crops is guaranteed.

The invention relates to the technical field of intelligent irrigation, and discloses an intelligent irrigation system for a fruit tree planting greenhouse. The system comprises a multi-dimensional data acquisition module, a data fusion processing module, an irrigation decision module and an irrigation control execution module which are connected in sequence. The system obtains a root soil image, a leaf surface temperature distribution map and stem micro-deformation data, and performs multi-dimensional fusion calculation to generate a spatial water potential distribution map capable of representing the overall moisture condition of crops. And calculating specific regional water demand and preferential irrigation sites based on the map, and further driving an execution terminal to realize precise irrigation. According to the method, the physiological water demand signal of the crop can be responded, the spatial difference of water stress can be identified, the limitation that the traditional technology depends on single soil information is overcome, the crossing from environment monitoring to crop body sensing is realized, and the irrigation accuracy and the water resource utilization efficiency are improved.

The application provides a soil vertical water flux monitoring method and system, and belongs to the technical field of soil water monitoring. The method comprises the following steps: collecting multi-layer soil water content and water potential data in real time, calculating soil vertical water flux of each layer by combining soil hydraulic conductivity, and determining soil water balance plane depth by detecting vertical water flux direction change. The upward evapotranspiration flux and downward seepage flux are calculated respectively based on the balance plane. The application can accurately identify the balance plane of vertical water migration direction change, realize synchronous dynamic monitoring of evapotranspiration and seepage, and effectively improve the continuity and accuracy of soil vertical water flux monitoring.

The invention discloses a fertilization method and system for improving CO2 absorption efficiency of greenhouse plants based on an SPAC system. The method comprises the following steps: acquiring moisture information and environment information of the greenhouse plants through a biological environment information acquisition module deployed in a greenhouse; according to the obtained moisture information and environment information, the current leaf water potential and the saturation vapor pressure difference are calculated; calculating the stomatal conductance of the plant by combining the soil water potential and the atmospheric pressure according to the calculated current leaf water potential and saturation vapor pressure difference; and regulating and controlling water and CO2 fertilization of the greenhouse plants according to the stomatal conductance of the plants. By means of the method, under the condition that the evaporation intensity is too high, plant water stress can be weakened, stomatal opening is promoted, stomatal conductivity and mesophyll conductivity are improved, CO2 absorption and utilization are promoted, the photosynthesis efficiency of greenhouse fruits and vegetables can be effectively improved, and plant growth and yield formation are promoted.

The application discloses a kind of based on the growth environment multi-factor comprehensive monitoring method and system of old tree protection, including step (S1) non-invasive perception network construction: in the crown layer area of old tree deployment meteorological monitoring unit, real-time acquisition photosynthetic active radiation intensity PAR and crown layer surface temperature T c ; with trunk as center, soil sensor array is radially laid in root distribution area, and soil volume water content θ and soil water potential are monitored in layers;Micro-invasive thermal diffusion probe is installed at the breast diameter of trunk, and xylem original liquid flow flux SF raw Is continuously measured, and initial liquid flow flux SF raw Calibration is carried out;Foundation interferometric radar is erected outside the protection zone, and three-dimensional spatial distribution point cloud P r Of root is obtained by surface scanning.This application can realize more comprehensive old tree monitoring, and timely find the existing abnormality of old tree environment.

This invention discloses a smart irrigation management system based on soil and crop moisture status identification, belonging to the field of crop moisture status monitoring technology. The system includes: acquiring leaf electrophysiological signal sequences and multi-depth water potential parameters of the rhizosphere microdomain of the target crop; determining the onset time of water stress and its corresponding first characteristic frequency based on the leaf electrophysiological signal sequences; determining the active water-uptake layer and its corresponding second characteristic water potential based on the multi-depth water potential parameters; performing a coupled comparison based on the first characteristic frequency and the second characteristic water potential, and determining whether irrigation triggering conditions are met based on the comparison results. If the irrigation triggering conditions are met, a differentiated irrigation quota is determined for different irrigation areas. This invention determines irrigation triggering conditions by comparing the consistency and degree of deviation between the first and second deviation directions, avoiding premature or late irrigation caused by misjudgment based on a single indicator.

An apparatus for effecting water potential in a water-containing media comprising a water-permeable housing, a volume changing material that can retain water, a compressible insert and a receiver for receiving and transducing a signal, is provided.

This application discloses a greenhouse water control method and system based on the root zone-plant-atmosphere system. The method includes: acquiring soil water potential, plant water potential, air temperature, and relative humidity information in real time through an information acquisition module; calculating atmospheric water potential based on the acquired air temperature and relative humidity; calculating transpiration pull and water supply power based on the atmospheric water potential, plant water potential, and soil water potential; determining the stomatal aperture of the greenhouse plant based on the ratio of transpiration pull to water supply power; and issuing control commands based on the stomatal aperture and the ratio of transpiration pull to water supply power to achieve water control of the greenhouse plant. The method adopted in this application is simple and efficient. By comprehensively controlling water based on the relative relationship between water supply power and transpiration pull, it can maintain the water supply and demand balance of the root zone-plant-atmosphere system, effectively reduce evaporation and conserve energy, and improve crop photosynthetic capacity, yield, and water use efficiency.

The invention relates to the technical field of agricultural information and intelligent sensors, and discloses a farmland soil moisture content real-time monitoring method based on multi-sensor fusion. The method comprises the steps that passive sensing nodes integrating water content, temperature, conductivity and water potential sensors are arranged, soil micro-vibration is converted into electric energy through a piezoelectric energy collection module and stored in a super capacitor, and low-power-consumption wide-area synchronous communication is achieved through the narrowband Internet of Things; and the cloud carries out time alignment, abnormity elimination and fusion processing on the multi-source data to generate a soil moisture status field, and outputs an irrigation decision in combination with a crop growth model. According to the invention, high-precision, self-powered and maintenance-free soil moisture content in-situ monitoring and intelligent irrigation closed-loop control are realized.