Visualized smart agriculture monitoring and management method and system

Abstract

The present invention relates to fields related to agricultural management, and discloses a visualized intelligent agricultural monitoring and management method and system. Through sensing equipment, automatic transpiration monitoring and evaluation of crop plants can be realized, and plant status monitoring and water management in cycles can be realized, so that crop plants are always in the best transpiration state, so as to achieve the purpose of optimizing plant growth efficiency. Compared with the plant water quantitative management method in the prior art, it can perform differentiated management on plants with different water content requirements due to various factors such as growth status, so as to obtain the best crop planting effect.

Description

Technical Field

[0001] The present invention relates to fields related to agricultural management, and in particular to a visualized smart agricultural monitoring and management method and system. Background Art

[0002] In the prior art, in the water management of agricultural crops, a certain average management is mostly adopted for different growth cycles of different crop types, that is, a unified water replenishment and humidification operation is adopted. In this way, the management workload of relevant managers can be effectively reduced.

[0003] However, in actual use, the actual root and stem and leaf growth states of plants in different growth states are different, so their water absorption capacity is also different. Too high soil moisture content will affect the respiration of plant roots, and too low soil moisture content will not be able to meet the optimal growth needs of plants. Therefore, unified control management is not conducive to the optimal growth of crops, and long-term accumulation may lead to an increase in the growth state of plants, affecting the economic value of crops. Summary of the invention

[0004] The purpose of the present invention is to provide a visualized smart agriculture monitoring and management method and system to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] Visualized smart agriculture monitoring and management method, including:

[0007] Evaluating the canopy volume occupied by crop plants; acquiring sensor image data of a crop planting area, and evaluating the spatial distribution of stems and leaves of crops based on the sensor image data to obtain the canopy volume occupied by the corresponding crop plants;

[0008] Monitoring of environmental factors of crop plants; obtaining plant environmental data based on a number of environmental sensors distributed in the vertical and horizontal spaces of the crop planting area, the plant environmental data including light data, temperature and humidity data, and infrared thermal radiation data;

[0009] Evaluating the transpiration status of crop plants; performing energy balance evaluation in the vertical space of the crop plant area based on plant environmental data to obtain plant transpiration latent heat flux and soil evaporation latent heat flux in the corresponding area;

[0010] Establishing management requirements based on the transpiration state of crop plants; continuously evaluating the plant transpiration latent heat flux of crop plants based on the proportional linear growth of the canopy occupied volume to obtain the corresponding soil moisture requirements corresponding to the optimal plant transpiration latent heat flux of crop plants, so as to establish and implement crop management requirements, and the crop management requirements are used to characterize the irrigation requirements of crop plants;

[0011] Establishment and feedback of visual intelligent monitoring; establish a twin spatial distribution model of the crop plant planting area, and perform range graphical mapping of the deviation of the plant transpiration latent heat flux from the optimal plant transpiration latent heat flux and the execution amount of the irrigation demand, and output them.

[0012] As a further solution of the present invention: the temperature and humidity data and infrared thermal radiation data of the same crop plant area are multiple groups, and the multiple groups of temperature and humidity data and infrared thermal radiation data are respectively used to characterize the environmental data of the crop plant area at various locations in the vertical space. The step of evaluating the transpiration state of the crop plant specifically includes:

[0013] The net radiation flux R_n and sensible heat flux H of the crop plant environment are evaluated and calculated through the sunlight data, light infrared radiation data and eddy measurement data in the plant environment data;

[0014] The latent heat flux LE is calculated based on the ground energy balance, which is expressed as R_n=H+LE+G, where G is used to characterize the soil heat flux, that is, the heat transferred from the bottom surface to the deep soil, and the soil specific flux is negligible in a short time;

[0015] Obtain infrared radiation measurement data in the vertical space of the plant environment data, and perform vertical layered evaluation on the infrared radiation measurement data to determine the transpiration heat ratio of the canopy layer and the lower layer of the canopy layer, that is, the ratio of the plant transpiration heat latent flux to the soil evaporation heat latent flux;

[0016] The real-time total amount of the plant transpiration latent heat flux is evaluated based on the ratio of the plant transpiration latent heat flux to the soil evaporation latent heat flux and the latent heat flux LE.

[0017] As a further solution of the present invention: the step of establishing the management requirements based on the transpiration state of the crop plants specifically includes:

[0018] Assessing the optimal transpiration humidity range of the crop plant based on the canopy volume occupied by the crop plant based on historical data to determine the initial soil moisture;

[0019] The plant transpiration latent heat flux and soil moisture data are obtained at preset monitoring time intervals, and the influence of the periodic change on the plant transpiration latent heat flux is determined based on the solar radiation data of two adjacent time intervals, wherein the solar radiation data is in an increasing function relationship with the transpiration of the plant within a certain range;

[0020] The incremental difference of the plant transpiration heat latent flux in consecutive time intervals is calculated based on the impact change. If the incremental difference is characterized by a negative value, the median of the soil moisture in adjacent time intervals is taken as the humidity control parameter of the next period; if the incremental difference is characterized by a positive value, the soil moisture control change in the current time interval is taken as the humidity control parameter of the next period.

[0021] As a further solution of the present invention: the canopy volume is used to characterize the spatial volume occupancy of the canopy structure of crop plants within a unit monitoring and management area. The unit monitoring and management area can be a single crop plant or an aggregate of multiple crop plants. The canopy volume is positively correlated with the transpiration.

[0022] As a further embodiment of the present invention, the step of evaluating the crop plant canopy space volume specifically includes:

[0023] The sensor data is judged based on image features and spatially marked to distinguish the stem and leaf distribution space and the flower and fruit distribution space of the crop;

[0024] Performing illumination simulation on the crop plants to obtain direct illumination area of ​​the crop plants, and calculating an evaluation optimization ratio of the direct illumination area to the occupied volume of the stem and leaf distribution space, wherein the evaluation optimization ratio is associated with the crop plant type and growth cycle;

[0025] The evaluation optimization ratio is judged according to the standard ratio range corresponding to the crop plant type and growth cycle. If it exceeds the standard ratio range, the crop plant is marked as a bad plant and output through the twin space distribution model.

[0026] The embodiment of the present invention aims to provide a visual smart agricultural monitoring and management system, comprising:

[0027] The space occupation assessment module is used to assess the space occupation volume of the crop canopy; obtain sensor image data of the crop planting area, and evaluate the spatial distribution of the stems and leaves of the crops based on the sensor image data to obtain the space occupation volume of the corresponding crop canopy;

[0028] The environmental monitoring module is used to monitor the environmental factors of crop plants; it obtains plant environmental data based on a number of environmental sensors distributed in the vertical and horizontal spaces of the crop planting area, and the plant environmental data includes light data, temperature and humidity data, and infrared thermal radiation data;

[0029] A transpiration assessment module is used to assess the transpiration status of crop plants; based on plant environmental data, an energy balance assessment is performed in the vertical space of the crop plant area to obtain plant transpiration latent heat flux and soil evaporation latent heat flux in the corresponding area;

[0030] A demand assessment module is used to establish management requirements based on the transpiration state of crop plants; based on the proportional linear growth of the canopy occupied volume, the plant transpiration latent heat flux of the crop plants is continuously evaluated to obtain the corresponding soil moisture requirement corresponding to the optimal plant transpiration latent heat flux of the crop plants, so as to establish and execute the crop management requirements, and the crop management requirements are used to characterize the irrigation requirements of the crop plants;

[0031] A visualization output module is used for the establishment and feedback of visualized intelligent monitoring; a twin spatial distribution model of the crop plant planting area is established, and a range graphical mapping is performed on the deviation of the plant transpiration latent heat flux from the optimal plant transpiration latent heat flux and the execution amount of the irrigation demand, and the output is output.

[0032] As a further solution of the present invention: the temperature and humidity data and infrared thermal radiation data of the same crop plant area are multiple groups, and the multiple groups of temperature and humidity data and infrared thermal radiation data are respectively used to characterize the environmental data of the crop plant area at various locations in the vertical space. The transpiration assessment module specifically includes:

[0033] The associated parameter calculation unit is used to evaluate and calculate the net radiation flux R_n and sensible heat flux H of the crop plant environment through the solar radiation data, light infrared radiation data and eddy measurement data in the plant environment data;

[0034] A latent heat flux calculation unit, used to calculate the latent heat flux LE based on the ground energy balance, wherein the ground energy balance is expressed as R_n=H+LE+G, wherein G is used to characterize the soil heat flux, i.e., the heat transferred from the bottom surface to the deep soil, and the soil specific flux is negligible in a short time;

[0035] A vertical distribution evaluation unit is used to obtain infrared radiation measurement data in the vertical space of the plant environment data, and to perform vertical layered evaluation on the infrared radiation measurement data to determine the transpiration heat ratio of the canopy layer and the lower layer of the canopy layer, that is, the ratio of the plant transpiration heat latent flux to the soil evaporation heat latent flux;

[0036] The total transpiration calculation unit is used to evaluate the real-time total amount of the plant transpiration latent heat flux based on the ratio of the plant transpiration latent heat flux to the soil evaporation latent heat flux and the latent heat flux LE.

[0037] As a further solution of the present invention: the demand assessment module includes:

[0038] An environmental initialization unit, for evaluating the optimal transpiration humidity range of the crop plant based on the canopy occupied volume of the crop plant based on historical data, and determining initial soil moisture;

[0039] A periodic state evaluation unit, used to obtain the plant transpiration latent heat flux and soil moisture data at preset monitoring time intervals, and determine the change amount of the influence of the periodic change on the plant transpiration latent heat flux based on the solar radiation data of two adjacent time intervals, wherein the solar radiation data is in an increasing function relationship with the transpiration of the plant within a certain range;

[0040] The environmental demand acquisition unit is used to calculate the incremental difference of the plant transpiration heat latent flux in consecutive time intervals based on the impact change. If the incremental difference is characterized by a negative value, the median of the soil moisture in adjacent time intervals is taken as the humidity control parameter of the next period; if the incremental difference is characterized by a positive value, the soil moisture control change in the current time interval is taken as the humidity control parameter of the next period.

[0041] As a further solution of the present invention: the canopy volume is used to characterize the spatial volume occupancy of the canopy structure of crop plants within a unit monitoring and management area. The unit monitoring and management area can be a single crop plant or an aggregate of multiple crop plants. The canopy volume is positively correlated with the transpiration.

[0042] As a further solution of the present invention: the steps of the occupancy assessment module include:

[0043] A stem and fruit distinguishing unit, used to judge and spatially mark the sensing data based on image features, so as to distinguish the stem and leaf distribution space and the flower and fruit distribution space of the crop;

[0044] A light simulation unit, used for performing light simulation on the crop plant to obtain the direct light area of ​​the crop plant, and calculating an evaluation optimization ratio of the direct light area to the occupied volume of the stem and leaf distribution space, wherein the evaluation optimization ratio is associated with the crop plant type and growth cycle;

[0045] The crop evaluation unit is used to judge the evaluation optimization ratio according to the standard ratio range corresponding to the crop plant type and growth cycle. If it exceeds the standard ratio range, the crop plant is marked as a bad plant and output through the twin space distribution model.

[0046] Compared with the prior art, the beneficial effects of the present invention are: automatic transpiration monitoring and evaluation of crop plants can be realized through sensing equipment, and then plant status monitoring and water management in cycles can be realized, so that crop plants are always in the best transpiration state, thereby achieving the purpose of optimizing plant growth efficiency. Compared with the plant water quantitative management method in the prior art, it can perform differentiated management on plants with different water content requirements due to various factors such as growth status, so as to obtain the best crop planting effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flowchart of the visual smart agriculture monitoring and management method.

[0048] Figure 2 A flowchart of the steps for visualizing transpiration status assessment in smart agriculture monitoring and management methods.

[0049] Figure 3 This is a block diagram of the components of a visual smart agriculture monitoring and management system. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0051] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0052] like Figure 1 The visual smart agriculture monitoring and management method provided by an embodiment of the present invention comprises the following steps:

[0053] S10, assessing the canopy volume occupied by crop plants; acquiring sensor image data of the crop planting area, and assessing the spatial distribution of the stems and leaves of the crops based on the sensor image data to obtain the canopy volume occupied by the corresponding crop plants.

[0054] S20, monitoring of environmental factors of crop plants; obtaining plant environmental data based on a plurality of environmental sensors distributed in the vertical space and horizontal space of the crop planting area, wherein the plant environmental data includes light data, temperature and humidity data, and infrared thermal radiation data.

[0055] S30, evaluating the transpiration status of the crop plants; performing energy balance evaluation in the vertical space of the crop plant area based on the plant environment data, and obtaining the plant transpiration latent heat flux and the soil evaporation latent heat flux of the corresponding area.

[0056] S40, establishing management requirements based on the transpiration status of crop plants; based on the proportional linear growth of the canopy occupied volume, continuously evaluating the plant transpiration latent heat flux of the crop plants to obtain the corresponding soil moisture requirement for the optimal plant transpiration latent heat flux of the crop plants, so as to establish and execute crop management requirements, and the crop management requirements are used to characterize the irrigation requirements of the crop plants.

[0057] S50, establishment and feedback of visualized intelligent monitoring; establishing a twin spatial distribution model of the crop plant planting area, and performing range graphical mapping of the deviation of the plant transpiration latent heat flux from the optimal plant transpiration latent heat flux and the execution amount of the irrigation demand, and outputting them.

[0058] In this embodiment, a visual smart agriculture monitoring and management method is provided, which realizes automatic transpiration monitoring and evaluation of crop plants through sensing equipment, and then can realize plant status monitoring and water management in cycles, so that crop plants are always in the best transpiration state, so as to achieve the purpose of optimizing plant growth efficiency. Compared with the plant water quantitative management method in the prior art, it can differentiate the management of plants with different water content requirements due to various factors such as growth status, so as to obtain the best crop planting effect; in the prior art, in crop planting, soil moisture is mainly used for monitoring and management, The management standards for the corresponding stages are adopted for crops of different types and different growth cycles, that is, the water application in an area is consistent, but in the actual crop growth, the actual root system and stem and leaf growth status of different plants are different, so the absorption capacity of water is also different, and too high soil moisture content will affect the respiration of plant roots, and too low moisture content will not be able to meet the optimal growth needs of plants; this application is to quantitatively monitor and evaluate the transpiration of plants, and then judge the adaptation state of plants to the optimal water content. The pulling force generated by the transpiration of plants is absorbed by the roots. Water absorption, that is, the power of water and inorganic salt transportation in the plant body, so by monitoring transpiration, it can be determined whether the water content of the plant root system is in the optimal state, and transpiration is achieved through the leaves of the plant (stomata and direct transpiration), so it is directly related to the occupied volume of the canopy structure of the vegetation. In step S10, the canopy occupied volume of the plant is evaluated by sensor image data, and the evaluation of transpiration intensity requires the use of sensors to measure ambient light, temperature and humidity data, and infrared radiation data, etc. The measuring instruments that can be used here include solar radiation meters and infrared radiometers, etc.; here After the latent heat flux is obtained through monitoring and calculation, the total amount of plant transpiration is obtained by the proportional distribution method, that is, judging by the ratio of the thermal radiation between the lower and upper layers of the plant, which can effectively avoid the difficulty in implementing direct quantitative measurement. After determining the total amount of transpiration, the trend is judged by changing the moisture content of the soil environment of the plant, that is, continuous evaluation, and judging whether the moisture content is too high or too low according to the change of the transpiration of the plant, thereby realizing intelligent control. For step S50, the state of transpiration and water management requirements are graphically converted and output, so as to facilitate managers to have an immediate understanding of crop plants.

[0059] like Figure 2 As shown, as another preferred embodiment of the present invention, the temperature and humidity data and infrared thermal radiation data of the same crop plant area are multiple groups, and the multiple groups of temperature and humidity data and infrared thermal radiation data are respectively used to characterize the environmental data of the crop plant area at various locations in the vertical space. The steps of evaluating the transpiration state of the crop plant specifically include:

[0060] S31, the net radiation flux R of the crop plant environment is calculated through the sunlight data, light infrared radiation data and eddy measurement data in the plant environment data. n , sensible heat flux H is evaluated and calculated;

[0061] S32, calculating the latent heat flux LE based on the ground energy balance, wherein the ground energy balance is expressed as R n =H+LE+G, where G is used to characterize soil heat flux, that is, the heat transferred from the bottom surface to the deep soil. The soil specific flux is negligible in a short time;

[0062] S33, obtaining infrared radiation measurement data of the vertical space in the plant environment data, and performing vertical layered evaluation on the infrared radiation measurement data to determine the transpiration heat ratio of the canopy layer and the lower layer of the canopy layer, that is, the ratio of the plant transpiration heat latent flux to the soil evaporation heat latent flux;

[0063] S34, evaluating the real-time total amount of the plant transpiration latent heat flux based on the ratio of the plant transpiration latent heat flux to the soil evaporation latent heat flux and the latent heat flux LE.

[0064] In this embodiment, the steps of transpiration state evaluation are specifically described, in which the ground energy balance equation is used, wherein LE represents latent heat flux, that is, the energy carried by water vapor generated by plant transpiration and soil evaporation, that is, the total evaporation and transpiration, including bottom surface evaporation and plant transpiration. The proportional relationship between them can be calculated by measuring thermal radiation in different vertical spaces of the plant, and then the total amount of LE is divided to determine the latent heat flux of plant transpiration required in the embodiment; Rn is the net radiation flux, including the net heat income after deducting the ground long-wave radiation and the atmospheric back radiation from the solar short-wave radiation, which can be calculated by measuring the solar radiation data; H is the sensible heat flux between the soil and the atmosphere, which is the heat exchange caused by the temperature difference, and can also be calculated by measuring the temperature of the ground and the ground air; G is used to characterize the soil heat flux. In a short time, its total amount is low and can be ignored in the measurement and calculation state of this application.

[0065] As another preferred embodiment of the present invention, the step of establishing management requirements based on the transpiration state of crop plants specifically includes:

[0066] Assessing the optimal transpiration humidity range of the crop plant based on the canopy volume occupied by the crop plant based on historical data to determine the initial soil moisture;

[0067] The plant transpiration latent heat flux and soil moisture data are obtained at preset monitoring time intervals, and the influence of the periodic change on the plant transpiration latent heat flux is determined based on the solar radiation data of two adjacent time intervals, wherein the solar radiation data is in an increasing function relationship with the transpiration of the plant within a certain range;

[0068] The incremental difference of the plant transpiration heat latent flux in consecutive time intervals is calculated based on the impact change. If the incremental difference is characterized by a negative value, the median of the soil moisture in adjacent time intervals is taken as the humidity control parameter of the next period; if the incremental difference is characterized by a positive value, the soil moisture control change in the current time interval is taken as the humidity control parameter of the next period.

[0069] In this embodiment, the steps for establishing the management requirements for the transpiration status of crop plants are explained. The main usage method here can be roughly viewed as a dichotomy, that is, after first determining a range, the water content is controlled as two sets of parameters before and after, and the transpiration amount is monitored and calculated. If it shows a downward trend after excluding the light factor, it indicates that the water content for optimal transpiration is within this range, and reverse control is performed, and so on, to achieve the judgment and range control of the optimal water content to achieve the best transpiration effect.

[0070] As another preferred embodiment of the present invention, the canopy volume is used to characterize the spatial volume occupancy of the canopy structure of crop plants within a unit monitoring and management area. The unit monitoring and management area may be a single crop plant or an aggregate of multiple crop plants. The canopy volume is positively correlated with the transpiration.

[0071] In this embodiment, the canopy volume can be measured in units of single plants or in units of the smallest management interval, depending on the different types of crops being supervised. For example, larger trees can be managed as single plants, but crops that are densely planted in clusters cannot be effectively evaluated in units of single plants and can be managed by dividing the unit area into small intervals.

[0072] As another preferred embodiment of the present invention, the step of evaluating the crop plant canopy volume specifically includes:

[0073] The sensor data is judged based on image features and spatially marked to distinguish the stem and leaf distribution space and the flower and fruit distribution space of the crop;

[0074] Performing illumination simulation on the crop plants to obtain direct illumination area of ​​the crop plants, and calculating an evaluation optimization ratio of the direct illumination area to the occupied volume of the stem and leaf distribution space, wherein the evaluation optimization ratio is associated with the crop plant type and growth cycle;

[0075] The evaluation optimization ratio is judged according to the standard ratio range corresponding to the crop plant type and growth cycle. If it exceeds the standard ratio range, the crop plant is marked as a bad plant and output through the twin space distribution model.

[0076] In this embodiment, different plants develop differently. For some plants, their development status may be poor and unable to meet the needs, or the growth distribution of stems and leaves is not conducive to subsequent sustained rapid growth. Therefore, special care of management personnel is required. The method adopted here is to judge the proportion of the plant's light area. If the direct light area is significantly smaller than the standard value, it will be marked and visualized to facilitate timely discovery by management personnel.

[0077] like Figure 3 As shown, the present invention also provides a visual smart agriculture monitoring and management system, which includes:

[0078] The space occupancy assessment module 100 is used to assess the space occupancy volume of the crop canopy; it obtains sensor image data of the crop planting area, and based on the sensor image data, assesses the spatial distribution of the crop stems and leaves to obtain the space occupancy volume of the corresponding crop canopy.

[0079] The environmental monitoring module 200 is used to monitor the environmental factors of crop plants; it obtains plant environmental data based on a plurality of environmental sensors distributed in the vertical space and horizontal space of the crop planting area, and the plant environmental data includes light data, temperature and humidity data, and infrared thermal radiation data.

[0080] The transpiration assessment module 300 is used to assess the transpiration status of crop plants; based on the plant environment data, an energy balance assessment is performed in the vertical space of the crop plant area to obtain the plant transpiration latent heat flux and the soil evaporation latent heat flux of the corresponding area.

[0081] The demand assessment module 400 is used to establish management requirements based on the transpiration status of crop plants; based on the proportional linear growth of the canopy occupied volume, the plant transpiration latent heat flux of the crop plants is continuously evaluated to obtain the corresponding soil moisture requirement corresponding to the optimal plant transpiration latent heat flux of the crop plants, so as to establish and execute crop management requirements, and the crop management requirements are used to characterize the irrigation requirements of the crop plants.

[0082] The visualization output module 500 is used for the establishment and feedback of visualized intelligent monitoring; a twin spatial distribution model of the crop plant planting area is established, and a range graphical mapping is performed on the deviation of the plant transpiration latent heat flux from the optimal plant transpiration latent heat flux and the execution amount of the irrigation demand, and the output is performed.

[0083] As another preferred embodiment of the present invention, the temperature and humidity data and infrared thermal radiation data of the same crop plant area are multiple groups, and the multiple groups of temperature and humidity data and infrared thermal radiation data are respectively used to characterize the environmental data of the crop plant area at various locations in the vertical space. The transpiration assessment module specifically includes:

[0084] The associated parameter calculation unit is used to calculate the net radiation flux R of the crop plant environment through the sunlight data, light infrared radiation data and eddy measurement data in the plant environment data. n , sensible heat flux H is evaluated and calculated;

[0085] A latent heat flux calculation unit is used to calculate the latent heat flux LE based on the ground energy balance, wherein the ground energy balance is expressed as R n =H+LE+G, where G is used to characterize soil heat flux, that is, the heat transferred from the bottom surface to the deep soil. The soil specific flux is negligible in a short time;

[0086] A vertical distribution evaluation unit is used to obtain infrared radiation measurement data in the vertical space of the plant environment data, and to perform vertical layered evaluation on the infrared radiation measurement data to determine the transpiration heat ratio of the canopy layer and the lower layer of the canopy layer, that is, the ratio of the plant transpiration heat latent flux to the soil evaporation heat latent flux;

[0087] The total transpiration calculation unit is used to evaluate the real-time total amount of the plant transpiration latent heat flux based on the ratio of the plant transpiration latent heat flux to the soil evaporation latent heat flux and the latent heat flux LE.

[0088] As another preferred embodiment of the present invention, the demand assessment module includes:

[0089] An environmental initialization unit, for evaluating the optimal transpiration humidity range of the crop plant based on the canopy occupied volume of the crop plant based on historical data, and determining initial soil moisture;

[0090] A periodic state evaluation unit, used to obtain the plant transpiration latent heat flux and soil moisture data at preset monitoring time intervals, and determine the change amount of the influence of the periodic change on the plant transpiration latent heat flux based on the solar radiation data of two adjacent time intervals, wherein the solar radiation data is in an increasing function relationship with the transpiration of the plant within a certain range;

[0091] The environmental demand acquisition unit is used to calculate the incremental difference of the plant transpiration heat latent flux in consecutive time intervals based on the impact change. If the incremental difference is characterized by a negative value, the median of the soil moisture in adjacent time intervals is taken as the humidity control parameter of the next period; if the incremental difference is characterized by a positive value, the soil moisture control change in the current time interval is taken as the humidity control parameter of the next period.

[0092] As another preferred embodiment of the present invention, the canopy volume is used to characterize the spatial volume occupancy of the canopy structure of crop plants within a unit monitoring and management area. The unit monitoring and management area may be a single crop plant or an aggregate of multiple crop plants. The canopy volume is positively correlated with the transpiration.

[0093] As another preferred embodiment of the present invention, the steps of the occupancy assessment module include:

[0094] A stem and fruit distinguishing unit, used to judge and spatially mark the sensing data based on image features, so as to distinguish the stem and leaf distribution space and the flower and fruit distribution space of the crop;

[0095] A light simulation unit, used for performing light simulation on the crop plant to obtain the direct light area of ​​the crop plant, and calculating an evaluation optimization ratio of the direct light area to the occupied volume of the stem and leaf distribution space, wherein the evaluation optimization ratio is associated with the crop plant type and growth cycle;

[0096] The crop evaluation unit is used to judge the evaluation optimization ratio according to the standard ratio range corresponding to the crop plant type and growth cycle. If it exceeds the standard ratio range, the crop plant is marked as a bad plant and output through the twin space distribution model.

[0097] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0098] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0099] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A visual smart agriculture monitoring and management method, characterized in that: Include: Evaluating the canopy volume occupied by crop plants; acquiring sensor image data of a crop planting area, and evaluating the spatial distribution of stems and leaves of crops based on the sensor image data to obtain the canopy volume occupied by the corresponding crop plants; Monitoring of environmental factors of crop plants; obtaining plant environmental data based on a number of environmental sensors distributed in the vertical and horizontal spaces of the crop planting area, the plant environmental data including light data, temperature and humidity data, and infrared thermal radiation data; Evaluating the transpiration status of crop plants; performing energy balance evaluation in the vertical space of the crop plant area based on plant environmental data to obtain plant transpiration latent heat flux and soil evaporation latent heat flux in the corresponding area; Establishing management requirements based on the transpiration state of crop plants; continuously evaluating the plant transpiration latent heat flux of crop plants based on the proportional linear growth of the canopy occupied volume to obtain the corresponding soil moisture requirements corresponding to the optimal plant transpiration latent heat flux of crop plants, so as to establish and implement crop management requirements, and the crop management requirements are used to characterize the irrigation requirements of crop plants; Establishment and feedback of visual intelligent monitoring; establish a twin spatial distribution model of the crop plant planting area, and perform range graphical mapping of the deviation of the plant transpiration latent heat flux from the optimal plant transpiration latent heat flux and the execution amount of the irrigation demand, and output; There are multiple groups of temperature and humidity data and infrared thermal radiation data for the same crop plant area, and the multiple groups of temperature and humidity data and infrared thermal radiation data are respectively used to characterize the environmental data of the crop plant area at various locations in the vertical space. The steps of evaluating the transpiration state of the crop plant specifically include: The net radiation flux of the crop plant environment is calculated through the sunlight data, light infrared radiation data and eddy measurement data in the plant environment data. , sensible heat flux Perform evaluation calculations; Latent heat flux based on ground energy balance The surface energy balance is expressed as , where G is used to characterize soil heat flux, that is, the heat transferred from the bottom surface to the deep soil. The soil specific flux is negligible in a short time; Obtain infrared radiation measurement data in the vertical space of the plant environment data, and perform vertical layered evaluation on the infrared radiation measurement data to determine the transpiration heat ratio of the canopy layer and the lower layer of the canopy layer, that is, the ratio of the plant transpiration heat latent flux to the soil evaporation heat latent flux; Based on the ratio of plant transpiration heat potential flux to soil evaporation heat potential flux and the latent heat flux Evaluating the real-time total amount of transpiration latent heat flux of the plant; The steps of establishing the management requirements based on the transpiration state of the crop plants specifically include: Assessing the optimal transpiration humidity range of the crop plant based on the canopy volume occupied by the crop plant based on historical data to determine the initial soil moisture; The plant transpiration latent heat flux and soil moisture data are obtained at preset monitoring time intervals, and the influence of the periodic change on the plant transpiration latent heat flux is determined based on the solar radiation data of two adjacent time intervals, wherein the solar radiation data is in an increasing function relationship with the transpiration of the plant within a certain range; Based on the impact change, the plant transpiration heat latent flux of the continuous time interval period is calculated by incremental difference. If the incremental difference is characterized by a negative value, the median of the soil moisture in the adjacent time interval period is taken as the humidity control parameter of the next period; if the incremental difference is characterized by a positive value, the soil moisture control change of the current time interval period is taken as the humidity control parameter of the next period; The step of evaluating the crop plant canopy space volume specifically includes: The sensor data is judged based on image features and spatially marked to distinguish the stem and leaf distribution space and the flower and fruit distribution space of the crop; Performing illumination simulation on the crop plants to obtain direct illumination area of ​​the crop plants, and calculating an evaluation optimization ratio of the direct illumination area to the occupied volume of the stem and leaf distribution space, wherein the evaluation optimization ratio is associated with the crop plant type and growth cycle; The evaluation optimization ratio is judged according to the standard ratio range corresponding to the crop plant type and growth cycle. If it exceeds the standard ratio range, the crop plant is marked as a bad plant and output through the twin space distribution model.

2. The visual smart agriculture monitoring and management method according to claim 1 is characterized in that: The canopy volume is used to characterize the spatial volume occupied by the canopy structure of crop plants within a unit monitoring and management area. The unit monitoring and management area may be a single crop plant or an aggregate of multiple crop plants. The canopy volume is positively correlated with the transpiration.

3. Visualized smart agricultural monitoring and management system, characterized by: Include: The space occupation assessment module is used to assess the space occupation volume of the crop canopy; obtain sensor image data of the crop planting area, and evaluate the spatial distribution of the stems and leaves of the crops based on the sensor image data to obtain the space occupation volume of the corresponding crop canopy; The environmental monitoring module is used to monitor the environmental factors of crop plants; it obtains plant environmental data based on a number of environmental sensors distributed in the vertical and horizontal spaces of the crop planting area, and the plant environmental data includes light data, temperature and humidity data, and infrared thermal radiation data; A transpiration assessment module is used to assess the transpiration status of crop plants; based on plant environmental data, an energy balance assessment is performed in the vertical space of the crop plant area to obtain plant transpiration latent heat flux and soil evaporation latent heat flux in the corresponding area; A demand assessment module is used to establish management requirements based on the transpiration state of crop plants; based on the proportional linear growth of the canopy occupied volume, the plant transpiration latent heat flux of the crop plants is continuously evaluated to obtain the corresponding soil moisture requirement corresponding to the optimal plant transpiration latent heat flux of the crop plants, so as to establish and execute the crop management requirements, and the crop management requirements are used to characterize the irrigation requirements of the crop plants; A visualization output module is used for establishing and providing feedback for visualization intelligent monitoring; establishing a twin spatial distribution model of the crop plant planting area, and performing range graphical mapping of the deviation of the plant transpiration latent heat flux from the optimal plant transpiration latent heat flux and the execution amount of the irrigation demand, and outputting the same; The temperature and humidity data and infrared thermal radiation data of the same crop plant area are multiple groups, and the multiple groups of temperature and humidity data and infrared thermal radiation data are respectively used to characterize the environmental data of the crop plant area at various locations in the vertical space. The transpiration assessment module specifically includes: The associated parameter calculation unit is used to calculate the net radiation flux and sensible heat flux of the crop plant environment through the sunlight data, light infrared radiation data and eddy measurement data in the plant environment data. Perform evaluation calculations; Latent heat flux calculation unit for latent heat flux based on ground energy balance The surface energy balance is expressed as , where G is used to characterize soil heat flux, that is, the heat transferred from the bottom surface to the deep soil. The soil specific flux is negligible in a short time; A vertical distribution evaluation unit is used to obtain infrared radiation measurement data in the vertical space of the plant environment data, and to perform vertical layered evaluation on the infrared radiation measurement data to determine the transpiration heat ratio of the canopy layer and the lower layer of the canopy layer, that is, the ratio of the plant transpiration heat latent flux to the soil evaporation heat latent flux; Total transpiration calculation unit, used to calculate the total transpiration amount based on the ratio of plant transpiration heat potential flux to soil evaporation heat potential flux and the latent heat flux Evaluating the real-time total amount of transpiration latent heat flux of the plant; The needs assessment module includes: An environmental initialization unit, for evaluating the optimal transpiration humidity range of the crop plant based on the canopy occupied volume of the crop plant based on historical data, and determining initial soil moisture; A periodic state evaluation unit, used to obtain the plant transpiration latent heat flux and soil moisture data at preset monitoring time intervals, and determine the change amount of the influence of the periodic change on the plant transpiration latent heat flux based on the solar radiation data of two adjacent time intervals, wherein the solar radiation data is in an increasing function relationship with the transpiration of the plant within a certain range; An environmental demand acquisition unit is used to calculate the incremental difference of the plant transpiration heat latent flux in the continuous time interval period based on the impact change amount, and if the incremental difference is characterized by a negative value, the median of the soil moisture in the adjacent time interval period is taken as the humidity control parameter of the next period; if the incremental difference is characterized by a positive value, the soil moisture control change amount of the current time interval period is taken as the humidity control parameter of the next period; The steps of the occupancy assessment module include: A stem and fruit distinguishing unit, used to judge and spatially mark the sensing data based on image features, so as to distinguish the stem and leaf distribution space and the flower and fruit distribution space of the crop; A light simulation unit, used for performing light simulation on the crop plant to obtain the direct light area of ​​the crop plant, and calculating an evaluation optimization ratio of the direct light area to the occupied volume of the stem and leaf distribution space, wherein the evaluation optimization ratio is associated with the crop plant type and growth cycle; The crop evaluation unit is used to judge the evaluation optimization ratio according to the standard ratio range corresponding to the crop plant type and growth cycle. If it exceeds the standard ratio range, the crop plant is marked as a bad plant and output through the twin space distribution model.

4. The visual intelligent agricultural monitoring and management system according to claim 3 is characterized in that: The canopy volume is used to characterize the spatial volume occupied by the canopy structure of crop plants within a unit monitoring and management area. The unit monitoring and management area may be a single crop plant or an aggregate of multiple crop plants. The canopy volume is positively correlated with the transpiration.

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