Digitalized plant canopy water evapotranspiration data mining system

Abstract

The application discloses a digital plant canopy water evaporation amount data mining system, comprising a main control unit, which is connected with a detection unit for detecting and acquiring water evaporation data of the plant canopy position, the detection unit comprising: a leaf physiological detection module for detecting leaves of the plant canopy position and acquiring the influence of environmental factors on leaf physiological processes; the leaf physiological detection module comprises a leaf temperature detection module; through the design of the application, on the basis of retaining existing conventional water evaporation detection means, corresponding analysis and detection can be made according to leaves of different plants, so that the acquired leaf water evaporation data is more accurate, and further detection of the conditions influencing leaf water evaporation is realized, so that the accuracy of data is further improved, the existing detection mode is more comprehensive, and data security is provided for later analysis.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of plant water evaporation, and particularly relates to a digital plant canopy water evaporation amount data mining system. BACKGROUND

[0002] The plant canopy refers to the dense top layer of the plant. Because the canopy photosynthesis rate is very high, the yield of fruits, seeds, flowers and leaves of these plants is relatively high, which supports the biodiversity and can attract a large number of wild animals and plants. The canopy is a water, gas and heat exchange place and plays an important role in regulating regional and global climate. In addition to absorbing solar energy and regulating climate, the canopy can intercept rainfall, weaken raindrop kinetic energy, and protect the understory leaf layer from strong light, dry wind and heavy rain. In order to evaluate the growth environment of the plant and estimate the fruit yield of the plant in the later period, the amount of water evaporation of the plant canopy needs to be calculated.

[0003] In the existing data mining and statistics of the water evaporation amount of the plant canopy, the conventional air, temperature and wind speed detection method is basically used. Although the water evaporation amount of the plant canopy can be obtained, the overall data deviates greatly from the actual water evaporation amount, and the growth environment, fruit yield and the like of the plant in the later period cannot be accurately evaluated and estimated. Therefore, there is room for improvement in how to improve the accuracy of water evaporation. SUMMARY

[0004] The purpose of the present application is to provide a digital plant canopy water evaporation amount data mining system to solve the problem of inaccurate data in the mining and acquisition of the water evaporation amount data of the plant canopy in the background art.

[0005] To achieve the above purpose, the present application provides the following technical scheme: a digital plant canopy water evaporation amount data mining system, comprising a main control unit, a detection unit connected to the main control unit for detecting and acquiring the water evaporation data of the plant canopy position, the detection unit comprising:

[0006] A leaf physiological detection module is used for detecting the leaves of the plant canopy position and acquiring the influence of environmental factors on the leaf physiological process. The leaf physiological detection module comprises a leaf temperature detection module that reflects the respiration coefficient of the leaves, and a leaf stomatal conductance detection module that detects and acquires the data of the leaf stomatal conductance.

[0007] A canopy area detection module is used for measuring the area of the plant canopy and reflecting the water evaporation amount of the plant canopy according to the measured area.

[0008] A radiation detection module is used for mining and collecting the effective radiation data received by the plant canopy.

[0009] The detection unit is respectively provided with a backup unit for backing up past plant canopy data, and a comparison unit for comparing the current collected plant canopy evapotranspiration data with the past data, and the comparison unit is connected with an output unit for outputting the compared data and the current collected plant canopy evapotranspiration data.

[0010] As a preferred technical solution in the application, the leaf stomatal conductance detection module utilizes the heat pulse rate method or the Granier heat dissipation probe method to continuously measure the sap flow of the tree trunk, calculates the transpiration of the whole tree, and obtains the crown stomatal conductance value from the Penman2Monteith equation.

[0011] As a preferred technical solution in the application, the equipment of the leaf stomatal conductance detection module includes an HPV plant sap flow meter, an ATMOS 41 weather station, and an NR LITE2 net radiation, and an HFP01 soil heat flux, wherein the HPV plant sap flow meter is installed on the trunk or stem of the plant, the NR LITE2 net radiation sensor measures the environmental net radiation Rn data, and the HFP01 soil heat flux sensor measures the heat conduction G data in the soil.

[0012] As a preferred technical solution in the application, the calculation formula of the respiration coefficient of the leaf temperature detection module is: R=r1*Q 10 0.1(Tcan-25) *r2LAI; wherein R is respiration, r1 is the respiration coefficient of the plant, Q10 is the coefficient of temperature affecting respiration, the value is 2, Tcan is the crown temperature, and r2 is the coefficient of converting leaf area into plant dry matter.

[0013] As a preferred technical solution in the application, the comparison unit is further connected with a cloud platform database, which is used to obtain the past plant canopy data in the backup unit.

[0014] As a preferred technical solution in the application, the detection unit is further provided with an air flow detection module and a temperature detection module for detecting the air flow and temperature around multiple plants.

[0015] As a preferred technical solution in the application, the air flow detection module, the temperature detection module, the crown area detection module, and the radiation detection module are in the same priority, and the leaf physiological detection module is in a secondary priority.

[0016] As a preferred technical solution in the application, the output unit includes a computer, a mobile phone, and a tablet, and the output form includes a chart.

[0017] Compared with the prior art, the application has the following advantages:

[0018] Through the design of the present application, on the basis of retaining the existing conventional water evaporation detection means, corresponding analysis and detection can also be made according to the leaves of different plants, so that the obtained leaf water evaporation data is more accurate, and the conditions affecting the leaf water evaporation are further detected, so that the accuracy of the data is further improved, and the existing detection method is more comprehensive, and data security is provided for later analysis. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 The system diagram of the present application. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0021] Please refer to Figure 1 The present application provides a technical solution: a digital plant canopy water evaporation data mining system, comprising a main control unit, which is connected with a detection unit for detecting and obtaining water evaporation data of the plant canopy position, the detection unit comprising:

[0022] A leaf physiological detection module is used for detecting the leaves of the plant canopy position and obtaining the influence of environmental factors on the physiological process of the leaves. The leaf physiological detection module comprises a leaf temperature detection module, which reflects the respiration coefficient of the leaves. When the leaves receive solar radiation energy, they transport it to the atmosphere in the form of sensible heat and latent heat. The former is transported in the form of heat conduction or turbulence, and the latter is transported in the form of transpiration. Therefore, the leaf temperature detection module can obtain the leaf water evaporation data mining of the plant canopy position. The leaf stomatal conductance detection module detects and obtains data of the leaf stomatal conductance. Since the leaf temperature also determines the saturated water vapor pressure in the stomatal cavity, it affects transpiration and thus the stomatal conductance. Therefore, detecting the leaf stomata can further improve the accuracy of the data.

[0023] A canopy area detection module is used for measuring the area of the plant canopy and reflecting the water evaporation amount of the plant canopy according to the measured area. The calculation method is as follows:

[0024] The extinction coefficient is analyzed by the light intensity of the top and bottom of the canopy, and the leaf area index is calculated by combining the canopy projection area and the ground area ratio. First, the leaf area index estimation method of a single plant adopts the extinction coefficient method to estimate the leaf area index, LAI0 is the leaf area index of single plant, Rtop is the solar radiation above the canopy, Rbot is the solar radiation below the canopy, k is the extinction coefficient of the specific plant canopy, and the value range of k is 0.13-1.15 according to the different leaf inclination angles of different crops. Estimation of the overall leaf area index of farmland: Wherein LAI is the estimated value of the overall leaf area index of farmland, S1 is the ground area of the projected canopy, and S2 is the ground area of the shooting area.

[0025] The radiation detection module is used for mining and collecting effective radiation data received by the plant canopy;

[0026] The detection unit is respectively provided with a backup unit for backing up past plant canopy data, and a comparison unit for comparing the current collected plant canopy evapotranspiration data with the past data, and the comparison unit is connected with an output unit for outputting the compared data and the current collected plant canopy evapotranspiration data.

[0027] In this embodiment, the leaf stomatal conductance detection module uses the heat pulse rate method or the Granier heat dissipation probe method to continuously measure the sap flow of the tree trunk, calculates the transpiration of the whole tree, and obtains the canopy stomatal conductance value from the Penman 2 Monteith equation, the formula is

[0028] Wherein F is the liquid flow density (kg m -2 s -1 ) measured by the HPV plant sap flow meter, λ is the latent heat of water (J kg -1 ), Ga is the canopy aerodynamic resistance (ms -1 ), Δ is the slope of the relationship between water vapor pressure and temperature [KPa ℃ -1 ], ρ is the density of dry air (kg m -3 )], C p is the specific heat of dry air at constant pressure (J kg-1 C -1 ), D is the vapor pressure deficit (KPa), γ is the humidity constant (KPa ℃ -1 ), Rn is the net radiation (MJ m -2 s -1 ), and G is the soil heat flux (MJ m -2 s -1 ).

[0029] In this embodiment, the equipment of the leaf stomatal conductance detection module includes an HPV plant stem flow meter, an ATMOS 41 weather station, an NR LITE2 net radiation sensor, and an HFP01 soil heat flux sensor. The HPV plant stem flow meter is installed on the trunk or stem of the plant, the NR LITE2 net radiation sensor measures the environmental net radiation Rn data, and the HFP01 soil heat flux sensor measures the heat conduction G data in the soil.

[0030] In this embodiment, the formula for calculating the respiration coefficient of the leaf temperature detection module is as follows:

[0031] R = r1 * Q 10 0.1(Tcan-25) *r2LAI; where R is respiration, r1 is the plant respiration coefficient, Q10 is the coefficient of temperature affecting respiration (value 2), Tcan is the canopy temperature, and r2 is the coefficient for converting leaf area into plant dry matter.

[0032] In this embodiment, the comparison unit is also connected to a cloud platform database. This cloud platform database is used to obtain past plant canopy data in the backup unit. In actual use, it can also automatically back up other plant data besides past plant canopy data, which is convenient for later analysis. By backing up the data, data loss can be avoided.

[0033] In this embodiment, the detection unit is also equipped with an air flow detection module and a temperature detection module to detect the air flow and temperature around multiple plants. These two modules can be used to collect statistics on the water evaporation data of the plant canopy, which is convenient for the subsequent analysis of the plant's growth status.

[0034] In this embodiment, the airflow detection module, temperature detection module, canopy area detection module, and radiation detection module are of the same priority, while the leaf physiological detection module is of secondary priority. After the airflow detection module, temperature detection module, canopy area detection module, and radiation detection module complete their detection, the leaf physiological detection module acquires the data from the above modules to achieve the final analysis of plant canopy water evapotranspiration data.

[0035] In this embodiment, the output unit includes a computer, a mobile phone, and a tablet, and the output format includes charts.

[0036] Although embodiments of the invention have been shown and described (see the detailed description above), it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A digital plant canopy water evapotranspiration data mining system, comprising a main control unit, characterized in that: The main control unit is connected to a detection unit for detecting and acquiring water evapotranspiration data at the plant canopy location. This detection unit includes: The leaf physiological detection module is used to detect leaves in the plant canopy and obtain the influence of environmental factors on leaf physiological processes. The leaf physiological detection module includes a leaf temperature detection module, which reflects the respiration coefficient of the leaf, and a leaf stomatal conductance detection module, which detects and acquires data on the stomatal conductance of the leaf. The canopy area detection module is used to measure the area of ​​the plant canopy and reflect the amount of water evaporation from the plant canopy based on the measured area. The radiation detection module is used to mine and collect effective radiation data received by the plant canopy. The detection unit is equipped with a backup unit for backing up past plant canopy data and a comparison unit for comparing the currently collected plant canopy water evapotranspiration data with past data. The comparison unit is connected to an output unit for outputting the comparison data and the currently collected plant canopy water evapotranspiration data.

2. The digital plant canopy evapotranspiration data mining system according to claim 1, characterized in that: The leaf stomatal conductance detection module uses the thermal pulse rate method or the Granier thermal dissipation probe method to continuously measure the sap flow in the trunk, calculates the transpiration of the whole tree, and obtains the stomatal conductance value of the canopy using the Penman 2 Monteith equation.

3. The digital plant canopy evapotranspiration data mining system according to claim 2, characterized in that: The equipment of the leaf stomatal conductance detection module includes an HPV plant stem flow meter, an ATMOS 41 weather station, an NR LITE2 net radiation sensor, and an HFP01 soil heat flux sensor. The HPV plant stem flow meter is installed on the trunk or stem of the plant, the NR LITE2 net radiation sensor measures the environmental net radiation Rn data, and the HFP01 soil heat flux sensor measures the heat conduction G data in the soil.

4. The digital plant canopy evapotranspiration data mining system according to claim 1, characterized in that: The formula for calculating the respiration coefficient of the leaf temperature detection module is as follows: R = r1 * Q 10 0.1(Tcan-25) *r2LAI; where R is respiration, r1 is the plant respiration coefficient, Q10 is the coefficient of temperature affecting respiration (value 2), Tcan is the canopy temperature, and r2 is the coefficient for converting leaf area into plant dry matter.

5. The digital plant canopy evapotranspiration data mining system according to claim 1, characterized in that: The comparison unit is also connected to a cloud platform database, which is used to obtain past plant canopy data from the backup unit.

6. The digital plant canopy evapotranspiration data mining system according to claim 1, characterized in that: The detection unit is also equipped with an airflow detection module and a temperature detection module to detect the airflow and temperature around multiple plants.

7. The digital plant canopy evapotranspiration data mining system according to claim 6, characterized in that: The airflow detection module, temperature detection module, canopy area detection module, and radiation detection module are of the same priority, while the leaf physiological detection module is of secondary priority.

8. The digital plant canopy evapotranspiration data mining system according to claim 1, characterized in that: The output units include computers, mobile phones, and tablets, and the output format includes charts.

Images