Spring tea low temperature frost monitoring and disaster warning method

Abstract

The application discloses a spring tea low-temperature frost monitoring and disaster early warning method, which comprises the following steps: S1, obtaining the ground surface temperature, air humidity and air temperature at the sampling points distributed in a tea garden; S2, calculating the canopy temperature at each sampling point; S3, carrying out gridization on the tea garden, and obtaining the canopy temperature of each grid point by adopting an inverse distance weighted interpolation algorithm based on the canopy temperature of each sampling point; S4, calculating the temperature mean value of all the canopy temperatures, and judging whether the temperature mean value is greater than a preset mean value; if yes, returning to the step S1 after a preset time length, otherwise, entering the step S5; S5, calculating the temperature drop speed according to a plurality of continuous temperature mean values; S6, judging whether the temperature drop speed is less than a preset threshold value; if yes, starting a film covering device and an anti-frost fan; otherwise, entering the step S7; S7, starting the film covering device and the anti-frost fan, and switching the inlet end of a drip irrigation pipe to be communicated with a hot air heating system, and the hot air is introduced into the ground surface of the tea garden.

Description

Technical Field

[0001] This invention relates to tea monitoring technology, specifically to a method for monitoring and early warning of low-temperature frost damage in spring tea. Background Technology

[0002] After the temperature rises in early spring, tea tree buds sprout one after another. If abnormal weather conditions such as a sudden drop in temperature, late frost, or even light snow occur during this period (a cold snap in spring), it will cause frost damage to the tea buds, seriously affecting the yield and quality of tea, causing serious losses in spring tea production, and delaying the time for the tea trees to sprout again.

[0003] To prevent tea leaves from being frostbitten, many tea gardens combine weather forecasts issued by the meteorological bureau with temperature predictions. When the temperature is below 4℃, they will turn on anti-freeze fans to blow the warmer parts of the tea garden downwards to improve the temperature near the ground. Alternatively, they will pile up damp straw, weeds, and leaves in open areas of the tea garden to create smoke and artificial clouds, which can suppress radiative cooling and prevent frostbite.

[0004] While the two methods mentioned above can effectively reduce the likelihood of frost in tea gardens in most cases, their implementation relies heavily on weather forecasts from the meteorological bureau. This information is based on regional averages and may deviate from the actual temperature in the tea garden. For example, if the meteorological bureau forecasts a temperature of 6°C, the tea garden may be located on a windward or low-lying area where the temperature could be below 4°C, thus still affecting the tea garden.

[0005] In addition, although smoke can form a barrier to raise the temperature of the surrounding air, it is unstable and easily dispersed by the wind. The smoke concentration on the tea garden ground will quickly decrease, making it difficult to play a role in frost prevention for a long time. On the other hand, smoke is mainly formed by combustion, and the smoke contains a large number of smoke particles, which will also cause pollution to the environment to some extent. Summary of the Invention

[0006] In view of the above-mentioned shortcomings in the prior art, the method for monitoring and early warning of low temperature frost in spring tea provided by the present invention solves the problem of large deviation between the temperature information obtained by the existing frost prevention technology and the actual temperature in the tea garden.

[0007] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows:

[0008] A method for monitoring and early warning of low-temperature frost damage in spring tea is provided, which includes the following steps:

[0009] S1. Obtain the surface temperature, air humidity, and air temperature at sampling points distributed throughout the tea garden;

[0010] S2. Calculate the canopy temperature at each sampling point based on the surface temperature, air humidity, and air temperature;

[0011] S3. The tea garden is divided into grids, and the canopy temperature of each grid point is obtained based on the canopy temperature of each sampling point using an inverse distance weighted interpolation algorithm;

[0012] S4. Calculate the average temperature of all canopy temperatures and determine whether the average temperature is greater than the preset average. If so, return to step S1 after a preset time; otherwise, proceed to step S5.

[0013] S5. Calculate the temperature drop rate based on multiple consecutive temperature averages. v :

[0014]

[0015] in, and The first i Time and the i Average temperature at time -1; N The total number of consecutive temperature averages;

[0016] S6. Determine whether the temperature drop rate is less than the preset threshold. If so, start the covering device on the windward side, low-lying area and hilltop to carry out the covering operation and start the anti-frost fan; otherwise, proceed to step S7.

[0017] S7. Start the mulching device on the windward side, low-lying areas and hilltops to carry out mulching operations and start the anti-frost fan. Switch the drip irrigation pipe inlet to connect to the hot air heating system to introduce hot air into the tea garden surface.

[0018] Furthermore, the method for obtaining the canopy temperature at each grid point using the inverse distance weighted interpolation algorithm includes:

[0019] S31. Obtain the plan view of the tea garden and the position coordinates of the point to be predicted at each sampling point and the center point of each grid on the plan view;

[0020] S32. Obtain the size of each grid, and use the radius of the circle that is completely contained within the grid and has the largest area as the neighborhood radius;

[0021] S33. Calculate the distance between each point to be predicted and all sampling points, and select the point to be predicted with the smallest distance as the initial point to be predicted.

[0022] S34. Determine all sampling points within the circle formed by the neighborhood radius of the initial point to be predicted. i If the quantity is less than the preset quantity, proceed to step S36; otherwise, proceed to step S35.

[0023] S35. Use a preset number of sampling points closest to the initial point to be predicted. i，Calculate the initial canopy temperature at the point to be predicted, and then proceed to step S37;

[0024] S36. Use all sampling points within a circle formed by the radius of the neighborhood of the initial point to be predicted. i Calculate the canopy temperature of the initial point to be predicted, and then proceed to step S37;

[0025] S37. Determine whether the canopy temperature of all points to be predicted has been obtained. If yes, terminate the calculation; otherwise, update the initial points to be predicted to the sampling points and return to step S33.

[0026] The formulas for calculating the initial canopy temperature of the point to be predicted in steps S35 and S36 are as follows:

[0027]

[0028] in, d ij Initial point to be predicted j With sampling points i Euclidean distance; t i Sampling points i Canopy temperature; n For preset quantity; ρ It is the power of the distance.

[0029] Furthermore, the formula for calculating the canopy temperature is:

[0030]

[0031]

[0032] in, t i Sampling points i Canopy temperature; Net radiation of the canopy; The albedo of the canopy; Ground absorption rate; For Stephen Boltzmann Changshu; It refers to the surface temperature; The area covered by tea trees; This refers to the total area of ​​the tea plantation. It is the saturated vapor pressure; This is the constant of the hygrometer; S This refers to solar radiation. f This represents the average leaf area density.

[0033] Furthermore, the formula for calculating the saturated water vapor pressure is as follows:

[0034]

[0035] in, T This refers to the air temperature.

[0036] Furthermore, the method for obtaining the coverage area of ​​the tea trees includes:

[0037] A1. During the peak tea growing season each year, drones equipped with high-definition cameras are used to collect high-definition images of the tea gardens along a preset motion trajectory.

[0038] A2. The acquired images are stitched together, and then the stitched whole-area tea garden image is preprocessed to remove noise;

[0039] A3. The RGB prior threshold segmentation method is used to perform initial segmentation on the whole tea garden image, retaining the main crop and weeds, removing the land background, and then the HSI threshold segmentation method is used to retain the edges of green plants.

[0040] A4. Use the OpenCV module to perform contour detection on the image that retains the edges of green plants, and calculate the area of ​​tea trees within each contour.

[0041] A5. Add up the areas of all tea trees to get the total area of ​​the tea garden.

[0042] Furthermore, the coating device includes a flexible coating, two rows of support columns and a power unit. Each row of support columns is fixed with an L-shaped bearing plate, and a sleeve rod is provided inside the bearing plate. Several collars that slide on the sleeve rod are provided at equal intervals on both sides of the coating length.

[0043] Each sleeve rod is equipped with a fixed sleeve fixed thereon and a movable sleeve slidably fitted thereon. A pair of fixed sleeves and a pair of movable sleeves are fixedly connected by a connecting rod; the two ends of the film width are respectively fitted onto a connecting rod.

[0044] The power unit includes a lead screw nut fixed on one of the movable sleeves, the lead screw nut being connected to a lead screw mounted on a bearing plate, and the lead screw being connected to a servo motor mounted on a bearing plate at a fixed sleeve via a coupling.

[0045] Furthermore, the methods for monitoring and early warning of low-temperature frost damage in spring tea also include methods for adjusting the temperature of the hot air generated by the hot air heating system:

[0046] S71. Control the initial temperature of the hot air generated by the hot air heating system to be equal to a preset threshold.

[0047] S72. Collect the hot air temperature at the drip irrigation pipe outlet every preset time interval, and adjust the initial temperature = 2 × initial temperature - hot air temperature;

[0048] S73. After the hot air heating system has been in operation for a preset time, turn off the hot air heating system and return to step S71 when the average temperature is less than the preset threshold.

[0049] Furthermore, the hot air heating system includes a temperature sensor, a controller, and an industrial heater connected to the controller. The inlet end of the drip irrigation main network is connected to the output pipe of the industrial heater via a tee pipe. The temperature sensor is located at the drip irrigation pipe furthest from the industrial heater.

[0050] Furthermore, methods for monitoring and early warning of low-temperature frost damage in spring tea production also include:

[0051] When the rate of temperature drop exceeds the preset threshold and the unharvested area is less than the preset area, the management personnel will be notified to organize manpower for harvesting.

[0052] When the temperature drop rate exceeds a preset threshold and the unharvested area is greater than or equal to a preset area, the drone is controlled to spray tea antifreeze onto the tea canopy surface.

[0053] The beneficial effects of this invention are as follows: This method first calculates the canopy temperature using surface temperature and air temperature, then uses interpolation to obtain the temperature of each grid point, and uses the average temperature obtained from these temperatures as the final temperature of the tea garden canopy. The canopy temperature obtained in this way is closer to the actual temperature of the tea garden canopy than the temperature released by the meteorological bureau. Based on this, frost prediction of tea gardens can be carried out, which can greatly improve the accuracy of frost prediction.

[0054] In addition, after obtaining the tea garden canopy temperature, when carrying out frost prevention and control, if the temperature drops slowly, frost-proof fans can be used to exchange the hot air above the tea garden with the cold air below to increase the tea garden canopy temperature; if the temperature drops rapidly, hot air, mulching, and frost-proof fans can be combined to increase the tea garden canopy temperature, thereby preventing frost when the temperature drops sharply, and ultimately ensuring that the quality of new buds is not affected by low temperatures. Attached Figure Description

[0055] Figure 1 A flowchart for monitoring and early warning methods for low-temperature frost damage in spring tea production.

[0056] Figure 2 This is a top view of the coating device.

[0057] Figure 3 This is a front view of the coating device.

[0058] Among them, 1. film covering; 2. support column; 3. power unit; 31. lead screw nut; 32. lead screw; 33. servo motor; 4. bearing plate; 5. sleeve rod; 51. fixed sleeve; 52. movable sleeve; 6. collar; 7. connecting rod. Detailed Implementation

[0059] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0060] refer to Figure 1 , Figure 1 A flowchart illustrating the methods for monitoring and early warning of low-temperature frost damage in spring tea production is shown; for example... Figure 1 As shown, the method S includes steps S1 to S7.

[0061] In step S1, the surface temperature, air humidity, and air temperature at sampling points distributed throughout the tea garden are obtained. Preferably, at least two sampling points exist within at least one grid, and sampling points are evenly distributed in the remaining areas of the tea garden to improve the accuracy of obtaining the canopy temperature of each grid point using the inverse distance weighted interpolation algorithm.

[0062] In step S2, the canopy temperature at each sampling point is calculated based on the surface temperature, air humidity, and air temperature.

[0063]

[0064]

[0065] in, t i Sampling points i Canopy temperature; Net radiation of the canopy; The albedo of the canopy; Ground absorption rate; For Stephen Boltzmann Changshu; It refers to the surface temperature; The area covered by tea trees; This refers to the total area of ​​the tea plantation. It is the saturated vapor pressure; This is the constant of the hygrometer; S This refers to solar radiation. f This represents the average leaf area density.

[0066] In implementation, the preferred formula for calculating saturated vapor pressure in this scheme is:

[0067]

[0068] in, T This refers to the air temperature.

[0069] This scheme takes into account parameters such as surface temperature, air temperature, and tea garden area when calculating canopy temperature, so that the calculated canopy temperature is closer to the real-time temperature of the tea garden canopy. Based on this, the accuracy of frost prediction for tea gardens can be greatly improved.

[0070] During implementation, the preferred methods for obtaining the tea tree coverage area in this plan include:

[0071] A1. During the peak tea growing season each year, drones equipped with high-definition cameras are used to collect high-definition images of the tea gardens along a preset motion trajectory.

[0072] A2. The acquired images are stitched together, and then the stitched whole-area tea garden image is preprocessed to remove noise;

[0073] A3. The RGB prior threshold segmentation method is used to perform initial segmentation on the whole tea garden image, retaining the main crop and weeds, removing the land background, and then the HSI threshold segmentation method is used to retain the edges of green plants.

[0074] A4. Use the OpenCV module to perform contour detection on the image that retains the edges of green plants, and calculate the area of ​​tea trees within each contour.

[0075] A5. Add up the areas of all tea trees to get the total area of ​​the tea garden.

[0076] As the age of the tea trees and the degree of pruning each year change, the coverage area of ​​the tea garden will also change accordingly. This plan uses the above method to calculate the tea garden area every year. Firstly, it can obtain the coverage area of ​​the tea garden relatively accurately. Secondly, when calculating the canopy temperature, a more accurate tea garden area will have a greater impact on the accuracy of the final canopy temperature.

[0077] In step S3, the tea garden is gridded, and the canopy temperature of each grid point is obtained by using an inverse distance weighted interpolation algorithm based on the canopy temperature of each sampling point.

[0078] In one embodiment of the present invention, the method for obtaining the canopy temperature of each grid point using an inverse distance weighted interpolation algorithm includes:

[0079] S31. Obtain the plan view of the tea garden and the position coordinates of the point to be predicted at each sampling point and the center point of each grid on the plan view;

[0080] S32. Obtain the size of each grid, and use the radius of the circle that is completely contained within the grid and has the largest area as the neighborhood radius;

[0081] S33. Calculate the distance between each point to be predicted and all sampling points, and select the point to be predicted with the smallest distance as the initial point to be predicted.

[0082] S34. Determine all sampling points within the circle formed by the neighborhood radius of the initial point to be predicted. i If the quantity is less than the preset quantity, proceed to step S36; otherwise, proceed to step S35.

[0083] S35. Use a preset number of sampling points closest to the initial point to be predicted. i， Calculate the initial canopy temperature at the point to be predicted, and then proceed to step S37;

[0084] S36. Use all sampling points within a circle formed by the radius of the neighborhood of the initial point to be predicted. i Calculate the canopy temperature of the initial point to be predicted, and then proceed to step S37;

[0085] S37. Determine whether the canopy temperature of all points to be predicted has been obtained. If yes, terminate the calculation; otherwise, update the initial points to be predicted to the sampling points and return to step S33.

[0086] The formulas for calculating the initial canopy temperature of the point to be predicted in steps S35 and S36 are as follows:

[0087]

[0088] in, d ij Initial point to be predicted j With sampling points i Euclidean distance; t i Sampling points i Canopy temperature; n For preset quantity; ρ It is the power of the distance.

[0089] This scheme first selects an initial point to be predicted, and then calculates the canopy temperature at that point. This ensures that there is a sampling point closest to the initial point to be predicted each time, thereby ensuring the accuracy of the canopy temperature obtained by subsequent inverse distance weighted interpolation.

[0090] In step S4, the average temperature of all canopy temperatures is calculated, and it is determined whether the average temperature is greater than the preset average. If so, the process returns to step S1 after a preset time; otherwise, it proceeds to step S5. The preferred preset average temperature in this scheme is 5℃.

[0091] In step S5, the temperature drop rate is calculated based on multiple consecutive temperature averages. v :

[0092]

[0093] in, and The first i Time and the i Average temperature at time -1; N The total number of consecutive temperature averages;

[0094] In step S6, it is determined whether the temperature drop rate is less than the preset threshold. If so, the covering device 1 on the windward side, low-lying area and hilltop is activated to perform the covering operation and the anti-frost fan is activated; otherwise, proceed to step S7.

[0095] This solution includes an early warning system for frost detection and disaster warning. The system includes a control module and sensors at each sampling point to collect surface temperature, air humidity and air temperature data. The mulch 1 device, the hot air heating system and all the sensors are connected to the control module.

[0096] like Figure 2 and Figure 3 As shown, the film covering device includes a flexible film covering 1, two rows of support columns 2 and a power unit 3. Each row of support columns 2 is fixed with an L-shaped bearing plate 4, and a sleeve rod 5 is provided inside the bearing plate 4. Several collars 6 that slide on the sleeve rod 5 are provided at equal intervals on both sides of the length of the film covering 1.

[0097] Each sleeve rod 5 is provided with a fixed sleeve 51 fixed thereon and a movable sleeve 52 slidably sleeved thereon. A pair of fixed sleeves 51 and a pair of movable sleeves 52 are fixedly connected by a connecting rod 7. The two ends of the width of the film 1 are respectively sleeved on a connecting rod 7.

[0098] The power unit 3 includes a lead screw nut 31 fixed on one of the movable sleeves 52. The lead screw nut 31 is connected to a lead screw 32 mounted on the bearing plate 4. The lead screw 32 is connected to a servo motor 33 mounted on the bearing plate 4 at the fixed sleeve 51 via a coupling. The servo motor 33 is connected to the control module.

[0099] The working principle of the film covering device in this scheme is as follows: when the power unit 3 receives the start signal sent by the control module, the servo motor 33 rotates, causing the lead screw 32 to move away from the servo motor 33 along with the movable sleeve 52 connected to the lead screw nut 31. Then, the film covering 1 gathered on the sleeve 5 is unfolded through the connecting rod 7 to cover the tea garden.

[0100] When the power unit 3 receives the film-receiving signal sent by the control module, the servo motor 33 rotates, causing the lead screw 32 to move in the direction of the servo motor 33 along with the movable sleeve 52 connected to the lead screw nut 31. Then, the unfolded film 1 slides along the sleeve 5 through the connecting rod 7, thereby achieving the gathering of the film 1.

[0101] In step S7, the film covering device 1 is activated on the windward side, low-lying areas and hilltops to perform film covering operation 1 and the anti-frost fan is activated. The drip irrigation pipe inlet is switched to connect to the hot air heating system to introduce hot air into the tea garden surface.

[0102] In one embodiment of the present invention, the method for monitoring and warning of low-temperature frost in spring tea further includes a method for adjusting the temperature of the hot air generated by the hot air heating system:

[0103] S71. Control the initial temperature of the hot air generated by the hot air heating system to be equal to a preset threshold.

[0104] S72. Collect the hot air temperature at the drip irrigation pipe outlet every preset time interval, and adjust the initial temperature = 2 × initial temperature - hot air temperature;

[0105] S73. After the hot air heating system has been in operation for a preset time, turn off the hot air heating system and return to step S71 when the average temperature is less than the preset threshold.

[0106] When implemented, the methods for monitoring and early warning of low-temperature frost damage to spring tea in this plan also include:

[0107] When the rate of temperature drop exceeds the preset threshold and the unharvested area is less than the preset area, the management personnel will be notified to organize manpower for harvesting.

[0108] When the temperature drop rate exceeds a preset threshold and the unharvested area is greater than or equal to a preset area, the drone is controlled to spray tea antifreeze onto the tea canopy surface.

[0109] The hot air heating system includes a temperature sensor, a controller connected to the control module, and an industrial warm air blower connected to the controller. The inlet end of the drip irrigation main network is connected to the output pipe of the industrial warm air blower through a tee pipe. The temperature sensor is set at the drip irrigation pipe furthest from the industrial warm air blower.

[0110] The hot air heating system in this plan can introduce heated gas into the near-ground area to heat the underground soil and the air near the ground, thereby increasing the temperature near the tea garden canopy. At the same time, the upward-moving hot air can move towards the tea tree canopy under the action of anti-frost fans, thereby increasing the residence time of the hot air in the tea garden and avoiding rapid heat loss.

[0111] In addition, when hot air is transported by drip irrigation, it can exchange heat with the nearby soil. Combined with the hot air entering near the ground, it can quickly raise the temperature of the tea garden. The fact that the hot air heating system and the drip irrigation system share drip irrigation pipes can increase the cost of low-temperature frost prevention and control in the tea garden to some extent.

[0112] In summary, this solution combines hot air, mulch 1, and frost-proof fans to increase the temperature of the tea garden canopy, thereby preventing frost when the temperature drops significantly, and ultimately ensuring that the quality of new buds is not affected by low temperatures.

Claims

1. A method for monitoring and early warning of low-temperature frost damage in spring tea, characterized in that, Including the following steps: S1. Obtain the surface temperature, air humidity, and air temperature at sampling points distributed throughout the tea garden; S2. Calculate the canopy temperature at each sampling point based on the surface temperature, air humidity, and air temperature; Methods for obtaining the canopy temperature at each grid point using inverse distance weighted interpolation include: S31. Obtain the plan view of the tea garden and the position coordinates of the point to be predicted at each sampling point and the center point of each grid on the plan view; S32. Obtain the size of each grid, and use the radius of the circle that is completely contained within the grid and has the largest area as the neighborhood radius; S33. Calculate the distance between each point to be predicted and all sampling points, and select the point to be predicted with the smallest distance as the initial point to be predicted. S34. Determine all sampling points within the circle formed by the neighborhood radius of the initial point to be predicted. i If the quantity is less than the preset quantity, proceed to step S36; otherwise, proceed to step S35. S35. Use a preset number of sampling points closest to the initial point to be predicted. i， Calculate the initial canopy temperature at the point to be predicted, and then proceed to step S37; S36. Use all sampling points within a circle formed by the neighborhood radius of the initial point to be predicted. i Calculate the canopy temperature of the initial point to be predicted, and then proceed to step S37; S37. Determine whether the canopy temperature of all points to be predicted has been obtained. If yes, terminate the calculation; otherwise, update the initial points to be predicted to the sampling points and return to step S33. The formulas for calculating the initial canopy temperature of the point to be predicted in steps S35 and S36 are as follows: in, d ij Initial point to be predicted j With sampling points i Euclidean distance; t i Sampling points i Canopy temperature; n For preset quantity; ρ The power of the distance; S3. The tea garden is divided into grids, and the canopy temperature of each grid point is obtained based on the canopy temperature of each sampling point using an inverse distance weighted interpolation algorithm; S4. Calculate the average temperature of all canopy temperatures and determine whether the average temperature is greater than the preset average. If so, return to step S1 after a preset time; otherwise, proceed to step S5. S5. Calculate the temperature drop rate based on multiple consecutive temperature averages. v : in, and The first i Time and the i Average temperature at time -1; N The total number of consecutive temperature averages; S6. Determine whether the temperature drop rate is less than the preset threshold. If so, start the covering device on the windward side, low-lying area and hilltop to carry out the covering operation and start the anti-frost fan; otherwise, proceed to step S7. S7. Start the mulching device on the windward side, low-lying areas and hilltops to carry out mulching operations and start the anti-frost fan. Switch the drip irrigation pipe inlet to connect to the hot air heating system to introduce hot air into the tea garden surface.

2. The method for monitoring and early warning of low-temperature frost damage to spring tea as described in claim 1, characterized in that, The formula for calculating the canopy temperature is: in, t i Sampling points i Canopy temperature; Net radiation of the canopy; The albedo of the canopy; Ground absorption rate; For Stephen Boltzmann Changshu; It refers to the surface temperature; The area covered by tea trees; This refers to the total area of ​​the tea plantation. It is the saturated vapor pressure; This is the constant of the hygrometer; S This refers to solar radiation. f This represents the average leaf area density.

3. The method for monitoring and early warning of low-temperature frost damage in spring tea according to claim 2, characterized in that, The formula for calculating the saturated water vapor pressure is: in, T This refers to the air temperature.

4. The method for monitoring and early warning of low-temperature frost damage in spring tea according to claim 2, characterized in that, The method for obtaining the coverage area of ​​the tea trees includes: A1. During the peak tea growing season each year, drones equipped with high-definition cameras are used to collect high-definition images of the tea gardens along a preset motion trajectory. A2. The acquired images are stitched together, and then the stitched whole-area tea garden image is preprocessed to remove noise; A3. The RGB prior threshold segmentation method is used to perform initial segmentation on the whole tea garden image, retaining the main crop and weeds, removing the land background, and then the HSI threshold segmentation method is used to retain the edges of green plants. A4. Use the OpenCV module to perform contour detection on the image that retains the edges of green plants, and calculate the area of ​​tea trees within each contour. A5. Add up the areas of all tea trees to get the total area of ​​the tea garden.

5. The method for monitoring and early warning of low-temperature frost damage to spring tea according to any one of claims 1-3, characterized in that, The coating device includes a flexible coating film, two rows of support columns and a power unit. Each row of support columns is fixed with an L-shaped bearing plate, and a sleeve rod is provided inside the bearing plate. Several collars that slide on the sleeve rod are provided at equal intervals on both sides of the coating film length. Each sleeve rod is equipped with a fixed sleeve fixed thereon and a movable sleeve slidably fitted thereon. A pair of fixed sleeves and a pair of movable sleeves are fixedly connected by a connecting rod; the two ends of the film width are respectively fitted onto a connecting rod. The power unit includes a lead screw nut fixed on one of the movable sleeves, the lead screw nut being connected to a lead screw mounted on a bearing plate, and the lead screw being connected to a servo motor mounted on a bearing plate at a fixed sleeve via a coupling.

6. The method for monitoring and early warning of low-temperature frost damage to spring tea according to any one of claims 1-3, characterized in that, It also includes methods for regulating the temperature of the hot air generated by the hot air heating system: S71. Control the initial temperature of the hot air generated by the hot air heating system to be equal to a preset threshold. S72. Collect the hot air temperature at the drip irrigation pipe outlet every preset time interval, and adjust the initial temperature = 2 × initial temperature - hot air temperature; S73. After the hot air heating system has been in operation for a preset time, turn off the hot air heating system and return to step S71 when the average temperature is less than the preset threshold.

7. The method for monitoring and early warning of low-temperature frost damage to spring tea as described in claim 6, characterized in that, The hot air heating system includes a temperature sensor, a controller, and an industrial heater connected to the controller. The inlet end of the drip irrigation main network is connected to the output pipe of the industrial heater through a tee pipe. The temperature sensor is located at the drip irrigation pipe furthest from the industrial heater.

8. The method for monitoring and early warning of low-temperature frost damage to spring tea according to claim 1, characterized in that, Also includes: When the rate of temperature drop exceeds the preset threshold and the unharvested area is less than the preset area, the management personnel will be notified to organize manpower for harvesting. When the temperature drop rate exceeds a preset threshold and the unharvested area is greater than or equal to a preset area, the drone is controlled to spray tea antifreeze onto the tea canopy surface.

Images