CN117441700A - Autonomous navigation glass greenhouse green prevention and control robot and its spraying and disinfection method - Google Patents
Autonomous navigation glass greenhouse green prevention and control robot and its spraying and disinfection method Download PDFInfo
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- CN117441700A CN117441700A CN202311765769.8A CN202311765769A CN117441700A CN 117441700 A CN117441700 A CN 117441700A CN 202311765769 A CN202311765769 A CN 202311765769A CN 117441700 A CN117441700 A CN 117441700A
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0025—Mechanical sprayers
- A01M7/0032—Pressure sprayers
- A01M7/0042—Field sprayers, e.g. self-propelled, drawn or tractor-mounted
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G13/00—Protection of plants
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0089—Regulating or controlling systems
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- Engineering & Computer Science (AREA)
- Environmental Sciences (AREA)
- Insects & Arthropods (AREA)
- Pest Control & Pesticides (AREA)
- Wood Science & Technology (AREA)
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Abstract
The invention relates to the technical field of agricultural special equipment, and provides an autonomous navigation glass greenhouse green prevention and control robot and a spraying and killing method thereof, wherein the autonomous navigation glass greenhouse green prevention and control robot comprises a control device, a mobile device and a spraying device; the mobile device is provided with a detection sensor; the control device comprises a man-machine interaction unit, a mobile control unit, a spraying control unit and a calculation unit; the man-machine interaction unit is used for inputting a set route; the mobile control unit controls the mobile device to move according to the set route; the detection sensor is used for acquiring crop plant images when the mobile device moves; the calculating unit is used for judging whether the crop plants have plant diseases and insect pests or not and determining the spraying quantity and the spraying position; moving the control unit to align the spraying device with the crop; the spraying control unit controls the spraying device to spray ozone water to kill plant diseases and insect pests. According to the autonomous navigation green prevention and control robot for the glass greenhouse, the optimal spraying amount is calculated, the medicine is precisely applied, and the disinfection effect is improved.
Description
Technical Field
The invention relates to the technical field of agricultural special equipment, in particular to an autonomous navigation glass greenhouse green prevention and control robot and a spraying and killing method thereof.
Background
Ozone is a highly reactive gas, slightly soluble in water, and is also a strong oxidizer with an oxidation potential of 2.07V. The strong oxidizing property of ozone can make it quickly sterilized, and its sterilizing power is better than that of chlorine, chlorine dioxide and chloramine. Can be used for disinfection and sterilization by spraying ozone water in a glass greenhouse to prevent and treat diseases and insect pests. In the existing spraying mode, the spraying amount of ozone water or other pesticides is usually controlled manually, and the situation that the damage to crops is caused by excessive spraying or the sterilization effect is poor due to insufficient spraying easily occurs.
Disclosure of Invention
The invention provides an autonomous navigation green prevention and control robot for a glass greenhouse and a spraying and killing method thereof, which are used for solving the problem that in the prior art, the spraying quantity is usually controlled manually, and damage to crops or poor killing effect caused by insufficient spraying easily occurs.
In a first aspect, the present invention provides an autonomous navigation glass greenhouse green prevention and control robot, comprising:
control device, mobile device and sprinkler;
The spraying device is arranged on the mobile device, and a detection sensor is arranged on the mobile device; the control device includes: the system comprises a man-machine interaction unit, a mobile control unit, a spraying control unit and a calculation unit which are electrically connected with each other; the spraying control unit is electrically connected with the spraying device, and the detection sensor is electrically connected with the calculation unit;
the man-machine interaction unit is used for inputting a set route;
the mobile control unit is used for controlling the mobile device to move according to the set route;
the detection sensor is used for acquiring a crop plant image in the process that the mobile device moves along the set route;
the calculating unit is used for judging whether a plant disease and insect damage exists on a crop plant according to the crop plant image, determining the area of the plant disease and insect damage and the degree of color change of the plant disease and insect damage, determining the spraying amount of ozone water according to the area of the plant disease and insect damage and the degree of color change of the plant disease and insect damage under the condition that the plant disease and insect damage exists, and determining the position information of the plant disease and insect damage according to the crop plant image;
the mobile control unit controls the mobile device and the spraying device according to the position information, so that the spraying device is aligned to crop plants with diseases and insect pests;
The spraying control unit is used for controlling the spraying device to spray ozone water to crop plants according to the spraying quantity so as to kill plant diseases and insect pests.
The control device of the autonomous navigation glass greenhouse green prevention and control robot further comprises an environmental factor detection unit, wherein the environmental factor detection unit is electrically connected with the calculation unit and is used for acquiring detection temperature, humidity and illumination intensity in the process that the mobile device moves along the set route;
the calculation unit is further used for determining the spraying amount of the ozone water based on the disease and pest prediction model according to temperature, humidity and illumination intensity in the case that no disease and pest is found due to the existence of the latent period of the disease and pest.
The autonomous navigation glass greenhouse green prevention and control robot according to the present invention, the spraying device comprises: the device comprises a water storage barrel, a pump, a water pipe, a bracket and a spray head;
the water storage barrel and the bracket are arranged on the mobile device; one end of the water pipe is communicated with the water storage barrel through the pump, and the other end of the water pipe is communicated with the spray head; one end of the water pipe and the spray head are arranged on the bracket, and the pump is electrically connected with the spray control unit.
According to the autonomous navigation glass greenhouse green prevention and control robot, the spraying device comprises a plurality of spray heads and at least one water pipe, one end of the water pipe is arranged on the support, and the spray heads are arranged at intervals along the water pipe and are communicated with the water pipe.
According to the autonomous navigation glass greenhouse green prevention and control robot, a concentration detector and a liquid level detector are arranged in a water storage barrel, the concentration detector is used for detecting the concentration of ozone water in the water storage barrel, and the liquid level detector is used for detecting the liquid level of ozone water in the water storage barrel;
the concentration detector and the liquid level detector are electrically connected with the man-machine interaction unit and the mobile control unit,
the man-machine interaction unit is used for reading and displaying the concentration and the liquid level of the ozone water in the water storage barrel;
and when the concentration of the ozone water in the water storage barrel is lower than a concentration threshold value and/or the liquid level of the ozone water is lower than a liquid level threshold value, the man-machine interaction unit displays alarm information, and the mobile control unit controls the mobile device to stop.
According to the autonomous navigation glass greenhouse green prevention and control robot, a front track wheel set, a differential wheel set and a rear track wheel set are sequentially arranged at the bottom of a mobile device, and the differential wheel set comprises a first differential wheel and a second differential wheel which are arranged side by side and are used for driving the mobile device to advance or retreat or turn when the mobile device runs on the ground; the front track wheel set comprises a first front track wheel and a second front track wheel which are arranged side by side, the rear track wheel set comprises a first rear track wheel and a second rear track wheel which are arranged side by side, and the front track wheel set and the rear track wheel set are used for driving the moving device to move forwards or backwards on a track arranged on the set route;
The bottom of the mobile device is also provided with a two-dimensional code reader for identifying the two-dimensional code on the ground, and the two-dimensional code reader is used for determining the position and the direction of the mobile device according to the two-dimensional code;
the two-dimensional code reader, the first differential wheel, the second differential wheel, the front track wheel set and the rear track wheel set are all electrically connected with the mobile control unit.
In a second aspect, the invention also provides a method for spraying and killing by using the autonomous navigation glass greenhouse green prevention and control robot, which comprises the following steps:
setting a set route according to a planting mode of crop plants, and controlling the moving device to move along the set route;
acquiring images, temperature, humidity and illumination intensity of crop plants in the process that the mobile device moves along a set route;
judging whether plant diseases and insect pests exist according to the crop plant images, and determining the spraying amount of ozone water and the plant position based on the crop plant images, the temperature, the humidity and the illumination intensity;
when spraying is needed, the moving device is controlled to stop, and the spraying device is controlled to aim at the crop plants for spraying according to the ozone water spraying amount.
According to the method for spraying and killing the glass greenhouse green prevention and control robot with autonomous navigation, provided by the invention, whether plant diseases and insect pests exist is judged according to the crop plant image, and the spraying amount of ozone water and the plant position are determined based on the crop plant image, the temperature, the humidity and the illumination intensity, and the method comprises the following steps:
Comparing the crop plant image with the standard crop plant image, and judging whether plant diseases and insect pests exist on the crop plant;
when the plant diseases and insect pests exist in the crop plants, comparing the crop plant images with the standard crop plant images to determine spraying positions, determining the area of the plant diseases and insect pests and the color change degree of the plant diseases, and determining the spraying amount of ozone water and the plant positions based on the area of the plant diseases and insect pests and the color change degree of the plant diseases;
when no crop plant diseases and insect pests are found, the spraying amount of the ozone water and the plant position are determined based on the disease and insect pest prediction model according to the temperature, the humidity and the illumination intensity.
According to the method for spraying and killing the glass greenhouse green prevention and control robot with autonomous navigation, before the step of setting a set route according to the planting mode of crop plants and controlling a mobile device to move along the set route, the method comprises the following steps:
a crop plant sample is selected and a standard crop plant image of the sample is obtained.
According to the method for spraying and killing the glass greenhouse green prevention and control robot with autonomous navigation, before the step of setting a set route according to the planting mode of crop plants and controlling a mobile device to move along the set route, the method comprises the following steps:
selecting crop plant samples with different degrees of plant diseases and insect pests, and obtaining the plant disease and insect pest area, the plant disease and insect pest color change degree, the temperature, the humidity and the illumination intensity of the environment of the samples;
And building a disease and pest prediction model based on the disease and pest area, the disease and pest discoloration degree, the temperature, the humidity and the illumination intensity of the crop plant sample.
According to the autonomous navigation glass greenhouse green prevention and control robot, a man-machine interaction unit is arranged to facilitate a user to set a working path of the autonomous navigation glass greenhouse green prevention and control robot by himself, and the autonomous navigation glass greenhouse green prevention and control robot can adapt to planting areas with different layouts and fully meet user requirements; meanwhile, by arranging the detection sensor and the calculation unit, the image of the crop plant is acquired and processed and analyzed, so that whether the crop plant generates plant diseases and insect pests is judged, the area and the position of the plant diseases and insect pests are determined, the optimal ozone water spraying amount is calculated according to the area of the plant diseases and insect pests, and the spraying device is controlled by the cooperation of the mobile control unit and the spraying control unit to aim at the crop plant generating the plant diseases and insect pests for spraying, so that accurate pesticide application is realized, the disinfection effect is better, and the problem that the disinfection effect is poor due to the fact that the spraying amount is controlled manually generally and the damage to the crop or the insufficient spraying is easily caused due to the fact that the excessive spraying occurs is effectively solved.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic diagram of an autonomous navigation glass greenhouse green prevention and control robot provided by an embodiment of the invention;
fig. 2 is a schematic diagram of a system of an autonomous navigation glass greenhouse green prevention and control robot provided by an embodiment of the invention;
FIG. 3 is a schematic diagram of a green prevention and control robot for an autonomous navigation glass greenhouse according to an embodiment of the present invention;
fig. 4 is a rear view of an autonomous navigation glass greenhouse green prevention and control robot provided by an embodiment of the present invention;
fig. 5 is a schematic structural diagram of the bottom of the autonomous navigation glass greenhouse green prevention and control robot provided by the embodiment of the invention;
fig. 6 is a schematic diagram of a spraying and killing operation performed by an autonomous navigation glass greenhouse green prevention and control robot provided by the embodiment of the invention;
FIG. 7 is a schematic flow chart of a method for spraying and killing by using an autonomous navigation glass greenhouse green prevention and control robot according to an embodiment of the present invention;
FIG. 8 is a second flow chart of a method for spraying and killing by using an autonomous navigation glass greenhouse green prevention and control robot according to an embodiment of the present invention;
fig. 9 is a schematic diagram of a plant disease and insect pest prediction model based on a neural network according to an embodiment of the present invention;
reference numerals:
1. autonomous navigation green prevention and control robot for glass greenhouse;
11. A control device; 12. a mobile device; 13. a spraying device;
111. a man-machine interaction unit; 112. a movement control unit; 113. a spray control unit; 114. a calculation unit; 115. an environmental factor detection unit; 121. a detection sensor; 122. a front rail wheel set; 123. a differential wheel set; 124. a rear rail wheel set; 125. a two-dimensional code reader; 126. a universal wheel; 131. a water storage bucket; 132. a pump; 133. a water pipe; 134. a bracket; 135. a spray head;
1221. a first front rail wheel; 1222. a second front rail wheel; 1231. a first differential wheel; 1232. a second differential wheel; 1241. a first rear rail wheel; 1242. and a second rear rail wheel.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Ozone is a strong oxidant, and is subjected to reduction reaction in water to generate monoatoms (O) and hydroxyl (OH) with extremely strong oxidizing ability, organic substances in water can be instantaneously decomposed, and the ozone is a strong oxidant and a catalyst, so that the organic substances can undergo chain reaction, and the reaction is extremely rapid. Ozone is slightly dissolved in water, so that carbon-carbon double bonds and carbon-nitrogen double bonds in the carbendazim can be opened, and meanwhile, the amino groups of the carbendazim can be subjected to strong oxidization, and the molecular structure of the carbendazim is greatly changed in the double-action mode, the property of the carbendazim pesticide is changed, and the effect of degrading the carbendazim is achieved.
The ozone water preparing device comprises an ozone preparing part, a gas-liquid mixing part, a magnetized water preparing part and an electric control part, wherein the ozone preparing part mainly comprises an oxygenerator, an ozone pipe and a high-frequency high-voltage power supply; the magnetized water after magnetization and ozone generated after high-frequency high-voltage power ionization of the ozone pipe are fully mixed by a gas-liquid mixing device to generate ozone water rich in ozone, and finally the ozone water enters a greenhouse irrigation system to carry out greenhouse sterilization disinfection irrigation. The magnetized water part mainly comprises a magnetizing coil and a magnetizing circuit board, and after the water is magnetized by the magnetizing circuit, the activity and the adsorption force are obviously increased, so that the water has a better mixing effect. The gas-liquid mixing part mainly comprises a gas-liquid mixing pump, an ozone oxidation tower and a suck-back prevention device; the electric control part mainly comprises a delay timer, an alternating current contactor, a self-locking switch, an air switch and an automatic alarm device, and is arranged through the independent switch, so that the equipment can spray ozone water in a greenhouse according to the degree of plant diseases and insect pests, the spraying quantity is determined according to the degree of the plant diseases and insect pests, and the running safety is guaranteed through the alarm device.
The ozone concentration control method comprises the following steps: the ozone water concentration is regulated mainly by controlling the gas outlet amount of ozone gas, the gas outlet amount of ozone is controlled by the oxygen amount and the high-voltage ionization effect, and the change of the ozone gas ionization effect is realized by regulating the frequency of a high-frequency high-voltage power supply. The high-frequency high-voltage power supply part is the core of the ozone water preparation part and provides external voltage for the ozone tube, so that oxygen in the ozone tube reacts to ozone. The production of ozone requires that ozone generation efficiency be improved as much as possible, which requires that a high-frequency high-voltage power supply be provided in cooperation therewith. The ozone content is thus regulated in the following way: (1) The ionization frequency of the power supply voltage is about 2-5 kHz, the grading is adjustable, and the peak value of the high voltage peak is about 4-8 kV. (2) To optimize the impedance matching of the output, the high voltage output should resonate with the internal air chamber of the ozone tube. (3) Strict overvoltage, overcurrent and overheat protection measures are required, and the safety and reliability of the circuit in the long-term working process are ensured.
The autonomous navigation glass greenhouse green prevention and control robot provided by the invention is described below with reference to fig. 1-6.
As shown in fig. 1 and 2, the autonomous navigation glass greenhouse green prevention and control robot 1 of the present invention includes: a control device 11, a moving device 12 and a spraying device 13; the spraying device 13 is arranged on the mobile device 12, and the detection sensor 121 is arranged on the mobile device 12; the control device 11 includes: a man-machine interaction unit 111, a movement control unit 112, a spray control unit 113, and a calculation unit 114 electrically connected to each other; the spraying control unit 113 is electrically connected with the spraying device 13, and the detection sensor 121 is electrically connected with the calculation unit 114; the man-machine interaction unit 111 is used for inputting a set route; the movement control unit 112 is used for controlling the movement of the mobile device 12 according to the set route; the detection sensor 121 is used for acquiring images of crop plants during the movement of the mobile device 12 along the set route; the calculating unit 114 is used for judging whether the plant diseases and insect pests exist on the crop plant according to the crop plant image, determining the area of the plant diseases and insect pests and the color change degree of the plant diseases, determining the spraying amount of ozone water according to the area of the plant diseases and insect pests and the color change degree of the plant diseases under the condition that the plant diseases and insect pests exist, and determining the position information of the plant diseases according to the crop plant image; the mobile control unit 112 controls the mobile device 12 and the spraying device 13 according to the position information, so that the spraying device 13 is aligned with crops with diseases and insect pests; the spraying control unit 113 is used for controlling the spraying device 13 to spray ozone water to crop plants according to the spraying amount so as to kill plant diseases and insect pests.
In the embodiment, the autonomous navigation glass greenhouse green prevention and control robot 1 is mainly used for spraying ozone water in crop planting areas such as farmlands, greenhouses and the like to sterilize. According to the planting distribution condition of crops, a user can plan a spraying route of the autonomous navigation glass greenhouse green prevention and control robot 1 and input the spraying route as a set route into the autonomous navigation glass greenhouse green prevention and control robot 1 through the man-machine interaction unit 111; the movement control unit 112 can control the movement of the moving device 12 along the set route so that the autonomous navigation glass greenhouse green prevention and control robot 1 can detect and spray crop plants on the set route; the method comprises the steps of obtaining an image of a crop plant by shooting, scanning and the like of the crop plant on a set route through a set detection sensor 121, and transmitting the image of the crop plant to a calculation unit 114; the computing unit 114 analyzes the crop plant image to determine whether there are plant diseases and insect pests on the crop plant; if the plant diseases and insect pests exist, further analyzing and acquiring the plant diseases and insect pests area and the plant diseases and insect pests color change degree, calculating the optimal ozone water spraying amount based on the plant diseases and insect pests area and the plant diseases and insect pests color change degree, and sending the spraying amount to the spraying control unit 113; meanwhile, the calculating unit 114 can also determine the position information of the occurrence of the plant diseases and insect pests according to the image of the plant diseases, and send the position information to the mobile control unit 112, and the mobile control unit 112 controls the mobile device 12 to stop near the plant diseases and insect pests to further adjust the spraying device 13 to aim at the plant diseases and insect pests; the spraying control unit 113 controls the spraying device 13 to spray the crop plants according to the calculated spraying amount, so as to realize accurate pesticide application, avoid excessive spraying or insufficient spraying, and ensure better disinfection effect.
According to the autonomous navigation glass greenhouse green prevention and control robot 1, the man-machine interaction unit 111 is arranged to facilitate a user to set the working path of the autonomous navigation glass greenhouse green prevention and control robot 1 by himself, the autonomous navigation glass greenhouse green prevention and control robot 1 can adapt to planting areas with different layouts, and the user requirements are fully met; meanwhile, by arranging the detection sensor 121 and the calculation unit 114, the image of the crop plant is acquired and processed and analyzed, so that whether the crop plant generates plant diseases and insect pests is judged, the area and the position of the plant diseases and insect pests are determined, the optimal ozone water spraying amount is calculated according to the area of the plant diseases and insect pests, and the spraying device 13 is controlled by the cooperation of the mobile control unit 112 and the spraying control unit 113 to spray the crop plant with the plant diseases and insect pests, so that the precise pesticide application is realized, the disinfection effect is better, and the problem that the disinfection effect is poor due to the fact that the damage or insufficient spraying of the crop is caused by the excessive spraying of the spraying amount which is usually controlled manually is effectively solved.
Alternatively, the detection sensor 121 may include one or a combination of a binocular camera, an infrared camera, a spectral camera.
In some embodiments, as shown in fig. 2, the control device 11 further includes an environmental factor detecting unit 115, where the environmental factor detecting unit 115 is electrically connected to the calculating unit 114, and is configured to obtain the detected temperature, humidity, and illumination intensity during the movement of the mobile device 12 along the set route; the calculating unit 114 is further configured to determine the amount of ozone water sprayed based on the pest prediction model according to the temperature, humidity and illumination intensity in the case where no pest is found, because of the existence of the pest latency.
In the present embodiment, the environmental factor detection unit 115 is provided to detect the temperature, humidity, and illumination intensity in the vicinity of the crop plants, and transmit the temperature, humidity, and illumination intensity to the calculation unit 114; when no plant diseases and insect pests are identified through the crop plant images, the calculation unit 114 predicts the possible plant diseases and insect pests based on the input temperature, humidity and illumination intensity, calculates the ozone water spraying amount according to the prediction result, sprays the crop plants to achieve the effect of preventing, reduces the possibility of plant diseases and insect pests, and has better effect of preventing and controlling the plant diseases and insect pests. Specifically, when the degree of the possible occurrence of the plant diseases and insect pests is calculated to be lower than a certain degree based on the temperature, the humidity and the illumination intensity, the calculated ozone water spraying amount is zero, so that the ozone water does not need to be sprayed; and when the degree of the possible occurrence of the plant diseases and insect pests calculated based on the temperature, the humidity and the illumination intensity exceeds a certain degree, the higher the degree of the possible occurrence of the plant diseases and insect pests is, the larger the spraying amount of the ozone water is.
Specifically, as shown in fig. 3 and 4, the spraying device 13 includes: a water storage tub 131, a pump 132, a water pipe 133, a bracket 134, and a spray head 135; the water storage tub 131 and the bracket 134 are provided on the moving device 12; one end of the water pipe 133 is communicated with the water storage barrel 131 through the pump 132, and the other end is communicated with the spray head 135; one end of the water pipe 133 and the spray head 135 are provided on the bracket 134, and the pump 132 is electrically connected to the spray control unit 113.
In the present embodiment, the water storage tub 131 is used to store the prepared ozone water, and the spray control unit 113 controls the pump 132 to draw the ozone water into the water pipe 133 from the water storage tub 131 and spray the ozone water from the spray head 135 at one end of the water pipe 133. The spray control unit 113 controls the amount of ozone water sprayed by controlling the on and off of the pump 132.
Alternatively, in some embodiments, a flow meter electrically connected to the spray control unit 113 may be provided on the water pipe 133, and the spray control unit 113 monitors the flow rate in the water pipe 133 through the flow meter so as to more accurately control the amount of ozone water sprayed.
Specifically, in some embodiments, the water storage barrel 131 is a stainless steel barrel, is rust-proof and corrosion-resistant, and is more stable and reliable.
Alternatively, in some embodiments, the spray head 135 is rotatably disposed on the stand 134, and the rotating mechanism thereof is electrically connected to the movement control unit 112, and the movement control unit 112 can drive the rotating mechanism to rotate the spray head 135 to align with the crop plants to be sprayed.
In some embodiments, as shown in fig. 3 and 4, the spraying device 13 includes a plurality of spray nozzles 135 and at least one water pipe 133, one end of the water pipe 133 is disposed on the bracket 134, and the plurality of spray nozzles 135 are disposed along the water pipe 133 at intervals and communicate with the water pipe 133.
In this embodiment, by arranging the water pipe 133 and the plurality of spray nozzles 135 at intervals along the water pipe 133 on the bracket 134, when ozone water spraying is performed, the plurality of spray nozzles 135 can cover a larger spraying range, the spraying is more uniform, and the disinfection effect is better.
In some embodiments, a concentration detector for detecting the concentration of the ozone water in the water storage tub 131 and a liquid level detector for detecting the liquid level of the ozone water in the water storage tub 131 are provided in the water storage tub 131; the concentration detector and the liquid level detector are electrically connected with the human-computer interaction unit 111 and the mobile control unit 112; the man-machine interaction unit 111 is used for reading and displaying the concentration and the liquid level of the ozone water in the water storage bucket 131; when the concentration of the ozone water in the water storage barrel 131 is lower than the concentration threshold value and/or the liquid level of the ozone water is lower than the liquid level threshold value, the man-machine interaction unit 111 displays alarm information, and the mobile control unit 112 controls the mobile device 12 to stop.
In this embodiment, as shown in fig. 6, the concentration detector and the liquid level detector are mainly used for monitoring the concentration of ozone water and the level of ozone water in the water storage barrel 131, when the concentration of ozone water in the water storage barrel does not meet the minimum concentration of disinfection requirements or the level of ozone water is too low (i.e. the volume of ozone water is too low), the human-computer interaction unit 111 displays alarm information to remind a user to supplement ozone water; while the movement control unit 112 controls the movement device 12 to stop so that the user supplements the ozone water.
Further, in some embodiments, the man-machine interaction unit 111 may be further connected to a remote terminal such as a computer, a mobile phone, etc., and remotely alarm by means of a short message. The user can access the man-machine interaction unit 111 through the remote terminal to acquire the running condition of the autonomous navigation glass greenhouse green prevention and control robot 1, and the remote operation is performed, so that the use is more convenient.
Specifically, in some embodiments, as shown in fig. 5, a front rail wheel set 122, a differential wheel set 123 and a rear rail wheel set 124 are sequentially installed at the bottom of the mobile device 12, and the differential wheel set 123 includes a first differential wheel 1231 and a second differential wheel 1232 disposed side by side for driving the mobile device 12 to advance or retreat or turn while traveling on the ground; the front rail wheel set 122 includes a first front rail wheel 1221 and a second front rail wheel 1222 arranged side by side, the rear rail wheel set 124 includes a first rear rail wheel 1241 and a second rear rail wheel 1242 arranged side by side, and the front rail wheel set 122 and the rear rail wheel set 124 are used for driving the moving device 12 to advance or retreat on a rail arranged on a set route; a two-dimensional code reader 125 for identifying the two-dimensional code on the ground is also installed at the bottom of the mobile device 12, and is used for determining the position and direction of the mobile device 12 according to the two-dimensional code; the two-dimensional code reader 125, the first differential wheel 1231, the second differential wheel 1232, the front rail wheel set 122 and the rear rail wheel set 124 are all electrically connected with the movement control unit 112.
In this embodiment, the mobile device 12 can move on the track and road surface, and can also automatically move up and down the track. Specifically, when the mobile device 12 is traveling on the ground, the first differential wheel 1231 and the second differential wheel 1232 synchronously rotate forward or backward at the same speed, i.e., forward or backward movement of the mobile device 12 can be achieved; when the vehicle needs to turn, the first differential wheel 1231 and the second differential wheel 1232 rotate reversely, so as to drive the moving device 12 to turn.
While traveling on the track, the mobile device 12 mainly contacts the track through the front rail wheel set 122 and the rear rail wheel set 124, and controls the front rail wheel set 122 and the rear rail wheel set 124 to rotate forward or backward simultaneously through the movement control unit 112, so that the mobile device 12 can move forward or backward on the track. The track is usually arranged on a set route, so that the track can play a role in guiding the mobile device 12, the yaw of the mobile device 12 is avoided, and the autonomous navigation glass greenhouse green prevention and control robot 1 can better spray and kill according to the set route.
Meanwhile, two-dimensional codes containing position and direction information are set on the ground according to a set route, so that the mobile control unit 112 can obtain the current position and direction of the mobile device 12 by reading the two-dimensional codes through the two-dimensional code reader 125 at the bottom of the mobile device 12, and the autonomous navigation glass greenhouse green prevention and control robot 1 can position and adjust the direction of the autonomous navigation glass greenhouse green prevention and control robot 1 when the ground runs, so that the autonomous navigation glass greenhouse green prevention and control robot 1 can keep running on the set route, and the function of automatically ascending and descending the rail is realized.
For example, when the front rail wheel set 122 of the mobile device 12 just can contact the rail, the ground position corresponding to the two-dimension code reader 125 is provided with a top rail two-dimension code; when the mobile device 12 integrally moves onto the track, the ground position corresponding to the two-dimensional code reader 125 is provided with a track-up completion two-dimensional code. When the mobile device 12 moves to the front of the track and recognizes the two-dimension code of the upper track, the mobile control unit 112 starts the front track wheel set 122 and the rear track wheel set 124 to start the upper track, and when recognizing that the upper track completes the two-dimension code, the mobile control unit 112 stops the rotation of the first differential wheel 1231 and the second differential wheel 1232, and the mobile device 12 moves on the track through the front track wheel set 122 and the rear track wheel set 124 to complete the automatic upper track. It will be appreciated that the process of automatically derailing the mobile device 12 is similar to the process of automatically loading the rail, and will not be described again.
Optionally, in some embodiments, as shown in fig. 5, universal wheels 126 are disposed around the bottom of the mobile device 12, and the universal wheels 126 are used to assist the differential wheel set 123 to drive the mobile device 12 to advance or retract or turn, so as to make the movement of the mobile device 12 smoother.
Optionally, in some embodiments, the mobile device 12 further includes a camera, a lidar, and a collision bar. The lidar includes a front lidar and a rear lidar, which are mounted on the front side of the mobile device 12 for recognizing a front obstacle so as to avoid the obstacle while advancing; a rear lidar is mounted on the rear side of the mobile device 12 for identifying rear obstacles for obstacle avoidance during the backward movement; the collision bar is installed around the moving device 12, and is electrically connected to the movement control unit 112, and when the collision body collides with an object, the movement control unit 112 controls the moving device 12 to stop immediately.
Optionally, in some embodiments, the autonomous navigation glass greenhouse green prevention and control robot 1 further comprises an alarm system comprising a buzzer and an alarm lamp. When the autonomous navigation glass greenhouse green prevention and control robot 1 recognizes that diseases and insect pests or operation are in trouble (such as equipment failure, low ozone water volume/concentration, encountering obstacles and the like), the alarm system sends out different sounds through the buzzer, and the alarm lamp sends out different frequency/or different color lights to prompt a user to process. The alarm system can also be electrically connected with a remote terminal such as a mobile phone, a computer and the like, and the user is reminded of processing through a remote message.
In a second aspect, as shown in fig. 6 and fig. 7, the present invention further provides a method for spraying and killing by using the autonomous navigation glass greenhouse green prevention and control robot 1 provided in any of the above embodiments; the method of the invention also has the advantages of the autonomous navigation glass greenhouse green prevention and control robot 1 by adopting the autonomous navigation glass greenhouse green prevention and control robot 1 of the embodiment, and is not repeated here; as shown in fig. 7, the method of the present invention comprises the steps of:
step S101: setting a set route according to the planting mode of the crop plants, and controlling the moving device to move along the set route.
Before spraying, a user sets an operation route of the autonomous navigation glass greenhouse green prevention and control robot 1 according to the planting distribution condition of crop plants, inputs the operation route as a set route through the man-machine interaction unit 111 and sends the set route to the mobile control unit 112; the movement control unit 112 controls the movement of the moving device 12 along the set route.
Step S102: and in the process that the mobile device moves along the set route, acquiring the image, temperature, humidity and illumination intensity of the crop plants.
When the autonomous navigation glass greenhouse green prevention and control robot 1 moves along a set route for operation, the autonomous navigation glass greenhouse green prevention and control robot 1 continuously shoots the two sides in front through the detection sensor 121 on the mobile device 12, thereby acquiring images of crop plants on the two sides in front of the mobile device 12, and sending the crop plant images to the computing unit 114; the environmental factor detecting unit 115 also continuously detects and acquires the temperature, humidity and illumination intensity in the surrounding environment, and sends the temperature, humidity and illumination intensity to the calculating unit 114.
Step S103: judging whether plant diseases and insect pests exist according to the crop plant images, and determining the spraying amount of the ozone water and the plant positions based on the crop plant images, the temperature, the humidity and the illumination intensity.
The calculating unit 114 receives the crop plant image, recognizes whether the crop plant has a pest through the characteristics of the color, the shape, etc. of the crop plant, and if the crop plant has a pest, calculates the required ozone water spray amount of the crop plant based on the characteristics of the color, the shape, etc. of the crop plant; if no pest has occurred, predicting a possible pest by temperature, humidity and illumination intensity, and determining a required ozone water spray amount for the crop plant based on the possible pest level; the ozone water spraying amount is zero, which indicates that spraying is not needed. At the same time, the computing unit 114 determines the relative position of the crop plant and the mobile device 12 from the crop plant image, thereby determining the plant position.
Step S104: when spraying is needed, the moving device is controlled to stop according to the ozone water spraying amount and the plant position, and the spraying device is controlled to aim at the crop plants for spraying.
If the spraying amount determined by the calculating unit 114 is not zero, spraying is needed, the calculating unit 114 sends the plant position to the moving control unit 112 and the spraying control unit 113, and the moving control unit 112 controls the moving device 12 to stop near the crop plants and controls the spraying device 13 to align the crop plants; the spray control unit 113 then controls the spraying device 13 to spray the crop plants in accordance with the spray amount, thereby completing the sterilization.
After the current crop plants are sprayed and killed, the autonomous navigation glass greenhouse green prevention and control robot 1 continues to move along the set route to guide the spraying operation on the whole set route to be completed.
According to the spraying and sterilizing method, the condition of the plant diseases and insect pests is judged by acquiring the image of the plant diseases and insect pests, and the required spraying quantity is calculated based on the characteristics of the color, the form and the like of the plant diseases and insect pests, so that the waste of spraying and even damage to the plant diseases caused by excessive ozone water spraying are avoided, the poor sterilizing effect caused by insufficient ozone water spraying is also avoided, the accurate application is realized, and the sterilizing effect is improved; meanwhile, when no plant diseases and insect pests occur, the possible plant diseases and insect pests are predicted based on temperature, humidity and illumination intensity, and the ozone water spraying amount is calculated according to the prediction result, so that the crop plants are sprayed to achieve the effect of prevention, the possibility of plant diseases and insect pests of the crop plants is reduced, and the plant diseases and insect pests are prevented and controlled.
Specifically, as shown in fig. 8, step S103: judging whether plant diseases and insect pests exist according to the crop plant image, and determining the spraying amount of ozone water and the plant position based on the crop plant image, the temperature, the humidity and the illumination intensity, wherein the method comprises the following steps:
Step S1031: and comparing the crop plant image with the standard crop plant image, and judging whether the crop plant has plant diseases and insect pests.
Step S1032: when the plant diseases and insect pests exist in the crop plants, the crop plant images and the standard crop plant images are compared to determine the spraying positions, the plant disease and insect pest area and the plant disease and insect pest color change degree are calculated, and the spraying amount of the ozone water and the plant positions are determined based on the plant disease and insect pest area and the plant disease and insect pest color change degree.
Step S1033: when no crop plant diseases and insect pests are found, determining the spraying amount of the ozone water based on the disease and insect pest prediction model according to the temperature, the humidity and the illumination intensity, wherein the spraying position aims at the crop plants and the plant positions.
First, the calculation unit 114 compares the crop plant image with the standard crop plant image, and determines whether there is a pest on the crop plant by the color change condition of the crop plant and the standard crop plant.
When the plant is a pest, the calculating unit 114 further compares the image of the crop plant with the image of the standard crop plant, thereby calculating the area and the discoloration degree of the pest-caused part of the crop plant, and determining the spraying amount of the ozone water based on the pest area and the discoloration degree of the pest; at the same time, the computing unit 114 determines the relative position of the crop plant and the mobile device 12 from the crop plant image, thereby determining the plant position.
Specifically, a plurality of groups of crop plants with different pest areas and pest discoloration degrees can be selected, and the optimal ozone water spraying quantity for killing each group of crop plants is obtained according to the past pest killing cases or experiments. And according to the multiple groups of pest areas, pest discoloration degrees and the corresponding optimal ozone water spraying amounts, establishing a mapping relation among the pest areas, the pest discoloration degrees and the optimal ozone water spraying amounts through a multiple regression model, so that the calculating unit 114 calculates the ozone water spraying amounts of different pest areas and the pest discoloration degrees based on the relation.
When the plant is not yet suffering from the plant diseases and insect pests, the calculating unit 114 calculates the occurrence probability of the plant diseases and insect pests based on the plant diseases and insect pests prediction model according to the temperature, the humidity and the illumination intensity, and determines the spraying amount of the ozone water according to the occurrence probability of the plant diseases and insect pests; at the same time, the computing unit 114 determines the relative position of the crop plant and the mobile device 12 from the crop plant image, thereby determining the plant position.
Specifically, in some embodiments, at step S101: setting a set route according to a planting mode of crop plants, and before controlling the moving device to move along the set route, comprising the following steps:
A crop plant sample is selected and a standard crop plant image of the sample is obtained.
The normal crop plant sample is selected to construct a standard crop plant image, so that the crop plant image obtained in the process of the autonomous navigation glass greenhouse green prevention and control robot 1 is compared with the standard crop plant image in the follow-up operation process, whether the crop plant is subjected to pest and disease damage is judged, and the pest and disease damage area and the pest and disease damage discoloration degree are calculated.
In some embodiments, at step S101: setting a set route according to a planting mode of crop plants, and before controlling the moving device to move along the set route, comprising the following steps:
and selecting crop plant samples with different degrees of plant diseases and insect pests, and obtaining the plant disease and insect pest area, the plant disease and insect pest color change degree, the temperature, the humidity and the illumination intensity of the environment of the samples.
And building a disease and pest prediction model based on the disease and pest area, the disease and pest discoloration degree, the temperature, the humidity and the illumination intensity of the crop plant sample.
Firstly, selecting a plurality of groups of crop plant samples with different degrees of insect diseases, and measuring and calculating the insect disease area, the insect disease discoloration degree and the temperature, the humidity and the illumination intensity of the crop plant samples.
And (3) establishing the relationship between the temperature, the humidity and the illumination intensity and the plant and insect pest area and the plant and insect pest color change degree through data of a plurality of groups of crop plant samples with different degrees of plant and insect pests, thereby establishing a plant and insect pest prediction model. So that the area and the color change degree of the plant diseases and insect pests possibly occurring in the current environment can be predicted through the data of the current temperature, the humidity and the illumination intensity in the operation process of the autonomous navigation glass greenhouse green prevention and control robot 1, and the optimal spraying amount of the ozone water can be calculated based on the area and the color change degree.
Specifically, as shown in fig. 9, a disease and pest prediction model may be established based on a neural network, where temperature (X in the figure), humidity (Y in the figure), illumination intensity (Z in the figure) are used as input layers, the extent of possible disease and pest (e.g., the area of disease and the extent of discoloration of the disease and pest) are used as output layers, and a first compensation amount (Bias 1 in the figure) and a second compensation amount (Bias 2 in the figure) are added to the prediction model. Further, the optimal spraying amount of ozone water can be directly used as the output layer.
In some embodiments, the set route includes a ground section and a plurality of tracks, the tracks typically being disposed on an area where the crop plants are more concentrated and orderly arranged, such as a aisle between two rows of crop plants; the ground section is typically located between two tracks, such as at a channel corner. The autonomous navigation green-house prevention and control robot 1 can automatically go up and down the track through the moving device 12, and can perform spraying operation on the track and the ground section.
When the autonomous navigation glass greenhouse green prevention and control robot 1 operates on a ground road section, the detection sensor 121 detects and acquires images of crop plants on two sides and transmits the images to the calculation unit 114, when the calculation unit 114 determines that the crop plants need to be sprayed through the images of the crop plants, the calculation unit 114 can give corresponding instructions and position information to the mobile control unit 112 and the spraying control unit 113, the mobile control unit 112 controls the mobile device 12 to be close to the crop plants and controls the spraying device 13 to be aligned to the crop plants, so that the autonomous navigation glass greenhouse green prevention and control robot 1 can be closer to the crop plants when operating on the ground road section, particularly on a corner road section, and the spraying killing effect is better.
When the autonomous navigation glass greenhouse green prevention and control robot 1 runs on the track, the detection sensor 121 detects and acquires the images of the crop plants on two sides and transmits the images to the calculation unit 114, when the calculation unit 114 determines that the crop plants need to be sprayed through the images of the crop plants, the calculation unit 114 can give corresponding instructions and position information to the mobile control unit 112 and the spraying control unit 113, the mobile control unit 112 controls the mobile device 12 to rest on the track at the position close to the crop plants and controls the spraying device 13 to aim at the crops, so that the autonomous navigation glass greenhouse green prevention and control robot 1 does not need to transversely adjust the positions of the mobile device 12 when running on the track, and therefore the detection and the spraying of the crop plant images on two sides can be more efficiently carried out along the track.
The above-described embodiments are merely illustrative, and some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An autonomous navigation's green prevention and control robot in glass greenhouse, characterized by comprising:
control device, mobile device and sprinkler;
the spraying device is arranged on the mobile device, and a detection sensor is arranged on the mobile device; the control device includes: the system comprises a man-machine interaction unit, a mobile control unit, a spraying control unit and a calculation unit which are electrically connected with each other; the spraying control unit is electrically connected with the spraying device, and the detection sensor is electrically connected with the calculation unit;
The man-machine interaction unit is used for inputting a set route;
the mobile control unit is used for controlling the mobile device to move according to the set route;
the detection sensor is used for acquiring a crop plant image in the process that the mobile device moves along the set route;
the calculating unit is used for judging whether a plant disease and insect damage exists on a crop plant according to the crop plant image, determining the area of the plant disease and insect damage and the degree of color change of the plant disease and insect damage, determining the spraying amount of ozone water according to the area of the plant disease and insect damage and the degree of color change of the plant disease and insect damage under the condition that the plant disease and insect damage exists, and determining the position information of the plant disease and insect damage according to the crop plant image;
the mobile control unit controls the mobile device and the spraying device according to the position information, so that the spraying device is aligned to crop plants with diseases and insect pests;
the spraying control unit is used for controlling the spraying device to spray ozone water to crop plants according to the spraying quantity so as to kill plant diseases and insect pests.
2. The autonomous navigation glass greenhouse green prevention and control robot of claim 1, wherein the control device further comprises an environmental factor detection unit electrically connected to the calculation unit for acquiring a detection temperature, humidity and illumination intensity during the movement of the mobile device along the set route;
The calculation unit is further used for determining the spraying amount of the ozone water based on the disease and pest prediction model according to temperature, humidity and illumination intensity in the case that no disease and pest is found due to the existence of the latent period of the disease and pest.
3. The autonomous navigational glass greenhouse green prevention and control robot according to claim 1, wherein said spraying device comprises: the device comprises a water storage barrel, a pump, a water pipe, a bracket and a spray head;
the water storage barrel and the bracket are arranged on the mobile device; one end of the water pipe is communicated with the water storage barrel through the pump, and the other end of the water pipe is communicated with the spray head; one end of the water pipe and the spray head are arranged on the bracket, and the pump is electrically connected with the spray control unit.
4. The autonomous navigation glass greenhouse green prevention and control robot of claim 3, wherein the spraying device comprises a plurality of spray heads and at least one water pipe, one end of the water pipe is arranged on the bracket, and the spray heads are arranged at intervals along the water pipe and are communicated with the water pipe.
5. The autonomous navigation glass greenhouse green prevention and control robot of claim 3, wherein a concentration detector and a liquid level detector are arranged in the water storage barrel, the concentration detector is used for detecting the concentration of ozone water in the water storage barrel, and the liquid level detector is used for detecting the liquid level of ozone water in the water storage barrel;
The concentration detector and the liquid level detector are electrically connected with the man-machine interaction unit and the mobile control unit,
the man-machine interaction unit is used for reading and displaying the concentration and the liquid level of the ozone water in the water storage barrel;
and when the concentration of the ozone water in the water storage barrel is lower than a concentration threshold value and/or the liquid level of the ozone water is lower than a liquid level threshold value, the man-machine interaction unit displays alarm information, and the mobile control unit controls the mobile device to stop.
6. The autonomous navigation glass greenhouse green prevention and control robot according to claim 1, wherein a front rail wheel set, a differential wheel set and a rear rail wheel set are sequentially installed at the bottom of the moving device, and the differential wheel set comprises a first differential wheel and a second differential wheel which are arranged side by side and are used for driving the moving device to advance or retreat or turn when the ground is driven; the front track wheel set comprises a first front track wheel and a second front track wheel which are arranged side by side, the rear track wheel set comprises a first rear track wheel and a second rear track wheel which are arranged side by side, and the front track wheel set and the rear track wheel set are used for driving the moving device to move forwards or backwards on a track arranged on the set route;
The bottom of the mobile device is also provided with a two-dimensional code reader for identifying the two-dimensional code on the ground, and the two-dimensional code reader is used for determining the position and the direction of the mobile device according to the two-dimensional code;
the two-dimensional code reader, the first differential wheel, the second differential wheel, the front track wheel set and the rear track wheel set are all electrically connected with the mobile control unit.
7. A method of spray disinfection using the autonomous navigational glass greenhouse green prevention and control robot of any one of claims 1-6 comprising:
setting a set route according to a planting mode of crop plants, and controlling the moving device to move along the set route;
acquiring images, temperature, humidity and illumination intensity of crop plants in the process that the mobile device moves along a set route;
judging whether plant diseases and insect pests exist according to the crop plant images, and determining the spraying amount of ozone water and the plant position based on the crop plant images, the temperature, the humidity and the illumination intensity;
when spraying is needed, the moving device is controlled to stop, and the spraying device is controlled to aim at the crop plants for spraying according to the ozone water spraying amount.
8. The method for spraying and sterilizing a self-contained navigation glass greenhouse green prevention and control robot according to claim 7, wherein the step of judging whether there is a pest and disease damage according to the crop plant image and determining the spraying amount of ozone water and the plant position based on the crop plant image and the temperature, humidity and illumination intensity comprises the steps of:
Comparing the crop plant image with the standard crop plant image, and judging whether plant diseases and insect pests exist on the crop plant;
when the plant diseases and insect pests exist in the crop plants, comparing the crop plant images with the standard crop plant images to determine spraying positions, determining the area of the plant diseases and insect pests and the color change degree of the plant diseases, and determining the spraying amount of ozone water and the plant positions based on the area of the plant diseases and insect pests and the color change degree of the plant diseases;
when no crop plant diseases and insect pests are found, the spraying amount of the ozone water and the plant position are determined based on the disease and insect pest prediction model according to the temperature, the humidity and the illumination intensity.
9. The method for spraying and sterilizing a self-contained navigation glass greenhouse green protection robot according to claim 8, wherein before the step of setting a set route according to the planting mode of the crop plants and controlling the mobile device to move along the set route, the method comprises:
a crop plant sample is selected and a standard crop plant image of the sample is obtained.
10. The method for spraying and sterilizing a self-contained navigation glass greenhouse green protection robot according to claim 8, wherein before the step of setting a set route according to the planting mode of the crop plants and controlling the mobile device to move along the set route, the method comprises:
Selecting crop plant samples with different degrees of plant diseases and insect pests, and obtaining the plant disease and insect pest area, the plant disease and insect pest color change degree, the temperature, the humidity and the illumination intensity of the environment of the samples;
and building a disease and pest prediction model based on the disease and pest area, the disease and pest discoloration degree, the temperature, the humidity and the illumination intensity of the crop plant sample.
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| CN119014255A (en) * | 2024-10-09 | 2024-11-26 | 青海大学 | Green control methods for tomato leafminer |
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| 李增智: "食品安全的理论与实践", 31 December 2005, 合肥工业大学出版社, pages: 192 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119014255A (en) * | 2024-10-09 | 2024-11-26 | 青海大学 | Green control methods for tomato leafminer |
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