US-12619215-B2 - Systems and methods for real-time measurement and control of sprayed liquid coverage on plant surfaces

Abstract

Presented herein are systems and methods for automatically determining liquid coverage on plant surfaces. More particularly, in certain embodiments, presented herein is a system for receiving an image depicting one or more plant surfaces, automatically identifying the plant surfaces in the image and distinguishing portions covered by liquid, and automatically determining a liquid coverage value. In some embodiments, the system determines changes to liquid spraying parameters to achieve desired liquid coverage values. In some embodiments, the system uses two cameras to cooperatively conduct background removal in images and determination of liquid coverage.

Inventors

• Vishnu Jayaprakash
• Kripa Kiran Varanasi

Assignees

• AgZen Inc.

Dates

Publication Date

20260505

Application Date

20240130

Claims (20)

1. 1 . A system for automatically quantifying liquid coverage on plant surfaces, the system comprising: a processor of a computing device; and a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to: receive an image comprising a region of interest corresponding to one or more plant surfaces; automatically identify one or more portions of the region of interest corresponding to liquid; and use (i) one or more pre-spray images corresponding to a field of view comprising the one or more plant surfaces prior to spraying with a liquid and (ii) one or more post-spray images corresponding to the field of view comprising the one or more plant surfaces after spraying with the liquid to automatically identify a liquid coverage value for the plant surfaces by: (i) removing background pixels in the one or more pre-spray images so that leaves remain; (ii) removing background pixels in the one or more post-spray images so that leaves remain; and (iii) calculating the liquid coverage value based on pixels corresponding to leaves and sprayed liquid in the one or more pre-spray images and the one or more post-spray images.
2. 2 . The system of claim 1 , further comprising one or more imaging devices and/or sensors for obtaining the image, wherein the one or more imaging devices and/or sensors comprises at least one member of the group consisting of a camera, a digital camera, a camera phone, a thermal imaging device, a night vision camera, a Light Detection and Ranging (LiDAR) device, an electronic image sensor, a charge-coupled device (CCD), an active-pixel sensor (CMOS sensor), a smart image sensor, an intelligent image sensor, and a short-wave infrared (SWIR) camera.
3. 3 . The system of claim 2 , wherein the liquid on the plant surfaces comprises a sprayed-on liquid, wherein the one or more imaging devices and/or sensors comprises the short-wave infrared (SWIR) camera, and wherein sufficient detectable contrast is achieved for accurate liquid coverage value determination without the need for any dyes to be added to the sprayed-on liquid.
4. 4 . The system of claim 1 , further comprising a first camera for receiving a first image corresponding to a field of view comprising the one or more plant surfaces and a second camera for receiving a second image corresponding to the field of view of the first image, wherein the instructions, when executed by the processor, cause the processor to automatically identify a background mask from the first image, said background mask corresponding to non-plant-surface portions of the first image, to apply the background mask to the second image, thereby eliminating non-plant surface portions from the second image, and to automatically identify the liquid coverage value for the plant surfaces depicted in the background-eliminated second image.
5. 5 . The system of claim 4 , wherein the first camera is a red-green-blue (RGB) camera and the second camera is a shortwave infrared (SWIR) camera.
6. 6 . The system of claim 5 , comprising an optical element that reflects infrared (IR) light and allows visible light to pass, said optical element positioned to allow alignment of fields of view of the first camera and the second camera.
7. 7 . The system of claim 1 , wherein the instructions, when executed by the processor, cause the processor to automatically determine a series of liquid coverage values for regions in a sequence of images in real time, as the sequence of images is obtained.
8. 8 . The system of claim 1 , the system further comprising: a display comprising a display screen and a graphical user interface (GUI), wherein the instructions cause the processor to graphically render the liquid coverage value for viewing by a person via the display.
9. 9 . The system of claim 1 , wherein the instructions, when executed by the processor, cause the processor to use the determined liquid coverage value or values to automatically determine an adjustment of one or more sprayer system parameters to achieve a desired level of liquid coverage, wherein the one or more sprayer system parameters comprises at least one member selected from the group consisting of a sprayer speed, a nozzle type, a nozzle positioning and/or orientation, a number of nozzles used, a spray pressure, an adjuvant and/or additive rate, an overall flow rate, and a boom orientation and/or height.
10. 10 . The system of claim 9 , wherein the system comprises one or more environmental sensors for capturing environmental data corresponding to one or more environmental conditions at a location and at a time the image(s) is/are obtained, and wherein the instructions, when executed by the processor, cause the processor to use the environmental data along with the identified liquid coverage value or values to automatically determine the adjustment of the one or more sprayer system parameters, wherein the one or more environmental sensors comprises one or more sensors selected from the group consisting of a temperature sensor, a humidity sensor, a pressure sensor, a wind sensor, a light sensor, an air quality sensor, a gas sensor, a rainfall sensor, a radiation sensor, and a soil sensor.
11. 11 . The system of claim 9 , wherein the instructions, when executed by the processor, cause the processor to automatically determine a series of liquid coverage values for regions of interest in a sequence of images and use the automatically determined values to automatically determine the adjustment of the one or more sprayer system parameters to achieve the desired level of liquid coverage, wherein the instructions cause the processor to automatically implement the determined adjustment(s) in real time via a control system for controlling the one or more sprayer system parameters, thereby operating the sprayer system in real time to improve liquid coverage by accounting for one or more changing conditions.
12. 12 . The system of claim 1 , wherein the liquid coverage value quantifies a total liquid volume on the depicted in the region of interest.
13. 13 . The system of claim 1 , wherein the liquid coverage value quantifies a total liquid volume per unit area of the plant surfaces depicted in the region of interest.
14. 14 . The system of claim 1 , wherein the liquid coverage value quantifies an absolute or relative surface area of the plant surfaces depicted in the region of interest that is covered by liquid.
15. 15 . The system of claim 1 , wherein the system is mounted to a spraying mechanism.
16. 16 . The system of claim 15 , wherein the spraying mechanism comprises at least one of a plow and an agricultural sprayer.
17. 17 . The system of claim 16 , comprising the agricultural sprayer, wherein the agricultural sprayer comprises a boom sprayer, a boomless sprayer nozzle, a mist sprayer, a three-point hitch sprayer, a truck-bed sprayer, a towing-hitch sprayer, a Utility Task Vehicle (UTV) sprayer, an All-Terrain Vehicle (ATV) sprayer, a self-propelled sprayer, a towed sprayer, a robotic sprayer, a hand sprayer, or a backpack sprayer.
18. 18 . The system of claim 16 , wherein the computing device is implemented as a portable device mounted on the spraying mechanism.
19. 19 . The system of claim 1 , wherein the system is mounted to a drone.
20. 20 . The system of claim 19 , wherein the drone comprises an unmanned aerial vehicle.

Description

CROSS REFERENCE TO RELATED APPLICATIONS This application is a continuation of U.S. patent application Ser. No. 18/118,989, filed Mar. 8, 2023, which claims benefit of U.S. Provisional Patent Application No. 63/342,034, filed May 13, 2022, and U.S. Provisional Patent Application No. 63/448,166, filed Feb. 24, 2023, and which is a continuation-in-part of U.S. patent application Ser. No. 17/982,866, filed Nov. 8, 2022, which claims the benefit of U.S. Provisional Patent Application No. 63/342,034, filed May 13, 2022. The disclosures of each of the above-referenced applications are incorporated by reference herein in their entireties. FIELD This invention relates generally to agricultural systems and methods. More particularly, in certain embodiments, the invention relates to systems and methods for real-time measurement and control of liquid coverage on plant surfaces. BACKGROUND Pesticide pollution is linked to acute illnesses such as cancer, neurological conditions, and birth defects. Furthermore, excess pesticides adversely affect soil chemistry and cause the death of non-target organisms, damaging soil microbiomes responsible for replenishing plant nutrients. Moreover, pesticides represent a major financial burden for farmers, for example, making up about 30% of the total production costs for crops such as cotton. Thus, it is important to improve the efficiency of pesticide application to reduce the amount of pesticide used while achieving efficacious pest control. Agrochemicals such as pesticides, foliar fertilizer, and nutrient formulations are usually applied to plants in liquid solutions using pressure-controlled spray systems. Foliar solutions (foliar fertilizers) and pesticide solutions are applied directly to the surface of plants (e.g., a surface of a leaf, a surface of a root, a surface of a fruit, a surface of a vegetable, or a surface of a flower of the plant) as opposed to being put in the soil. In such agrochemical spray systems, pressurized pesticide solutions and/or foliar solutions are forced through nozzles at specific flow rates to achieve spray patterns that cover leaves or other plant surfaces with a significant number of droplets. For pesticide sprays to be efficacious in controlling pests and for foliar solutions to be efficacious as fertilizer, it is critical to achieve a high degree of liquid coverage (e.g., droplets, films, and/or pools of liquid) and liquid retention on target plant surfaces. In order to maximize the efficiency of agrochemical sprays and achieve adequate liquid coverage, there are several parameters that operators can control and optimize. These parameters include the speed at which the sprayer moves through the field, the operational pressure of the spray system, the nozzle design (which impacts both the spray pattern and the droplet size distribution), the nozzle position relative to both the target plant surface and other nozzles, and the chemistry of the applied product. Each of these parameters can have a significant impact on spray characteristics, which can in turn influence pest outcomes and crop yield. While spray applicators are tasked with carefully optimizing these interdependent parameters to achieve optimal pest control, there is a lack of technology that can estimate the effectiveness of a given spray application directly in real time. For example, farmers lack effective tools that can quantify liquid coverage on plant surfaces. Without such tools, farmers are forced to run season-long or year-long experiments to determine whether a certain set of parameters can lead to efficient pest control and the desired yield. The inability to monitor liquid coverage directly on crops also reduces the efficiency of spray applications under changing environmental and crop conditions. For example, a certain set of parameters that results in optimal liquid coverage when wind speeds are negligible could be much less efficient when on-field wind speeds increase to as little as 2-3 mph. In addition to making pesticide and foliar fertilizer spraying more efficient, the ability to monitor liquid coverage directly on plants could have broader implications on pesticide and foliar fertilizer use in general. For example, currently, farms are advised to apply pesticides at a specific rate per acre as specified by the pesticide label. These rates are determined by field testing of pesticides under standard conditions in small acreage plots. However, a recommended application rate per acre does not account for variability in application efficiency on plants or the impact of variations in environmental and crop conditions on different fields. The ability to monitor coverage on leaves and other plant surfaces could allow farms to move away from application rates per acre and move towards more relevant metrics such as application rates for a given area of the target plant surface, e.g., the leaf area. There is a need for spraying technology that improves agrochemical application