By Angie Peltier and Ryan Miller, UMN Extension crops educators, Ryan Huffman, Iowa State University Digital Ag Innovation Lab senior research manager and Jorden Kuntz, founder of Biosphere Drone Solutions
On March 19, 2025, Ryan Huffman, Iowa State University Digital Ag Innovation Lab senior research manager and Jorden Kuntz, founder of Biosphere Drone Solutions, joined UMN Extension crops educator Ryan Miller for a discussion about drones in row crop agriculture. This was the penultimate weekly episode of the 2025 Strategic Farming: Let’s talk crops! webinars.
To watch this episode: http://z.umn.edu/StrategicFarmingRecordings
Near-infrared light (750-1,000 nm wavelength) can provide an additional information above and beyond visible wavelengths. Normalized difference vegetation index (NDVI) is a plant health index related to near-infrared wavelengths and an example of the type of high-resolution data that can be collected by drone. NDVI data can be used to inform management decisions in-season such as whether to replant sections of a field with subpar plant stands or making a fungicide application to deal with a ground-truthed disease problem. Drones can reduce the amount of time that humans need to effectively scout whole fields, making it so that a smaller number of managers can effectively manage ever increasing acreage. Weed mapping is also something that an imagery drone can accomplish. Something as simple as a map of residue spread by a combine can help to explain the patterns in growth and development of the following crop.
Spray drones can be easily adjusted by application rate, droplet size (and canopy penetration), application speed, boom height and swath width.
When spray drones were first developed, they were designed to mimic ground-based spray rigs, which use pressurized liquid that is expelled from a nozzle. With ground-based spray rigs, the more carrier volume (gallons per acre), the better the spray coverage. Drones use ‘prop wash’ or the down pressure caused by propeller-mediated air movement to deposit droplets down and into the crop canopy. Drones nozzles and spinner-type spreaders are typically located directly below propellers. Droplet size is adjusted by the speed that the spinner spreader rotates, with the spinner essentially ‘slicing’ larger droplets into smaller droplets and faster spin speeds leading to smaller droplets.
Jorden Kuntz’s team is busy comparing coverage and yield impacts of using drone versus ground-based spray rigs. Despite using ~1/10th of the carrier volume of a ground-based rig, results of pesticide applications using drones are similar.
Kuntz sees a disconnect between drone-based sprayers and precision sprayers (ala See-and-Spray technology), theorizing that drones are unlikely to have similar capabilities in the near term. Precision sprayers are designed to identify weeds in need of spraying and in a split second deliver a very targeted application over a very small area, while spray drones have been optimized to cover the largest swaths as possible – strategies at loggerheads with one another. Drones have also been designed to compensate for environmental conditions not encountered by ground-based spray rigs -such as cross winds- which can make it so that the sort of precision that exists with precision sprayers may not be achievable via drone.
A: For a drone, batteries and chargers it would cost a minimum of $35,000, it costs ~$40,000 for a trailer set up to haul and service the drone and $2,000 for a generator for charging the drone’s batteries for a total of $80-85,000 for a single spray drone. Commercial drone operators with 3 drones minimum will end up spending ~$150,000.
Q: What about the cost of an imagery drone?
A: One can be purchased for less than $5,000 plus the costs associated with the software needed to stitch all of the images collected by the drone together into a cohesive field-scale picture. At-home software cost is in the hundreds of dollars but one needs robust enough computer processing capacity to do the job. For those that aren’t as tech savvy, there are services that can be hired to stitch together these drone-gathered images that cost $1,000 or more. Whether one does the processing on their own or hires it out will largely depend upon one’s comfort level with this sort of technology.
One strategy to consider would be to start by hiring someone to process your imagery while working to build your own capacity to process imagery, comparing the images that you have stitched together to those produced by experts to see how well you did.
Q: Because NDVI map images very closely mimic yield map images, what decisions can be made using the NDVI that would be too late to implement using a yield map?
A: NDVI images are essentially a roadmap pointing a farmer to those areas of a given field to investigate further (ground truth) in-season. This can help farmers to save time and to potentially mitigate problems (nutrient deficiencies, disease pressure, etc) in-season.
Q: Does one truly need these special visual filters for their drone to generate NDVI or can a RGB filter provide enough information to be of use?
A: RGB filters can be used to generate a “VARI map” that doesn’t require the use of an infrared filter/band. These maps are similar in nature to an NDVI but may have more limited resolution and scale. RGB filters are fine for a ‘quick and dirty’ look at general plant health, but more precise and actionable insights will likely require NDVI.
Q: What does someone interested in adopting this technology need to be concerned about as far as licensing and liability?
A: To fly a drone for commercial use either as a for-hire service or to produce a crop that you plan to sell, one first needs to obtain a 107 license or a commercial drone operators license issued by the Federal Aviation Administration (FAA). Testing to obtain this license can be done at one of the FAA testing center locations. There are study materials on the FAA website and this training helps one to learn how to read aeronautical maps, learn how airports operate and how to communicate with airport control towers to avoid collisions with other aircraft. Drones also need to be registered by the FAA.
Rules and regulations regarding using a drone to apply pesticides will vary by state and so the best bet would be for someone to contact their state’s department of agriculture. Private pesticide applicators in Minnesota will need to obtain the FAA-issued license and a separate endorsement on their private applicators license to spray using a drone. There is also a medical exam required of drone operators seeking to obtain their FAA license – this requirement is a holdover from medical exams required of pilots of manned aircraft.
Q: Is there risk involved in using drones that are not made in the US?
A: DJI drones are made in China and there has been a lot of attention paid to national and data security concerns with Chinese-made drones. There have been various pieces of legislation proposed to ground all Chinese-made drones, but all proposed legislation has grandfathered in those drones already present in the US.
Q: What type of file do the multi-spectral images come in and what software do you typically use for analysis?
A: The images are in a JPG format. Because Jorden’s company sells DJI drones, he pointed out that DJI has built in software through their online smart farm series. One needs to develop a separate map for the data gathered by each sensor. The ISU team has used Pix4D and DroneDeploy commercial software and ESRI open source software to stitch together drone images into a field map.
Q: Do you have experience seeding cover crops via drone?
A: Jorden’s company seeded 8,300 acres of cover crops in Dubuque County, IA in fall 2024 under an NRCS-funded program, making applications between August 10 and October 10. They were impressed by how well the drones worked to spread seed. UMN Extension personnel have hired drone operators to spread cover crops seed in growers fields for randomized replicated strip trial research. This was required to accurately seed cover crops into standing corn which is impractical using a crop dusting plane.
Q: What is the typical dry payload of a spray drone hopper?
A: DJI T-50 drone (the largest model that DJI makes) can carry up to 125 lbs, enough to seed approximately 3 acres of cover crops seed at NRCS-approved seeding rates flying 14-15 feet above the crop with 24-25 ft swath width.
Q: How well can drone imagery alert one to insect feeding injury that is scattered throughout the canopy? Can one use this imagery for N-content sensing?
A: With today’s technology it is difficult to determine where in the canopy any feeding injury is occurring. Using RGB filters one can use green pixels as a proxy for how much green biomass is present in the field. If one begins to see a decline in the amount of green biomass over time, one could safely assume that there is something feeding on the biomass – ground-truthing would be required to determine whether there is a pest or disease issue as management strategies will change according to the organism causing the decline. As for N-content sensing, machine-learning models have been developed and trained to be ~80% accurate compared to ground-truthed tissue testing for nutrient deficiencies. Continued research and development is needed but field scale N-content sensing is not far off from growers leveraging this layer of information.
Q: Do you have any experience with applying contact herbicides (where coverage is key!) with a spray drone?
A: There are liability concerns related to herbicide application by drone and it is important to consult your preferred herbicide’s label to determine whether aerial application is allowed. EPA approves these labels and so has taken the time to balance risks/rewards with aerial applications for each active ingredient.
Thanks to the Minnesota Soybean Research & Promotion Council and the Minnesota Corn Research & Promotion Council for their generous support of this program!
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| Showcasing drones at a field day in northwest Iowa, 2024. Credit: Ryan Huffman. |
To watch this episode: http://z.umn.edu/StrategicFarmingRecordings
ISU Digital Ag Innovation Lab
Working as agriculture researchers at a public university typically results in publications in a peer-reviewed journals, where the over-arching goal is to ‘move the ball further down the field’ in the quest for better understanding of the biological systems in which we work. What makes the ISU Digital Innovation Lab unique is that it is focused on creating successful partnerships between ISU researchers/innovators working to develop products and companies in the agriculture sector capable of taking technological innovations to market and working to serve their clientele.Imagery drones
Drones can provide information that we hadn’t had until quite recently by providing a ‘bird’s eye view’ of the crop. Imagery drones use sensors to visualize different wavelengths of light that are reflected to the sensor from the crop. This visualization can provide information regarding general health of the crop by comparing reflected wavelengths from healthy crops to those from crops experiencing some form of stress.Near-infrared light (750-1,000 nm wavelength) can provide an additional information above and beyond visible wavelengths. Normalized difference vegetation index (NDVI) is a plant health index related to near-infrared wavelengths and an example of the type of high-resolution data that can be collected by drone. NDVI data can be used to inform management decisions in-season such as whether to replant sections of a field with subpar plant stands or making a fungicide application to deal with a ground-truthed disease problem. Drones can reduce the amount of time that humans need to effectively scout whole fields, making it so that a smaller number of managers can effectively manage ever increasing acreage. Weed mapping is also something that an imagery drone can accomplish. Something as simple as a map of residue spread by a combine can help to explain the patterns in growth and development of the following crop.
Spray drones
Drones designed for spraying crop protection chemicals can provide a bit more flexibility in-season than either a traditional ground-based or aerial spray rig. Drones can be used in fields with water-saturated soil and at the time and place of the farmer’s choosing and not according to schedules dictated by custom applicators. Drones also allow for precision spot spraying of areas that cannot be accessed by crop dusting airplanes, including near power, tree and power lines. Spray drones can also be fitted with hoppers to spread dry materials like cover crop seed.Spray drones can be easily adjusted by application rate, droplet size (and canopy penetration), application speed, boom height and swath width.
When spray drones were first developed, they were designed to mimic ground-based spray rigs, which use pressurized liquid that is expelled from a nozzle. With ground-based spray rigs, the more carrier volume (gallons per acre), the better the spray coverage. Drones use ‘prop wash’ or the down pressure caused by propeller-mediated air movement to deposit droplets down and into the crop canopy. Drones nozzles and spinner-type spreaders are typically located directly below propellers. Droplet size is adjusted by the speed that the spinner spreader rotates, with the spinner essentially ‘slicing’ larger droplets into smaller droplets and faster spin speeds leading to smaller droplets.
Jorden Kuntz’s team is busy comparing coverage and yield impacts of using drone versus ground-based spray rigs. Despite using ~1/10th of the carrier volume of a ground-based rig, results of pesticide applications using drones are similar.
Kuntz sees a disconnect between drone-based sprayers and precision sprayers (ala See-and-Spray technology), theorizing that drones are unlikely to have similar capabilities in the near term. Precision sprayers are designed to identify weeds in need of spraying and in a split second deliver a very targeted application over a very small area, while spray drones have been optimized to cover the largest swaths as possible – strategies at loggerheads with one another. Drones have also been designed to compensate for environmental conditions not encountered by ground-based spray rigs -such as cross winds- which can make it so that the sort of precision that exists with precision sprayers may not be achievable via drone.
FAQs
Q: What does it cost to purchase a multi-purpose spray drone?A: For a drone, batteries and chargers it would cost a minimum of $35,000, it costs ~$40,000 for a trailer set up to haul and service the drone and $2,000 for a generator for charging the drone’s batteries for a total of $80-85,000 for a single spray drone. Commercial drone operators with 3 drones minimum will end up spending ~$150,000.
Q: What about the cost of an imagery drone?
A: One can be purchased for less than $5,000 plus the costs associated with the software needed to stitch all of the images collected by the drone together into a cohesive field-scale picture. At-home software cost is in the hundreds of dollars but one needs robust enough computer processing capacity to do the job. For those that aren’t as tech savvy, there are services that can be hired to stitch together these drone-gathered images that cost $1,000 or more. Whether one does the processing on their own or hires it out will largely depend upon one’s comfort level with this sort of technology.
One strategy to consider would be to start by hiring someone to process your imagery while working to build your own capacity to process imagery, comparing the images that you have stitched together to those produced by experts to see how well you did.
Q: Because NDVI map images very closely mimic yield map images, what decisions can be made using the NDVI that would be too late to implement using a yield map?
A: NDVI images are essentially a roadmap pointing a farmer to those areas of a given field to investigate further (ground truth) in-season. This can help farmers to save time and to potentially mitigate problems (nutrient deficiencies, disease pressure, etc) in-season.
Q: Does one truly need these special visual filters for their drone to generate NDVI or can a RGB filter provide enough information to be of use?
A: RGB filters can be used to generate a “VARI map” that doesn’t require the use of an infrared filter/band. These maps are similar in nature to an NDVI but may have more limited resolution and scale. RGB filters are fine for a ‘quick and dirty’ look at general plant health, but more precise and actionable insights will likely require NDVI.
Q: What does someone interested in adopting this technology need to be concerned about as far as licensing and liability?
A: To fly a drone for commercial use either as a for-hire service or to produce a crop that you plan to sell, one first needs to obtain a 107 license or a commercial drone operators license issued by the Federal Aviation Administration (FAA). Testing to obtain this license can be done at one of the FAA testing center locations. There are study materials on the FAA website and this training helps one to learn how to read aeronautical maps, learn how airports operate and how to communicate with airport control towers to avoid collisions with other aircraft. Drones also need to be registered by the FAA.
Rules and regulations regarding using a drone to apply pesticides will vary by state and so the best bet would be for someone to contact their state’s department of agriculture. Private pesticide applicators in Minnesota will need to obtain the FAA-issued license and a separate endorsement on their private applicators license to spray using a drone. There is also a medical exam required of drone operators seeking to obtain their FAA license – this requirement is a holdover from medical exams required of pilots of manned aircraft.
Q: Is there risk involved in using drones that are not made in the US?
A: DJI drones are made in China and there has been a lot of attention paid to national and data security concerns with Chinese-made drones. There have been various pieces of legislation proposed to ground all Chinese-made drones, but all proposed legislation has grandfathered in those drones already present in the US.
Q: What type of file do the multi-spectral images come in and what software do you typically use for analysis?
A: The images are in a JPG format. Because Jorden’s company sells DJI drones, he pointed out that DJI has built in software through their online smart farm series. One needs to develop a separate map for the data gathered by each sensor. The ISU team has used Pix4D and DroneDeploy commercial software and ESRI open source software to stitch together drone images into a field map.
Q: Do you have experience seeding cover crops via drone?
A: Jorden’s company seeded 8,300 acres of cover crops in Dubuque County, IA in fall 2024 under an NRCS-funded program, making applications between August 10 and October 10. They were impressed by how well the drones worked to spread seed. UMN Extension personnel have hired drone operators to spread cover crops seed in growers fields for randomized replicated strip trial research. This was required to accurately seed cover crops into standing corn which is impractical using a crop dusting plane.
Q: What is the typical dry payload of a spray drone hopper?
A: DJI T-50 drone (the largest model that DJI makes) can carry up to 125 lbs, enough to seed approximately 3 acres of cover crops seed at NRCS-approved seeding rates flying 14-15 feet above the crop with 24-25 ft swath width.
Q: How well can drone imagery alert one to insect feeding injury that is scattered throughout the canopy? Can one use this imagery for N-content sensing?
A: With today’s technology it is difficult to determine where in the canopy any feeding injury is occurring. Using RGB filters one can use green pixels as a proxy for how much green biomass is present in the field. If one begins to see a decline in the amount of green biomass over time, one could safely assume that there is something feeding on the biomass – ground-truthing would be required to determine whether there is a pest or disease issue as management strategies will change according to the organism causing the decline. As for N-content sensing, machine-learning models have been developed and trained to be ~80% accurate compared to ground-truthed tissue testing for nutrient deficiencies. Continued research and development is needed but field scale N-content sensing is not far off from growers leveraging this layer of information.
Q: Do you have any experience with applying contact herbicides (where coverage is key!) with a spray drone?
A: There are liability concerns related to herbicide application by drone and it is important to consult your preferred herbicide’s label to determine whether aerial application is allowed. EPA approves these labels and so has taken the time to balance risks/rewards with aerial applications for each active ingredient.
Thanks to the Minnesota Soybean Research & Promotion Council and the Minnesota Corn Research & Promotion Council for their generous support of this program!
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