Unmanned Aerial Vehicles

Corn, Soybean and Wheat


Corn, Soybean and Wheat

UAV Benefits

  • Quickly fly your field, collecting pictures and video throughout the growing season
  • Increase efficiency and reduce risks of missing a potential problem
  • Map your entire field with stitching software to generate data associated with specific geographic coordinates
  • Further investigate areas of concern after stitching an image of your field
  • Higher-precision nutrient application through the creation of a field prescription
  • Visualize changes in the field you may not otherwise see from the ground

UAV Challenges

Clouds: Broken skies can ruin image quality.

  • Tip: Fly when skies are fully overcast or clear for optimal image quality.

Air traffic: Low-flying aircraft can threaten commercial UAV operations.

  • Tip: Watch for helicopters or crop dusters – the most common aircraft.

Camera settings: Incorrect settings can affect image quality.

  • Tip: It takes a little experience. Familiarize yourself with general camera settings and know the goals of each particular flight.

Examples

Improved algorithms for corn stand assessment

Flown by John Scott, Digital Agriculture Extension Coordinator, Purdue Extension

Three plant health maps were compared alongside RGB to determine if additional sensors would result in a complete map for better decision making. While the NDVI appears to showcase the most detail, we still need to conduct more research and ground-truthing. We will continue exploring different plant health indices to see how each tool fits into management strategies.

Stand Count

Plant health mapping comparison

Flown by Adam Shanks, Agriculture & Natural Resources Educator, Purdue Extension - Clinton County

Three plant health maps were compared alongside RGB to determine if additional sensors would result in a complete map for better decision making. While the NDVI appears to showcase the most detail, we still need to conduct more research and ground-truthing. We will continue exploring different plant health indices to see how each tool fits into management strategies.

INFIELDRGB_Corn

RGB: A truecolor image using red, green and blue wavelengths. It is an affordable option and the most accessible sensor for producers. RGB images are similar to what can be seen by the human eye, making data easy to interpret.

INFIELDVARI_Corn

VARI: Visible Atmospherically Resistant Index (VARI) is designed to work with RGB sensors to identify crop stress and generate variable rate prescriptions.

INFIELDNDVI_Corn

NDVI: Normalized Difference Vegetation Index (NDVI) uses a combination of visual red light and near-infrared (NIR) light and is a trusted indicator of plant health. It correlates with chlorophyll, and plants reflect more green light when they are healthy.

INFIELDNDRE_Corn

NDRE: Normalized Difference Red Edge (NDRE) is similar to NDVI but uses a combination of NIR light and a frequency band called Red Edge. It can be a valuable index when monitoring health of mature plants because the red edge band can measure further down into the canopy.

Sprayer drone demonstration

Flown by Alex Helms, Southeast Purdue Agriculture Center

This DJI Agras spray drone is designed for precision variable rate application of liquid pesticides, fertilizers and herbicides as well as an attachment to spread dry treatments. The spraying system automatically adjusts its speed according to the flight for an even application. It is 40 to 60 times faster than manual spraying, bringing a new level of efficiency to agricultural operations.

Purdue Extension and the Purdue Agriculture Center (PACs) jointly purchased this intelligent spraying system in 2019.

Weed suppression

Flown mid-July to mid-August 2018 by Ashley Adair, Purdue Extension Organic Agriculture Specialist

A non-chemical weed suppression technique using electricity to boil water in plant cells causes them to rupture when contacted by this tractor device. This video can be used in Extension outreach to showcase a weed management technique.

Flame weeding demonstration

Flown by Ashley Adair, Purdue Extension Organic Agriculture Specialist

Flame weeding is a practice that organic farmers can use to control grass and broadleaf weeds in corn. In this case, corn was flame-weeded around growth stage V6. Multiple passes through the field were needed due to a number of factors, including calibration of equipment and rain. Each burner can produce somewhere between 500,000 and 1,000,000 BTUs. Flame weeding may look scary at first, but corn plants recover and still produce marketable grain.

Green snap damage in corn

Flown by Andrew Westfall, Agriculture & Natural Resources Educator, Purdue Extension – White County

A severe storm passed through White County, Ind. in July 2020, causing wind and hail damage to corn. UAV images were used to compare with a crop insurance assessment to evaluate crop loss.

Taken July 28, 2020 -- 18 days after the sever storm.
Taken July 28, 2020 -- 18 days after the sever storm.
Stitched aerial image from August 13, 2020.
Stitched aerial image from August 13, 2020.
Plant health image collected on August 13, 2020.
Plant health image collected on August 13, 2020.

Images of the field were collected on July 28, August 13 and September 8 of 2020. The farmer planted a different variety approximately halfway through the field, and they found the variety more susceptible to wind damage was used on the border rows. Note: The northern panhandle portion of the field was protected by a windbreak and buildings.

Using the "plant health" map feature in Drone Deploy, they determined that approximately ten acres (+/- two acres) were severely damaged by wind. Mid-August seemed to provide the most accurate assessment and hybrid selection played a large role in withstanding high winds.

VARI_Histogram_8-13

Cercospora leaf blight in soybeans

Flown by Adam Shanks, Agriculture & Natural Resources Educator, Purdue Extension – Clinton County

Premature leaf drop triggered the detection of the fungus Cercospora kikuchii which attacks both leaves and seeds of soybeans. The field was flown to see the widespread impact, and the diseased areas were quantified. The disease pattern (in blue) raised questions regarding soil type and influence on the diseased areas. A soil map was layered (in orange) with the annotated UAV map to observe variation, but it appeared independent of the soil type.

Cercospora_raw
Cercospora_Annotation
Cercospora_All

Tar spot in corn

Flown by Crystal Van Pelt, Agriculture & Natural Resources Educator, Purdue Extension – Steuben County

Tar spot was discovered at a Purdue irrigation research plot and monitored by Darcy Telenko, Extension plant pathology specialist, and Lyndon Kelly, Extension irrigation specialist from August through October. The plot was flown mid-October to observe disease impact. Plants not under the pivot irrigation system were decimated while the plants under the system were severely damaged. Collecting data earlier in the season and over more fields will help in future years to help us understand the disease progression.

Highlighter green soybeans and field management

Flown by Jon Charlesworth, Agriculture & Natural Resources Educator, Purdue Extension – Benton/Warren County

A Warren County farmer was interested in understanding differences between tillage, other field operations, cover crop and fertilizer amendments using crop health maps. Below are the stitched RGB and NDVI (crop health) maps of the field taken around stage R3. Like many soybean fields in Warren County, the plants had suffered through an extremely wet June and early July. Many of the plants were yellow and stunted.

It was obvious from the patterns in these maps that soybeans directly over drainage tile lines were healthier than plants in between tile lines. There is a definite demarcation line located about two-thirds of the way through the field when moving from North to South. The general health of the soybeans in the southern one-third of the field is considerably better than in the northern two-thirds of the field. The maps were shared with the producer and follow-up occurred after harvest to discuss the value of the imagery.

RGB
WarrenRGB
NDVI
WarrenNDVI

Comparing plant health in different corn hybrids

Flown by John Scott, Digital Agriculture Extension Coordinator, Purdue Extension

The red streak in the middle of this field near the Ivy Tech Community College site in Lafayette indicates a problem with a certain hybrid. This indicates a need for further investigation on the ground.

GLS Plant Health

A closer view shows a clear difference in plant health between the problem hybrid (left) and the healthy hybrid (right).

GLS still

Because a problem was detected from the air, an in-field observation led to the discovery of grey leaf spot (GLS) in the problem hybrid, which is a fungal disease.

GLS Look down a row

Ear size was similar between hybrids but those with GLS were much closer to physiological maturity. The seed fill window was reduced, which may later result in lower yields.

GL Sears

Fixed-wing trial

Flown Mark Carter, Agriculture & Natural Resources Educator, Purdue Extension – Delaware County

A map series was generated during testing of the Quantix fixed-wing UAV in 2019. The fixed-wing excels in covering large tracts of land quickly and delivers actionable maps for near-real time decision making. It can cover around 350 acres in 45 minutes on one battery. It also launches and lands vertically, removing the need for runways.

Quantix
Carter_RGB
Carter_GNDVI
Carter_NDVI

Wheat

Flown May 2018 by Mark Carter, Agriculture & Natural Resources Educator, Purdue Extension – Delaware County

wheat streaking aerial

The streaking in this imagery caused concern that fertilizer was not spread properly. The farmer left a test strip and reapplied fertilizer – resulting in a 5 to 10 bushel-per-acre increase in comparison.

wheat streaking data view

Tile drain observation -- installation to harvest

Spring to Fall 2021 by Ashley Adair, Purdue Extension Organic Agriculture Specialist

Pattern tile installation occurred on this field during winter 2020-21 with 50-foot lateral spans connected to main tile lines. The upper left quadrant was not tiled at this time, so it is possible to see tile installation recovery and observe differences in drained and undrained areas. The 80-acre field is located in northern Montgomery County and was planted to group 2.8 soybeans this year.

Discing and planting the field leveled out the ridges from tiling, but the ground was not completely settled even during harvest in November as indicated by combine tracks.

Notice in the late season images that many of the tiled areas of the field are showing less stress (greener in the RGB and NDRE plant health maps); however, the six weeks leading up to this point we only saw 2.5 in. of rain. The field is showing some drought stress and some struggles with water hemp.

3-13RGB_TileLines_Edit
5-5RGB_Planting_edit
8-11RGB_Edit
8-11NDRE_edit

Interaction of land features with developing crops

Flown by Bob Bruner, Agriculture & Natural Resources Educator, Purdue Extension – Clay/Owen County

Detecting unique land features

Drones are not only effective at recording plant health, but also at detecting how land features interact with developing crops. In a Greene County field, drone flights revealed unique land features that had a direct impact on plant health. Differences in the landscape could be due to a creek or washout over time.

LandscapeRGB
Topography and elevation

Elevation mapping demonstrates clear ridges and drops in height as you move towards the southwest corner of the field. A steady drop in elevation can be seen in a north-to-south trajectory, moving toward a running water source to the south. Ridges in southern area may be evidence of the land shifting over time due to washouts.

LandscapeELE
Plant health analysis

Plant Health Analysis shows how the different topographical features are impacting the developing crop. As the topography varies, the developing corn struggled, most likely due to a difference in water availability. Crop development appears to correlate closely to the topography shown in the elevation map.

LandscapeVARI
What does this mean for growers?

Farmers can use this information to plan for problems areas more effectively. Mapping and analytics can help a grower plan for changes to fields, such as tile installation, indicating that drones not only serve a purpose during the season during plant growth but also before planting by looking at land features and topography.