Unmanned Aerial Vehicles

Corn and Soybean


Corn and Soybean

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

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

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, Agriculture & Natural Resources Educator, Purdue Extension – Montgomery County

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.

Green snap damage in corn

Flown by Hanz Schmitz, Agriculture & Natural Resources Educator, Purdue Extension – Posey County

Partnering with a local co-op, Purdue Extension collected images for a producer to identify intensity and variability of green snap in corn. The producer was able to work closely with insurance to plan out yield loss due to a spring storm.

Posey Co. Greensnap

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.

Conventional vs. cover crop in soybeans

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

These flights evaluate conventional management with no-till cover crop management. The field on the left uses cereal rye as a cover with 30-inch soybean rows planted into the cover. The field on the right was tilled without cover crops and planted in 15-inch rows.

It’s evident the no-till field has more bare spots which can attribute to vertebrate pest damage.

RGB: Orthomosaic
SoyCover_Conventional_RGB wsubarea
Sub-Area 1
SoyCover_Conventional_RGB_Closeup2
Sub-Area 2
SoyCover_Conventional_RGB_Closeup
VARI: Plant health
SoyCover_Conventional_VARI

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

Locating tile at Davis Purdue Ag Center (PAC)

Flown July 2018 by Jeff Boyer, Superintendent, Davis PAC

Field Tile Ortho

The upper orthomosaic map and lower plant-health map features corn and soybeans. Patterns start to emerge, showing a difference in canopy coverage of each crop as well as vertical lines representing field tile. This aerial imagery is a quick and relatively inexpensive way to get a high-resolution field tile map.

Field Tile Plant Health

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