By Robert Burns

Team members of the Texas A&M Coordinated Agricultural Unmanned Aerial Systems Project had a lot to “show and tell” when they met on Dec. 21, said Dr. Alex Thomasson, Texas A&M AgriLife Research agricultural engineer, College Station.

“The original purpose of the meeting was to make clear to administrators what the group has accomplished over the last six to eight months,” Thomasson said. “We have had basically five teams and over 30 scientists involved in this project.”

Unmanned aerial systems is an umbrella term encompassing what are commonly referred to as drones or unmanned aerial vehicles, known as UAVs.

The project, established a year ago, was designed to be a multi-disciplinary, multi-agency effort. It is comprised of a wide range of scientists from AgriLife Research, Texas A&M AgriLife Extension Service, the Texas Engineering Experiment Station, the Texas A&M Center for Autonomous Vehicles and Sensor Systems, the Texas A&M Center for Geospatial Sciences, Applications and Technology and others.

Within AgriLife Research and AgriLife Extension, there were engineers, such as Thomasson, from the Texas A&M department of biological and agricultural engineering. There were also plant breeders, weed scientists, soil scientists and others specializing in various crops from the Texas A&M department of soil and crop sciences.

The first step of the project was getting Federal Aviation Administration approval to fly unmanned vehicles over the 1,400 acres of crops at the Texas A&M farm on State Highway 60 near College Station.

“We didn’t get our FAA approval to fly unmanned vehicles over the research farm until around the first of June, and that’s when we started in earnest flying multiple UAVs there,” Thomasson said.

There were several main teams, Thomasson said. He led a sensor team that was responsible for ensuring multispectral cameras and other sensors were properly installed and calibrated and that other scientists received useful data from the flights.

There were three flight teams, but the main one was led by Dr. John Valasek, an aerospace engineer who heads the Center for Autonomous Vehicles and Sensor Systems.

“His group did the most flights,” Thomasson said. “He mainly flew one particular fixed-wing aircraft with a multispectral camera, and flew it a couple of times a week over the research farm.”

Another group was led by Dr. Sorin Popescu, an AgriLife Research scientist in the Texas A&M department of ecosystem science and management.

“He has a rotary wing aircraft that flies low and slow, hovering over parts of the field that we are interested in gathering very highly detailed data on,” Thomasson said.

The third flight team was led by Dr. Dale Cope, a Texas A&M mechanical engineering department professor. Cope is working with PrecisionHawk, a Raleigh, North Carolina, company specializing in agricultural uses of unmanned aerial vehicles, according to Thomasson. “And they have made available to him an entire commercial system, that includes a fixed-wing aircraft, a multispectral camera and all of their online cloud-based storage and processing services for the image data he collects.”

All of this work contributes to two research goals. The first is the long-established goal of his team and other AgriLife teams of taking precision agriculture to the next level. The second is enabling breeders to accelerate crop improvements by using UAVs for high-throughput phenotyping (HTP), Thomasson said.

“Precision ag and HTP are truly different technologies, although there is significant overlap in the research,” he said.

Precision agriculture technology today is largely about adjusting inputs to known variability within a field, he said. For example, instead of applying fertilizer at the same rate across a 160-acre center pivot circle, precision agriculture systems use data on soil type and residual fertilizer variability to define different management zones within the 160 acres. Fertilizer is then applied to the management zones at optimal rates controlled by a GPS/computer-equipped tractor or through the irrigation system.

In comparison, high-throughput phenotyping, in which UAVs will play a huge role, involves developing sensor/computer hardware and software that can determine the status a