The big picture
Agricultural drones survey property and collect data to improve quality and increase yields
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sky-high perspective of farm operations offers more than just a pretty picture. As drone functionality soars and units become more affordable, Virginia agriculturists are exploring their use in improving crop quality, increasing yields and surveying livestock and property. Light- and distance-measuring technologies affixed to drones can accurately determine crop status, and even predict disease symptom onset, resulting in greater profit for producers. Whether the devices are used for checking on sheep, looking for wildlife damage, counting crops or measuring plant volume to calculate yields, researchers want to make drones accessible to Virginia farmers.
Sky’s the limit for technological potential What will save tobacco growers the most money and make their operations more profitable? Researchers at Virginia Tech’s Southern Piedmont Agricultural Resource and Extension Center in Nottoway County are developing systems that should answer that question. Hyperspectral imaging devices may have potential to detect slight indicators of crop quality, often invisible to the naked eye. In 2018, while Austin Hayes was studying for his master’s degree at the center, they conducted an experiment in a grower’s black-shank infested tobacco field. “We were trying to see if we could separate healthy plants from plants that appeared healthy but soon became symptomatic,” Hayes said. “We took several readings over a period of two weeks. By doing that, we were able to look through the lens of time, to tell 16
VIRGINIA FARM BUREAU NEWS
PHOTOS COURTESY OF VIRGINIA TECH
BY NICOLE ZEMA
A bird’s-eye view of Virginia Tech’s Kentland Farm and Sheep Center as seen with drones, which are used in the college’s Agricultural Technology program.
which plants were pre-symptomatic, and when.” Comparing the readings, researchers found statistical differences in data between healthy plants and seemingly strong plants that would later become symptomatic for the soil-borne disease.
Equipment pinpoints unhealthy crops “We used a hyperspectral radiometer, which takes a point measurement rather than an entire image,” Hayes explained. “Hyperspectral sensors and cameras allow us to measure beyond the range of visible light to get a unique spectral signature for an object.” A spectral signature can ultimately illuminate those minor differences. That information could be empowering to tobacco growers, who can follow up with a precise management decision, like fungicide or early harvest. But the typical farmer may not have the expertise or computational resources to interpret layers of data that will describe the field, or $70,000 to purchase a hyperspectral radiometer. “We’re trying to take first steps into developing a system so a grower can fly a drone over their own field and interpret the information and act on it,” Hayes said.
To make the device more affordable, research is directed toward identifying the specific bands of the spectrum needed to detect specific diseases and other plant stresses, said Dr. David Reed, tobacco agronomist at the center. Graduate research assistant Caleb Hinkle is working on multiple projects to study how nicotine levels vary among different tobacco varieties, the ability of drone technology to determine tobacco yields, and the implementation of drones as a scouting tool in farming operations. Specialized cameras affixed to drones measures leaf area, volume and plant size, and categorizes tobacco plants as small, medium or large. These data may be used to highlight areas in the field that are underperforming and may require management attention. “The camera works directly with a specialized sensor that measures ambient light, cloud cover and atmospheric densities of gasses that can change light that we can’t see,” Hinkle said. “You can go out and see what the issue is in that specific spot, so you’re not scouting an entire 100-acre field.” Reed’s team has been contacted by a company interested in implementing drone-assisted precision agriculture on a countrywide basis. “They could predict what the yield
