Our faculty pursue a vigorous research agenda for digital agriculture (DA) through interdisciplinary collaborations that will transform agriculture and foster a pipeline of practical innovations. Through the use of new and advanced technologies that autonomously collect, integrate and transmit information, DA is creating new tools and providing practical solutions to improve effective, real-time decision-making on farms and at many points throughout agricultural systems.

Digital technologies include sensors, robotics, unmanned aviation systems, communication networks, artificial intelligence, machine learning and other advanced systems and devices. The ability to integrate data from different technologies and deliver it to the appropriate people in an understandable format is critical to support informed farming operations and to enhance farm productivity and profitability.

Recent digital agriculture projects

Tracking plant diseases traveling across the earth on dust

A NASA grant was awarded to Katie Gold, assistant professor of plant pathology and plant microbe-biology, to use her expertise in remote sensing, plant pathology and genomics to better understand how plant pathogens that travel the globe with dust particles might put crops at risk, especially in places where people struggle to eat.

High resolution sensors for vineyard nutrient measurement

The U.S. Department of Agriculture’s National Institute of Food and Agriculture has awarded a $676,000 grant to a pair of Cornell researchers aiming to use high resolution sensors to help vineyard growers identify nutrient deficiencies.

The researchers – Terry Bates, senior research associate at the Cornell Lake Erie Research and Extension Labaoratory, and Justine Vanden Heuvel, professor of horticulture, will develop affordable, efficient and accessible technologies to support the health of vineyards across New York state and beyond.

Using hyperspectral sensors to determine fungicide resistance

Evidence has been found that grape powdery mildew is developing resistance to some fungicides on the East coast. Using hyperspectral sensors, Katie Gold, assistant professor of plant pathology and plant-microbe biology will detect fungicide resistance right from the vineyard while keeping grapes on the vine. The hyperspectral sensors Gold will use measure light reflectance in the visible to shortwave infrared range of the electromagnetic spectrum – a range of light seven times larger than the human eye can see.

Grant funds high-tech system to improve grapevine pruning

​​​​​​Justin Vandenheuvel, professor of viticulture and Yu Jiang, assistant research professor of systems engineering and data analytics, are working to develop a thermal and multispectral imaging system for growers that they can attach to an all-terrain vehicle, drive through their vineyard, and have a map produced of live and dead buds that then can be used to guide their pruning practices.

Robots armed with UV light fight grape mildew

Senior research associate David Gadoury is using ultraviolet light robots to kill grape powdery mildew as part of a research trial at Cornell AgriTech and at Anthony Road Winery in the Finger Lakes region of New York state. Gadoury’s research has proven ultraviolet light to be an effective means for controlling this form of grape disease. The robotic technology will become commercially available to wineries soon.

Satellite world map
Terry Bates looks at computer while on his tractor
Green leaves with white powder on them
women holds drone while stnading in a vinyard
UV light technology being used at night to suppress powdery mildew on grapevines at a Cornell AgriTech research field

Spotlight: the Efficient Vineyard Project

Funded through the USDA-NIFA Specialty Crop Research Initiative, the Efficient Vineyard project is a national effort to advance the use of precision viticulture in wine, juice and table grape production. The disciplines of engineering, precision agriculture, viticulture and economics come together to measure vineyard soil, canopy and crop characteristics, model spatial data for viticulture information and manage vineyard crop load through variable-rate machine applications.

Sensor measures grape crop load