In testing, researchers found the patch was able to detect a viral infection in tomatoes more than a week before growers would be able to detect any visible symptoms of disease.
“This is important because the earlier growers can identify plant diseases or fungal infections, the better able they will be to limit the spread of the disease and preserve their crop,” says Qingshan Wei, an assistant professor of chemical and biomolecular engineering at North Carolina State University and corresponding author of a paper in Science Advances.
“In addition, the more quickly growers can identify abiotic stresses, such as irrigation water contaminated by saltwater intrusion, the better able they will be to address relevant challenges and improve crop yield.”
The technology builds on a previous prototype patch, which monitors volatile organic compounds (VOCs) emitted by plants to detect disease. Plants emit different combinations of VOCs under different circumstances. By targeting VOCs that are relevant to specific diseases or plant stress, the sensors can alert users to specific problems.
“The new patches incorporate additional sensors, allowing them to monitor temperature, environmental humidity, and the amount of moisture being ‘exhaled’ by the plants via their leaves,” says co-corresponding author Yong Zhu, professor of mechanical and aerospace engineering.
The patches themselves are small—only 30 millimeters long—and consist of a flexible material containing sensors and silver nanowire-based electrodes. The patches are placed on the underside of leaves, which have a higher density of stomata—the pores that allow the plant to “breathe” by exchanging gases with the environment.
The researchers tested the patches on tomato plants in greenhouses, and experimented with patches that incorporated different combinations of sensors. The tomato plants were infected with three different pathogens: tomato spotted wilt virus (TSWV); early blight, which is a fungal infection; and late blight, which is a type of pathogen called an oomycete. The plants were also exposed to a variety of abiotic stresses, such as overwatering, drought conditions, lack of light, and high salt concentrations in the water.
The researchers took data from these experiments and plugged them into an artificial intelligence program to determine which combinations of sensors worked most effectively to identify both disease and abiotic stress.
“Our results for detecting all of these challenges were promising across the board,” Wei says. “For example, we found that using a combination of three sensors on a patch, we were able to detect TSWV four days after the plants were first infected. This is a significant advantage, since tomatoes don’t normally begin to show any physical symptoms of TSWV for 10-14 days.”Click here to see more...