Researchers at The University of Texas at Austin announced on Mar. 30 the development of a new electronic tattoo sensor that can measure the hydration levels of plant leaves in real time without damaging them.
This advancement is significant because leaf water content is a key indicator for wildfire risk, crop health, and ecosystem monitoring. Traditional methods for measuring moisture in live leaves are invasive and often harm the plants, while indirect approaches may not provide accurate data.
The newly developed device uses graphene, a flexible and sustainable material, to create an electronic tattoo that adheres to living leaves. Jean Anne Incorvia, associate professor in the Cockrell School of Engineering’s Chandra Family Department of Electrical and Computer Engineering and one of the study’s lead researchers, said: “Being able to directly measure and monitor the live leaf over time, at the point of photosynthesis, gives us more information to understand the health of our plant ecosystems, whether that’s an individual plant or an entire forest.”
Ashley Matheny, associate professor in the Jackson School of Geosciences’ Department of Earth and Planetary Sciences who specializes in vegetation-water interactions related to droughts and wildfires, explained: “Leaf water levels represent the best indicator of ‘live fuel moisture content.’ And this content is one of the leading predictors of wildfires, but it is difficult to measure.” Matheny added: “Instead of having to send people out at all different times of day, we can collect data nearly instantaneously in critical periods like early morning and late afternoon… We’re able to gather so much more information than what our current technology can, and in a much easier way.”
The sensors require very little energy—just 23 attojoules per conductance update—and could be powered by modest solar panels for large-scale deployment. They also feature artificial synaptic behavior allowing them to process data on-site rather than sending it elsewhere for analysis.
The research team includes faculty members Deji Akinwande from electrical engineering; Dmitry Kireev from biomedical engineering; Utkarsh Misra (lead author); Philip Varkey; Ning Liu; Samuel Liu; Benjamin K. Keitz from chemical engineering; as well as undergraduate contributor Maya Borowicz. The team plans future work combining this technology with previous research on soil and wood hydration levels for improved wildfire prediction.
“If I know something about the leaves, I can better predict what’s going on with the wood,” said Matheny. “We are looking at everything from stress responses to what’s happening in the forest right now to understand the risk to the public. If we have some sort of ignition event, what will happen to the forest?”
