Sensors Did You Know an Electronic Tattoo Can Track Moisture Levels in Plant Leaves?

Researchers have developed an electronic tattoo for leaves that uses hyperflexible and sustainable material graphene to track hydration levels in plant leaves. This solution could predict wildfires, improve agricultural yield, conserve water and food security.

Texas/USA – Is your houseplant thirsty? Are crops getting enough water? Is a forest at high risk of wildfire? Leaf health can answer all these questions, and researchers at The University of Texas at Austin have developed new technology to measure hydration levels with greater accuracy and without hurting the plant.

The researchers developed an electronic tattoo for leaves that uses the hyperflexible and sustainable material graphene to track hydration levels. It sticks on the leaves without harming them, a major improvement over current methods that work only with dead or dried-out leaves or provide indirect measurements.

“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,” said Jean Anne Incorvia, associate professor in the Cockrell School of Engineering’s Chandra Family Department of Electrical and Computer Engineering and one of the leaders on the new research published recently in Nano Letters.

Why it matters

Leaf water levels represent the best indicator of “live fuel moisture content,” said Ashley Matheny, an associate professor in the Jackson School of Geosciences’ Department of Earth and Planetary Sciences. And this content is one of the leading predictors of wildfires, but it is difficult to measure.

Gathering moisture content directly from live leaves today is a very manual and detrimental process. Most methods involve snipping off branches or in some cases, even shooting branches down.

The UT Austin technology offers a simpler, more efficient way to measure moisture levels in living leaves over longer periods.

“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, or on a hot windy day so we can see how it responds to that environmental signal,” said Matheny, who focuses on vegetation, water and soil and how they impact major issues such as drought and wildfire. “We’re able to gather so much more information than what our current technology can, and in a much easier way.”

In addition to predicting wildfires, this method could lead to improvements in agricultural yields, water conservation and food security.

How it works

A small jolt from the applied sensor causes ions within a leaf to move toward or away from the device, altering its conductance. This change indicates the leaf’s hydration level. The devices require just 23 attojoules (aJ) of energy per conductance update and 0.23 microwatt of power for reading data. A modest solar panel could power millions of these sensors simultaneously, making them ideal for large-scale deployment in remote agricultural fields or large forests.

The sensors also exhibit artificial synaptic behavior, meaning they can store and process information like a biological brain. This capability allows the sensors to perform computations at the point of data collection, reducing the need for energy-intensive data transmission to external processors.

A key connection

This technology might never have made it out of the lab if not for a UT program that connects newly tenured professors. Researchers in Incorvia’s lab were working on another project around sensing proton movement using graphene, and a visiting undergraduate student, Maya Borowicz, who is one of the authors, had the idea to apply it to leaves.

It was a fun summer project that got a second life when Incorvia met Matheny through UT’s Associate Professor Experimental program, which aims to foster cross-disciplinary relationships between faculty members on the Forty Acres. Incorvia came in unsure about what to do with her leaf sensor.

In Matheny, she found the perfect partner. Matheny’s work had mostly focused on wood and soil to that point, but she was looking to expand her work to develop a clearer picture of ecosystem health and risks from fires, drought and heat stress.

The full team includes two more faculty members: graphene expert and electrical and computer engineer Deji Akinwande and his former postdoctoral researcher Dmitry Kireev, who is now an assistant professor of biomedical engineering at the University of Massachusetts Amherst. Other members of the team are lead author Utkarsh Misra, Philip Varkey, Ning Liu and Samuel Liu from the Chandra Family Department of Electrical and Computer Engineering and Benjamin K. Keitz from the McKetta Department of Chemical Engineering.

The researchers plan to combine this work with Matheny’s previous research on soil and wood hydration levels to help improve wildfire prediction capabilities.

“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?”

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