Impedimetric
wearable sensors are a promising strategy for determining
the loss of water content (LWC) from leaves because they can afford
on-site and nondestructive quantification of cellular water from a
single measurement. Because the water content is a key marker of leaf
health, monitoring of the LWC can lend key insights into daily practice
in precision agriculture, toxicity studies, and the development of
agricultural inputs. Ongoing challenges with this monitoring are the
on-leaf adhesion, compatibility, scalability, and reproducibility
of the electrodes, especially when subjected to long-term measurements.
This paper introduces a set of sensing material, technological, and
data processing solutions that overwhelm such obstacles. Mass-production-suitable
electrodes consisting of stand-alone Ni films obtained by well-established
microfabrication methods or ecofriendly pyrolyzed paper enabled reproducible
determination of the LWC from soy leaves with optimized sensibilities
of 27.0 (Ni) and 17.5 kΩ %–1 (paper). The
freestanding design of the Ni electrodes was further key to delivering
high on-leaf adhesion and long-term compatibility. Their impedances
remained unchanged under the action of wind at velocities of up to
2.00 m s–1, whereas X-ray nanoprobe fluorescence
assays allowed us to confirm the Ni sensor compatibility by the monitoring
of the soy leaf health in an electrode-exposed area. Both electrodes
operated through direct transfer of the conductive materials on hairy
soy leaves using an ordinary adhesive tape. We used a hand-held and
low-power potentiostat with wireless connection to a smartphone to
determine the LWC over 24 h. Impressively, a machine-learning model
was able to convert the sensing responses into a simple mathematical
equation that gauged the impairments on the water content at two temperatures
(30 and 20 °C) with reduced root-mean-square errors (0.1% up
to 0.3%). These data suggest broad applicability of the platform by
enabling direct determination of the LWC from leaves even at variable
temperatures. Overall, our findings may help to pave the way for translating
“sense–act” technologies into practice toward
the on-site and remote investigation of plant drought stress. These
platforms can provide key information for aiding efficient data-driven
management and guiding decision-making steps.