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\begin{document}

\title{Low-cost, Low-profile Dendrometer Optimized for Grapevines}



\author[1]{Cameron Clonch}%
\author[1]{Mark Huynh}%
\author[1]{Bryson Goto}%
\author[2]{Alexander Levin}%
\author[3]{John Selker}%
\author[3]{Chet Udell}%
\affil[1]{Openly Published Environmental Sensing (OPEnS) Lab, Oregon State University, Corvallis, Oregon, USA}%
\affil[2]{Department of Horticulture, Oregon State University, Corvallis, Oregon, USA}%
\affil[3]{Openly Published Environmental Sensing (OPEnS) Lab, Oregon State University, Corvallis, OR, USA}%


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  \date{May 26, 2024}


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\begin{abstract}
Increasing agricultural demand for fresh water resources in the face of
a changing climate requires improved irrigation management solutions to
maximize resource efficiency while maintaining crop yield and quality.
Soil water deficits can significantly reduce plant growth and
development, dictating the quantity and quality of the crop. While
plant-based measures of water deficits are considered to be the best
measures of water stress, current methods for achieving precise stress
measurements are time-consuming and inefficient. Dendrometers are one
plant-based tool that have shown potential to improve irrigation
management in high-value woody perennial crops. High-precision
dendrometers continuously measure small fluctuations (\selectlanguage{ngerman}± 1 micron) in
stem diameter throughout the day, which directly correlates to water
stress. However, currently available dendrometers are expensive, have
mechanical hysteresis, and are subject to mechanical and environmental
issues such as material expansion; weather and animal disruptions; and
bulky, invasive design. The dendrometer created at the OPEnS Lab -
tailored for grapevines - alleviates these key failure points through
the use of zero-thermal expansion carbon fiber, spring tension, and a
linear magnetic encoder. The design is also significantly less expensive
than that of the competition, costing around \$200 as opposed to \$1000.
Mass deployment of these automated dendrometers has the potential to
provide a continuous picture of vineyard water stress at the whole-block
level, thus providing valuable decision support for vineyard irrigation
management. Follow the project at open-sensing.org/projects.%
\end{abstract}\selectlanguage{ngerman}%



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