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\begin{document}

\title{Portable High-Throughput Digital Confocal Microscope for Early Disease
Detection}



\author[1]{Tianzhang Zhao}%
\author[1]{Morgan Goodnight}%
\author[1]{Darcy Telenko}%
\author[1]{Jian Jin}%
\affil[1]{Affiliation not available}%


\vspace{-1em}



  
  \date{June 11, 2024}


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\begin{abstract}
Northern corn leaf blight (NCLB), caused by the fungus
\emph{Setosphaeira turcica}, is one of the most devastating corn
diseases in the U.S. and has reduced Indiana yields for the last decade.
NCLB can cause significant yield loss if conditions are favorable for
early disease onset near tassel/silk (VT/R1) growth stages. Therefore,
early detection and timely disease management are essential to mitigate
yield loss and optimize fungicide applications. Remote sensing
technologies have broad applications in plant phenotyping areas, but
they present specific challenges in the early detection of diseases,
particularly for diseases where lesions first appear in the lower crop
canopy. While laboratories can provide more accurate results than remote
sensing, their throughput is limited. To achieve higher throughput and
more precise measurements for improved early disease detection, a
portable digital microscope prototype has been developed. Distinct from
other portable microscopes, this device can detect pathogens and
directly monitor their growth on live plant tissue due to its 1 nm
spatial resolution. Moreover, it is built with a confocal configuration
to capture high-resolution reflective images, thereby outperforming
traditional microscopes in throughput. This feature also permits
repetitive non-destructible measurements on a single leaf and
accommodates leaves of varying thicknesses. By analyzing time-series
images of infected leaves, this portable digital microscope has proven
its ability to detect spores and germ tubes of the pathogen before
symptoms are visibly apparent. It has the potential to effectively
bridge the gap between precision and throughput, providing critical
insights into disease management.%
\end{abstract}%



\sloppy


\emph{\textbf{Tianzhang Zhao\textsuperscript{1}}, ~\emph{Morgan
Goodnight}\textsuperscript{\emph{1}}, \emph{Darcy
Telenko}\textsuperscript{\emph{1}}\emph{,} Jian Jin\textsuperscript{1}}

\emph{\textsuperscript{1}Purdue University, West Lafayette, U.S.}

\textbf{ORCiD:} 0009-0007-3756-2532

\textbf{Keywords:} Early Disease Detection, Plant Phenotyping, Digital
Microscope, Imaging Processing

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