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\begin{document}

\title{Examining Root System Variability in Soybean Using Imaging Technologies}



\author[1]{Sujata Bogati}%
\author[2]{Joshua Carpenter}%
\author[3]{Ellen Woods}%
\author[2]{Jinha Jung}%
\author[1]{Diane R Wang}%
\affil[1]{Purdue University -Agronomy}%
\affil[2]{Purdue University -Civil Engineering}%
\affil[3]{Auburn University}%


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  \date{May 24, 2024}


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\begin{abstract}
ORCiD: {[}\url{https://orcid.org/0000-0003-0655-2343}{]}

Keywords: Root imaging, root-system architecture (RSA), soybean,
2D-phenotyping \& 3D-phenotyping

Roots are a major part of plant systems and are essential to obtaining
water and nutrients. Despite their importance, roots have not been
extensively examined as compared to their aboveground counterparts, due
primarily to the difficulties of access and lack of standard methods to
quantify root morphology. While there have been several experiments
performed under controlled environments, comparatively fewer studies
have examined root architectures under field conditions. Here, we apply
two imaging techniques to characterize variability in Root System
Architecture (RSA) in diverse soybean genotypes under field settings
with two contrasting soil conditions. Thus, our objectives are to (1)
quantify root system architecture using 2D image techniques (e.g.,
Winrhizo and Image J) and (2) evaluate a contrasting subset of these
samples (n = 30) using a novel 3D phenotyping approach. The research
seeks to meet the need for enhanced methods in root system architecture
analysis across diverse field conditions potentially leading to more
resilient, high-yielding soybean varieties.%
\end{abstract}%



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