\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[english]{babel}



\usepackage{float}








\begin{document}

\title{Hyperspectral Image-Based Spatial and Spectral Feature Mining for
Phosphorus Deficiency Symptom Differentiation at Corn's Early Vegetative
Stage~~~}



\author[1]{Jinnuo Zhang}%
\author[1]{Xing Wei}%
\author[1]{Zhihang Song}%
\author[1]{Chad J. Penn}%
\author[1]{Jian Jin}%
\affil[1]{Affiliation not available}%


\vspace{-1em}



  
  \date{May 15, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Phosphorus (P) is a vital macronutrient for building up essential
biomolecules in plants, and its accurate quantification can guide
effective crop management and increase crop growers' profit. Traditional
chemical reaction-based methods for measuring P levels in plants are
destructive and complex. Hyperspectral imaging offers a real-time,
non-destructive avenue for assessing crop nutrient status. While these
images are rich in both spatial and spectral information, limitations in
current devices and analytical algorithms have led most studies to
concentrate solely on the spectral features. In this study, a novel
algorithm to combine features in spatial and spectral domains is
proposed and implemented to differentiate phosphorus deficiency symptoms
in corn plants. At the V6 vegetative stage, leaf-level hyperspectral
images from three P levels and two leaf positions were collected using
the handheld proximal hyperspectral imager, LeafSpec. Spatial and
spectral features that exhibit significant differences between the P
treatments were generated by integrating pre-designed spatial partitions
with spectral index maps. The correlation coefficient between the P
content and elected spatial and spectral features was treated as the
standard to further refine the mining results. The spatial and spectral
joint effects showed superior ability than spectral indices in
differentiating P deficiency at both leaf positions, especially for
medium P and sufficient P. Related visualization maps also gave out a
preliminary insight into the differences in P deficiency symptoms. This
study highlights the great potential and effectiveness of combining
spatial and spectral features in differentiating P levels at corn's
early vegetative stage.%
\end{abstract}%



\sloppy


\emph{\textbf{Jinnuo Zhang\textsuperscript{1}}, Xing
Wei\textsuperscript{1}, Zhihang Song\textsuperscript{1}, Chad J.
Penn\textsuperscript{2}, Jian Jin\textsuperscript{1}}

\emph{\textsuperscript{1}} \emph{Department of Agricultural and
Biological Engineering, Purdue University, West Lafayette, IN 47907,
USA}

\emph{\textsuperscript{2}} \emph{National Soil Erosion Research
Laboratory, USDA-ARS, West Lafayette, IN47907, USA}

\textbf{ORCiD:} {[}0000-0003-1435-5702{]}

\textbf{Keywords:} Feature mining, Hyperspectral image processing,
Phosphorus deficiency symptom differentiation, Early detection

\par\null\par\null

\selectlanguage{english}
\FloatBarrier
\end{document}

