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@ARTICLE{Burridge:888607,
      author       = {Burridge, James D. and Black, Christopher K. and Nord, Eric
                      A. and Postma, Johannes A. and Sidhu, Jagdeep S. and York,
                      Larry M. and Lynch, Jonathan P.},
      title        = {{A}n {A}nalysis of {S}oil {C}oring {S}trategies to
                      {E}stimate {R}oot {D}epth in {M}aize ({Z}ea mays) and
                      {C}ommon {B}ean ({P}haseolus vulgaris)},
      journal      = {Plant phenomics},
      volume       = {2020},
      issn         = {2643-6515},
      address      = {Washington, D.C.},
      publisher    = {American Association for the Advancement of Science},
      reportid     = {FZJ-2020-05063},
      pages        = {1 - 20},
      year         = {2020},
      abstract     = {A soil coring protocol was developed to cooptimize the
                      estimation of root length distribution (RLD) by depth and
                      detection offunctionally important variation in root system
                      architecture (RSA) of maize and bean. The
                      functional-structural modelOpenSimRoot was used to perform
                      in silico soil coring at six locations on three different
                      maize and bean RSA phenotypes.Results were compared to two
                      seasons of field soil coring and one trench. Two one-sided
                      T-test (TOST) analysis of in silico datasuggests a
                      between-row location 5 cm from plant base (location 3), best
                      estimates whole-plot RLD/D of deep, intermediate, andshallow
                      RSA phenotypes, for both maize and bean. Quadratic
                      discriminant analysis indicates location 3 has $~70\%$
                      categorizationaccuracy for bean, while an in-row location
                      next to the plant base (location 6) has $~85\%$
                      categorization accuracy in maize.Analysis of field data
                      suggests the more representative sampling locations vary by
                      year and species. In silico and field studiessuggest
                      location 3 is most robust, although variation is significant
                      among seasons, among replications within a field season,
                      andamong field soil coring, trench, and simulations. We
                      propose that the characterization of the RLD profile as a
                      dynamic rhizocanopy effectively describes how the RLD
                      profile arises from interactions among an individual plant,
                      its neighbors, and thepedosphere.},
      cin          = {IBG-2},
      ddc          = {580},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {582 - Plant Science (POF3-582)},
      pid          = {G:(DE-HGF)POF3-582},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {33313549},
      UT           = {WOS:000705527000010},
      doi          = {10.34133/2020/3252703},
      url          = {https://juser.fz-juelich.de/record/888607},
}