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@ARTICLE{Wilke:894570,
      author       = {Wilke, Norman and Siegmann, Bastian and Postma, Johannes A.
                      and Muller, Onno and Krieger, Vera and Pude, Ralf and
                      Rascher, Uwe},
      title        = {{A}ssessment of plant density for barley and wheat using
                      {UAV} multispectral imagery for high-throughput field
                      phenotyping},
      journal      = {Computers and electronics in agriculture},
      volume       = {189},
      issn         = {0168-1699},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2021-03286},
      pages        = {106380 -},
      year         = {2021},
      abstract     = {Cereal plant density is a relevant agronomic trait in
                      agriculture and high-throughput phenotyping of plant density
                      is important for the decision-making process in precision
                      farming and breeding. It influences the water as well as the
                      fertilization requirements, the intraspecific competition,
                      and the occurrence of weeds or pathogens. Recent studies
                      have determined plant density using machine-learning
                      approaches and feature extraction. This requires spatially
                      very highly resolved images (0.02 cm) because the accuracy
                      distinctly decreased when images had lower resolution. In
                      this study, we present an approach that uses the linear
                      relationship between plant density manually counted in the
                      field and fractional cover derived from a RGB and a
                      multispectral camera equipped on an unmanned aerial vehicle
                      (UAV). We assumed that at an early seedling stage fractional
                      cover is closely related to the number of plants. Spring
                      barley and spring wheat experiments, each with three
                      genotypes and four different sowing densities, were
                      examined. The practicability and repeatability of the
                      methodology were evaluated with an independent experiment
                      consisting of 42 winter wheat genotypes. This experiment
                      mainly differed for genotypes, sowing density and season.},
      cin          = {IBG-2},
      ddc          = {004},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {2173 - Agro-biogeosystems: controls, feedbacks and impact
                      (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2173},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000696702600002},
      doi          = {10.1016/j.compag.2021.106380},
      url          = {https://juser.fz-juelich.de/record/894570},
}