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@ARTICLE{Ruett:894927,
      author       = {Ruett, Marius and Junker-Frohn, Laura Verena and Siegmann,
                      Bastian and Ellenberger, Jan and Jaenicke, Hannah and
                      Whitney, Cory and Luedeling, Eike and Tiede-Arlt, Peter and
                      Rascher, Uwe},
      title        = {{H}yperspectral imaging for high-throughput vitality
                      monitoring in ornamental plant production},
      journal      = {Scientia horticulturae},
      volume       = {291},
      issn         = {0304-4238},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier Science},
      reportid     = {FZJ-2021-03486},
      pages        = {110546 -},
      year         = {2022},
      abstract     = {Ornamental heather (Calluna vulgaris) production is
                      characterized by high risks such as occurrence of fungal
                      diseases and plant losses. Given the general absence of
                      formal research on this economically important production
                      system, farmers depend on their own approaches to assess
                      plant vitality. We provide a reproducible, affordable and
                      transparent workflow for assessing ornamental plant vitality
                      with spectroscopy data. We use hyperspectral imaging as a
                      non-invasive alternative for monitoring plant performance by
                      combining the long-term experience of experts with
                      hyperspectral images taken with a portable hyperspectral
                      camera. We tested a custom-made setup deployed in a
                      horticultural production facility and screened thousands of
                      heather plants over a period of 14 weeks during their
                      development from cuttings to young plants under production
                      conditions. The vitality of shoots and roots was classified
                      by experts for comparison with spectral signatures of shoot
                      tips of healthy and stressed plants. To identify wavelengths
                      that allow distinguishing between healthy and stressed
                      heather plants, we evaluated the datasets using Partial
                      Least Squares regression. Reflectance in the green
                      (519–575 nm) and red-edge (712–718 nm) region of the
                      spectrum was identified as most important for classifying
                      plants as healthy or stressed. We transferred the trained
                      Partial Least Squares regression model to independent test
                      data obtained on a different date, correctly classifying
                      $98.1\%$ of the heather plants. The setup we describe here
                      is adjustable and can be used to measure different plant
                      species. We identify challenges in data evaluation, point
                      out promising evaluation approaches, and make our dataset
                      available to facilitate further studies on plant vitality in
                      horticultural production systems.},
      cin          = {IBG-2},
      ddc          = {640},
      cid          = {I:(DE-Juel1)IBG-2-20101118},
      pnm          = {2171 - Biological and environmental resources for
                      sustainable use (POF4-217)},
      pid          = {G:(DE-HGF)POF4-2171},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000697541900002},
      doi          = {10.1016/j.scienta.2021.110546},
      url          = {https://juser.fz-juelich.de/record/894927},
}