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@INPROCEEDINGS{MllerLinow:1046469,
      author       = {Müller-Linow, Mark and Grundmann, Lena and He, Fang},
      title        = {{AI}-supported optimization of the harvest time of {A}rnica
                      montana},
      reportid     = {FZJ-2025-03821},
      year         = {2025},
      abstract     = {Arnica montana is an economically important medicinal plant
                      whose extracts, containing the active ingredients helenalin
                      and dihydrohelenalin, are used as raw materials in the
                      pharmaceutical industry due to their various properties.
                      However, the asynchronous flower development of Arnica
                      montana poses a major challenge for determining the optimal
                      harvest time in controlled cultivation, as the active
                      ingredient content and harvestability depend heavily on the
                      phenological stage of the flowers. To solve this problem, a
                      methodological approach was developed that uses image-based
                      monitoring together with a neural network to classify seven
                      defined flower stages in a field-suitable and non-invasive
                      manner. This enables quantitative recording of the stage
                      distribution in the plant population over time. With known
                      concentrations of the target compounds helenalin and
                      dihydrohelenalin for each characteristic stage it is
                      possible to estimate the temporal progression of the
                      potential total active ingredient yield of a crop. The
                      results enable a well-founded determination of the harvest
                      window, taking into account active ingredient accumulation
                      and decreasing harvest efficiency. The presented method has
                      transfer potential to other medicinal plants where
                      morphological characteristics can be used as proxies for
                      ingredient concentrations.},
      month         = {Sep},
      date          = {2025-09-16},
      organization  = {European Plant Phenomics Symposium,
                       Jülich (Germany), 16 Sep 2025 - 19 Sep
                       2025},
      subtyp        = {After Call},
      cin          = {IBG-2},
      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)24},
      url          = {https://juser.fz-juelich.de/record/1046469},
}