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@ARTICLE{Bhler:848194,
      author       = {Bühler, Jonas and von Lieres, Eric and Huber, Gregor},
      title        = {{M}odel-{B}ased {D}esign of {L}ong-{D}istance {T}racer
                      {T}ransport {E}xperiments in {P}lants},
      journal      = {Frontiers in Functional Plant Ecology},
      volume       = {9},
      issn         = {1664-462X},
      address      = {Lausanne},
      publisher    = {Frontiers Media88991},
      reportid     = {FZJ-2018-03460},
      pages        = {773},
      year         = {2018},
      abstract     = {Studies of long-distance transport of tracer isotopes in
                      plants offer a high potential for functional phenotyping,
                      but so far measurement time is a bottleneck because
                      continuous time series of at least 1 h are required to
                      obtain reliable estimates of transport properties. Hence,
                      usual throughput values are between 0.5 and 1 samples h−1.
                      Here, we propose to increase sample throughput by
                      introducing temporal gaps in the data acquisition of each
                      plant sample and measuring multiple plants one after each
                      other in a rotating scheme. In contrast to common time
                      series analysis methods, mechanistic tracer transport models
                      allow the analysis of interrupted time series. The
                      uncertainties of the model parameter estimates are used as a
                      measure of how much information was lost compared to
                      complete time series. A case study was set up to
                      systematically investigate different experimental schedules
                      for different throughput scenarios ranging from 1 to 12
                      samples h−1. Selected designs with only a small amount of
                      data points were found to be sufficient for an adequate
                      parameter estimation, implying that the presented approach
                      enables a substantial increase of sample throughput. The
                      presented general framework for automated generation and
                      evaluation of experimental schedules allows the
                      determination of a maximal sample throughput and the
                      respective optimal measurement schedule depending on the
                      required statistical reliability of data acquired by future
                      experiments.},
      cin          = {IBG-1 / IBG-2},
      ddc          = {570},
      cid          = {I:(DE-Juel1)IBG-1-20101118 / I:(DE-Juel1)IBG-2-20101118},
      pnm          = {583 - Innovative Synergisms (POF3-583)},
      pid          = {G:(DE-HGF)POF3-583},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:29930567},
      UT           = {WOS:000434388900001},
      doi          = {10.3389/fpls.2018.00773},
      url          = {https://juser.fz-juelich.de/record/848194},
}