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@ARTICLE{ElJarroudi:887699,
      author       = {El Jarroudi, Moussa and Lahlali, Rachid and Kouadio, Louis
                      and Denis, Antoine and Belleflamme, Alexandre and El
                      Jarroudi, Mustapha and Boulif, Mohammed and Mahyou, Hamid
                      and Tychon, Bernard},
      title        = {{W}eather-{B}ased {P}redictive {M}odeling of {W}heat
                      {S}tripe {R}ust {I}nfection in {M}orocco},
      journal      = {Agronomy},
      volume       = {10},
      number       = {2},
      issn         = {2073-4395},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2020-04356},
      pages        = {280 -},
      year         = {2020},
      abstract     = {Predicting infections by Puccinia striiformis f. sp.
                      tritici, with sufficient lead times, helps determine whether
                      fungicide sprays should be applied in order to prevent the
                      risk of wheat stripe rust (WSR) epidemics that might
                      otherwise lead to yield loss. Despite the increasing threat
                      of WSR to wheat production in Morocco, a model for
                      predicting WSR infection events has yet to be developed. In
                      this study, data collected during two consecutive cropping
                      seasons in 2018–2019 in bread and durum wheat fields at
                      nine representative sites (98 and 99 fields in 2018 and
                      2019, respectively) were used to develop a weather-based
                      model for predicting infections by P. striiformis. Varying
                      levels of WSR incidence and severity were observed according
                      to the site, year, and wheat species. A combined effect of
                      relative humidity > $90\%,$ rainfall ≤ 0.1 mm, and
                      temperature ranging from 8 to 16 °C for a minimum of 4
                      continuous hours (with the week having these conditions for
                      $5\%$ to $10\%$ of the time) during March–May were optimum
                      to the development of WSR epidemics. Using the weather-based
                      model, WSR infections were satisfactorily predicted, with
                      probabilities of detection ≥ 0.92, critical success index
                      ranging from 0.68 to 0.87, and false alarm ratio ranging
                      from 0.10 to 0.32. Our findings could serve as a basis for
                      developing a decision support tool for guiding on-farm WSR
                      disease management, which could help ensure a sustainable
                      and environmentally friendly wheat production in Morocco},
      cin          = {IBG-3},
      ddc          = {640},
      cid          = {I:(DE-Juel1)IBG-3-20101118},
      pnm          = {255 - Terrestrial Systems: From Observation to Prediction
                      (POF3-255)},
      pid          = {G:(DE-HGF)POF3-255},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000521366400120},
      doi          = {10.3390/agronomy10020280},
      url          = {https://juser.fz-juelich.de/record/887699},
}