@article{fdi:010085218,
  title = {{H}ow process-based modeling can help plant breeding deal with {G} x {E} x {M} interactions},
  author = {{H}ajjarpoor, {A}mir and {N}elson, {W}. {C}. {D}. and {V}adez, {V}incent},
  editor = {},
  language = {{ENG}},
  abstract = {{G}enotype-by-{E}nvironment-by-{M}anagement ({G}x{E}x{M}) interactions represent many unknowns for crop improvement programs, which hampers the development of improved varieties, especially for highly variable environments like those limited by rainfall. {W}hile breeding programs have traditionally used statistical tools to deal with these interactions, process-based crop modeling has recently become an alternative and powerful approach. {O}verall, while statistical methods remain the most optimal solution to deal with {G}x{E}x{M} interactions when many production datasets across time and space are available from multi-environment trials ({MET}), in silico methods like crop modeling can be used if such data is lacking, or if {MET} data don't cover the entire target region. {Y}et, despite several reviews on the potential uses of process-based modeling tools to aid such issues, their practical use in helping breeding programs is still in its infancy. {A}fter exposing the pros and cons of process-based modeling, this paper presents the step-by-step process that would allow breeding programs to harness this tool to help guide their breeding decisions. {W}e also argue that the issue of {G}x{E}x{M} interactions should be tackled in a co-construction process, involving breeders, agronomists, extensionists, and modelers from the beginning, and this would bring crop models one step closer to being used to help make plant breeding decisions.},
  keywords = {{C}rop improvement {M}ulti-{E}nvironment {T}rials ; ({MET}) ; {P}rocess-based ; modeling ; {S}tatistical analysis ; {T}arget {P}opulation of {E}nvironment ({TPE})},
  booktitle = {},
  journal = {{F}ield {C}rops {R}esearch},
  volume = {283},
  numero = {},
  pages = {108554 [12 p.]},
  ISSN = {0378-4290},
  year = {2022},
  DOI = {10.1016/j.fcr.2022.108554},
  URL = {https://www.documentation.ird.fr/hor/fdi:010085218},
}