Plant science in the age of simulation intelligence

Michiel Stock, Olivier Pieters, Tom De Swaef, Francis wyffels

Onderzoeksoutput: Bijdrage aan tijdschriftArtikelpeer review

Uittreksel

Historically, plant and crop sciences have been quantitative fields that intensively use measurements and modeling. Traditionally, researchers choose between two dominant modeling approaches: mechanistic plant growth models or data-driven, statistical methodologies. At the intersection of both paradigms, a novel approach referred to as “simulation intelligence”, has emerged as a powerful tool for comprehending and controlling complex systems, including plants and crops. This work explores the transformative potential for the plant science community of the nine simulation intelligence motifs, from understanding molecular plant processes to optimizing greenhouse control. Many of these concepts, such as surrogate models and agent-based modeling, have gained prominence in plant and crop sciences. In contrast, some motifs, such as open-ended optimization or program synthesis, still need to be explored further. The motifs of simulation intelligence can potentially revolutionize breeding and precision farming towards more sustainable food production.
Oorspronkelijke taalEngels
TijdschriftFrontiers in Plant Science
Volume14
ISSN1664-462X
DOI's
PublicatiestatusGepubliceerd - 16-jan.-2024

Trefwoorden

  • artificial intelligence
  • digital agriculture
  • digital twin
  • modeling
  • phenotyping
  • quantified plant
  • scientific computing
  • simulation intelligence

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