Crops in silico: Generating virtual crops using an integrative and multi-scale modeling platform

Amy Marshall-Colon*, Stephen P. Long, Douglas K. Allen, Gabrielle Allen, Daniel A. Beard, Bedrich Benes, Susanne Von Caemmerer, A.J. Christensen, Donna J. Cox, Xinyou Yin

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

105 Citations (Scopus)

Abstract

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Original languageEnglish
Article number786
JournalFrontiers in Plant Science
Volume8
DOIs
Publication statusPublished - 2017

Keywords

  • Computational framework
  • Crop yield
  • Integration
  • Model
  • Multiscale

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