Plant science in the age of simulation intelligence

Area of Science:

• Plant and crop sciences
• Computational biology
• Agricultural technology

Background:

• Plant and crop sciences traditionally rely on mechanistic or statistical modeling.
• A gap exists in integrating these approaches for complex system analysis.
• Simulation intelligence emerges as a unifying paradigm.

Purpose of the Study:

• To explore the nine motifs of simulation intelligence in plant and crop sciences.
• To highlight the transformative potential of simulation intelligence.
• To identify underexplored areas within simulation intelligence for future research.

Main Methods:

• Review and conceptualization of simulation intelligence motifs.
• Application of motifs to diverse plant science problems, from molecular processes to greenhouse control.
• Discussion of existing and novel simulation intelligence techniques.

Main Results:

• Simulation intelligence offers a powerful framework for understanding and controlling plant and crop systems.
• Motifs like surrogate models and agent-based modeling are increasingly adopted.
• Areas such as open-ended optimization and program synthesis require further investigation.

Conclusions:

• Simulation intelligence holds significant potential to advance plant and crop sciences.
• This approach can drive innovation in breeding and precision farming.
• Adoption of simulation intelligence can contribute to more sustainable food production.