Simulation Intelligence Approaches in Plant Sciences

Simulation intelligence approaches, including artificial intelligence (AI), machine learning (ML), deep learning (DL), and computational modeling, have revolutionized plant sciences by enabling precise predictions, optimizing agricultural practices, and improving plant health monitoring. These technologies facilitate the simulation of plant growth, crop yield prediction, plant–environment interactions, and disease management. AI-driven digital twins and virtual plant models provide insights into plant physiology and adaptation strategies, while genomic and systems biology applications enhance our understanding of plant genetics. Despite challenges such as data complexity and ethical concerns, the integration of simulation intelligence with plant sciences holds immense potential for advancing precision agriculture, enhancing sustainability, and ensuring global food security. This chapter explores the diverse applications of AI-driven simulations in plant research and discusses their future implications in agricultural and environmental sciences.