News: How Biophysical Modelling Is Revolutionizing Plant Science and Engineering.
- Manuel Basegla
- Oct 31
- 2 min read
Published 11:50 AM EST, Fri Oct 31, 2025
Biophysical and computational models are transforming how we understand plant growth, connecting molecular signals to the dynamics of entire organisms. By simulating genetic, metabolic, and physiological processes, researchers can predict plant behavior and design smarter strategies for sustainable agriculture.
Plant scientists are increasingly turning to computers and mathematics to unravel the hidden complexity of plant growth and development. From the molecular level of genes and hormones to the intricate architecture of tissues and entire organisms, researchers are working to connect how plants build themselves and adapt to their environment. While experiments have revealed many of the key players, such as hormone pathways, gene networks, and metabolic reactions, scientists say the next challenge is understanding how these pieces work together as one system.
To meet that challenge, new modelling approaches are stepping into the spotlight. Using mathematical and computational tools, researchers can now simulate everything from gene regulation and cell division to nutrient flow and leaf formation. Reaction–kinetic and Boolean models help decode molecular signaling, while geometry-based and mechanical models explain how plants shape their tissues. Meanwhile, metabolic and hydraulic simulations map how plants move and allocate resources. These digital blueprints allow scientists to make predictions, test “what-if” scenarios, and guide future experiments more efficiently.
By blending different modelling strategies, researchers hope to create a complete picture of plant life from the smallest molecule to the full-grown plant. This integrative approach could help improve stress tolerance, boost growth under limited nutrients, and even design plants with specific traits. It represents a step toward precision biology, where data-driven insights can help agriculture and biotechnology meet the demands of a changing world.
The cannabis industry stands to gain significantly from these advances. Predictive plant models could help growers fine-tune lighting, nutrients, and environmental conditions to enhance cannabinoid and terpene production. Computational tools might also guide breeding programs by forecasting how genetic changes influence potency, flavor, and resilience. In tissue culture and propagation, mechanical and physiological models could improve cloning success and plant regeneration. As modelling technologies evolve, they could help transform cannabis cultivation into a high-tech, resource-efficient, and scientifically optimized enterprise. Source: Frontiers
