DIRECTION – Data science driven leaf architecture optimization

Photosynthesis, the biochemical process that converts carbon dioxide and water into oxygen and sugars in plant leaves, is the vital process to crop yield and life on Earth. Optimization of photosynthesis is there-fore of crucial importance to an improved agriculture, but has largely focused on enhancing the bio-chemical reaction. However, the architecture of leaf cells critically supports photosynthesis as it allows for efficient exchange of carbon dioxide, water vapor and oxygen. Here, we take a new perspective on photosynthesis by using a multi-scale framework that bridges machine learning and mechanistic model-ling with biology to optimize the leaf cell architecture. The outcomes may provide new targets to enhance photosynthesis, much needed for biotechnological advances. Furthermore, enhancing photosynthesis-driven carbon sequestration would contribute substantially to the ambitious Danish governmental agenda to reach carbon neutrality by 2050.