In order to enhance the sustainability of crop systems, it is crucial to select plant root systems that are well adapted to specific environments. To achieve this, a comprehensive understanding of the underlying traits is essential, which can be done by testing dynamically the development of in silico plants. In this study, we constructed a structured network by integrating various models ranging from the cellular level to the plant scale. This network enabled us to virtually simulate water flow dynamics in the soil-plant system over a period of 50 days. Specifically, we generated a population of 7168 maize plants (Zea mays var. B73) under three distinct pedological conditions, while also considering high evaporative demand and water-limiting conditions. Through our analyses, we identified that the root radius of zero-order roots and the contribution of aquaporins to cell membrane permeability were the most influential variables affecting root water uptake in these in silico phenotypes. These findings shed light on the key anatomical traits that significantly impact the water uptake efficiency of plants under specific pedoclimatic constraints. Overall, our novel modelling pipeline demonstrated its capability to estimate optimal anatomical traits for plants based on the pedoclimatic conditions. This approach provides valuable insights for designing plant root systems that are better suited to individual environments, ultimately contributing to the advancement of sustainable agriculture practices.
Heymans, A., Couvreur, V., & Lobet, G. (2023). Multi-scale Analysis of Water Flow Determinants in the Soil Root System. Rank Prize Symposium, Grasmere, UK. https://hdl.handle.net/2078.5/239977