The Digital Agricultural Avatar is a digital twin of the agricultural system ultimately encompassing interacting process based models of the biogeochemical, and -physical, agricultural management and economic components. They simulate how crops respond to various environmental challenges, offering a sneak peek into the future of our crops. It’s like having a virtual test field, helping farmers make informed decisions. DAA integrates diverse models, from detailed organ-specific analysis to comprehensive field-scale evaluations. Our models include:

1. 🌾 GRANAR and MECHA: For anatomical network generation of root cells and Organ-level simulation.
2. 🌍 CPlantBox: Detailed plant structure modeling, encompassing roots and shoots.
3. 🌦️ SCOPE: Simulates radiative transfer and photosynthesis in vegetation canopies, integrating satellite observations with land surface processes.
4. 💧 AgroC: Focused on carbon dynamics within agricultural soil at crop scale.
5. 🚜 SIMPLACE: Simulates interactions among crops, soil, and climate at crop scale.
6. 🌾 TerrSysMP: Simulates land-atmosphere interactions at continental scales.

The Digital Agricultural Avatar aims to be a sophisticated modeling framework designed to enhance agricultural decision-making by providing high-resolution data and predictions for crop management at the scale of 50 meters. This platform integrates real-time sensor data, advanced modeling techniques, and forecasts to optimize agricultural practices and resource management. We aim to intertwine models like GRANAR, MECHA, CPlantBox, AgroC, SIMPLACE, SCOPE and TerrSysMP, to forge a comprehensive understanding of agricultural processes. This integration is important for unraveling the complexities of agricultural ecosystems, from the microcosm of root cell anatomies to the macrocosm of land-atmosphere interactions. Highlighting examples of ongoing coupling efforts, such as linking GRANAR’s detailed root anatomies with CPlantBox’s whole-plant models, and integrating AgroC’s insights on carbon dynamics with TerrSysMP’s large-scale environmental simulations, PhenoRob DAA aims to advance predictive power in agricultural science and precision farming.

1. 🌾 High-Resolution Forecasting: We aim to forecase agricultural systems at resolutions finer than 50 meters, allowing for precise agricultural planning and management.
2. 🌍 Real-Time Data Integration: Our models will continously update its simulation with real-time sensor data from various sources, including drones and remote sensors, to improve accuracy and responsiveness of the forecasts.
3. 🌦️ Multiscale Modeling: Our modeling aresenal will operate across multiple scales, from continental to local, ensuring that users can apply the model effectively across different geographic domains.