Dynamiske prediksjoner og ressursallokeringer i global matprodukjson

Offentlig prosjektsammendrag

This project aims to enhance the Sensonomic agribusiness platform by integrating new data crucial for crop development and regenerative agriculture. The main goal is to adapt the platform to better predict yields and manage resources for new crops, while also supporting regenerative agricultural practices, which lack clear metrics in fresh fruit cultivation. Key challenges include identifying critical phenological stages, defining regenerative practices, and integrating diverse data sources such as third-party sensors. The project will employ methods such as consulting agricultural experts, re-parameterizing mechanistic and data-driven prediction and resource allocation models, user-centered app design, and leveraging machine learning for algorithm development. By reconfiguring the platform and building new integrations, the project will ultimately support sustainable agricultural practices and improve crop management and yield predictions.