crossrefAgronomy2025-06-30
Enhancing Registration Offices’ Communication Through Interpretable Machine-Learning Techniques
Danilo Augusto Sarti, Tommaso Bardelli, Pier Giacomo Bianchi, Anna Pia Maria Giulini
This study presents a protocol for applying Interpretable Machine Learning (IML) to enhance communication within Variety Registration Offices (VROs). Rather than focusing on a model comparison, we illustrate how two IML-compatible models—Random Forests and AMBARTI—can support a c…