Transformer-Based Phenotyping of Rice Root Aerenchyma Across Environments Enables Climate-Smart Rice Selection
Hani Atef, Laura Fierro-Dominguez, Paula Andrea Lozano-Montaña, Sergi Navarro Sanz, Julie Bals, Benoît Clerget, Christophe Périn, María Camila Rebolledo, Romain Fernandez
This paper develops a transformer-based deep learning pipeline to automate aerenchyma quantification in rice roots across environments, achieving expert-level accuracy and supporting climate-smart breeding.
bioRxiv · Feb 3, 2026 · PreprintPhysiology