Benoît Clerget

This study investigates the role of daylength in sorghum flowering, finding that daily changes in sunrise and sunset times (dSR/dSS) are more significant than daylength alone.

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.