Nuria De Diego

LOCOPOTS identifies stress-resilient potato genotypes using low-cost imaging and machine learning, revealing metabolic biomarkers for abiotic stress responses.

The paper uses a hyperbolic topological atlas to analyze Arabidopsis rosette development under different polyamine and nutrient conditions, revealing how these factors influence developmental trajectories.

The paper shows that increasing polyamine thermospermine transport with cytokinin reprograms xylem identity from woody to fleshy in Arabidopsis.

AMULET predicts plant phenotypes using imaging and machine learning before visible changes occur, improving breeding and agricultural management.