Predicting flowering time using integrated morphophysiological and genomic data with machine learning models
Mehdi Babaei, Hossein Nemati, Hossein Arouiee, Davoud Torkamaneh
This study uses machine learning to classify flowering time in Cannabis landraces by integrating genomic and morphophysiological data, achieving 96.6% accuracy.
Scientific Reports · May 21, 2026Peer-reviewedPlant Biology