Research:2026-05-21/Journal article/integrating-temporal-morphophysiological-and-genomic-markers-for-precise-classification-of-flowering-time-in-c

21 May 2026 Journal article

Iran

Integrating temporal morphophysiological and genomic markers for precise classification of flowering time in cannabis

Mehdi Babaei, Hossein Nemati, Hossein Arouiee, Davoud Torkamaneh

Scientific Reports · 2026

Classifies flowering time across 25 Iranian Cannabis landrace populations, 145 accessions in total, by integrating temporal morphophysiological measurement with genomic and environmental data. Machine-learning integration of 234,002 features separated autoflowering from photoperiod-sensitive material and identified validated markers at CsFTL3 and CsCFL1. The panel is the same Iranian landrace collection behind the record of Babaei and Torkamaneh's trait-architecture study, which this analysis extends to flowering time specifically.

Source DOI

2026-05-21 2026-08-08 Integrating temporal morphophysiological and genomic markers for precise classification of flowering time in cannabis Journal article Mehdi Babaei, Hossein Nemati, Hossein Arouiee, Davoud Torkamaneh Scientific Reports 2026 10.1038/s41598-026-53686-y https://doi.org/10.1038/s41598-026-53686-y Classifies flowering time across 25 Iranian Cannabis landrace populations, 145 accessions in total, by integrating temporal morphophysiological measurement with genomic and environmental data. Machine-learning integration of 234,002 features separated autoflowering from photoperiod-sensitive material and identified validated markers at CsFTL3 and CsCFL1. The panel is the same Iranian landrace collection behind the record of Babaei and Torkamaneh's trait-architecture study, which this analysis extends to flowering time specifically. Iran