A breeder in the sky: scoring flowering with fewer flights
Zhongjie Ji, Aaron J. DeSalvio, Alper Adak, Mustafa Arık, David Ertl, Shawn M. Kaeppler, Jode W. Edwards, Sherry A. Flint-Garcia, Candice N. Hirsch, Addie M. Thompson, Jacob D. Washburn, Natalia de León, Bijesh Maharjan, Dipak Santra, Pascal Izere, , James C. Schnable
This paper introduces a regression-based framework to predict flowering time from sparse UAV observations, reducing the need for repeated data collection.
bioRxiv · Sep 22, 2026 · PreprintPlant Biology