Evaluating UAV-based phenotyping strategies for Megathyrsus maximus
, demonstrating that combining advanced digital traits with machine learning accurately predicts key agronomic traits and significantly enhances genotype selection efficiency in forage breeding programs.
Authors
- Guilherme Francio Niederauer (ORCID: https://orcid.org/0000-0002-3032-778X)
- Alexandre Hild Aono (ORCID: https://orcid.org/0000-0003-4871-6625)
- Liana Jank (ORCID: https://orcid.org/0000-0001-9436-3678)
- Anete Pereira de Souza (6670913)
- Celina de Medeiros Ragalzi
- Mateus Figueiredo Santos
Institutions
- Universidade Estadual de Campinas (UNICAMP) (BR)
- Brazilian Agricultural Research Corporation (BR)
- Swedish University of Agricultural Sciences (SE)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2026-04-22
- DOI
- https://doi.org/10.3389/fpls.2026.1798414
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00