UAV-based multispectral image analysis revealed stay-green haplotypes in wheat specific for different soil nitrogen levels
The newly identified stay-green haplotypes can be further used for fine-mapping and identifying the underlying genes as well as for selecting for higher stay-green and grain yield. Thereby our results can contribute to improving our understanding of the complex genetic regulation underlying stay-green in different environments and to breeding new cultivars with stable performance across N levels or specifically under low N availability.
Authors
- Helen Behn
- Annaliese S. Mason (ORCID: https://orcid.org/0000-0003-2701-7964)
- Agim Ballvora (ORCID: https://orcid.org/0000-0003-0949-8311)
- Mohammad Bahman Sadeqi (ORCID: https://orcid.org/0000-0002-8991-812X)
- Facundo Ramón Ispizua Yamati (ORCID: https://orcid.org/0000-0001-5775-3554)
- Uwe Rascher (ORCID: https://orcid.org/0000-0002-9993-4588)
- Juliane Bendig (ORCID: https://orcid.org/0000-0002-6454-5654)
- Anne‐Katrin Mahlein (ORCID: https://orcid.org/0000-0003-1091-3690)
- Jens Léon (ORCID: https://orcid.org/0000-0002-6514-3112)
- Ahossi Patrice Koua (ORCID: https://orcid.org/0000-0001-9949-2137)
Institutions
- University of Bonn (DE)
- Forschungszentrum Jülich (DE)
- Institute of Sugar Beet (CN)
- Klein Buendel (United States) (US)
Publication Details
- Journal
- BMC Plant Biology
- Published
- 2025-10-21
- DOI
- https://doi.org/10.1186/s12870-025-07441-6
- Citations
- 3
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 5.15
Funders
- Leibniz-Gemeinschaft