Biomarker genes for model-based prediction of drought-stress perception levels in rice
We identified DSBM genes and developed a machine learning model as a robust tool for assessing drought-stress perception levels in rice. Monitoring and predicting drought-stress perception levels should contribute to more efficient crop management and breeding schemes. Furthermore, our dataset would serve as a resource for further understanding the mechanisms of drought resistance in rice.
Authors
- Shota Teramoto (ORCID: https://orcid.org/0000-0001-6295-2208)
- Yusaku Uga (ORCID: https://orcid.org/0000-0003-4006-954X)
- Yuko Numajiri (ORCID: https://orcid.org/0000-0001-8119-9848)
- R. Tanaka (ORCID: https://orcid.org/0000-0002-3479-377X)
- Taiji Kawakatsu (ORCID: https://orcid.org/0000-0002-6871-9199)
- Kanami Yoshino (ORCID: https://orcid.org/0000-0002-5279-4864)
- Yuka Kitomi
- Saki Yoshida (ORCID: https://orcid.org/0009-0004-9160-6776)
Institutions
- Tokyo University of Agriculture (JP)
- National Agriculture and Food Research Organization (JP)
- Utsunomiya University (JP)
- Institute of Agrobiological Sciences (JP)
- RIKEN BioResource Research Center (JP)
Publication Details
- Journal
- BMC Plant Biology
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1186/s12870-025-07175-5
- Primary Topic
- Plant responses to water stress
- Type
- article
- Field-Weighted Citation Impact
- 0.00