Integrative phenomics, metabolomics and genomics analysis provides new insights for deciphering the genetic basis of metabolism in polished rice
Our findings indicate that hyperspectral imaging combined with machine learning methods could serve as a powerful tool for quickly and inexpensively assessing crop metabolites.
Authors
- Jiawei Shi (ORCID: https://orcid.org/0000-0001-6303-0061)
- Wanneng Yang (ORCID: https://orcid.org/0000-0003-1095-1355)
- Yuan Gao (ORCID: https://orcid.org/0000-0003-2374-7580)
- Luis A. J. Mur (ORCID: https://orcid.org/0000-0002-0961-9817)
- Zhuang Yang (ORCID: https://orcid.org/0000-0003-3886-1044)
- Yongqi Chen (ORCID: https://orcid.org/0000-0002-5929-8118)
- Guoxin Dai (ORCID: https://orcid.org/0009-0002-2062-4972)
- Yufei Li (ORCID: https://orcid.org/0000-0003-2783-6468)
- Jingyan Song
- Lejun Yu (ORCID: https://orcid.org/0000-0002-3611-1103)
- Bingjie Lu
- Hui Feng (ORCID: https://orcid.org/0000-0002-0570-5718)
Institutions
- Aberystwyth University (GB)
- Huazhong Agricultural University (CN)
- Hainan University (CN)
- Sanya University (CN)
- Hainan Medical University (CN)
Publication Details
- Journal
- Genome biology
- Published
- 2025-03-12
- DOI
- https://doi.org/10.1186/s13059-025-03513-w
- Citations
- 8
- Primary Topic
- GABA and Rice Research
- Type
- article
- Field-Weighted Citation Impact
- 14.00
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Fundamental Research Funds for the Central Universities
- Wuhan Science and Technology Project