Sorghum yield prediction using UAV multispectral imaging and stacking ensemble learning in arid regions
Integrating UAV multispectral data with machine learning methods enables efficient sorghum yield prediction, with the jointing stage identified as the optimal monitoring period. This study provides crucial technical support for precision planting and efficient sorghum management in arid regions.
Authors
- Yihua Yan (ORCID: https://orcid.org/0000-0002-7106-6029)
- Wuping Zhang
- Xifeng Liu (ORCID: https://orcid.org/0000-0002-2684-6309)
- Juanjuan Mu
- Yaoyu Li (ORCID: https://orcid.org/0000-0002-7362-7897)
- Zhimin Zhang (ORCID: https://orcid.org/0000-0002-0622-7789)
- Shujie Jia
- Linqiang Deng
Institutions
- Shanxi Agricultural University (CN)
- Jinzhong University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-10-09
- DOI
- https://doi.org/10.3389/fpls.2025.1636015
- Citations
- 2
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 3.43