A sorghum seed variety identification method based on image–hyperspectral fusion and an improved deep residual convolutional network
These results confirm that the proposed model can accurately and non-destructively classify sorghum seed varieties. The method offers a dependable and efficient approach for seed screening and has practical value in agricultural applications.
Authors
- Yihan Chen (ORCID: https://orcid.org/0000-0003-2085-9480)
- Shaozhong Song (ORCID: https://orcid.org/0009-0004-6807-779X)
- Zhimin Zhang (ORCID: https://orcid.org/0000-0002-0531-9112)
- Yang Xu (ORCID: https://orcid.org/0009-0000-9798-0903)
Institutions
- Changchun University of Science and Technology (CN)
- Jilin Engineering Normal University (CN)
- Jilin Academy of Agricultural Sciences (CN)
- Changchun University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-08-22
- DOI
- https://doi.org/10.3389/fpls.2025.1632698
- Primary Topic
- Spectroscopy and Chemometric Analyses
- Type
- article
- Field-Weighted Citation Impact
- 0.00