Using preprocessed datasets to construct and interpret multiclass identification models
This study expands the applicability of image and NIR spectroscopic data, offering researchers an effective methodology for investigating factors crucial to the quality control and improvement of agricultural products.
Authors
- Shengtao Ma (ORCID: https://orcid.org/0000-0001-8959-4260)
- Yufeng Fu (ORCID: https://orcid.org/0000-0001-7095-0472)
- Zhicai Wang (ORCID: https://orcid.org/0000-0002-3186-2135)
- Cong Nie
- Wei Huang (ORCID: https://orcid.org/0000-0002-4985-9911)
- Qiang Liu (ORCID: https://orcid.org/0000-0001-7668-622X)
- Shan Li (ORCID: https://orcid.org/0000-0002-0824-251X)
- Cong Wang (ORCID: https://orcid.org/0000-0002-4106-6108)
- Hongbo Wang (ORCID: https://orcid.org/0000-0001-5003-3124)
- Song Yang (ORCID: https://orcid.org/0000-0003-2372-694X)
- J. Guo (ORCID: https://orcid.org/0000-0002-6402-2124)
- R. Wan
- Le Zhao
- Huimin Liu (ORCID: https://orcid.org/0009-0007-0175-3476)
Institutions
- China Tobacco (CN)
- Tobacco Research Institute (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-08-20
- DOI
- https://doi.org/10.3389/fpls.2025.1597673
- Primary Topic
- Spectroscopy and Chemometric Analyses
- Type
- article
- Field-Weighted Citation Impact
- 0.00