Research on the prediction model of mastitis in dairy cows based on time series characteristics
The XGBoost model demonstrates strong potential as an accurate predictive tool for subclinical mastitis in dairy cows. This study presents an effective early-warning approach through time-series modeling that offers significant practical value for mastitis prevention in dairy farm management.
Authors
- Junjie Hu (ORCID: https://orcid.org/0000-0002-1911-4361)
- Rui Guo (ORCID: https://orcid.org/0000-0001-6908-1724)
- Yongqiang Dai (ORCID: https://orcid.org/0000-0002-4200-964X)
Institutions
- Gansu Agricultural University (CN)
Publication Details
- Journal
- Frontiers in Veterinary Science
- Published
- 2025-04-24
- DOI
- https://doi.org/10.3389/fvets.2025.1575525
- Citations
- 8
- Primary Topic
- Milk Quality and Mastitis in Dairy Cows
- Type
- article
- Field-Weighted Citation Impact
- 15.22
Funders
- Natural Science Foundation of Gansu Province