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Testing AI Against Traditional Models for Predicting Cattle Feed Efficiency
Jenn Hoskins
18th March, 2024
![Testing AI Against Traditional Models for Predicting Cattle Feed Efficiency](https://static.naturalsciencenews.com/images/articles/756_main.jpg)
Key Findings
- Study from São Paulo State University found new ways to predict cattle feed efficiency
- Machine learning methods outperformed traditional genetic prediction methods
- These methods could lead to more sustainable cattle breeding practices
References
Main Study
1) Benchmarking machine learning and parametric methods for genomic prediction of feed efficiency-related traits in Nellore cattle.
Published 17th March, 2024
https://doi.org/10.1038/s41598-024-57234-4
Related Studies
2) A guide for kernel generalized regression methods for genomic-enabled prediction.
3) Efficient weighting methods for genomic best linear-unbiased prediction (BLUP) adapted to the genetic architectures of quantitative traits.
4) Multitrait genomic prediction of methane emissions in Danish Holstein cattle.
5) Weighted single-step genome-wide association study and pathway analyses for feed efficiency traits in Nellore cattle.