|EAGLEN, SOPHIE - National Association Of Animal Breeders|
|MALTECCA, CHRISTIAN - North Carolina State University|
|MULDER, HERMAN - Wageningen University And Research Center|
|PRYCE, JENNIE - La Trobe University|
Submitted to: Animal Frontiers
Publication Type: Review Article
Publication Acceptance Date: 1/31/2020
Publication Date: 4/1/2020
Citation: Cole, J.B., Eaglen, S.A.E., Maltecca, C., Mulder, H.A., Pryce, J.E. 2020. The future of phenomics in dairy cattle breeding. Animal Frontiers. 10(2):37-44. https://doi.org/10.1093/af/vfaa007.
Interpretive Summary: In order to meet the growing worldwide demand for animal-sourced protein it is essential that the dairy industry make the most efficient use possible of the cow’s ability to upcycle inedible plant matter. This will require the efficient use of all inputs needed on the farm, reduction of undesirable outputs from animal agriculture, high-quality management of cows and their environment, and assurances to consumers that dairy animals are healthy and well-cared-for. Innovative technologies based on low-cost sensors and cutting-edge data analysis tools will be necessary to meet those objectives. This work reviews the current literature related to deep-phenotyping of dairy cattle, identifies opportunities and challenges associated with new technology for measuring animal performance, and discusses how these promising new tools may be applied in practice.
Technical Abstract: Increasingly complex dairy cattle production systems require that all aspects of animal performance are measured across individuals’ lifetimes. Selection emphasis is shifting away from traits related to animal productivity towards those related to efficient resource utilization. The goal of phenomics is to provide information for making decisions related to on-farm management, as well as genetic improvement. This work will review the current literature related to deep-phenotyping of dairy cattle, identify opportunities and challenges associated with new technology for measuring animal performance, and discuss how these promising new tools may be applied in practice.