16 Opportunities and challenges from deep-phenotyping of dairy cattle

John B. Cole, Sophie A.E. Eaglen, Christian Maltecca, Han A. Mulder, Jennie Pryce

Research output: Contribution to journalAbstractAcademic


Genetic selection has been a very successful tool for the long-term improvement of livestock populations, and the rapid adoption of genomic selection over the last decade has doubled the rate of gain in some populations. However, the full expression of genetic potential requires that animals are placed in environments that support such performance. 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 and increased animal welfare. However, phenotypes for many of these new traits are difficult or expensive to measure, or both. This is driving interest in sensor-based systems that provide continuous measurements of the farm environment, individual animal performance, and detailed milk composition. The goal of phenomics is to provide information for making decisions related to on-farm management, as well as genetic improvement. However, many challenges accompany these new technologies, including a lack of standardization, the need for high-speed Internet connections, increased computational requirements, and training to integrate these tools with more traditional management tools. There also is a lack of translational research on the use of these data for real-time precision management. We will identify opportunities and challenges associated with phenomics and discuss on-farm applications of these new tools.
Original languageEnglish
Pages (from-to)5-6
JournalJournal of Animal Science
Issue numberSupplement_4
Publication statusPublished - 30 Nov 2020


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