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Abstract
The increased uptake of sensor technologies and precision farming tools for the dairy cattle sector is enabling real-time monitoring of animal health, welfare,
and productivity. These digital advancements provide high-frequency, objective, and large-scale phenotypic data for breeding purposes. This review explores the
potential of sensor-derived data to improve genetic and genomic evaluations in dairy cattle and outlines key challenges, opportunities, and approaches associated with their implementation. While these data streams have great potential for genetic evaluations, their integration into national and international breeding programs remains limited due to fragmentation across sensor brands, lack of standardization, and challenges related to data accessibility, data access and portability rights, business interests, and governance. A crucial aspect of leveraging digital technologies in dairy cattle breeding is data harmonization and integration. We highlight the importance of establishing standardized data collection and data sharing protocols, implementing robust quality control and data cleaning methodologies, as well as defining novel sensor-based traits and estimating their genetic background. In this context, we compiled heritability estimates for novel traits derived from data recorded by sensors and other technologies in dairy cattle populations. The development of phenomics in breeding programs, which involves integrating multisource data—including sensor-based, genomic, and management
information—will be key to accelerating genetic progress, especially for traits related to animal welfare, health, resilience, and efficiency. This review presents
a roadmap for the effective use of sensor-derived data in genetic evaluations, advocating for centralized data infrastructures, transparent data-sharing agreements, and the role of different stakeholders from academia and industry, including organizations such as the International Committee on Animal Recording (ICAR) in establishing global standards and guidelines. By addressing
these challenges, dairy breeding programs can fully harness precision dairy farming technologies to enhance production and environmental efficiency, improve animal health and welfare, and drive sustainable genetic advancements in the dairy cattle sector.
and productivity. These digital advancements provide high-frequency, objective, and large-scale phenotypic data for breeding purposes. This review explores the
potential of sensor-derived data to improve genetic and genomic evaluations in dairy cattle and outlines key challenges, opportunities, and approaches associated with their implementation. While these data streams have great potential for genetic evaluations, their integration into national and international breeding programs remains limited due to fragmentation across sensor brands, lack of standardization, and challenges related to data accessibility, data access and portability rights, business interests, and governance. A crucial aspect of leveraging digital technologies in dairy cattle breeding is data harmonization and integration. We highlight the importance of establishing standardized data collection and data sharing protocols, implementing robust quality control and data cleaning methodologies, as well as defining novel sensor-based traits and estimating their genetic background. In this context, we compiled heritability estimates for novel traits derived from data recorded by sensors and other technologies in dairy cattle populations. The development of phenomics in breeding programs, which involves integrating multisource data—including sensor-based, genomic, and management
information—will be key to accelerating genetic progress, especially for traits related to animal welfare, health, resilience, and efficiency. This review presents
a roadmap for the effective use of sensor-derived data in genetic evaluations, advocating for centralized data infrastructures, transparent data-sharing agreements, and the role of different stakeholders from academia and industry, including organizations such as the International Committee on Animal Recording (ICAR) in establishing global standards and guidelines. By addressing
these challenges, dairy breeding programs can fully harness precision dairy farming technologies to enhance production and environmental efficiency, improve animal health and welfare, and drive sustainable genetic advancements in the dairy cattle sector.
| Original language | English |
|---|---|
| Article number | 26554 |
| Pages (from-to) | 10447-10474 |
| Number of pages | 28 |
| Journal | Journal of Dairy Science |
| Volume | 108 |
| Issue number | 10 |
| Early online date | 20 Aug 2025 |
| DOIs | |
| Publication status | Print publication - Oct 2025 |
Bibliographical note
The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).Keywords
- genetic parameters
- genomic selection
- heritability
- novel traits
- precision livestock farming
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Dive into the research topics of 'Invited review: Using data from sensors and other precision farming technologies to enhance the sustainability of dairy cattle breeding programs'. Together they form a unique fingerprint.Projects
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RESAS 22-27: SRUC-a3-2 Eu Exit ? Challenges And Opportunities For Animal Welfare.
D'Eath, R. (PI), Donbavand, J. (CoI), Lawrence, A. (CoI), Akaichi, F. (CoI), Dwyer, C. (CoI), Wemelsfelder, F. (CoI), Turner, S. (CoI), Haskell, M. (CoI), Baxter, E. (CoI) & Rutherford, K. (CoI)
Scottish Government: Rural & Environment Science & Analytical Services
1/04/22 → 31/03/27
Project: Research