Invited review: Using data from sensors and other precision farming technologies to enhance the sustainability of dairy cattle breeding programs
Elsevier
2025
Brito_etal_2025_JDairySci_Sensor_data.pdf - Publisher's version - 703.34 KB
How to cite: Luiz F. Brito, Bjørg Heringstad, Ilka Christine Klaas, Katharina Schodl, Victor E. Cabrera, Anna Stygar, Michael Iwersen, Marie J. Haskell, Kathrin F. Stock, Nicolas Gengler, Jeffrey Bewley, Miel Hostens, Elsa Vasseur, Christa Egger-Danner, Invited review: Using data from sensors and other precision farming technologies to enhance the sustainability of dairy cattle breeding programs, Journal of Dairy Science, Volume 108, Issue 10, 2025, Pages 10447-10474, https://doi.org/10.3168/jds.2025-26554.
Pysyvä osoite
Tiivistelmä
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.
ISBN
OKM-julkaisutyyppi
A2 Katsausartikkeli tieteellisessä aikakauslehdessä
Julkaisusarja
Journal of dairy science
Volyymi
108
Numero
10
Sivut
Sivut
10447-10474
ISSN
0022-0302
1525-3198
1525-3198
