Invited review: Milking the data for value-driven dairy farming
Precision dairy farming is rapidly transforming the global dairy sector through the application of data-driven technologies. This review explores current knowledge and emerging ideas across 5 key areas: (1) the economic value of data, highlighting its role in optimizing productivity and profitability; (2) advances in integrating artificial intelligence (AI), sustainability, and innovation, showcasing how these elements drive efficiency; (3) the drivers and barriers to technology adoption, data integration, and connectivity, identifying factors that enable or hinder progress; (4) sustainable data stewardship, addressing governance, standardization, and ethical concerns to ensure responsible data use; and (5) cross-sector insights from healthcare that can inform and strengthen dairy practices. It also provides recommendations for the dairy industry stakeholders on how best to promote, apply, and benefit from data-driven technologies in dairy farming. Emerging technologies such as AI, sensor-based monitoring, and automation are discussed for their potential to disrupt traditional practices and open new possibilities in dairy management. To advance the dairy industry and maximize the value of these technologies, it is essential to prioritize sustainable data stewardship, ensure clear data ownership, and uphold robust cybersecurity measures. Equally important is the need for increased investment in data infrastructure and the integration of computer science into agricultural and veterinary education. Effective interdisciplinary collaboration and structured support for technology adoption are critical to achieving these goals. Emphasizing practical opportunities and challenges, the review offers a forward-looking perspective on shaping a resilient, efficient, and technology-driven dairy industry.
Authors
- Víctor E. Cabrera (ORCID: https://orcid.org/0000-0003-1739-7457)
- Hélène Soyeurt (ORCID: https://orcid.org/0000-0001-9883-9047)
- Enhong Liu
- J.M. Bewley (ORCID: https://orcid.org/0000-0002-7347-2741)
- Michael Iwersen (ORCID: https://orcid.org/0000-0001-7893-6050)
- Sumit Sharma (ORCID: https://orcid.org/0000-0002-4824-7569)
- Meike van Leerdam
- M. Hostens
- Rebeca Villalobos-Barquero
- Joao R.R. Dorea (ORCID: https://orcid.org/0000-0001-9849-7358)
- Haowen Hu
Institutions
- University of Wisconsin–Madison (US)
- Cornell University (US)
- Gembloux Agro-Bio Tech (BE)
- New York State College of Agriculture & Life Sciences (US)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Journal of Dairy Science
- Published
- 2026-02-01
- DOI
- https://doi.org/10.3168/jds.2025-27011
- Primary Topic
- Milk Quality and Mastitis in Dairy Cows
- Type
- article
- Field-Weighted Citation Impact
- 0.00