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Invited review: Milking the data for value-driven dairy farming
Sumit Sharma1, Enhong Liu1, Meike van Leerdam1
1Department of Animal Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY 14853.
Journal of Dairy Science
|February 12, 2026
Summary
Precision dairy farming uses data-driven technologies to boost productivity and profitability. Key areas include AI integration, technology adoption, data stewardship, and cross-sector insights for a resilient dairy industry.
Area of Science:
- Agricultural Technology
- Data Science in Agriculture
- Dairy Management Systems
Background:
- Precision dairy farming leverages data-driven technologies to transform the global dairy sector.
- The integration of artificial intelligence (AI), sustainability, and innovation is crucial for enhancing efficiency.
Purpose of the Study:
- To review current knowledge and emerging ideas in precision dairy farming.
- To provide recommendations for stakeholders on adopting data-driven technologies.
Main Methods:
- Exploration of key areas: economic value of data, AI integration, technology adoption drivers/barriers, sustainable data stewardship, and healthcare cross-sector insights.
- Discussion of emerging technologies like AI, sensor-based monitoring, and automation.
Main Results:
- Data optimization enhances productivity and profitability.
- AI, sustainability, and innovation drive efficiency in dairy farming.
- Understanding adoption drivers/barriers and ensuring sustainable data stewardship are critical.
Conclusions:
- Prioritizing sustainable data stewardship, clear data ownership, and cybersecurity is essential.
- Investment in data infrastructure and interdisciplinary collaboration are vital for advancing the dairy industry.
- A forward-looking perspective is needed to shape a resilient, efficient, and technology-driven dairy sector.
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