Papers

5

Total Citations

59

H-Index

4

About

Xiangyu Song’s research sits at the intersection of precision livestock farming and advanced materials engineering, with a primary focus on dairy cow health monitoring. His most impactful work introduces a groundbreaking 3-dimensional vision system to automatically assess reticulo-ruminal motility in dairy cows—a critical indicator of gastrointestinal health. This innovation, detailed in his highly cited 2019 paper (41 citations), replaces labor-intensive, costly traditional methods with a practical, automated solution suitable for routine farm use. Song further demonstrated the system’s value in a longitudinal study (2022, 5 citations), linking automated rumen function assessments to feed changes and milk production, thereby offering farmers actionable insights for herd management. Earlier, he contributed to automatic detection of clinical mastitis in robotic milking systems (2010, 6 citations). Beyond animal science, Song explores novel materials for dielectric elastomer actuators, developing sodium alginate composite films with oxidized MWCNTs (2024, 5 citations) and SEBS elastomers with barium titanate nanoparticles (2025, 2 citations) for applications in bionic robotics and wearable electronics. His cross-disciplinary work—combining computer vision, animal health, and materials science—showcases a unique ability to solve practical agricultural challenges through technological innovation.

Research Focus

Key Achievements

4
H-Index
5
Papers
59
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Hot topic: Automated assessment of reticulo-ruminal motility in dairy cows using 3-dimensional vision
41 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Lely (Netherlands), Zhengzhou University of Light Industry, Wageningen University & Research

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago