Asja Ebinghaus
Papers
1
Total Citations
28
H-Index
1
About
Asja Ebinghaus is a researcher whose work sits at the intersection of dairy science, animal behavior, and precision livestock farming. Her key research areas focus on utilizing data from automatic milking systems (AMS) to improve animal welfare and herd management. Her most notable contribution is a pioneering 2018 study that estimated genetic parameters for behavioral and health indicator traits generated by AMSs. By analyzing over 70,700 observations from 922 Holstein cows across a 30-day period, she demonstrated that traits like milking speed, visit frequency, and step-kick behavior are heritable and can be used for genetic selection. This work, which has garnered 28 citations, provides a foundation for breeding cows better adapted to automated systems while improving health monitoring. Ebinghaus’s research bridges quantitative genetics and practical dairy management, offering a data-driven path to more resilient livestock. Her findings are particularly valuable for researchers and breeders seeking to integrate sensor-based technologies into selective breeding programs.
Research Focus
Key Achievements
Top Papers
- 1