Biquan Zhao

Avatar for Biquan Zhao

Biquan Zhao

Post-Doctoral Research Associate Animal Science University of Nebraska-Lincoln

Contact

Address
ANSC C203
Lincoln NE 68583-0908
Phone
402-472-3571 On-campus 2-3571
Email
bzhao10@unl.edu
Website

Dr. Biquan Zhao has served as a Post-Doctoral Research Associate for the Department of Animal Science and Biological Systems Engineering since 2024.

Education

Research

My research focuses on utilizing various technologies like remote sensing (drone, satellite, etc.), GPS, and deep learning to develop tools in range monitoring and gathering useful information to inform grazing and forage management. One of my current projects is to develop an easy-access dashboard for producers to estimate forage availability. Other ongoing projects include integration of virtual fencing collars and accelerometers on cattle to establish modern and precision rangeland management.

Selected Publications

  • Zhao, B., McDermott, R. L., Erickson, G. E., Xiong, Y., Technical Note: Assessing GPS Sensor Accuracy Using Real-Time Kinematic Device for Livestock Tracking. Journal of Animal Science. (Accepted on 16-Aug-2024). 
  • Zhao, B., Stephenson, M., Awada, T., Volesky, J., Wardlow, B., Zhou, Y., Shi, Y. (2024). 15-Yr Biomass Production in Semiarid Nebraska Sandhills Grasslands: Part 2—Plant Functional Group Analysis. Rangeland Ecology & Management. (Under Review) 
  • Zhao, B., Stephenson, M., Awada, T., Volesky, J., Wardlow, B., Zhou, Y., Shi, Y. (2024). 15-Yr Biomass Production in Semiarid Nebraska Sandhills Grasslands: Part 1—Plant Functional Group Analysis. Rangeland Ecology & Management, 93, 49-61. 
  • Heil, H. A., Zhao, B., Troyer, B. C., Sjostrand, R. L., Xiong, J., Watson, A. K., Erickson. G. E., Okalebo, J., Shi Y., Xiong, Y. (2023). Characterizing Yearling Beef Steers Grazing on Smooth Bromegrass Pasture Using Global Positioning Technology. Journal of Animal Science, 101, 11-12. 
  • Zhao, B., Khound, R., Ghimire, D., Zhou, Y., Maharjan, B., Santra, D. K., & Shi, Y. (2022). Heading percentage estimation in proso millet (Panicum miliaceum L.) using aerial imagery and deep learning. The Plant Phenome Journal, 5(1), e20049.