Yeyin Shi, PhDAssistant Professor and Agricultural Information System Engineer
- Ph.D., Biosystems and Agricultural Engineering, Oklahoma State University, May 2014
- M.S., Biosystems and Agricultural Engineering, Oklahoma State University, December 2010
- B.S., Mechanical Engineering, Nanjing Forestry University, China, July 2007
- 50% research, 50% teaching
- Agricultural information/data generation, analysis, modeling and management
- Agricultural remote sensing systems (satellite, aircraft, and UAS/drone based platforms)
- Crop abiotic and biotic stresses sensing and modeling
- Field-based high-throughput phenotyping
- Precision crop and livestock management
Yeyin’s research group at UNL creates and applies information technology to record, transmit, manage and use digital information related to the health, productivity and sustainability of agricultural production systems. Yeyin grew up in the province of Jiangsu in China, one of the most traditional and productive farming areas for rice and poultry production along the Yangtze River. She received both her doctoral and master’s degrees in the Biosystems and Agricultural Engineering Department at Oklahoma State University. She also worked as a postdoctoral associate in the Citrus Research and Extension Center at University of Florida and an assistant research scientist in the Biological and Agricultural Engineering Department at Texas A&M University prior to joining UNL. Yeyin is currently looking for talented students with passion and determination and active collaborators to work together.
- ASABE Outstanding Manuscript Reviewer for the 2014 publication year, Information Technology, Sensors, & Control Systems Division, April 2015.
- 1st Place in the postdoc category, 4th Annual Poster Research Gallery and Competition, Citrus Research and Education Center, University of Florida, April 2015.
- 2nd Place in Student Robotic Competition (team), 2012 ASABE Annual International Meeting. 2012.
- Precision Agriculture Outstanding Graduate Student Award 2010, 10th International Conference on
Precision Agriculture Awards Committee, 2010.
- Sitlington Enriched Graduate Scholarship, Division of Agricultural Sciences and Natural Resources,
Oklahoma State University, 2010.
- Alpha Epsilon, Honor Society for Outstanding Biological and Agricultural Engineers, 2008
- Li, J., Shi, Y., Lan, Y., & Guo, S. (2019). Vertical distribution and vortex structure of rotor wind field under the influence of rice canopy. Computers and Electronics in Agriculture, 159, 140-146.
- Yuan, W., Li, J., Bhatta, M., Shi, Y., Baenziger, P., & Ge, Y. (2018). Wheat Height Estimation Using LiDAR in Comparison to Ultrasonic Sensor and UAS. Sensors, 18(11), 3731.
- Li, J., Shi, Y., Veeranampalayam-Sivakumar, A. N., & Schachtman, D. P. (2018). Elucidating sorghum biomass, nitrogen and chlorophyll contents with spectral and morphological traits derived from unmanned aircraft system. Frontiers in Plant Science, 9, 1406. https://doi.org/10.3389/fpls.2018.01406
- Zhao, B., Zhang, J., Yang, C., Zhou, G., Ding, Y., Shi, Y., ... & Liao, Q. (2018). Rapeseed seedling stand counting and seeding performance evaluation at two early growth stages based on unmanned aerial vehicle imagery. Frontiers in Plant Science, 9, 1362.
- Chen, D., Shi, Y., Huang, W., Zhang, J., & Wu, K. (2018). Mapping wheat rust based on high spatial resolution satellite imagery. Computers and Electronics in Agriculture, 152, 109-116.
- Shafian, S., Rajan, N., Schnell, R., Bagavathiannan, M., Valasek, J., Shi, Y., & Olsenholler, J. (2018). Unmanned aerial systems-based remote sensing for monitoring sorghum growth and development. PloS one, 13(5), e0196605.
- Zhao, X., Zhang, J., Yang, C., Song, H., Shi, Y., Zhou, X., ... & Zhang, G. (2018). Registration for Optical Multimodal Remote Sensing Images Based on FAST Detection, Window Selection, and Histogram Specification. Remote Sensing, 10(5).
- Lu, J., Ehsani, R., Shi, Y., Castro, A. I., & Wang, S. (2018). Detection of multi-tomato leaf diseases (late blight, target and bacterial spots) in different stages by using a spectral-based sensor. Scientific reports, 8(1), 2793.
- Zhang, J., Yang, C., Zhao, B., Song, H., Clint Hoffmann, W., Shi, Y., ... & Zhang, G. (2017). Crop Classification and LAI Estimation Using Original and Resolution-Reduced Images from Two Consumer-Grade Cameras. Remote Sensing, 9(10), 1054.
- Lu, J., Ehsani, R., Shi, Y., Abdulridha, J., de Castro, A. I., & Xu, Y. (2017). Field detection of anthracnose crown rot in strawberry using spectroscopy technology. computers and electronics in agriculture, 135, 289-299.
- Shi, Y., Thomasson, J. A., Murray, S. C., Pugh, N. A., Rooney, W. L., Shafian, S., ... & Rana, A. (2016). Unmanned aerial vehicles for high-throughput phenotyping and agronomic research. PloS one, 11(7), e0159781.
- Defterli, S. G., Shi, Y., Xu, Y., & Ehsani, R. (2016). Review of robotic technology for strawberry production. Applied Engineering in Agriculture, 32(3), 301-318.
- Navid, H., Taylor, R. K., Yazgi, A., Wang, N., Shi, Y., & Weckler, P. (2015). Detecting Grain Flow Rate Using a Laser Scanner. Transactions of the ASABE, 58(5), 1185-1190.
- Shi, Y., Wang, N., Taylor, R. K., & Raun, W. R. (2015). Improvement of a ground-LiDAR-based corn plant population and spacing measurement system. Computers and Electronics in Agriculture, 112, 92-101.
- Yuan, L., Zhang, J., Shi, Y., Nie, C., Wei, L., & Wang, J. (2014). Damage mapping of powdery mildew in winter wheat with high-resolution satellite image. Remote sensing, 6(5), 3611-3623.
- Shi, Y., Wang, N., Taylor, R. K., Raun, W. R., & Hardin, J. A. (2013). Automatic corn plant location and spacing measurement using laser line-scan technique. Precision Agriculture, 14(5), 478-494.