Geng (Frank) Bai, Ph.D.

Contact Information:
207 L.W. Chase Hall (CHA)
Lincoln: East Campus
(402) 472-9387
gbai2@unl.edu
Email   

Research Assistant Professor
Academic Degrees
  • Ph.D., Environmental Science and Technology, Niigata University, Japan
  • M.E., Agricultural Soil and Water Engineering, China Agricultural University, China
  • B.E., Hydraulic and Hydro-Power Engineering, China Agricultural University, China
Appointment
  • 100% Research
Areas of Research and Professional Interest
  • Advanced plant phenotyping in field and greenhouse environment

  • Precision Agriculture
Selected Publications

Refereed Journal Articles in Past 5 Years

  • Bai, G., Jenkins, S., Yuan, W., Graef, G.L., Ge, Y., 2018. Field-based scoring of soybean iron deficiency chlorosis using RGB imaging and statistical learning. Frontiers in Plant Science 9, 1002.
  • Bai G., Blecha, S., Ge, Y., Walia, H., Phansak, P., 2017. Characterizing wheat response to water limitation using multispectral and thermal imaging. Transaction of the ASABE 60(5), 1457-1466.
  • Ge, Y., Bai, G., Stoerger, V., Schnable, J.C., 2016. Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging. Computers and Electronics in Agriculture 127, 625-632.
  • Bai, G., Ge, Y., Hussain, W., Baenziger, P.S., Graef, G., 2016. A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding. Computers and Electronics in Agriculture 128, 181-192.
  • Bai, G., Nakano, K., Ohashi, S., Mizukami, T., Yan, H., Kramchote, S., 2016. The influence of design parameters on the initial spray characteristics of the high-pressure air inclusion nozzle. Atomization and Sprays 26(4), 301-317.
  • Li, Y., Bai, G., Yan, H., 2015. Development and validation of a modified model to simulate the sprinkler water distribution. Computers and Electronics in Agriculture 111, 38-47.
  • Kramchote, S., Nakano, K., Kanlayanarat, S., Ohashi, S., Takizawa, K., Bai, G., 2014. Rapid determination of cabbage quality using visible and near-infrared spectroscopy. LWT-Food Science and Technology 59 (2), 695-700.
  • Bai, G., Nakano, K., Mizukami, T., Miyahara, S., Ohashi S., Kubota, Y., Takizawa, K., Yan, H., 2013. Characteristics and classification of Japanese nozzles based on relative spray drift potential, Crop Protection 46, 88-93.