Yufeng Ge

Avatar for Yufeng Ge

Yufeng Ge

Professor Biological Systems Engineering University of Nebraska-Lincoln

Contact

Address
CHA 211
Lincoln NE 68583-0726
Phone
402-472-1413 On-campus 2-1413
Email
yge2@unl.edu

Appointment

  • 20% Teaching
  • 55% Research
  • 25% Administration

Areas of Research and Professional Interest

  • Sensor-based plant phenotyping
  • Optoelectronic sensor development in agriculture
  • VIS/NIR/MIR Spectroscopy
  • Agricultural remote sensing and image analysis
  • Precision agriculture and spatial statistics

Teaching Interests

  • Measurement and control in agriculture
  • Proximal and remote sensing/Spectroscopy
  • Optoelectronic sensor design

Education

  • Ph.D., Biological & Agricultural Engineering, Texas A&M University
  • M.S., Mechanical Engineering, Nanjing Forestry University, China
  • B.S., Mechanical Engineering, Nanjing Forestry University, China

Certifications

  • Ph.D.

In the News

Nov 08, 2022: Project aims to boost ag tech through improved field connectivity

Septemeber 3, 2020: Husker-led project to advance, standardize field of phenotyping

Honors and Awards

  • 2016 Early Career Award by Association of Overseas Chinese Agricultural, Biological, and Food Engineers
  • 2011 Young Engineer of the Year award by ASABE Texas Section
  • 2009 ASABE Superior Paper Award by ASABE
  • 2008 Distinguished Scholarly Achievement Award in Doctoral Research by the Association of Former Students and the Office of Graduate Studies at Texas A&M University

Selected Publications

Refereed Journal Articles in Past 4 Years (Total 43) 

  • Yao, Y., Ge, Y., Thomasson, J.A., Sui, R., 2018. Algae optical density sensor for pond monitoring and production process control. International Journal of Agricultural and Biological Engineering 11(1), 212-217.
  • Liang, Z., Pandey, P., Stoerger, V., Xu, Y., Qiu, Y., Ge, Y., Schnable, J.C., 2018. Conventional and hyperspectral time-series imaging of maize lines widely used in field trials. GigaScience 7(2), 1-11.
  • Bai, G., Blecha, S., Ge, Y., Walia, H., Phansak, P., 2017. Characterizing wheat response to water limitation using multispectral and thermal imaging. Transactions of the ASABE 60, 1457-1466.
  • Pandey, P., Ge, Y., Stoerger, V., Schnable, J.C., 2017. High throughput in vivo analysis of plant leaf chemical properties using hyperspectral imaging. Frontiers in Plant Science 8.
  • Ackerson, J.P., Morgan, C.L.S., Ge, Y., 2017. Penetrometer-mounted VisNIR spectroscopy: Application of EPO-PLS to in situ VisNIR spectra. Geoderma 286, 131-138.
  • 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.
  • 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.
  • Bagnall, G.C., Thomasson, J.A., Ge, Y., 2016. Animal-drawn conservation-tillage planter designed for small farms in developing world. Applied Engineering in Agriculture 32(6), 791-799.
  • Ge, Y., and Thomasson, J.A. 2016. NIR reflectance and MIR attenuated total reflectance spectroscopy for characterizing algal biomass composition. Transactions of the ASABE 59(2): 435-442.
  • Cribben, C.D., Thomasson, J.A., Ge, Y., Morgan, C.L.S., Yang, C., Isakeit, T., and Nichols, R.L. 2016. Site-specific relationships between cotton root rot and soil properties. Journal of Cotton Science 20, 67-75.
  • Wijewardane, N.K., Ge, Y., and Morgan, C.L.S. 2016. Moisture insensitive prediction of soil properties from VNIR reflectance spectra based on external parameter orthogonalization. Geoderma 267(1): 92-101.
  • Wijewardane, N.K., Ge, Y., Wills, S., Loecke, T., 2016. Prediction of soil carbon in Conterminous US: VisNIR analysis of Rapid Carbon Assessment Project. Soil Science Society of America Journal 80(4), 973-982.
  • Wijewardane, N.K., Ge, Y., Morgan, C.L.S., 2016. Prediction of soil organic and inorganic carbon at different moisture contents with dry ground VNIR: A comparative study of different approaches. European Journal of Soil Science 67(5), 605-615.
  • Ge, Y., C.L.S. Morgan, and J. Ackerson.  2014.  VisNIR spectra of dried ground soil predict properties of soils scanned moist and intact.  Geoderma.  Accepted.
  • Ge, Y., J.A. Thomasson, and C.L.S. Morgan.  2014.  Mid infrared attenuated total reflectance spectroscopy for soil particle size and carbon determination.  Geoderma 213:57-63.

Professional Memberships: