Ron Yoder is Professor and Head, Department of Biological Systems Engineering (BSE), and Associate Director of Agricultural Water Management, University of Nebraska–Lincoln and has been a BSE faculty member for the past five years. He was honored with the PEI Professional Engineer of the Year Award, ASABE in 2008. Before coming to UNL Yoder was Professor and Head, Biosystems Engineering and Environmental Science Department, UT, 2000 – 2004; Associate Professor, Agricultural and Biosystems Engineering Department, UT, 1996 – 2000; Coordinator, Tennessee Agricultural Experiment Station Interdisciplinary Water Quality Research Team; and Assistant Professor, Agricultural Engineering Department, University of Tennessee, 1992 – 1996, among other past appointments.
- Ph.D. Agricultural Engineering, Colorado State University, 1988
- M.S. Agricultural Engineering, Clemson University, 1978 B.S.
- Civil Engineering, Drexel University, 1976
- Tyner, J. S., W. C. Wright, and R. E. Yoder. 2007. Identifying Long-Term Preferential and Matrix Flow Recharge at the Field Scale. TRANSACTIONS of the ASABE. 50(6):2001-2006.
- Miranda, F. R., R. E. Yoder, and J. B. Wilkerson. 2005. An Autonomous Controller for Site-Specific Management of Fixed Irrigation Systems. Computers and Electronics in Agriculture 48:183-197.
- Yoder, R. E., L. O. Odhiambo, and W. C. Wright. 2005. Effects of Vapor Pressure Deficit and Net-Irradiance Calculation Methods on the Accuracy of the Standardized Penman-Monteith Equation in a Humid Climate. ASCE J. of Irr. and Dr. 131(3):228-237.
- Yoder, R. E., L. O. Odhiambo, and W. C. Wright. 2005. Evaluation of Methods for Estimating Daily Reference Crop Evapotranspiration at a Site in the Humid Southeast of USA. Applied Engineering in Agriculture 21(2):197-202.
- Li, J., R. E. Yoder, L. O. Odhiambo, and J. Zhang. 2004. Simulation of Nitrate Distribution Under Drip Irrigation Using Artificial Neural Networks. Irrigation Science 23:29-37.
- Odhiambo, L. O., R. S. Freeland, R. E. Yoder, and J. W. Hines. 2004. Investigation of a Fuzzy-Neural Network Application in Classification of Soils using Ground-Penetrating Radar Imagery. Applied Engineering in Agriculture, 20(1):1-9.