Michael P Popp

Dr. Michael P Popp is the Harold F. Ohlendorf Professor in the Department of Agricultural Economics and Agribusiness at the University of Arkansas. He teaches senior-level agribusiness and advanced farm management courses, with prior teaching roles in financial risk management and agricultural financial records. His career spans institutions in Canada (University of Manitoba) and the U.S., including promotions to Associate Professor (2001) and Full Professor (2006).

• Education:
  • Ph.D., Agricultural and Resource Economics, Colorado State University (1995)
  • MBA, Finance, University of Colorado (1991)
  • Bachelor of Commerce, Management Information Systems, University of Manitoba (1990)

Dr. Popp’s research focuses on farm and agribusiness management, emphasizing alternative production practices and their implications for economic returns, risk, and environmental sustainability. He has developed web-based decision support tools for soybean and switchgrass production, analyzing greenhouse gas emissions, water footprint, and precision agriculture technologies like tractor guidance systems. His work extends to biochar and hemp economics, integrating consumer behavior and policy analysis.

Recent publications reveal a strong focus on soybean and corn production economics, forage systems, and renewable energy applications in agriculture. His decision support software addresses herbicide management, fertilizer optimization, and climate resilience. Articles also highlight cross-disciplinary work in agricultural education and consumer perceptions of genetically modified crops.

• Scientific Awards:
  • Outstanding Teacher Recognition (University of Manitoba, 1998)
  • Poster Awards (2001, 2011, 2016)
  • Gamma Sigma Delta Research Award of Merit (2017)
  • Agricultural and Resource Economics Review Fellow (2018)

Dr. Popp has also explored livestock profitability, soil nutrient management, and remote sensing applications for conservation agriculture, with projects spanning Arkansas, Manitoba, and the Mid-Southern U.S. His methodologies include stochastic modeling, partial life cycle assessments, and neural networks for profitability analysis.