Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the number of specific types of precision agriculture technologies adopted by cotton farmers. Particular attention is...

Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the intensity of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the...

This paper analyzes the geographic distribution of “green energy” sector clustering in the lower 48 United States using recent developments in industry concentration analysis. Evidence suggests that the ten green energy subsectors and the aggregate of the firms comprising the green energy...

In the United States, biomass is the largest source of renewable energy accounting for over 3 percent of the energy consumed domestically and is currently the only source for liquid, renewable, transportation fuels. Continued development of biomass as a renewable energy source is being driven in...

We estimate a bivariate probit model with sample selection to identify factors affecting adoption and abandonment of precision farming technologies for cotton farmers, using the 2009 Southern Cotton Precision Farming Survey conducted in 12 Southern states in the United States. Farmers for whom...

A multiobjective optimization model integrating with high-resolution geographical data was applied to examine the optimal switchgrass supply system in Tennessee that considers both feedstock cost and greenhouse gas (GHG) emissions in the system. Results suggest that the type of land converted...

Costs differ among variable rate application systems. Most feasible in Tennessee are the 1-bin and 2-bin spreader beds mounted to existing chassis with an owner-added variable rate controller and global positioning system. Truck spreader systems required more acreage or larger custom charges...

This research evaluated the factors that influenced cotton producers to adopt remote sensing for variable rate application of inputs. Farmers who were younger, more highly educated, had a larger farm operation, and were more technologically savvy were more likely to have adopted remote sensing.

Precision Farming by Cotton Producers in Eleven Southern States: Results from the 2005 Southern Precision Farming Survey

Precision Farming by Cotton Producers in Six Southern States: Results from the 2001 Southern Precision Farming Survey