Master of Agribusiness / Department of Agricultural Economics / Arlo Biere / With a large portion of U.S. farm production expenditures related to the cost of fertilizer, seed, and chemicals, producers within the Corn Belt region are looking for new methods and/or planting processes that would deliver higher levels of production efficiencies and lower operating costs. Specifically within the planting operation, Corn Belt producers are faced with the challenge to better manage the higher cost of crop inputs in order to sustain profitability. The primary objective of this thesis is to examine new planting technologies that would better manage planting applications while directly lowering related input costs. Another objective is to understand through regression analysis how various planting variables affect yield potential. Results from the regression analysis illustrate how the various planting variables affect yield and show the importance of “realtime” planter management, advancements possible only with the new planter technology. Customer surveys and several on-site customer visits were conducted throughout the Corn Belt to better understand the actual needs of producers for new planting technologies. Throughout the customer visits, specific questions about the producers’ planting operation were asked to find new ways for precision technology to help increase overall productivity and ultimately profitability. Producer comments and feedback were analyzed through Quality Functional Deployment (QFD) practices and aligned into product development programs. The products developed from the customer research will help producers in the Corn Belt to reduce corn production inefficiencies and, potentially, increase profit margins, assuming profit levels remain steady and/or increase in lieu of reduced input costs.Farm level net present value (NPV) analyses of new planting technologies were performed. Corresponding yield data from efficiencies gained in seed corn placement and control during “real-time” planting applications were integrated into the NPV analyses along with the precision technology costs. The NPV results were positive.