In farming operation, machinery represents a major cost; therefore, good fleet management can have a great impact on the producer’s profit, especially considering the increasing costs of fuel and production inputs in recent years. One of the tasks to be accomplished in order to improve fleet management is planning the path that the machine should take to cover the field while working. Information such as distance traveled, time and fuel consumption as well as agricultural inputs wasted due to off-target-application areas are crucial in the path planning process. Parameters such as field boundary size and geometry, machine total width as well as control width resolution present a great impact on the information necessary for path planning. Researchers around the world have proposed methods that approach specific aspects related to path planning, the majority addressing machine field efficiency per-se, which a function of total time spent in the field as well as effective working time. However, wasted inputs due to off-target-application areas in the maneuvering regions, especially in oddly shaped agricultural fields might be as important as field efficiency when it comes down to the total operation cost. Thus, the main purpose of this research was to develop a path planning method that accounts for not only machinery field efficiency, but also the supply inputs. This research was accomplished in a threefold approach where in the first step an algorithm for computing off-target application area was developed, implemented and validated resulting in a computational tool that can be used to evaluate potential savings when using automatic section control on agricultural fields of complex field boundary. This tool allowed accomplishment of the second step, which was an investigation and better understanding of field size and shape as well as machine width of the effects on off-target application areas resulting in an empirical method for such estimations based on object shape descriptors. Finally, a path planning algorithm was developed and evaluated taking into consideration the aspects of machine field efficiency as well as off-target application areas.

The world population is projected to rise, and there is a growing concern of future food availability. Precision agriculture technologies are one solution to this problem as they aim to produce more food on less land. This study examines the adoption and intensity of precision agriculture technology usage by producers in North Dakota. Data from a North Dakota State University survey was collected and analyzed using an econometric double-hurdle model. Results of the study describe which producers adopt precision agriculture technologies, which technologies complement each other, and what affects the intensity of technology usage. Several technologies were found to have complementary effects on each other, larger farms are more likely to adopt PATs, and crop choices have varying impacts on the adoption and usage of PATs. Most of these findings agree with previous literature, although new light was shed on some new findings and predictions.