Evaluating field shape descriptors for estimating off-target application area in agricultural fields

Abstract

The decision to adopt different precision agriculture (PA) technologies can be difficult for producers due to the high cost and complexity encountered with different systems. Thus, a method of estimating potential savings resulting from specific technologies based on operating conditions would considerably contribute the decision making process. For instance, the benefits of automatic section control can be dependent on the field size, shape, and field operation patterns. Thus, knowing the potential reduction in overlapped areas of a specific field would be desirable in order to justify the acquisition of such a technology package. Researchers have reported computational methods for estimating off-target application areas based on actual field boundaries. While the reported methods are valid, it requires a considerable amount of computational power to execute lengthy routines written on dedicated software. The goal of this study was to develop a simplified approach for estimating off-target application areas in agricultural fields considering the combined effects of field shape, field size, and implement width. The results revealed that the descriptor headland area (H) over the field area (A), presented the best relationship with off-target application. A linear model for predicting average off-target application was adjusted based on H/A and presented estimating errors within ±6.7% at 2 standard deviations.