A Case Study to Evaluate Field Shape Factors for Estimating Overlap Errors with Manual and Automatic Section Control

Abstract

Understanding how field shape and size may affect overlap errors during spraying operations would provide producers with better information on how to improve field operations and cut costs. The goal of this study was to evaluate field shape factors through single-variable and multivariate regression analyses for predicting overlap from a manual section control (MSC) and two automatic section control (ASC) systems. Actual field coverage data collected from three self-propelled agricultural sprayers with boom widths of 24.8 m were used in the analysis. Results of statistical analyses indicated that significant relationships existed between over-application error and multiple field shape factors. The strongest single-variable relationship existed between field perimeter-to-area ratio (P/A) and the overlap error (% of field area) for the MSC and seven- and nine-section ASC systems, with model standard errors of 4.95%, 1.45%, and 0.81%, respectively. Multivariate regression yielded strong relationships with different combinations of field shape factors and overlap error; however, multivariate models did not result in a vast improvement over the single-variable model using P/A. Errors increased at a greater rate with MSC, which suggested that as field inclusions (e.g., grassed waterways) increase, or the field boundary becomes more complex, overlap error reduction may be reduced with ASC. As expected, nine-section ASC resulted in reduced overlap errors compared to the seven-section system as P/A increased. Comparing models for the ASC systems indicated that the reduction in overlap application may not significantly improve when adding two additional control sections for fields with low P/A values (<0.0175).