Pesticide application coverage training (PACT) tool: development and evaluation of a sprayer performance diagnostic tool
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Pesticide application coverage training (PACT) tool: development and evaluation of a sprayer performance diagnostic tool C. A. Shearer1 · J. D. Luck2 · J. T. Evans3 · J. P. Fulton4 · A. Sharda5 Accepted: 26 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Current operator feedback from in-field pesticide application operations conveys limited information and often does not allow the operator to visualize a true representation of their performance. Farm management information systems (FMIS) typically do not account for overlap, varying application rates across the width of the spray boom during turns, or offrate errors due to controller response. The pesticide application coverage training (PACT) tool was developed to deploy data analytics methodologies to sprayer operational data collected during field applications. The goal was to compare enhanced feedback via the PACT tool versus data generated from commercially available FMIS software today. Data were collected for multiple Nebraska fields and processed by the PACT program which consisted of a novel MATLAB program developed for this project. The PACT program successfully generated high-resolution as-applied maps and the automated application report further quantified the contributions of these errors to the total error to illustrate how overlap, turning errors or controller response issues may have individually affected application accuracy. PACT program output metrics were compared with current data provided by FMIS software. Field-average metrics were not found to be significantly different when comparing the PACT program to the FMIS output; however, when examining how in-field errors were distributed amongst various application rate ranges, significant differences were noted in comparison to the FMIS output. Thus, the PACT program was able to quantify and illustrate application rate variation due to boom section overlap and turning movements unaccounted for in traditional FMIS software. Keywords Data analytics · As-applied mapping · Software · Digital agriculture
* J. D. Luck [email protected] 1
Huffman Engineering, Inc., 5301 N 57th St #101, Lincoln, NE 68507, USA
2
University of Nebraska-Lincoln, 204 Chase Hall, Lincoln, NE 68583, USA
3
Purdue University, 225 South University Street, West Lafayette, IN 47907, USA
4
The Ohio State University, 212 Agricultural Engineering, 590 Woody Hayes Dr., Columbus, OH, USA
5
Kansas State University, 1042 Seaton Hall, Manhattan, KS 66506, USA
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Precision Agriculture
Introduction and literature review Extensive herbicide, fungicide and insecticide (i.e., pesticides) use to control pests has become commonplace on farms across the USA. According to the 2012 USA census of agriculture, 114 Mha of cropland were treated with herbicides while an additional 40 Mha were treated with insecticides in 2012 (USDA 2012). In 2016, USA crop producers spent US$ 15.2 × 109 on these products to control pests in their fields (USDA 2017). At a global level, 2.7
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