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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #203367


item Sudduth, Kenneth - Ken
item Drummond, Scott

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/28/2007
Publication Date: 11/1/2007
Citation: Sudduth, K.A., Drummond, S.T. 2007. Yield editor: Software for removing errors from crop yield maps. Agronomy Journal. 99:1471-1482.

Interpretive Summary: Yield maps are a key component of precision agriculture, used both in developing and evaluating precision management strategies. Unfortunately, yield monitors produce complex datasets that often contain a large number of errors. These errors should be removed, as they may cause serious problems when yield data are used for research and analysis tasks. Even when yield maps are merely used in an interpretive fashion, or to visualize patterns in the data, the conclusions drawn by the user may be adversely affected by these error sources. To help yield map users remove errors from their maps, we developed the “Yield Editor”, interactive software that incorporates several automated filters and also allows the user to manually remove bad data. Tests of Yield Editor on several datasets showed its usefulness and provided information about the relative importance of the various filter types. This research is a step toward a standardized procedure to clean yield data, a result that would improve data quality for both researchers and producers involved in precision agriculture. Improved yield map data will allow more accurate development and assessment of precision management strategies for improved farm profitability and environmental protection.

Technical Abstract: Yield maps are a key component of precision agriculture, due to their usefulness in both development and evaluation of precision management strategies. The value of these yield maps can be compromised by the fact that raw yield maps contain a variety of inherent errors. Researchers have reported that 10-50% of the observations in a given field contain significant errors and should be removed. Methods for removing these outliers from raw yield data have not been standardized, although many different filtering techniques have been suggested to address specific error types. We developed a software tool called Yield Editor to simplify the process of applying filtering techniques for yield data outlier detection and removal. Yield Editor includes a map view of the yield data, allowing the user to interactively set, assess the effects of, and refine a number of previously reported automated filtering methods. Additionally, Yield Editor allows manual selection of erroneous points, transects, or regions for investigation and possible deletion. This paper describes the filters implemented in Yield Editor, discusses input, output, and filtering options, and documents availability of the program. Example applications of Yield Editor on five test fields are used to show how the user interacts with the software and to analyze the relative importance of the various filters.