Cleaning yield monitor observations to remove erroneous points can improve the accuracy of yield estimates used for farm record keeping or on-farm research data collection, but current practices are time-intensive and cumbersome. cleanRfield is an open-source R package to improve the efficiency of processing spatial agricultural data such as yield maps. Compared with current standard yield monitor data cleaning solutions, cleanRfield can read and interpret a broader range of input data formats. Other key features of cleanRfield include automatic field boundary delineation and batch processing of data from multiple fields. In this Scientific Note, we overview functions within the cleanRfield package and introduce an integrative pipeline to evaluate and visualize yield monitor data. The package is being distributed under the GNU General Public License 2, and a more detailed tutorial including downloading instructions is available at https://github.com/filipematias23/cleanRfield.

中文翻译：

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使用 cleanRfield 包在 R 环境中过滤、编辑和裁剪产量图

清理产量监测观察以消除错误点可以提高用于农场记录保存或农场研究数据收集的产量估计的准确性，但目前的做法是时间密集型和繁琐的。cleanRfield 是一个开源 R 包，用于提高处理空间农业数据（如产量图）的效率。与当前的标准产量监控数据清洗解决方案相比，cleanRfield 可以读取和解释更广泛的输入数据格式。cleanRfield 的其他主要功能包括自动字段边界描绘和来自多个字段的数据的批处理。在本科学笔记中，我们概述了 cleanRfield 包中的功能，并引入了一个集成管道来评估和可视化良率监控数据。