Plot size has an important impact on variation among plots in agronomic field trials, but is rarely considered during the design process. Uniformity trials can inform a researcher about underlying variance, but are seldom used due to their laborious nature. The objective of this research was to describe variation in maize field trials among field plots of varying size and develop a tool to optimize field-trial design using uniformity-trial statistics. Six uniformity trials were conducted in 2015–2016 in conjunction with Iowa State University and WinField United. All six uniformity trials exhibited a negative asymptotic relationship between variance and plot size. Variance per unit area was reduced over 50% with plots 41.8 m² in size and over 75% when using a plot size >111.5 m² compared to a 13.9 m² plot. Plot shape within a fixed plot size did not influence variance. The data illustrated fewer replicates were needed as plot size increased, since larger plots reduced variability. Use of a Shiny web application is demonstrated that allows a researcher to upload a yield map and consider uniformity-trial statistics to inform plot size and replicate decisions.

中文翻译：

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自动化均匀性试验以优化农艺田间试验的精度

地块大小对农艺田间试验中地块之间的变异有重要影响，但在设计过程中很少考虑。均匀性试验可以告知研究人员潜在的差异，但由于其费力的性质而很少使用。本研究的目的是描述不同大小田间地块之间玉米田间试验的变化，并开发一种使用均匀性试验统计优化田间试验设计的工具。2015-2016 年与爱荷华州立大学和 WinField United 联合进行了六次均匀性试验。所有六次均匀性试验都表现出方差和地块大小之间的负渐近关系。41.8 m ²地块的单位面积方差减少了 50% 以上，而当地块面积大于 111.5 m ²时，每单位面积的方差减少了75% 以上与 13.9 m ^{2 的}地块相比。固定地块大小内的地块形状不影响方差。数据表明，随着地块大小的增加，需要的重复次数更少，因为更大的地块减少了变异性。演示了 Shiny Web 应用程序的使用，该应用程序允许研究人员上传产量图并考虑均匀性试验统计数据，以告知小区大小和重复决策。