Evaluation of the Papadakis technique applied to methods for estimating the size of experimental plots in soybean crops

• DOI: https://doi.org/10.22533/at.ed.929422419032

• Palavras-chave: Experimental planning, experimental precision, moving average, maximum curvature, data fit.

• Keywords: Experimental planning, experimental precision, moving average, maximum curvature, data fit.

• Abstract:

  The experimental plot size must be adequate to reduce experimental error and increase precision, hence there is a need to have more efficient experiments. And, to determine the sizes of experimental plots, many methods are found in the literature that present adequate results, but some methods have presented unsatisfactory results, with excessively small or large sizes. To overcome this problem, an alternative is to use the Papadakis technique. Therefore, the objective of this work is to evaluate the use of the Papadakis method for estimating the size of experimental plots for application in soybean cultivation. To estimate the size of plots, the modified maximum curvature method, the segmented linear model method with plateau and the maximum curvature coefficient of variation method were used considering the original data and the data adjusted by the Papadakis method. It was found that the use of the Papadakis method provides a good fit in estimating plot sizes of experimental plots using estimates from the modified maximum curvature methods and the maximum curvature coefficient of variation method.