Effect of neighborhood and plot size on experiments with multiple-harvest oleraceous crops

Abstract

The objective of this work was to determine the efficiency of the Papadakis method on the quality evaluation of experiments with multiple-harvest oleraceous crops, and on the estimate of the covariate and the ideal plot size. Data from nine uniformity trials (five with bean pod, two with zucchini, and two with sweet pepper) and from one experiment with treatments (with sweet pepper) were used. Through the uniformity trials, the best way to calculate the covariate was defined and the optimal plot size was calculated. In the experiment with treatments, analyses of variance and covariance were performed, in which the covariate was calculated by the Papadakis method, and experimental precision was evaluated based on four statistics. The use of analysis of covariance with the covariate obtained by the Papadakis method increases the quality of experiments with multiple-harvest oleraceous crops and allows the use of smaller plot sizes. The best covariate is the one that considers a neighboring plot of each side of the reference plot.

Nonlinear regression and plot size to estimate green beans production

“…Among these researches, we can mention the ones carried out by Haesbaert et al (2011) to estimate sample size and Santos et al (2012aSantos et al ( , 2012bSantos et al ( , 2014, to estimate plot size and viability of implementation of Papadakis method for the experimental error adjustment. The researches aiming…”