Size of plots for experiments with cactus pear cv. Gigante

Abstract

The definition of experimental plot size is an essential tool to ensure precision in statistical analysis in experiments. The objective of this study was to estimate the plot size for the cactus pear cv. Gigante using the Modified Maximum Curvature Method, under the semi-arid conditions of Northeastern Brazil. The uniformity test was conducted at the Federal Institute of Bahia, Guanambi Campus, Bahia state, Brazil, during the agricultural period from 2009 to 2011. The spatial arrangement was composed of ten rows with 50 plants each, whose evaluated area was formed by the eight central rows with 48 plants per row, making 384 plants and area of 153.60 m2. The following variables were evaluated: plant height; length, width and thickness of cladode; number of cladodes; total area of cladodes; cladode area and green mass yield in the third production cycle. In the evaluations, each plant was considered as a basic experimental unit (BEU), with an area of 0.4 m2, comprising 384 basic units (BU), whose adjacent ones were combined to form 15 pre-established plot sizes with rectangular shapes and in rows. The characteristics total area of cladodes and green mass yield require larger plot sizes to be evaluated with greater experimental accuracy. For experimental evaluation of cactus pear cv. Gigante, plot size should be eight plants in the direction of the crop row.

Plot Size and Shape for Field Trials With Forage Cactus Pear

“…Thus, a plot size of eight BUs and 8 C x 1 R shape ensures higher efficiency in the experimental evaluation since this combination between size and shape has a better control of soil heterogeneity, thereby reducing experimental error and significantly increasing precision. It is worth noting that the size of the experimental plot recommended in this study agree with the findings reported by Guimarães et al (2019a).…”

“…Obtaining significant results consistent with the proposal of the study at a minimum operational cost depends mainly on increasing experimental precision (DONATO et al, 2018). Thus, there are several promising methods for determining the optimum plot size in basic units, such as Modified Maximum Curvature Method - (LESSMAN and ATKINS, 1963), as verified by Guimarães et al (2019aGuimarães et al ( , 2019b; Comparison of Variances Method (VALLEJO and MENDONZA, 1992), studied by Guimarães et al (2019bGuimarães et al ( , 2019c; Linear Response Plateau Model and Quadratic Response Plateau Model (PARANAÍBA et al, 2009), presented by Guimarães et al (2019b) and Hatheway's Convenient Plot Size (HATHEWAY, 1961), corroborated by Guimarães et al (2020).…”

Didactic tool for experimental demonstration with ‘Gigante’ forage cactus pear

“…However, determining plot sizes is a quantitative discrete process, that is, integer values are used (Guimarães et al, 2019), and one usually measures all aforementioned characteristics in field trials with 'Gigante' cactus pear; therefore, a single plot size should be selected. When conducting agricultural experiments or field trials, it is necessary that the researcher or instructor defines what the experimental basic unit will consist of, thereby aiming at the highest precision by reducing the experimental error.…”

Methods for Estimating Optimum Plot Size for ‘Gigante’ Cactus Pear

“…However, since studies on forage cactus generally investigate all aforementioned vegetative traits, the largest plot size must be used to allow measuring every characteristic, as reported by Donato et al (2008). For this reason, eight basic unit plot sizes estimated by the modified maximum curvature is the one to be used for experiments on forage cactus pear (Guimarães et al, 2019). Paludo et al (2015) further explained that the modified maximum curvature method, despite its algebraic precision at determining the optimum plot size, estimates smaller plot sizes than other estimating methods, but with a better R 2 .…”

“…Several studies have been carried out on the use of the aforementioned methods for estimating the optimum plot size: modified maximum curvature method (Sousa et al, 2016;Cargnelutti Filhoet al, 2018;Guimarães et al, 2019), Hatheway's method (Sousa et al, 2016;Cargnelutti Filhoet al, 2016;Donato et al, 2018) andlinear response plateau regression (Sousa et al, 2015;Leonardo et al, 2014;Sampaio Filhoet al, 2019). These studies agree on the dependent relationship between plot size and CV of the characteristic; thus, characteristics with higher variability need larger unit areas to show significant differences between treatments (Donato et al, 2018).…”