Plot size and replications number for triticale experiments

Abstract

The hybridization between wheat and rye crops resulted in the triticale crop, which presents rusticity, versatility in animal and human food and possibility of use as a cover plant. The objective of this research was to determine the optimal plot size and the replications number to evaluate the fresh weight of triticale in two evaluation moments. An experiment was carried out with the triticale cultivar IPR111. The experimental area was divided into 48 uniformity trials, each containing 36 basic experimental units of 0.51 m2. The fresh weight was evaluated in 24 uniformity trials at 99 days after sowing (DAS) and in 24 uniformity trials at 127 DAS. The optimal plot size was determined by the method of the maximum curvature of the coefficient of variation and the replications number was determined in scenarios of treatments number and differences between means to be detected as significant by Tukey test. To determine the fresh weight of triticale, the optimal plot size is 3.12 m2, with coefficient of variation of 13.69%. Six replications are sufficient to identify as significant, differences between treatment means of 25% for experiments with up to seven treatments and of 30% for experiments with up to 28 treatments, regardless of the experimental design.

Plot size and number of repetitions in forage wheat

“…In the rye crop, Chaves et al (2018a) determined plot sizes of 3.43, 3.82 and 6.08 m² to evaluate fresh matter, dry matter and grain yield, respectively. Toebe et al (2020a) defined the plot size of 3.12 m 2 to evaluate fresh matter in triticale. In studies with wheat crop, plot sizes of 6.48 m 2 (LORENTZ et al, 2007), 0.68 m 2 (PARANAÍBA; MORAIS; FERREIRA, 2009) and 1.6 m 2 and 2.4 m 2 (HENRIQUES NETO et al, 2009) were determined for evaluation of mass and/or grain yield, respectively.…”

Repeatability and genotypic stability in intraspecific hybrids of Paspalum notatum Flügge

“…The significant time and resource requirements involved in obtaining consistent data within breeding programs, considering the extensive number of genotypes and characters studied (Jank et al, 2014), requires the determination of the minimum number of measurements for the selection of superior genotypes (Rodrigues et al, 2020). This is a major issue faced by forage breeding programs, which need to determine the number of measurements necessary to accurately estimate the differences between genotypes (Toebe et al, 2020). This is generally determined through repeatability analysis, which aims to predict the genotypic value of a genotype over time with predefined determination coefficients (Chaves et al, 2018).…”