Plot size and number of replications to evaluate the grain yield in oat cultivars

Abstract

The objectives of this study were to determine the optimum plot size (Xo) and the number of replications to evaluate grain yield and verify the variability of Xo among oat cultivars. Thirtytwo uniformity trials of 3 × 3 m were performed, being 8 from each cultivar (URS Charrua, URS Taura, URS Estampa, and URS Corona). Each uniformity trial was divided in 36 basic experimental units (BEU) of 0.5 × 0.5 m. Grain yield was determined in each BEU. The Xo was determined by the method of maximum curvature of the coefficient of variation model. Mean comparisons among cultivars were performed by the Scott-Knott test via bootstrap. The number of replications was calculated by an iterative process until convergence for experiments in completely randomized design (CRD) and randomized block CRop pRoduCTion And MAnAgeMenT-Article

Plot Size and Number of Replications for Evaluation of the Yield of Grains in Cultivars and Dates of Sowing of Rye

“…When estimating the optimum plot size using different methods and checking the possible precision in experiments with the wheat crop, Lorentz et al (2007) found a plot size from 0.89 m 2 to 6.48 m 2 for grains yield. In order to evaluate the grains yield of oat, Lavezo et al (2017) verified that there is variability in X o among the cultivars, with value determined in 1.57 m².…”

Optimal plot size for experimental trials with Opuntia cactus pear

“…The dimensioning of the plots from the basic unit formation components, CVe, index b, d, t and r, establish similarity between the variables, mainly due to the influence of the CVe and the difference to be detected -d, since it configures a direct relationship between the variability of the data and the size of the plot (Smith, 1938;Hatheway, 1961), a fact supported in several studies (Schmildt et al, 2016;Sousa et al, 2016;Lavezo et al, 2017;Cargnelutti Filho et al, 2018). However, the lower required experimental accuracy -d, implies reduced BEUs.…”

“…According to Lavezo et al (2017), the experimental design, applied in an efficient way, seeks to promote the adequate arrangement between statistical factors, treatments, replicates and plot size, in order to optimize the experimental area and achieve maximum accuracy for the evaluated parameters. Based on the Hatheway method (1961), a statistical matrix was obtained, making it possible to identify the ideal combination in the experimental plan between the vegetative characteristics ( Table 1).…”

“…The estimation of plot sizes by the statistical proposal of Hatheway (1961) was investigated in several studies (Cargnelutti Filho, Toebe, Burin, Casarotto, & Alves, 2014;Schmildt, Schmildt, Cruz, Cattaneo, & Ferreguetti, 2016;Lavezo et al, 2017; with wide recommendation for the use of smaller plots with a greater number of replications to reach the maximum experimental accuracy and, with this, a greater efficiency in the use of the area. These results reinforce the need to plan smaller and more efficient experiments on accuracy and costs.…”

Alguns modelos para a estimação do tamanho de parcelas em experimentos

“…The method of maximum curvature and relative efficiency were used by Lohmor et al (2017 a, b) to obtain the optimum plot size and the shape of blocks in a uniformity trial with sunflower. The method of maximum curvature of the variation coefficient model, proposed by Paranaíba et al (2009), was used by Lavezo et al (2017) in the estimation of the optimum plot size and number of replications in an experiment to evaluate the production of oat cultivars. Using the percentage efficiency of different plot sizes, Shah et al (2017) found that long and narrow plots were more efficient compared to smaller and wider plots of the same size.…”