Optimal plot size for the evaluation of phenotypic traits in soybean seedlings

Abstract

Phenotypic traits with discriminatory capacity have been studied in recent years. However, scientific studies often employ experimental plots of varying sizes. Therefore, the objective of this study was to estimate the optimal plot size for the evaluation of phenotypic traits in soybean seedlings. Two blank trials were conducted, each consisting of 120 basic experimental units. Each basic experimental unit consisted of a single plant grown in a pot, which was evaluated during the juvenile stage. Coefficients of variation and optimal plot sizes were estimated using a segmented linear model with plateau response, a segmented quadratic model with plateau response, and the modified maximum curvature method. Model fit quality was assessed based on the adjusted coefficient of determination, Akaike information criterion (AIC), and Bayesian information criterion (BIC). Plot size recommendations were obtained, but there are variations in the optimal plot size for the different traits evaluated in two soybean cultivars.