Experimental precision of grain yield components and selection of superior common bean lines

Research Article High precision experimental statistics for the selection of common bean lines that have superior agronomic performance

“…However, for the number of grains per pod and for the mass of 100 grains, BMS showed no correlation with the other statistics, or it was of low magnitude (r ≤ 0.490). Cargnelutti Filho et al (2009) and Ribeiro et al (2017) also found an absence of correlation or low correlation between BMS and other statistics evaluated for grain yield in competition experiments of common bean genotypes, which agrees with the results obtained in our study for the number of grains per pod and mass of 100 grains.…”

“…Twelve statistics were analyzed in this study: block mean square (BMS), genotype mean square (GMS), error mean square (EMS), overall mean of the experiment (M), amplitude of the means (A), F-test value for genotype (Fc), coefficient of experimental variation (CEV), coefficient of genetic variation (CGV), significant minimum difference (SMD) among genotypes means estimated by the Tukey's test at 5% probability, heritability (h²), coefficient of relative variation (CRV) and selective accuracy (SA). The statistics A, Fc, CEV, CGV, SMD, h², CRV and SA were obtained as described by Ribeiro et al (2017).…”

“…The statistics Fc, heritability (h²) and selective accuracy (SA) have been shown to be adequate to evaluate the experimental precision of grain yield in competition experiments with common bean (Cargnelutti Filho et al, 2009;Ribeiro et al, 2017), soybean (Cargnelutti Filho et al, 2009), and wheat (Benin et al, 2013) genotypes. Recently, it was demonstrated that these statistics enable the selection of common bean genotypes with high experimental precision for primary yield components (Ribeiro et al, 2017) and for earliness and upright plant architecture traits (Ribeiro ND, Steckling SDM, Maziero SM and Kläsener GR, unpublished results). However, in the routine of a breeding program, it is not feasible to use various experimental precision statistics to select common bean genotypes that have superior agronomic performance.…”

“…In competition experiments involving common bean genotypes, a positive correlation estimate was observed between Fc and h², Fc and coefficient of relative variation (CRV), Fc and SA, h² and CRV, h² and SA, and CRV and SA for grain yield (Ribeiro et al, 2017). This means that these statistics should not be used together, because they involve redundant information.…”

Consumer preference and the technological and nutritional quality of different bean colours

“…The Scott-Knott test at 5% probability was used to compare the means. Experimental precision was evaluated by the coefficient of experimental variation and selective accuracy, as described by Ribeiro et al (2017).…”