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

Abstract

performance in Value of Cultivation and Use experiments. The SA makes the correct ranking of the common bean genotypes for agronomic performance traits possible, based on genetic superiority; consequently, SA should be implemented in the routine of common bean breeding programs.

Technological quality characters evaluated in common bean lines with higher precision statistics

“…For absorption and cooking time, the Fc, GVC, RVC, h 2 , and SA statistics are in agreement in the identification of more precise experiments (Tables 3 and 4), which can be explained by the fact that these five statistics include genetic variance (genotype mean square) in their estimates. The Fc, GVC, RVC, h 2 , and SA statistics show a positive correlation with the genotype mean square for grain yield (Ribeiro et al, 2017), yield components, and characters related to earliness and upright plant architecture in common bean (Ribeiro et al, 2018). Correlated statistics provide redundant information, so they should not be presented together.…”

“…Selective accuracy has been indicated for use in common bean experiments as a measure of experimental classification for agronomic characters (Cargnelutti Filho et al, 2009;Ribeiro et al, 2017Ribeiro et al, , 2018Ribeiro et al, , 2020b and mineral concentration (Ribeiro et al, Pesq. agropec.…”

“…Conversely, the SA refers to the correlation between the true genotypic value of the genetic treatment and that estimated, or predicted from information of the experiments (Resende & Duarte, 2007). For this reason, SA showed to be an easily interpreted and efficient statistic to identify more precise experiments to select superior common bean lines for agronomic characters (Ribeiro et al, 2017(Ribeiro et al, , 2018(Ribeiro et al, , 2020b and mineral concentration (Ribeiro et al, 2020a). The Fc, GVC, RVC, h 2 , and SA statistics considered the genetic variance in their calculation and exhibited a positive correlation with the genotype mean square (Ribeiro et al, 2018).…”

“…For this reason, SA showed to be an easily interpreted and efficient statistic to identify more precise experiments to select superior common bean lines for agronomic characters (Ribeiro et al, 2017(Ribeiro et al, , 2018(Ribeiro et al, , 2020b and mineral concentration (Ribeiro et al, 2020a). The Fc, GVC, RVC, h 2 , and SA statistics considered the genetic variance in their calculation and exhibited a positive correlation with the genotype mean square (Ribeiro et al, 2018). Therefore, in experiments conducted by the commonbean breeding programs, it is important to evaluate other statistics that provide high experimental precision in the selection of superior lines.…”

Precisão experimental em ensaios de competição de genótipos de trigo nos estados do Rio Grande do Sul e Paraná

“…Outras estatísticas, tais como o coeficiente de variação genético (CVg) (CRUZ, 2016), o coeficiente de variação relativa (CVr) (CRUZ, 2016) Essas estatísticas foram utilizadas para avaliar a precisão experimental em ensaios de competição de genótipos de milho STORCK, 2007CARGNELUTTI FILHO et al, 2018), soja (CARGNELUTTI FILHO; STORCK; RIBEIRO, 2009;STORCK et al, 2010), feijão (CARGNELUTTI FILHO; STORCK; RIBEIRO, 2009;MEZZOMO, 2018;RIBEIRO et al, 2020; RIBEIRO; KLÄSENER; SANTOS, 2022), cana-de-açúcar (CARGNELUTTI FILHO; BRAGA JUNIOR; LÚCIO, 2012), arroz irrigado e trigo (BENIN et al, 2013). Esses estudos apontam que quanto maior for o escore dessas estatísticas maior é a precisão experimental.…”