Genetic gain via REML/BLUP and selection indices in snap bean

Abstract

The aim of this study was to compare four selection indexes and REML/BLUP methodology in the evaluation of predicted genetic gains of traits of interest in snap bean breeding program. We evaluated 17 selected lines, in a randomized complete block design, with four replicates, in four environments, Bom Jesus de Itapaboana-RJ, in 2011 and 2012 and Cambuci-RJ, in 2011 and 2013. The evaluated traits were pod and grain productivity, number of pods per plant, number of seeds per pod and weight of 100 seeds. For gain prediction, the employed selection indexes were Pesek & Baker, Smith & Hazel, Mulamba & Mock, Williams and REML/BLUP methodology. Among the tested selection indexes, Mulamba & Mock was the one which showed the best gain distribution considering the tested variables, such as the higher coincidence coefficients in comparison to REML/BLUP, resulting in 62% of grain productivity and pod productivity per plant. The REML/BLUP methodology permitted to select lines with high relative performances and obtained simultaneous gains for the evaluated traits, being superior in relation to the tested selection indexes for snap bean crop.

Selection of top cross hybrids for green maize yield via REML/Blup method

“…Thus, the REML/Blup methodology is an important statistical tool, which can help breeders to conduct breeding programs during selection processes. Similar results demonstrating the potential for the REML/Blup technique were seen in studies on beans, by Sousa et al (2017), Gomes et al (2018), and Cruz et al (2018); and maize, by Arnhold et al (2009), Oliveira et al (2016), Entringer et al (2016), and Mendonça et al (2016), all confirming the results of this study. ) and mean grain mass, municipality of Jataí, Goiás State, Brazil, UFG, 2018.…”

Selection indexes in the simultaneous increment of yield components in topcross hybrids of green maize

“…solution vector, by the REML/BLUP. This corrects the values of environmental effects, predicting the genotypic values in a precise and nonbiased manner, which leads to a maximizing of the genetic gains with the selection (Freitas et al, 2013;Rodrigues et al, 2013;Silva et al, 2017;Gomes et al, 2018). By the REML/BLUP method, the estimates of the overall mean (u) of the experiment were: SEYIELD (14,670.92 kg ha -1 ); CEYIELD (5,314.96 kg ha -1 ); MASS (130.77 g); EL (18.05 cm;ED (4.61 cm); and NER (15.04 rows).…”

“…Besides the use of selection indexes, a widely used alternative with great accuracy in the selection process is the use of variance components estimated by the restricted maximum likelihood (REML) and the genetic or genotypic values predicted by the best linear unbiased predictor (BLUP) (Rodrigues et al, 2013). These procedures provide additional relevant parameters for the identification of superior genotypes (Maia et al, 2011;Ramalho & Araújo, 2011;Freitas et al, 2013;Gomes et al, 2018).…”

Selection strategies for identifying fast cooking, mineral-biofortified bean cultivars with high agronomic performance

“…The sign and/or magnitude of the obtained individual gains varied, which enabled the analysis and definition of the best combination of selection index and economic weight to be used for the selection of superior common bean cultivars for all the traits evaluated. The use of selection indices allowed the simultaneous selection for several important traits for common bean (Bertoldo et al, 2010;Gomes et al, 2018;Jost et al, 2012;Maziero et al, 2015) and soybean (Costa et al, 2004) breeding programs. The higher total genetic gain estimate and/or the attainment of individual -----------------------------------------------------------------------------------------------------------------------------------------------% ----------------------------------------------------------------------------------------------------------------------------------------------- gains favorable to the selection objectives defined the best selection index to be employed in the selection of superior common bean cultivars.…”

“…This is because direct selection allowed for a high genetic gain for traits analyzed individually, but caused undesirable changes in other important traits for selection (Jost et al, 2012;Maziero et al, 2015). Selection indices, in turn, allowed for the identification of superior common bean cultivars for several traits (Arns et al, 2018;Bertoldo et al, 2010;Dias et al, 2020;Gomes et al, 2018;Jost et al, 2012;Maziero et al, 2015;Ribeiro et al, 2019a;Silva et al, 2018;Zanotti et al, 2020), thereby enhancing the efficiency of breeding programs.…”