Genetic parameters and multiple-trait selection in wheat genotypes

Abstract

Mixed models and multivariate analysis are powerful tools for selecting superior genotypes in plant breeding programs. The BLUP (best linear unbiased prediction) method has been used to predict genetic values without environmental effects. Furthermore, the FAI-BLUP (ideotype-design index) procedure is especially valuable for plant breeding because of multiple-trait selection. This study aimed to determine the genetic potential of advanced wheat generations using REML/BLUP in combination with multivariate techniques for the selection of superior genotypes. The experiment consisted of eleven wheat (Triticum aestivum L.) genotypes. The experimental design was randomized blocks, with three replications. Plant height, spike insertion height, number of tillers, number of spikelets, kernel width, hectoliter weight and kernel weight per plant were determined. The genetic parameters were estimated using the REML/BLUP methodology, and the FAI-BLUP index was calculated using predicted genetic values. The genotypes UFSMFW 1-02, UFSMFW 1-05 and UFSMFW 1-04 show potential to increase the grain yield. The selection gains for number of tillers (14.63 %) and kernel weight per plant (22.35 %) indicate the potential to select superior genotypes.

Estabilidade e adaptabilidade de cultivares de alface em diferentes substratos

“…On the other hand, the G x E interaction and the residual variance, respectively, were the most important variations, which most contributed to the phenotypic variation, evidencing the influence of the substrate compositions on the cultivars. Meier et al (2021) started that greater residual variation is associated to the components of the random effects that are considered in the prediction of the response variable.…”

Multitrait selection in seedless grape hybrids in semiarid regions of Brazil

“…Although proposed only recently, the FAI‐BLUP index has already been used efficiently in (i) the evaluation and selection of sorghum hybrids for biomass increase and energy cogeneration (Oliveira et al., 2019; Silva et al., 2018); (ii) soybean selection for biodiesel production (Woyann et al., 2020); (iii) selection of superior common bean progenies (Rocha et al., 2019); (iv) selection of Jatropha curcas L. genotypes for bioenergetic purposes (Rodrigues et al., 2020); (v) selection of superior pumpkin genotypes with smaller size and higher seed yield for oil production (Oliveira et al., 2020); (vi) combined selection in maize (Peixoto et al., 2021); (vii) simultaneous selection of mangaba based on eleven agronomic traits (Almeida et al., 2021); (viii) selection of early soybean progenies that are more erect and have higher grain yield potential (Volpato et al., 2021); (ix) and selection of superior wheat genotypes for grain yield, tiller number and grain weight per plant (Meier et al., 2021).…”

“…Almeida et al (2021), selecting mangaba genotypes using the FAI-BLUP index, also found desirable gains for most of the variables considered in the study. In the selection of superior wheat genotypes, it was also possible to obtain desirable genetic gains for yield traits (Meier et al, 2021).…”

“…The efficiency of this selection index has been reported for the improvement of different crops (Almeida et al, 2021;Meier et al, 2021;Oliveira et al, 2019Oliveira et al, , 2021Peixoto et al, 2021;Rocha et al, 2019;Silva et al, 2018;Volpato et al, 2021;Woyann et al, 2020). However, no references were found for the use of the FAI-BLUP index in the genetic improvement of grapevines.…”

Multiple-Traits Selection in White Guinea Yam (Dioscorea rotundata) Genotypes

“…This view is supported by the suggestion that close attention should also be paid to genotypes that are very close to the cut-off point [ 13 ]. The FAI-BLUP index model has also been utilized for the evaluation of wheat genotypes involving genetic constitutions with desirable characteristics for grain yield [ 32 ]. Our study demonstrated that the simultaneous selection for multiple traits based on the ideotype-design FAI-BLUP index contributes to the identification of high performing genotypes and expected gain from selecting those genotypes for the traits considered.…”