This study proposes a new multitrait index based on factor analysis and ideotype-design (FAI-BLUP index), and validates its potential on the selection of elephant grass genotypes for energy cogeneration. Factor analysis was carried out, and afterwards, factorial scores of each ideotype were designed according to the desirable and undesirable factors, and the spatial probability was estimated based on genotype-ideotype distance, enabling genotype ranking. In order to quantify the potential of the FAI-BLUP index, genetic gains were predicted and compared with the Smith-Hazel classical index. The FAI-BLUP index allows ranking the genotypes based on multitrait, free from multicollinearity, and it does not require assigning weights, as in the case of the SmithHazel classical index and its derived indices. Furthermore, the genetic correlation -positive or negative -within each factor was taken into account, preserving their traits relationship, and giving biological meaning to the ideotypes. The FAI-BLUP index indicated the 15 elephant grass with the highest performance for conversion to bioenergy via combustion, and predicted balanced and desirable genetic gains for all traits. In addition, the FAI-BLUP index predicted gains of approximately 62% of direct selection, simultaneously for all traits that are desired to be increased, and approximately 33% for traits which are desired to be decreased. The genotypes selected by the FAI-BLUP index have potential to improve all traits simultaneously, while the Smith-Hazel classical index predicted gains of 66% for traits that are desired to be increased, and À32% for traits that are desired to be decreased, and it does not have potential to improve all traits simultaneously. The FAI-BLUP index provides an undoubtable selection process and can be used in any breeding programme aiming at selection based on multitrait.

Resumo -O objetivo deste trabalho foi estimar os parâmetros genéticos e predizer o valor genético de populações e indivíduos oriundos de populações segregantes de trigo, com o uso da metodologia de modelos mistos ("restricted maximum likelihood"/"best linear unbiased prediction", REML/BLUP). Trinta e seis populações segregantes de trigo e quatro controles foram avaliados na geração F 3 , em delineamento de blocos ao acaso, com informações de indivíduo retiradas de dentro das parcelas. Os caracteres avaliados foram: produção de grãos, índice de colheita, número de perfilhos e altura de planta. Observou-se a existência de variabilidade genética entre populações em todos os caracteres avaliados. A herdabilidade média variou de 39,15 a 92,78%, e a acurácia, de 62,57 a 96,32%, na seleção de populações. A herdabilidade individual no sentido restrito foi baixa dentro das populações, em todos os caracteres. A acurácia na seleção individual apresentou magnitude média, quanto ao caráter altura de plantas, e baixa quanto aos demais caracteres. A herdabilidade individual contribui para maior ganho nos caracteres altura de planta e índice de colheita com o uso do BLUP individual, em comparação ao BLUP de populações. As populações segregantes Embrapa22/BRS207, Embrapa22/ VI98053, Embrapa22/IVI01041, BRS254/BRS207, BRS254/VI98053, BRS254/UFVT1Pioneiro e BRS264/ BRS207 destacam-se por apresentar valor genético aditivo elevado em dois ou mais caracteres.Termos para indexação: Triticum aestivum, análise de deviance, dados desbalanceados, estratégias de melhoramento, população segregante, REML/BLUP. Estimation of genetic parameters and prediction of additive genetic value for wheat by mixed modelsAbstract -The objective of this work was to estimate the genetic parameters and to predict the genotypic value of populations and individuals from wheat segregating populations, using the methodology of mixed models (restricted maximum likelihood/best linear unbiased prediction, REML/BLUP). Thirty-six wheat segregating populations and four controls were evaluated in the F 3 generation, in a randomized complete block design, with individual information taken from within the plots. The evaluated traits were: grain yield, harvest index, number of tillers, and plant height. Genetic variability between populations was observed for all evaluated traits. The mean heritability varied from 39.15 to 92.78%, and accuracy varied from 62.57 to 96.32% in the selection of populations. The narrow-sense individual heritability was low within populations for all traits. The accuracy for individual selection had a moderate value for plant height, and low values for the other traits. Individual heritability contributes to a greater gain for the traits plant height and harvest index with the use of individual BLUP, in comparison to population BLUP. The segregating populations Embrapa22/BRS207, Embrapa22/VI98053, Embrapa22/IVI01041, BRS254/BRS207, BRS254/VI98053, BRS254/UFVT1Pioneiro, and BRS264/BRS207 stand out with high additive genetic value, for two or mor...

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Persistence may be defined as high sustained yield over multi-harvest. Genetic insights about persistence are essential to ensure the success of breeding programs and any biomass-based project. This paper focuses on assessing the biomass yield persistence for bioenergy purpose of 100 elephantgrass clones measured in six growth seasons in Brazil. To assess the clones' persistence, an index based on random regression models and genotype-ideotype distance was proposed. Results suggested the existence of wide genetic variability between elephantgrass clones, and that the yield trajectories along the harvests generate genetic insights into elephantgrass clones’ persistence and G x E interaction. A gene pool that acts over the biomass yield (regardless of the harvest) was detected, as well as other gene pools, which show differences on genes expression (these genes are the major responsible for clones’ persistence). The lower and higher clones’ persistence was discussed based on genome dosage effect and natural biological nitrogen fixation ability applied to bioenergy industry. The huge potential of energy crops necessarily is associated with genetic insights into persistence, so just this way, breeding programs could breed a new cultivar that fulfills the bioenergy industries.

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