At present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F 2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; ) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of . Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny.

The world population is expected to be larger and wealthier over the next few decades and will require more animal products, such as milk and beef. Tropical regions have great potential to meet this growing global demand, where pasturelands play a major role in supporting increased animal production. Better forage is required in consonance with improved sustainability as the planted area should not increase and larger areas cultivated with one or a few forage species should be avoided. Although, conventional tropical forage breeding has successfully released well-adapted and high-yielding cultivars over the last few decades, genetic gains from these programs have been low in view of the growing food demand worldwide. To guarantee their future impact on livestock production, breeding programs should leverage genotyping, phenotyping, and envirotyping strategies to increase genetic gains. Genomic selection (GS) and genome-wide association studies play a primary role in this process, with the advantage of increasing genetic gain due to greater selection accuracy, reduced cycle time, and increased number of individuals that can be evaluated. This strategy provides solutions to bottlenecks faced by conventional breeding methods, including long breeding cycles and difficulties to evaluate complex traits. Initial results from implementing GS in tropical forage grasses (TFGs) are promising with notable improvements over phenotypic selection alone. However, the practical impact of GS in TFG breeding programs remains unclear. The development of appropriately sized training populations is essential for the evaluation and validation of selection markers based on estimated breeding values. Large panels of single-nucleotide polymorphism markers in different tropical forage species are required for multiple application targets at a reduced cost. In this context, this review highlights the current challenges, achievements, availability, and development of genomic resources and statistical methods for the implementation of GS in TFGs. Additionally, the prediction accuracies from recent experiments and the potential to harness diversity from genebanks are discussed. Although, GS in TFGs is still incipient, the advances in genomic tools and statistical models will speed up its implementation in the foreseeable future. All TFG breeding programs should be prepared for these changes.

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RESUMO -Foram avaliadas as relações entre os componentes físicos e químicos do maracujá-doce cultivado em Viçosa-MG. Cem frutos foram colhidos no estágio final do amadurecimento, com pericarpo com forte coloração amarelo-palha. Os frutos foram analisados quanto às características físicas e químicas, e os dados foram submetidos à análise de correlação de Pearson. Houve grande variação entre os valores de cada característica, sobremaneira para massa da matéria fresca e volume dos frutos, e massa da matéria fresca do pericarpo, que apresentaram médias de 194,53 ± 42,19 g, 253,85 ± 49,73 cm 3 e 143,30 ± 40,50 g, respectivamente. O número de sementes variou de 110 a 379 por fruto. Verificaram-se correlações significativas entre a maioria das características avaliadas. O diâmetro apresentou correlação positiva com a massa da matéria fresca da polpa e negativa com o percentual de polpa, indicando que frutos maiores têm, proporcionalmente, menos polpa que os menores. A massa da matéria seca das sementes correlacionou-se positivamente com a massa da matéria fresca da polpa (0,6248**) e com a porcentagem de polpa (0,4375**). Semelhantemente, o número de sementes também apresentou correlação positiva com a massa da matéria fresca da polpa (0,5119**) e com a porcentagem de polpa (0,3957**), indicando que frutos com mais sementes apresentam maior rendimento de polpa. Contudo, houve correlação negativa entre número de sementes e teor de sóli-dos solúveis (-0,2161*), sugerindo a diluição do suco devido ao maior número de sementes e ao aumento da proporção de polpa. Também houve correlação negativa entre a espessura e a massa da matéria fresca do pericarpo e a porcentagem de polpa, indicando que a casca mais espessa reduz o diâmetro da cavidade interna do fruto, onde se acumula a polpa comestível. Termos de indexação: Passiflora alata Curtis, composição do fruto, rendimento de polpa. RELATIONS AMONG PHYSICAL AND CHEMICAL CHARACTERISTICS OF SWEET PASSION FRUIT CULTIVATED IN VIÇOSA, MGABSTRACT -The relationships between the physical and chemical components of sweet passion fruits produced in Viçosa, MG, were evaluated. One hundred fruits were harvested in the final stage of ripening, when the pericarp showed strong straw-yellow color. The fruits were analyzed for their physical and chemical characteristics and the data were analyzed by Pearson correlation. There was great variation among the values of each feature, especially for fresh weight and volume of the fruit and the fresh weight of the pericarp, which showed average values of 194.53 ± 42.19 g, 253.85 ± 49.73 cm3 and 143.30 ± 40.50 g, respectively. The number of seeds ranged from 110 to 379 per fruit, and there were significant correlations among most traits. The diameter was positively correlated with the fresh weight of the pulp and negatively with the percentage of pulp, indicating that large fruits have proportionally less pulp than smaller ones. The dry weight of the seeds was positively correlated with the fresh weight of the pulp (0.6248 **) and the percentage of p...

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