1. Combining ability and selection for agronomic and nutritional traits in Urochloa spp. hybrids.
- Author
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Gouveia, Beatriz Tomé, Mateus, Rogério Gonçalves, Barrios, Sanzio Carvalho Lima, do Valle, Cacilda Borges, de Sousa Bueno Filho, Júlio Sílvio, Fernando Rios, Esteban, Dias, Alexandre Menezes, and Rodrigues Nunes, José Airton
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SIGNALGRASS , *ANIMAL breeding , *NUTRITIONAL value , *PARENT-child legal relationship - Abstract
The Urochloa spp. breeding program at EMBRAPA‐Brazil targets the development of apomictic hybrids to improve animal performance, while reducing the environmental impact of livestock. In summary, breeders perform multiple crosses between apomictic and sexual parents, and screen progeny to perform selections for agronomic and nutritional traits across several harvests, years and locations. Thus, choosing the right parents and the cross combinations is crucial for the success of the breeding program. The objectives of this study were to: (i) estimate the general (GCA) and specific (SCA) combining ability, and contribution of additive and nonadditive effects, from a partial diallel cross design between three apomictic and ten sexual parents, for agronomical and nutritional traits in Urochloa spp.; (ii) assess genetic gain for all traits by selecting for yield of high nutritional value leaf mass (NLM); (iii) characterize the genotype profiles using genotype by yield*trait (GYT) biplot analysis. A total of 1380 interspecific hybrids from 29 full‐sib progenies were evaluated and then the hybrid selection was performed based on studentized best linear unbiased prediction of NLM. The 10% top‐performing hybrids were used in the GYT analysis using NLM as the basic variable. There was a predominance of nonadditive effects on the phenotypic expression of agronomic and nutritional value traits. The GCA was observed only for some traits in sexual parents, whereas SCA was observed in all traits. The selection based on NLM provided favorable gains for most of the agronomic traits and GYT biplot analysis was efficient to characterize genotype profiles. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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