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| AONO, A. H.; FERREIRA, R. C. U.; MORAES, A. da C. L.; LARA, L. A. de C.; PIMENTA, R. J. G.; COSTA, E. A.; PINTO, L. R.; LANDELL, M. G. de A.; SANTOS, M. F.; JANK, L.; BARRIOS, S. C. L.; VALLE, C. B.; CHIARI, L.; GARCIA, A. A. F.; KUROSHU, R. M.; LORENA, A. C.; GORJANC, G.; SOUZA, A. P. de. |
| Poaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of... |
| Tipo: Artigo de periódico |
Palavras-chave: Cana de Açúcar; Gramínea Forrageira; Recurso Genético; Forage grasses; Genetic resources; Plant breeding; Poaceae; Polyploidy; Saccharum; Sugarcane. |
| Ano: 2022 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1150365 |
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| MARTINS, F. B.; SOUZA, A. P. DE; VIGNA, B. B. Z.; VALLE, C. B. do; JANK, L.; SANTOS, M. F.; BARRIOS, S. C. L.; SIMEÃO, R. M.; CHIARI, L.; FERREIRA, R. C. U.; AONO, A. H.; MORAES, A. C. L.. |
| Artificial hybridization plays a fundamental role in plant breeding programs since it generates new genotypic combinations that can result in desirable phenotypes. Depending on the species and mode of reproduction, controlled crosses may be challenging, and contaminating individuals can be introduced accidentally. In this context, the identification of such contaminants is important to avoid compromising further selection cycles, as well as genetic and genomic studies. The main objective of this work was to propose an automated multivariate methodology for the detection and classification of putative contaminants, including apomictic clones (ACs), self-fertilized individuals, half-siblings (HSs), and full contaminants (FCs), in biparental polyploid... |
| Tipo: Artigo de periódico |
Palavras-chave: GBS; Apomictic clones; Self fertilization; Half sibling; Allele dosage; Clustering analysis; Shiny; Principal component analysis. |
| Ano: 2021 |
URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1137227 |
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