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Genomic prediction in multi-environment trials in maize using statistical and machine learning methods. In the context of multi-environment trials (MET), genomic prediction is proposed as a tool that allows the prediction of the phenotype of single cross hybrids that were not tested in field trials. Thi... ... Repository: BDPA Publication year: 2024
Using visual scores for genomic prediction of complex traits in breeding programs. An approach for handling visual scores with potential errors and subjectivity in scores was evaluated in simulated and blueberry recurrent selection breeding schemes to assist breeders in their decisi... ... Repository: BDPA Publication year: 2024
Agregação do solo sob diferentes usos e cobertura vegetal no bioma Cerrado. O objetivo do trabalho foi avaliar a agregação do solo sob diferentes usos e manejo da terra e em área sob vegetação de mata nativa do Cerrado, no município de Unaí (MG). Repository: BDPA Publication year: 2023
Population size in QTL detection using quantile regression in genome?wide association studies. The aim of this study was to evaluate the performance of Quantile Regression (QR) in Genome-Wide Association Studies (GWAS) regarding the ability to detect QTLs (Quantitative Trait Locus) associated w... ... Repository: BDPA Publication year: 2023
Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models. Yield is one of the most important traits of arabica coffee. Plant breeders seek to maximize yield directly or indirectly, using other related traits. The standard multi-trait genome-wide association... ... Repository: BDPA Publication year: 2023
Tamanho amostral e detecção de genes via GWAS em características quantitativas do cafeeiro. O presente documento refere-se à avaliação prática do potencial da GWAS no melhoramento dos cafeeiros das espécies Coffea arabica e Coffea canephora. O objetivo geral é orientar a aplicação eficiente... ... Repository: BDPA Publication year: 2022
Increasing cassava root yield: additive-dominant genetic models for selection of parents and clones. Genomic selection has been promising in situations where phenotypic assessments are expensive, laborious, and/or inefficient. This work evaluated the efficiency of genomic prediction methods combined... ... Repository: BDPA Publication year: 2022
Marker effects and heritability estimates using additive-dominance genomic architectures via artificial neural networks in Coffea canephora. Many methodologies are used to predict the genetic merit in animals and plants, but some of them require priori assumptions that may increase the complexity of the model. Artificial neural network (AN... ... Repository: BDPA Publication year: 2022
Determination of optimal number of independent components in yield traits in rice. The principal component regression (PCR) and the independent component regression (ICR) are dimensionality reduction methods and extremely important in genomic prediction. These methods require the ch... ... Repository: BDPA Publication year: 2022
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. The Fisher?s infinitesimal model is traditionally used in quantitative genetics and genomic selection, and it attributes most genetic variance to additive variance. Recently, the dominance maximizatio... ... Repository: BDPA Publication year: 2022

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