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Rodrigo R. Amadeu

Researcher at University of Florida

Publications -  26
Citations -  503

Rodrigo R. Amadeu is an academic researcher from University of Florida. The author has contributed to research in topics: Population & Quantitative trait locus. The author has an hindex of 10, co-authored 24 publications receiving 288 citations. Previous affiliations of Rodrigo R. Amadeu include University of São Paulo & Escola Superior de Agricultura Luiz de Queiroz.

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AGHmatrix: R Package to Construct Relationship Matrices for Autotetraploid and Diploid Species: A Blueberry Example

TL;DR: An R package for autopolyploids to construct the relationship matrix is developed and the level and effect of double reduction in blueberry is estimated.
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Genomic Prediction of Autotetraploids; Influence of Relationship Matrices, Allele Dosage, and Continuous Genotyping Calls in Phenotype Prediction.

TL;DR: Comparing the use of read depth as continuous parameterization with ploidy parameterizations in the context of genomic selection (GS) and the genotypic and phenotypic data used in this study are made available for comparative analysis of dosage calling and genomic selection prediction models in the contexts of autopolyploids.
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How can a high-quality genome assembly help plant breeders?

TL;DR: The results of genome-wide association studies and genomic selection that were already published using a blueberry draft genome as reference are compared with the results using the recent released chromosome-scale and haplotype-phased blueberry genome.
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Genomic Selection with Allele Dosage in Panicum maximum Jacq.

TL;DR: This work provides bioinformatic and modeling guidelines to consider tetraploid dosage and observed that genomic selection may lead to additional gains in recurrent selection program of P. maximum.
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Estimation of genetic parameters and prediction of breeding values in an autotetraploid blueberry breeding population with extensive pedigree data

TL;DR: Evaluating the use of REML/BLUP in the University of Florida blueberry breeding program in order to estimate genetic parameters and predict BVs of primary selection traits found the highest narrow-sense heritabilities for fruit weight, scar diameter, and yield.