Author

Saulo Fabrício da Silva Chaves

Universidade Federal de ViçosaORCID 0000-0002-0694-1798Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetics· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 1

Frequent Co-Authors

Rodrigo Silva AlvesiD· 3 shared Filipe Manoel FerreiraiD· 2 shared Kaio Olímpio das Graças DiasiD· 2 shared Luíz Antônio dos Santos DiasiD· 2 shared Alexandre Bryan HeinemanniD· 1 shared Alexandre Magno SebbenniD· 1 shared André Ricardo Gomes BezerraiD· 1 shared Elizabete Keiko TakahashiiD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersGenetics

Rodrigo Silva AlvesORCID

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3 papers

Recent·Most cited

GeneticsTheoretical and Applied GeneticsPeer-reviewedMar 12, 2024

GIS-FA: An approach to integrate thematic maps, factor-analytic and envirotyping for cultivar targeting

Maurício dos Santos Araújo, Saulo Fabrício da Silva Chaves, Luíz Antônio dos Santos Dias…·Kaio Olímpio das Graças Dias

The paper introduces GIS-FA, a method integrating GIS, factor-analytic models, and envirotyping to predict cultivar performance in untested environments and support decision-making.

34 citationstop 2%

statistical modelbenchmarking

𝕏 PostBluesky

GeneticsbioRxivPreprintApr 14, 2023

A data-driven approach for enhancing forest productivity by accounting for indirect genetic effects

Filipe Manoel Ferreira, Saulo Fabrício da Silva Chaves, Leonardo Lopes Bhering…·Kaio Olímpio das Graças Dias

The paper develops a method to enhance forest productivity by analyzing indirect genetic effects in clonal composites of Eucalyptus hybrids.

DOI 10.1101/2023.04.14.536978

statistical model

𝕏 PostBluesky

GeneticsEuphyticaPeer-reviewedNov 10, 2021

Theobroma grandiflorum breeding optimization based on repeatability, stability and adaptability information

Saulo Fabrício da Silva Chaves, Rafael Moysés Alves, Rodrigo Silva Alves…·Luíz Antônio dos Santos Dias

This study estimates the optimal number of harvests for genetic selection of Theobroma grandiflorum progenies and identifies the most promising ones based on productivity, stability, and adaptability.

15 citations

statistical model

𝕏 PostBluesky