Author

Pedro Crescêncio Souza Carneiro

Universidade Federal de ViçosaORCID 0000-0002-0872-5618Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:statistical model· 2

Frequent Co-Authors

Alexandre Bryan HeinemanniD· 1 shared André Ricardo Gomes BezerraiD· 1 shared F. BreseghelloiD· 1 shared Fabíola dos Santos Dias· 1 shared Filipe Manoel FerreiraiD· 1 shared Germano Costa‐NetoiD· 1 shared Guilherme Rodrigues PereiraiD· 1 shared João Romero do Amaral Santos de Carvalho RochaiD· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperGenetics

Alexandre Bryan HeinemannORCID

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2 papers

Recent·Most cited

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, Filipe Manoel Ferreira, Guilherme Rodrigues Pereira, André Ricardo Gomes Bezerra, Rodrigo Silva Alves, Alexandre Bryan Heinemann, F. Breseghello, Pedro Crescêncio Souza Carneiro, Matheus Dalsente Krause, Germano Costa‐Neto, 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.

Theoretical and Applied Genetics · Mar 12, 2024Peer-reviewedGenetics

New genotypic adaptability and stability analyses using Legendre polynomials and genotype-ideotype distances

Michel Henriques de Souza, José Domingos Pereira Júnior, Skarlet De Marco Steckling, Jussara Mencalha, Fabíola dos Santos Dias, João Romero do Amaral Santos de Carvalho Rocha, Pedro Crescêncio Souza Carneiro, José Eustáquio de Souza Carneiro

The paper introduces a new methodology for analyzing genotypic adaptability and stability using Legendre polynomials and genotype-ideotype distances, showing improved accuracy in predicting cultivar performance across environments.

PLoS ONE · Dec 2, 2020Peer-reviewedGenetics