Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Mayara Azevedo"'
Autor:
Gabriela França Oliveira, Ana Carolina Campana Nascimento, Camila Ferreira Azevedo, Maurício de Oliveira Celeri, Laís Mayara Azevedo Barroso, Isabela de Castro Sant’Anna, José Marcelo Soriano Viana, Marcos Deon Vilela de Resende, Moysés Nascimento
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)
Abstract 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 with phenotypic traits of interest, consid
Externí odkaz:
https://doaj.org/article/c8f503afa7e047199e44ff82de5f7c2c
Autor:
Cristiane Botelho Valadares, Moysés Nascimento, Maurício de Oliveira Celeri, Ana Carolina Campana Nascimento, Laís Mayara Azevedo Barroso, Isabela de Castro Sant’Anna, Camila Ferreira Azevedo
Publikováno v:
Ciência Rural, Vol 53, Iss 10 (2023)
ABSTRACT: Quantile Random Forest (QRF) is a non-parametric methodology that combines the advantages of Random Forest (RF) and Quantile Regression (QR). Specifically, this approach can explore non-linear functions, determining the probability distribu
Externí odkaz:
https://doaj.org/article/38f408c6b9a0423b94ae962a949cead4
Autor:
Moysés Nascimento, Paulo Eduardo Teodoro, Isabela de Castro Sant’Anna, Laís Mayara Azevedo Barroso, Ana Carolina Campana Nascimento, Camila Ferreira Azevedo, Larissa Pereira Ribeiro Teodoro, Francisco José Correia Farias, Helaine Claire Almeida, Luiz Paulo de Carvalho
Publikováno v:
Agronomy, Vol 11, Iss 11, p 2179 (2021)
The aim of this work was to answer the following question: can influential points modify the recommendation of genotypes, based on regression methods, in the presence of genotype × environment (G × E)? Therefore, we compared the parameters of the a
Externí odkaz:
https://doaj.org/article/3a6afbe41c404d4da8ccccd2debd5660
Akademický článek
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Autor:
Laís Mayara Azevedo Barroso, Moysés Nascimento, Leiri Daiane Barili, Ana Carolina Campana Nascimento, Naine Martins do Vale, Fabyano Fonseca e Silva, José Eustáquio de Souza Carneiro
Publikováno v:
Ciência Rural, Vol 49, Iss 3 (2019)
ABSTRACT: The aim of this study was to use quantile regression (QR) to characterize the effect of the adaptability parameter throughout the distribution of the productivity variable on black bean cultivars launched by different national research inst
Externí odkaz:
https://doaj.org/article/203284e491ad4e0896c35896a52de2c8
Akademický článek
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Autor:
Gabi Nunes Silva, Laís Mayara Azevedo Barroso, Cosme Damião Cruz, Rodrigo Barros Rocha, Fábio Medeiros Ferreira
Publikováno v:
Coffee Science. 17:1-8
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5e80076ed30e46206987c04b7c24018
https://doi.org/10.25186/.v17i.1985
https://doi.org/10.25186/.v17i.1985
Autor:
Valadares, Cristiane Botelho, Nascimento, Moysés, Celeri, Maurício de Oliveira, Nascimento, Ana Carolina Campana, Barroso, Laís Mayara Azevedo, Sant’Anna, Isabela de Castro, Azevedo, Camila Ferreira
Publikováno v:
Ciência Rural, Volume: 53, Issue: 10, Article number: e20220327, Published: 28 FEB 2023
Quantile Random Forest (QRF) is a non-parametric methodology that combines the advantages of Random Forest (RF) and Quantile Regression (QR). Specifically, this approach can explore non-linear functions, determining the probability distribution of a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______608::350460fac977ad973bfc4f2bbf05c29d
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782023001000403&lng=en&tlng=en
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782023001000403&lng=en&tlng=en
Autor:
Paulo Eduardo Teodoro, Laís Mayara Azevedo Barroso, Moysés Nascimento, Francisco Eduardo Torres, Edvaldo Sagrilo, Adriano dos Santos, Larissa Pereira Ribeiro
Publikováno v:
Pesquisa Agropecuária Brasileira, Vol 50, Iss 11, Pp 1054-1060 (2015)
Resumo: O objetivo deste trabalho foi verificar a concordância entre as redes neurais artificiais (RNAs) e o método de Eberhart & Russel na identificação de genótipos de feijão-caupi (Vigna unguiculata) com alta adaptabilidade e estabilidade fe
Externí odkaz:
https://doaj.org/article/407339b9e1cb4b8cabafa45d4d63d6b8
Autor:
Paulo Eduardo Teodoro, Moysés Nascimento, Francisco Eduardo Torres, Laís Mayara Azevedo Barroso, Edvaldo Sagrilo
Publikováno v:
Pesquisa Agropecuária Brasileira, Vol 50, Iss 10, Pp 878-885 (2015)
Resumo:O objetivo deste trabalho foi selecionar, sob a perspectiva bayesiana, genótipos de feijão-caupi (Vigna unguiculata) que reúnam alta adaptabilidade e estabilidade fenotípicas, no Estado do Mato Grosso do Sul. Foram utilizados dados de quat
Externí odkaz:
https://doaj.org/article/0893aa5105a2402c8fac92aeea2a2939