Unravelling the role of key genes involved coffee leaf rust resistance

Autor: Danúbia Rodrigues Alves, Dênia Pires de Almeida, Edson Mario de Andrade Silva, Isabel Samila Lima Castro, Pedro Ricardo Rossi Marques Barreiros, Tiago Antônio de Oliveira Mendes, Laércio Zambolim, Eveline Teixeira Caixeta

Publikováno v: Current Plant Biology, Vol 38, Iss , Pp 100347- (2024)

The biotrophic fungus Hemileia vastatrix is the pathogen responsible for coffee leaf rust, a devastating disease in several coffee-producing countries. Despite the importance of studying the interaction between Coffea and H. vastatrix, a more compreh

Externí odkaz: https://doaj.org/article/3a5026dca700473095ec53d84b753e02

Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms

Autor: Ithalo Coelho de Sousa, Moysés Nascimento, Gabi Nunes Silva, Ana Carolina Campana Nascimento, Cosme Damião Cruz, Fabyano Fonseca e Silva, Dênia Pires de Almeida, Kátia Nogueira Pestana, Camila Ferreira Azevedo, Laércio Zambolim, Eveline Teixeira Caixeta

Publikováno v: Scientia Agricola, Vol 78, Iss 4 (2020)

ABSTRACT Genomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the prediction of genetic merit. In general, s

Externí odkaz: https://doaj.org/article/3c56719c58f047acad58b7a1217ff577

Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee

Autor: Gabi Nunes Silva, Moysés Nascimento, Isabela de Castro Sant’Anna, Cosme Damião Cruz, Eveline Teixeira Caixeta, Pedro Crescêncio Souza Carneiro, Renato Domiciano Silva Rosado, Kátia Nogueira Pestana, Dênia Pires de Almeida, Marciane da Silva Oliveira

Publikováno v: Pesquisa Agropecuária Brasileira, Vol 52, Iss 3, Pp 186-193 (2017)

Abstract: The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica). This study used 245 individuals o

Externí odkaz: https://doaj.org/article/6e4a39e66d3f453ea08547554608f9bf

The role of receptor-like kinases in fungal/microbial resistance in plants

Autor: Geleta Dugassa Barka, Isabel Samila Lima Castro, Danúbia Rodrigues Alves, Dênia Pires de Almeida, Eveline Teixeira Caixeta

Publikováno v: Plant Receptor-Like Kinases ISBN: 9780323905947

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::09753fee6c9e5e24e68b695fab4aa538
https://doi.org/10.1016/b978-0-323-90594-7.00019-3

Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms

Autor: Ithalo Coelho de Sousa, Moysés Nascimento, Gabi Nunes Silva, Ana Carolina Campana Nascimento, Cosme Damião Cruz, Fabyano Fonseca e Silva, Dênia Pires de Almeida, Kátia Nogueira Pestana, Camila Ferreira Azevedo, Laércio Zambolim, Eveline Teixeira Caixeta

Publikováno v: Scientia Agricola, Vol 78, Iss 4 (2020)
Scientia Agricola, Volume: 78, Issue: 4, Article number: e20200021, Published: 08 JUL 2020
Scientia Agricola v.78 n.4 2021
Scientia Agrícola
Universidade de São Paulo (USP)
instacron:USP
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice)
Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA

Genomic selection (GS) emphasizes the simultaneous prediction of the genetic effects of thousands of scattered markers over the genome. Several statistical methodologies have been used in GS for the prediction of genetic merit. In general, such metho

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b979dcf41f544e3b7dadbe6ffa09f0c2
https://doi.org/10.1590/1678-992x-2020-0021