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Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee PAB
Silva,Gabi Nunes; Nascimento,Moysés; Sant’Anna,Isabela de Castro; Cruz,Cosme Damião; Caixeta,Eveline Teixeira; Carneiro,Pedro Crescêncio Souza; Rosado,Renato Domiciano Silva; Pestana,Kátia Nogueira; Almeida,Dênia Pires de; Oliveira,Marciane da Silva.
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 of a F2 population derived from the self-fertilization of the F1 H511-1 hybrid, resulting from a crossing between the susceptible cultivar Catuaí Amarelo IAC 64 (UFV 2148-57) and the resistant parent Híbrido de Timor (UFV 443-03). The 245 individuals were genotyped with 137 markers. Artificial neural networks and Bayesian generalized linear regression analyses were performed. The artificial neural networks were able to identify four important markers belonging to linkage groups that have been recently mapped,...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea arabica; Hemileia vastatrix; Artificial intelligence; Molecular markers; Prediction.
Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017000300186
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Assessment of EST-SSR markers for genetic analisys on coffee Bragantia
Missio,Robson Fernando; Caixeta,Eveline Teixeira; Zambolim,Eunize Maciel; Pena,Guilherme Ferreira; Ribeiro,Ana Paula; Zambolim,Laércio; Pereira,Antônio Alves; Sakiyama,Ney Sussumu.
EST-SSR markers were used to investigate the genetic diversity among and within coffee populations, to explore the possibility of their use for fingerprinting of cultivars and to assist breeding programs. Seventeen markers, developed from ESTs (Expressed Sequence Tags) from the Brazilian Coffee Genome Project, were used. All markers showed polymorphism among the genotypes assessed. The average number of allele per primer was 5.1. The highest polymorphisms were found within C. canephora (88.2%) and rust-resistant varieties (35.3%). About 29.4% of the markers differentiated C. arabica from Híbrido de Timor; it was also possible to identify those closest and farthest from C. arabica . The analysis of population-grouped genotypes revealed a 64.0% genetic...
Tipo: Info:eu-repo/semantics/article Palavras-chave: DNA markers; Coffea sp.; UPGMA; Amova; Microsatellite markers.
Ano: 2009 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052009000300003
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Genomic prediction of leaf rust resistance to Arabica coffee using machine learning algorithms Scientia Agricola
Sousa,Ithalo Coelho de; Nascimento,Moysés; Silva,Gabi Nunes; Nascimento,Ana Carolina Campana; Cruz,Cosme Damião; Silva,Fabyano Fonseca e; Almeida,Dênia Pires de; Pestana,Kátia Nogueira; Azevedo,Camila Ferreira; Zambolim,Laércio; Caixeta,Eveline Teixeira.
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, such methodologies require certain assumptions about the data, such as the normality of the distribution of phenotypic values. To circumvent the non-normality of phenotypic values, the literature suggests the use of Bayesian Generalized Linear Regression (GBLASSO). Another alternative is the models based on machine learning, represented by methodologies such as Artificial Neural Networks (ANN), Decision Trees (DT) and related possible refinements such as Bagging, Random Forest and Boosting. This study aimed to...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Hemileia vastatrix; Statistical learning; Plant breeding; Artificial intelligence.
Ano: 2021 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000401102
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Herança da resistência do Híbrido de Timor UFV 443-03 à ferrugem-do-cafeeiro PAB
Capucho,Alexandre Sandri; Caixeta,Eveline Teixeira; Zambolim,Eunize Maciel; Zambolim,Laércio.
O objetivo deste trabalho foi caracterizar a herança da resistência do Híbrido de Timor UFV 443-03 à ferrugem-do-cafeeiro (Hemileia vastatrix). Para isso, a raça II e o patótipo 001 de ferrugem foram inoculados em 246 plantas da população F2, 115 plantas do retrocruzamento suscetível (RC S) e 87 plantas do retrocruzamento resistente (RC R), originadas do cruzamento entre o genótipo suscetível cv. Catuaí Amarelo IAC 64 e a fonte de resistência Híbrido de Timor UFV 443-03. Para ambos os inóculos, a cv. Catuaí Amarelo IAC 64 foi suscetível, enquanto o Híbrido de Timor UFV 443-03, a planta representante da geração F1 e as plantas do RC R foram resistentes. As plantas F2, quando inoculadas com a raça II, apresentaram dois padrões de segregação significativos:...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea arabica; Hemileia vastatrix; Herança genética; Resistência a doenças; Resistência vertical.
Ano: 2009 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2009000300009
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In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases Genet. Mol. Biol.
Alvarenga,Samuel Mazzinghy; Caixeta,Eveline Teixeira; Hufnagel,Bárbara; Thiebaut,Flávia; Maciel-Zambolim,Eunize; Zambolimand,Laércio; Sakiyama,Ney Sussumu.
Sequences potentially associated with coffee resistance to diseases were identified by in silico analyses using the database of the Brazilian Coffee Genome Project (BCGP). Keywords corresponding to plant resistance mechanisms to pathogens identified in the literature were used as baits for data mining. Expressed sequence tags (ESTs) related to each of these keywords were identified with tools available in the BCGP bioinformatics platform. A total of 11,300 ESTs were mined. These ESTs were clustered and formed 979 EST-contigs with similarities to chitinases, kinases, cytochrome P450 and nucleotide binding site-leucine rich repeat (NBS-LRR) proteins, as well as with proteins related to disease resistance, pathogenesis, hypersensitivity response (HR) and...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea; Data mining; ESTs; Genomics; In silico; Bioinformatics.
Ano: 2010 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572010000400031
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Marcadores moleculares derivados de sequências expressas do genoma café potencialmente envolvidas na resistência à ferrugem PAB
Alvarenga,Samuel Mazzinghy; Caixeta,Eveline Teixeira; Hufnagel,Bárbara; Thiebaut,Flávia; Maciel-Zambolim,Eunize; Zambolim,Laércio; Sakiyama,Ney Sussumu.
O objetivo deste trabalho foi identificar marcadores moleculares relacionados à resistência do cafeeiro (Coffea arabica) à ferrugem (Hemileia vastatrix). Foram identificadas sequências de DNA potencialmente envolvidas na resistência do cafeeiro a doenças, por meio de análise "in silico", a partir das informações geradas pelo Projeto Brasileiro do Genoma Café. A partir das sequências mineradas, foram desenhados 59 pares de iniciadores para amplificá-las. Os 59 iniciadores foram testados em 12 cafeeiros resistentes e 12 susceptíveis a H. vastatrix. Vinte e sete iniciadores resultaram em bandas únicas e bem definidas, enquanto um deles amplificou fragmento de DNA em todos os cafeeiros resistentes, mas não nos suscetíveis. Esse marcador molecular polimórfico...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea arabica; Hemileia vastatrix; Bioinformática; EST-PCR; Genes de resistência; Mineração de dados.
Ano: 2011 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2011000800015
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Molecular characterization of arabica and Conilon coffee plants genotypes by SSR and ISSR markers BABT
Motta,Ludymila Brandão; Soares,Taís Cristina Bastos; Ferrão,Maria Amélia Gava; Caixeta,Eveline Teixeira; Lorenzoni,Rodrigo Monte; Souza Neto,José Dias de.
The molecular characterization of ten genotypes of the Coffea arabica plants and of seven genotypes of C. canephora having interesting features for coffee breeding programs was carried to select the parents for breeding. A total of 40 SSR and 29 ISSR primers were used. The primers generated a total of 331 (307 polymorphic and 24 monomorphic) bands. Analysis of genetic diversity presented dissimilarity intervals ranging from 0.22 to 0.44 between the Conilon genotypes, from 0.02 to 0.28 between the Arabica genotypes, and from 0.49 to 0.60 between the genotypes of the two species in the joint analysis. Four groups were formed: I = genotypes of C. arabica, II = four progenies of C. canephora, Conilon group, and one non defined C. canephora (Conilon or...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea Arabica; Coffea canephora; Genetic diversity; Molecular markers.
Ano: 2014 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132014000500728
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Receptor-Like Kinase (RLK) as a candidate gene conferring resistance to Hemileia vastatrix in coffee Scientia Agricola
Almeida,Dênia Pires de; Castro,Isabel Samila Lima; Mendes,Tiago Antônio de Oliveira; Alves,Danúbia Rodrigues; Barka,Geleta Dugassa; Barreiros,Pedro Ricardo Rossi Marques; Zambolim,Laércio; Sakiyama,Ney Sussumu; Caixeta,Eveline Teixeira.
ABSTRACT: The biotrophic fungus Hemileia vastatrix causes coffee leaf rust (CLR), one of the most devastating diseases in Coffea arabica . Coffee, like other plants, has developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs) have been identified in certain plants as candidates for resistance ( R ) genes or membrane receptors that activate the R genes. The RGAs identified in different plants possess conserved domains that play specific roles in the fight against pathogens. Despite the importance of RGAs, in coffee plants these genes and other molecular mechanisms of disease resistance are still unknown. This study aimed to sequence and characterize candidate genes from coffee plants...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Coffea arabica; Coffee leaf rust; Resistance gene analogs; Molecular markers; Plant breeding.
Ano: 2021 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162021000601101
Registros recuperados: 8
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