Bayesian factorial design as a tool in the identification of rice blast resistance sources.

Bayesian factorial design as a tool in the identification of rice blast resistance sources.

Rice germplasm banks have many promising sources of resistance to pathogens. However, identification of resistant genotypes is often arduous, notably when the host-pathogen relationship is complex as in rice blast. In addition, selection of representative Magnaporthe oryzae isolates to adequately identify sources of broad-spectrum resistance is challenging. To overcome these obstacles, data from pathogenicity assays were analyzed as a factorial design, where the pairwise combination comprised rice genotypes and blast isolates. Using this methodology, we aimed to access information about host resistance.

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Main Authors: MELLO, R. N., MORAIS JUNIOR, O. P., ABREU, A. G., BORBA, T. C. O.
Other Authors: RAQUEL NEVES DE MELLO, CNPAF; ODILON PEIXOTO MORAIS JUNIOR; ALUANA GONCALVES DE ABREU, CNPAF; TEREZA CRISTINA DE OLIVEIRA BORBA, CNPAF.
Format: Parte de livro biblioteca
Language:English
eng
Published: 2016-12-20
Subjects:Arroz, Oryza sativa, Brusone, Doença de planta, Resistência, Blast disease, Bayesian theory, Magnaporthe oryzae,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1058998
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spelling dig-alice-doc-10589982017-08-16T03:56:19Z Bayesian factorial design as a tool in the identification of rice blast resistance sources. MELLO, R. N. MORAIS JUNIOR, O. P. ABREU, A. G. BORBA, T. C. O. RAQUEL NEVES DE MELLO, CNPAF; ODILON PEIXOTO MORAIS JUNIOR; ALUANA GONCALVES DE ABREU, CNPAF; TEREZA CRISTINA DE OLIVEIRA BORBA, CNPAF. Arroz Oryza sativa Brusone Doença de planta Resistência Blast disease Bayesian theory Magnaporthe oryzae Rice germplasm banks have many promising sources of resistance to pathogens. However, identification of resistant genotypes is often arduous, notably when the host-pathogen relationship is complex as in rice blast. In addition, selection of representative Magnaporthe oryzae isolates to adequately identify sources of broad-spectrum resistance is challenging. To overcome these obstacles, data from pathogenicity assays were analyzed as a factorial design, where the pairwise combination comprised rice genotypes and blast isolates. Using this methodology, we aimed to access information about host resistance. 2016-12-20T11:11:11Z 2016-12-20T11:11:11Z 2016-12-20 2016 2017-03-06T11:11:11Z Parte de livro In: INTERNATIONAL RICE BLAST CONFERENCE, 7., 2016, Manila. New insights into the rice-Maganaporthe Oryzae interactions for better management of rice blast: program and abstract. Manila: IRRI, 2016. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1058998 en eng openAccess p. 112.
institution EMBRAPA
collection DSpace
country Brasil
countrycode BR
component Bibliográfico
access En linea
databasecode dig-alice
tag biblioteca
region America del Sur
libraryname Sistema de bibliotecas de EMBRAPA
language English
eng
topic Arroz
Oryza sativa
Brusone
Doença de planta
Resistência
Blast disease
Bayesian theory
Magnaporthe oryzae
Arroz
Oryza sativa
Brusone
Doença de planta
Resistência
Blast disease
Bayesian theory
Magnaporthe oryzae
spellingShingle Arroz
Oryza sativa
Brusone
Doença de planta
Resistência
Blast disease
Bayesian theory
Magnaporthe oryzae
Arroz
Oryza sativa
Brusone
Doença de planta
Resistência
Blast disease
Bayesian theory
Magnaporthe oryzae
MELLO, R. N.
MORAIS JUNIOR, O. P.
ABREU, A. G.
BORBA, T. C. O.
Bayesian factorial design as a tool in the identification of rice blast resistance sources.
description Rice germplasm banks have many promising sources of resistance to pathogens. However, identification of resistant genotypes is often arduous, notably when the host-pathogen relationship is complex as in rice blast. In addition, selection of representative Magnaporthe oryzae isolates to adequately identify sources of broad-spectrum resistance is challenging. To overcome these obstacles, data from pathogenicity assays were analyzed as a factorial design, where the pairwise combination comprised rice genotypes and blast isolates. Using this methodology, we aimed to access information about host resistance.
author2 RAQUEL NEVES DE MELLO, CNPAF; ODILON PEIXOTO MORAIS JUNIOR; ALUANA GONCALVES DE ABREU, CNPAF; TEREZA CRISTINA DE OLIVEIRA BORBA, CNPAF.
author_facet RAQUEL NEVES DE MELLO, CNPAF; ODILON PEIXOTO MORAIS JUNIOR; ALUANA GONCALVES DE ABREU, CNPAF; TEREZA CRISTINA DE OLIVEIRA BORBA, CNPAF.
MELLO, R. N.
MORAIS JUNIOR, O. P.
ABREU, A. G.
BORBA, T. C. O.
format Parte de livro
topic_facet Arroz
Oryza sativa
Brusone
Doença de planta
Resistência
Blast disease
Bayesian theory
Magnaporthe oryzae
author MELLO, R. N.
MORAIS JUNIOR, O. P.
ABREU, A. G.
BORBA, T. C. O.
author_sort MELLO, R. N.
title Bayesian factorial design as a tool in the identification of rice blast resistance sources.
title_short Bayesian factorial design as a tool in the identification of rice blast resistance sources.
title_full Bayesian factorial design as a tool in the identification of rice blast resistance sources.
title_fullStr Bayesian factorial design as a tool in the identification of rice blast resistance sources.
title_full_unstemmed Bayesian factorial design as a tool in the identification of rice blast resistance sources.
title_sort bayesian factorial design as a tool in the identification of rice blast resistance sources.
publishDate 2016-12-20
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1058998
work_keys_str_mv AT mellorn bayesianfactorialdesignasatoolintheidentificationofriceblastresistancesources
AT moraisjuniorop bayesianfactorialdesignasatoolintheidentificationofriceblastresistancesources
AT abreuag bayesianfactorialdesignasatoolintheidentificationofriceblastresistancesources
AT borbatco bayesianfactorialdesignasatoolintheidentificationofriceblastresistancesources
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