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 | Acesso ao texto completo restrito à biblioteca da Embrapa Trigo. Para informações adicionais entre em contato com cnpt.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Trigo. |
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Data corrente: |
04/03/2022 |
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Data da última atualização: |
04/03/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
VICENTINI, S. N. C.; CASADO, P. S.; CARVALHO, G. de; MOREIRA, S. I.; DORIGAN, A. F.; SILVA, T. C.; SILVA, A. G. da; CUSTÓDIO, A. A. de P.; GOMES, A. C. dos S.; MACIEL, J. L. N.; HAWKINS, N.; MCDONALD, B. A.; FRAAIJE, B. A.; CERESINI, P. C. |
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Afiliação: |
SAMARA N. C. VICENTINI, UNESP; PRISCILA S. CASADO, UNESP; GISELLE DE CARVALHO, UNESP; SILVINO I. MOREIRA, UNESP; ADRIANO F. DORIGAN, UFLA; TATIANE CARLA SILVA, UNESP; ABIMAEL GOMES DA SILVA, UNESP; ADRIANO AUGUSTO DE PAIVA CUSTÓDIO, IAPAR; ANA CAROLINA DOS SANTOS GOMES, UNESP; JOAO LEODATO NUNES MACIEL, CNPT; NICHOLA HAWKINS, National Institute of Agricultural Botany; BRUCE A. MCDONALD, Plant Pathology Group; BART A. FRAAIJE, National Institute of Agricultural Botany; PAULO C. CERESINI, UNESP. |
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Título: |
Monitoring of Brazilian wheat blast field populations reveals resistance to QoI, DMI, and SDHI fungicides. |
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Edição: |
, |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Plant Pathology, v. 71, n. 2, p. 304-321, 2021. |
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DOI: |
https://doi.org/10.1111/ppa.13470 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Wheat blast is one of the most important and devastating fungal diseases of wheat in South America, South-east Asia, and now in southern Africa. The disease can reduce grain yield by up to 70% and is best controlled using integrated disease management strategies. The difficulty in disease management is compounded by the lack of durable host resistance and the ineffectiveness of fungicide sprays. New succinate dehydrogenase inhibitor (SDHI) fungicides were recently introduced for the management of wheat diseases. Brazilian field populations of the wheat blast pathogen Pyricularia oryzae Triticum lineage (PoTI) sampled from different georgraphical regions in 2012and 2018 were shown to be resistant to both QoI (strobilurin) and DMI (azole) fungicides. The main objective of the current study was to determine the SDHI baseline sensitivity in these populations. Moderate levels of SDHI resistance were detected in five out of the six field populations sampled in 2012 and in most of the strains isolated in 2018. No association was found between target site mutations in the sdhB, sdhC, and sdhD genes and the levels of SDHI resistance, indicating that a pre-existing resistance mechanism not associated with target site mutations is probably present in Brazilian wheat blast populations. |
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Palavras-Chave: |
Carboxiami; Fluxapiroxade; Fluxapyroxad; Linhagem Pyricularia oryzae Triticum; Non target site resistance; Pyricularia oryzae Triticum; Resistência a fungicidas; Resistência do local não-alvo; Second-generation carboxamides; Succinate dehydrogenase inhibitors. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02613naa a2200421 a 4500
001 2140558
005 2022-03-04
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1111/ppa.13470$2DOI
100 1 $aVICENTINI, S. N. C.
245 $aMonitoring of Brazilian wheat blast field populations reveals resistance to QoI, DMI, and SDHI fungicides.$h[electronic resource]
250 $a,
260 $c2021
520 $aAbstract: Wheat blast is one of the most important and devastating fungal diseases of wheat in South America, South-east Asia, and now in southern Africa. The disease can reduce grain yield by up to 70% and is best controlled using integrated disease management strategies. The difficulty in disease management is compounded by the lack of durable host resistance and the ineffectiveness of fungicide sprays. New succinate dehydrogenase inhibitor (SDHI) fungicides were recently introduced for the management of wheat diseases. Brazilian field populations of the wheat blast pathogen Pyricularia oryzae Triticum lineage (PoTI) sampled from different georgraphical regions in 2012and 2018 were shown to be resistant to both QoI (strobilurin) and DMI (azole) fungicides. The main objective of the current study was to determine the SDHI baseline sensitivity in these populations. Moderate levels of SDHI resistance were detected in five out of the six field populations sampled in 2012 and in most of the strains isolated in 2018. No association was found between target site mutations in the sdhB, sdhC, and sdhD genes and the levels of SDHI resistance, indicating that a pre-existing resistance mechanism not associated with target site mutations is probably present in Brazilian wheat blast populations.
653 $aCarboxiami
653 $aFluxapiroxade
653 $aFluxapyroxad
653 $aLinhagem Pyricularia oryzae Triticum
653 $aNon target site resistance
653 $aPyricularia oryzae Triticum
653 $aResistência a fungicidas
653 $aResistência do local não-alvo
653 $aSecond-generation carboxamides
653 $aSuccinate dehydrogenase inhibitors
700 1 $aCASADO, P. S.
700 1 $aCARVALHO, G. de
700 1 $aMOREIRA, S. I.
700 1 $aDORIGAN, A. F.
700 1 $aSILVA, T. C.
700 1 $aSILVA, A. G. da
700 1 $aCUSTÓDIO, A. A. de P.
700 1 $aGOMES, A. C. dos S.
700 1 $aMACIEL, J. L. N.
700 1 $aHAWKINS, N.
700 1 $aMCDONALD, B. A.
700 1 $aFRAAIJE, B. A.
700 1 $aCERESINI, P. C.
773 $tPlant Pathology$gv. 71, n. 2, p. 304-321, 2021.
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Registro original: |
Embrapa Trigo (CNPT) |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
14/07/2020 |
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Data da última atualização: |
14/07/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
CARVALHO, H. F.; GALLI, G.; FERRÃO, L. F. V.; NONATO, J. V. A.; PADILHA, L.; MALUF, M. P.; RESENDE JR, M. F. R. de; GUERREIRO FILHO, O.; FRITSCHE-NETO, R. |
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Afiliação: |
HUMBERTO FANELLI CARVALHO, INSTITUTO AGRONÔMICO DE CAMPINAS - IAC; GIOVANNI GALLI, UNIVERSIDADE DE SÃO PAULO; LUÍS FELIPE VENTORIM FERRÃO, UNIVERSITY OF FLORIDA; JULIANA VIEIRA ALMEIDA NONATO, INSTITUTO AGRONÔMICO DE CAMPINAS - IAC; LILIAN PADILHA, CNPCa; MIRIAN PEREZ MALUF, CNPCa; MÁRCIO FERNANDO RIBEIRO DE RESENDE JR, UNIVERSITY OF FLORIDA; OLIVEIRO GUERREIRO FILHO, INSTITUTO AGRONÔMICO DE CAMPINAS - IAC; ROBERTO FRITSCHE-NETO, UNIVERSIDADE DE SÃO PAULO. |
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Título: |
The effect of bienniality on genomic prediction of yield in arabica coffee. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Euphytica, v. 216, n. 101, p. 100-111, 2020. |
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DOI: |
https://doi.org/10.1007/s10681-020-02641-7 |
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Idioma: |
Inglês |
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Conteúdo: |
The most popular beverage worldwide, coffee, is responsible for a billionaire market chain with arabica coffee leading the production. Coffee breeding programs are focusing on high yield, excellent beverage quality, and disease resistance, but the bienniality comes to a challenge to overcome bean production. The bienniality, the seasonal variation between high and low yielding, is a genetically controlled physiological event that affects yield stability in arabica coffee. However, there are no studies on the best strategies to implement genomic selection in coffee, including how to establish training populations and deal with the biennially. Thus, the objective was evaluated the potential of genomic selection applied to arabica coffee, with particular consideration on how to estimate bienniality effect on genomic prediction accuracy for yield. The population (n = 586) high-density genotyped by GBS was measured in the low (2005 and 2007), and high (2006 and 2008) yield years. The genomic prediction models were established considering genotype and genotype × year effects. Different prediction scenarios were proposed, considering single-year training sets and grouping the data according to bienniality. Overall, training genomic models on biennium of successive years, and predicting the following biennium appears to be the most effective strategy between all tested scenarios. The comparison of phenotypic and prediction approaches revealed an increased selection response using genomic selection, mainly due to the reduced time per breeding cycle. These results can shed light on the implementation of a genome-based selection of arabica coffee and lead to more efficient breeding strategies. MenosThe most popular beverage worldwide, coffee, is responsible for a billionaire market chain with arabica coffee leading the production. Coffee breeding programs are focusing on high yield, excellent beverage quality, and disease resistance, but the bienniality comes to a challenge to overcome bean production. The bienniality, the seasonal variation between high and low yielding, is a genetically controlled physiological event that affects yield stability in arabica coffee. However, there are no studies on the best strategies to implement genomic selection in coffee, including how to establish training populations and deal with the biennially. Thus, the objective was evaluated the potential of genomic selection applied to arabica coffee, with particular consideration on how to estimate bienniality effect on genomic prediction accuracy for yield. The population (n = 586) high-density genotyped by GBS was measured in the low (2005 and 2007), and high (2006 and 2008) yield years. The genomic prediction models were established considering genotype and genotype × year effects. Different prediction scenarios were proposed, considering single-year training sets and grouping the data according to bienniality. Overall, training genomic models on biennium of successive years, and predicting the following biennium appears to be the most effective strategy between all tested scenarios. The comparison of phenotypic and prediction approaches revealed an increased sel... Mostrar Tudo |
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Palavras-Chave: |
Sequenciamento genético. |
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Thesagro: |
Coffea Arábica; Genoma; Seleção Genética. |
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Thesaurus NAL: |
Genome; Plant selection guides. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02622naa a2200301 a 4500
001 2123829
005 2020-07-14
008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s10681-020-02641-7$2DOI
100 1 $aCARVALHO, H. F.
245 $aThe effect of bienniality on genomic prediction of yield in arabica coffee.$h[electronic resource]
260 $c2020
520 $aThe most popular beverage worldwide, coffee, is responsible for a billionaire market chain with arabica coffee leading the production. Coffee breeding programs are focusing on high yield, excellent beverage quality, and disease resistance, but the bienniality comes to a challenge to overcome bean production. The bienniality, the seasonal variation between high and low yielding, is a genetically controlled physiological event that affects yield stability in arabica coffee. However, there are no studies on the best strategies to implement genomic selection in coffee, including how to establish training populations and deal with the biennially. Thus, the objective was evaluated the potential of genomic selection applied to arabica coffee, with particular consideration on how to estimate bienniality effect on genomic prediction accuracy for yield. The population (n = 586) high-density genotyped by GBS was measured in the low (2005 and 2007), and high (2006 and 2008) yield years. The genomic prediction models were established considering genotype and genotype × year effects. Different prediction scenarios were proposed, considering single-year training sets and grouping the data according to bienniality. Overall, training genomic models on biennium of successive years, and predicting the following biennium appears to be the most effective strategy between all tested scenarios. The comparison of phenotypic and prediction approaches revealed an increased selection response using genomic selection, mainly due to the reduced time per breeding cycle. These results can shed light on the implementation of a genome-based selection of arabica coffee and lead to more efficient breeding strategies.
650 $aGenome
650 $aPlant selection guides
650 $aCoffea Arábica
650 $aGenoma
650 $aSeleção Genética
653 $aSequenciamento genético
700 1 $aGALLI, G.
700 1 $aFERRÃO, L. F. V.
700 1 $aNONATO, J. V. A.
700 1 $aPADILHA, L.
700 1 $aMALUF, M. P.
700 1 $aRESENDE JR, M. F. R. de
700 1 $aGUERREIRO FILHO, O.
700 1 $aFRITSCHE-NETO, R.
773 $tEuphytica$gv. 216, n. 101, p. 100-111, 2020.
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