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Registro Completo |
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Biblioteca(s): |
Embrapa Amazônia Ocidental. |
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Data corrente: |
04/12/1997 |
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Data da última atualização: |
04/12/1997 |
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Autoria: |
CATTO, J. B.; SERENO, J. R.; COMASTRI FILHO, J. A. (org.). |
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Título: |
Tecnologia e informações para a pecuária de corte no Pantanal. |
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Ano de publicação: |
1997 |
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Fonte/Imprenta: |
Corumbá: EMBRAPA-CPAP, 1997. |
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Páginas: |
161 p. |
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Idioma: |
Português |
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Conteúdo: |
Pastagens nativas. Pastagens cultivadas. Nutricao mineral de bovinos. Manejo reprodutivo: desmama e estacao de monta. Manejo e melhoramento genetico. Doencas da reproducao. Profilaxia e controle dos principais ectoparasitos de bovinos: mosca-dos-chifres e mosca-varejeira. Verminoses de bovinos. Anemia infecciosa equina. Manejo da fauna e da flora silvestre como alternativa de producao agropecuaria e mecanismo de conservacao do pantanal. |
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Palavras-Chave: |
Bovino de corte; Brasil; Diseases; Helmintoses; Management; Melhoramento genetico; Mosca pantaneira; Pasture. |
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Thesagro: |
Anemia; Desmama; Doença; Manejo; Mineralização; Nutrição; Parasito; Pastagem; Reprodução; Verminose. |
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Thesaurus Nal: |
beef cattle; breeding; mineralization; nutrition; Pantanal; parasites; reproduction; swamps. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01527nam a2200457 a 4500
001 1664759
005 1997-12-04
008 1997 bl uuuu 00u1 u #d
100 1 $aCATTO, J. B.
245 $aTecnologia e informações para a pecuária de corte no Pantanal.
260 $aCorumbá: EMBRAPA-CPAP$c1997
300 $a161 p.
520 $aPastagens nativas. Pastagens cultivadas. Nutricao mineral de bovinos. Manejo reprodutivo: desmama e estacao de monta. Manejo e melhoramento genetico. Doencas da reproducao. Profilaxia e controle dos principais ectoparasitos de bovinos: mosca-dos-chifres e mosca-varejeira. Verminoses de bovinos. Anemia infecciosa equina. Manejo da fauna e da flora silvestre como alternativa de producao agropecuaria e mecanismo de conservacao do pantanal.
650 $abeef cattle
650 $abreeding
650 $amineralization
650 $anutrition
650 $aPantanal
650 $aparasites
650 $areproduction
650 $aswamps
650 $aAnemia
650 $aDesmama
650 $aDoença
650 $aManejo
650 $aMineralização
650 $aNutrição
650 $aParasito
650 $aPastagem
650 $aReprodução
650 $aVerminose
653 $aBovino de corte
653 $aBrasil
653 $aDiseases
653 $aHelmintoses
653 $aManagement
653 $aMelhoramento genetico
653 $aMosca pantaneira
653 $aPasture
700 1 $aSERENO, J. R.
700 1 $aCOMASTRI FILHO, J. A.
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Registro original: |
Embrapa Amazônia Ocidental (CPAA) |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
07/12/2017 |
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Data da última atualização: |
07/12/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
FERRÃO, L. F. V.; FERRÃO, R. G.; FERRAO, M. A. G.; FONSECA, A. F. A. da; GARCIA, A. A. F. |
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Afiliação: |
LUIS FELIPE VENTORIM FERRÃO, DG/ESALQ; ROMÁRIO GAVA FERRÃO, INCAPER; MARIA AMELIA GAVA FERRAO, SAPC; AYMBIRE FRANCISCO A DA FONSECA, SAPC; ANTONIO AUGUSTO FRANCO GARCIA, DG/ESALQ. |
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Título: |
A mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Tree Genetics & Genomes, v. 13, n. 95, 2017. |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic selection (GS) has been studied in several crops to increase the rates of genetic gain and reduce the length of breeding cycles. Despite its relevance, there are only a modest number of reports applied to the genus Coffea. Effective implementation depends on the ability to consider genomic models, which correctly represent breeding scenario in which the species are inserted. Coffee experimentation, in general, is represented by evaluations in multiple locations and harvests to understand the interaction and predict the performance of untested genotypes. Therefore, the main objective of this study was to investigate GS models suitable for use in Coffea canephora. An expansion of traditional GBLUP was considered and genomic analysis was performed using a genotyping-by-sequencing (GBS) approach, showed good potential to be used in coffee breeding programs. Interactions were modeled using the multiplicative mixed model theory, which is commonly used in multi-environment trials (MET) analysis in perennial crops. The effectiveness of the method used was compared with other genetic models in terms of goodness-of-fit statistics and prediction accuracy. Different scenarios that mimic coffee breeding were used in the cross-validation process. The method used had the lowest AIC and BIC values and, consequently, the best fit. In terms of predictive ability, the incorporation of the MET modeling showed higher accuracy (on average 10–17% higher) and lower prediction errors than traditional GBLUP. The results may be used as basis for additional studies into the genus Coffea and can be expanded for similar perennial crops. MenosGenomic selection (GS) has been studied in several crops to increase the rates of genetic gain and reduce the length of breeding cycles. Despite its relevance, there are only a modest number of reports applied to the genus Coffea. Effective implementation depends on the ability to consider genomic models, which correctly represent breeding scenario in which the species are inserted. Coffee experimentation, in general, is represented by evaluations in multiple locations and harvests to understand the interaction and predict the performance of untested genotypes. Therefore, the main objective of this study was to investigate GS models suitable for use in Coffea canephora. An expansion of traditional GBLUP was considered and genomic analysis was performed using a genotyping-by-sequencing (GBS) approach, showed good potential to be used in coffee breeding programs. Interactions were modeled using the multiplicative mixed model theory, which is commonly used in multi-environment trials (MET) analysis in perennial crops. The effectiveness of the method used was compared with other genetic models in terms of goodness-of-fit statistics and prediction accuracy. Different scenarios that mimic coffee breeding were used in the cross-validation process. The method used had the lowest AIC and BIC values and, consequently, the best fit. In terms of predictive ability, the incorporation of the MET modeling showed higher accuracy (on average 10–17% higher) and lower prediction errors than tr... Mostrar Tudo |
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Palavras-Chave: |
GBLUP; Genotyping-by-sequencing; Multi-environment trials; Perennial crops. |
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Thesaurus NAL: |
Marker-assisted selection. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/168435/1/A-mixed-model-to-multiple-harvest-location.pdf
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Marc: |
LEADER 02351naa a2200229 a 4500
001 2081803
005 2017-12-07
008 2017 bl uuuu u00u1 u #d
100 1 $aFERRÃO, L. F. V.
245 $aA mixed model to multiple harvest-location trials applied to genomic prediction in Coffea canephora.$h[electronic resource]
260 $c2017
520 $aGenomic selection (GS) has been studied in several crops to increase the rates of genetic gain and reduce the length of breeding cycles. Despite its relevance, there are only a modest number of reports applied to the genus Coffea. Effective implementation depends on the ability to consider genomic models, which correctly represent breeding scenario in which the species are inserted. Coffee experimentation, in general, is represented by evaluations in multiple locations and harvests to understand the interaction and predict the performance of untested genotypes. Therefore, the main objective of this study was to investigate GS models suitable for use in Coffea canephora. An expansion of traditional GBLUP was considered and genomic analysis was performed using a genotyping-by-sequencing (GBS) approach, showed good potential to be used in coffee breeding programs. Interactions were modeled using the multiplicative mixed model theory, which is commonly used in multi-environment trials (MET) analysis in perennial crops. The effectiveness of the method used was compared with other genetic models in terms of goodness-of-fit statistics and prediction accuracy. Different scenarios that mimic coffee breeding were used in the cross-validation process. The method used had the lowest AIC and BIC values and, consequently, the best fit. In terms of predictive ability, the incorporation of the MET modeling showed higher accuracy (on average 10–17% higher) and lower prediction errors than traditional GBLUP. The results may be used as basis for additional studies into the genus Coffea and can be expanded for similar perennial crops.
650 $aMarker-assisted selection
653 $aGBLUP
653 $aGenotyping-by-sequencing
653 $aMulti-environment trials
653 $aPerennial crops
700 1 $aFERRÃO, R. G.
700 1 $aFERRAO, M. A. G.
700 1 $aFONSECA, A. F. A. da
700 1 $aGARCIA, A. A. F.
773 $tTree Genetics & Genomes$gv. 13, n. 95, 2017.
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Registro original: |
Embrapa Café (CNPCa) |
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