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Registro Completo |
Biblioteca(s): |
Embrapa Arroz e Feijão. |
Data corrente: |
19/03/2024 |
Data da última atualização: |
19/03/2024 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
ARAÚJO, M. S.; CHAVES, S. F. S.; DIAS, L. A. S.; FERREIRA, F. M.; PEREIRA, G. R.; BEZERRA, A. R. G.; ALVES, R. S.; HEINEMANN, A. B.; BRESEGHELLO, F.; CARNEIRO, P. C. S.; KRAUSE, M. D.; COSTA-NETO, G.; DIAS, K. O. G. |
Afiliação: |
MAURICIO S. ARAUJO, UFV; SAULO F. S. CHAVES, UFV; LUIZ A. S. DIAS, UFV; FILIPE M. FERREIRA, UNESP, Botucatu-SP; GUILHERME R. PEREIRA, UFV; ANDRE R. G. BEZERRA, LIMAGRAIN BRAZIL, Jataí-GO; RODRIGO S. ALVES, UFV; ALEXANDRE BRYAN HEINEMANN, CNPAF; FLAVIO BRESEGHELLO, CNPAF; PEDRO C. S. CARNEIRO, UFV; MATHEUS D. KRAUSE, IOWA STATE UNIVERSITY; GERMANO COSTA-NETO, CORNELL UNIVERSITY; KAIO O. G. DIAS, UFV. |
Título: |
GIS-FA: an approach to integrating thematic maps, factor-analytic, and envirotyping for cultivar targeting. |
Ano de publicação: |
2024 |
Fonte/Imprenta: |
Theoretical and Applied Genetics, v. 137, 80, Mar. 2024. |
ISSN: |
0040-5752 |
DOI: |
https://doi.org/10.1007/s00122-024-04579-z |
Idioma: |
Inglês |
Conteúdo: |
Parsimonious methods that capture genotype-by-environment interaction (GEI) in multi-environment trials (MET) are important in breeding programs. Understanding the causes and factors of GEI allows the utilization of genotype adaptations in the target population of environments through environmental features and factor-analytic (FA) models. Here, we present a novel predictive breeding approach called GIS-FA, which integrates geographic information systems (GIS) techniques, FA models, partial least squares (PLS) regression, and enviromics to predict phenotypic performance in untested environments. The GIS-FA approach enables: (i) the prediction of the phenotypic performance of tested genotypes in untested environments, (ii) the selection of the best-ranking genotypes based on their overall performance and stability using the FA selection tools, and (iii) the creation of thematic maps showing overall or pairwise performance and stability for decision-making. We exemplify the usage of the GIS-FA approach using two datasets of rice [Oryza sativa (L.)] and soybean [Glycine max (L.) Merr.] in MET spread over tropical areas. In summary, our novel predictive method allows the identification of new breeding scenarios by pinpointing groups of environments where genotypes demonstrate superior predicted performance. It also facilitates and optimizes cultivar recommendations by utilizing thematic maps. |
Thesagro: |
Sistema de Informação Geográfica. |
Thesaurus Nal: |
Cultivars; Environmental indicators. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 02413naa a2200325 a 4500 001 2162951 005 2024-03-19 008 2024 bl uuuu u00u1 u #d 022 $a0040-5752 024 7 $ahttps://doi.org/10.1007/s00122-024-04579-z$2DOI 100 1 $aARAÚJO, M. S. 245 $aGIS-FA$ban approach to integrating thematic maps, factor-analytic, and envirotyping for cultivar targeting.$h[electronic resource] 260 $c2024 520 $aParsimonious methods that capture genotype-by-environment interaction (GEI) in multi-environment trials (MET) are important in breeding programs. Understanding the causes and factors of GEI allows the utilization of genotype adaptations in the target population of environments through environmental features and factor-analytic (FA) models. Here, we present a novel predictive breeding approach called GIS-FA, which integrates geographic information systems (GIS) techniques, FA models, partial least squares (PLS) regression, and enviromics to predict phenotypic performance in untested environments. The GIS-FA approach enables: (i) the prediction of the phenotypic performance of tested genotypes in untested environments, (ii) the selection of the best-ranking genotypes based on their overall performance and stability using the FA selection tools, and (iii) the creation of thematic maps showing overall or pairwise performance and stability for decision-making. We exemplify the usage of the GIS-FA approach using two datasets of rice [Oryza sativa (L.)] and soybean [Glycine max (L.) Merr.] in MET spread over tropical areas. In summary, our novel predictive method allows the identification of new breeding scenarios by pinpointing groups of environments where genotypes demonstrate superior predicted performance. It also facilitates and optimizes cultivar recommendations by utilizing thematic maps. 650 $aCultivars 650 $aEnvironmental indicators 650 $aSistema de Informação Geográfica 700 1 $aCHAVES, S. F. S. 700 1 $aDIAS, L. A. S. 700 1 $aFERREIRA, F. M. 700 1 $aPEREIRA, G. R. 700 1 $aBEZERRA, A. R. G. 700 1 $aALVES, R. S. 700 1 $aHEINEMANN, A. B. 700 1 $aBRESEGHELLO, F. 700 1 $aCARNEIRO, P. C. S. 700 1 $aKRAUSE, M. D. 700 1 $aCOSTA-NETO, G. 700 1 $aDIAS, K. O. G. 773 $tTheoretical and Applied Genetics$gv. 137, 80, Mar. 2024.
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Embrapa Arroz e Feijão (CNPAF) |
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Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia. |
Data corrente: |
22/10/2015 |
Data da última atualização: |
17/03/2023 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
MÜLLER, B. S. F.; NEVES, L. G.; RESENDE JÚNIOR, M. F. R.; MUÑOZ, P. R.; KIRST, M.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; GRATTAPAGLIA, D. |
Afiliação: |
Bárbara S. F. Müller, UnB; Leandro G. Neves, RAPiD Genomics LLC; Márcio F. R. Resende Júnior, RAPiD Genomics LLC; Patricio R. Muñoz, University of Florida; Matias Kirst, University of Florida; PAULO EDUARDO TELLES DOS SANTOS, CNPF; ESTEFANO PALUDZYSZYN FILHO, CNPF; DARIO GRATTAPAGLIA, CENARGEN. |
Título: |
Genomic selection for growth traits in Eucalyptus benthamii and E. pellita populations using a genome-wide Eucalyptus 60K SNPs chip. |
Ano de publicação: |
2015 |
Fonte/Imprenta: |
In: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2015, Florence. Forests: the importance to the planet and society. [S.l.]: IBBR: ICCOM, 2015. |
Idioma: |
Inglês |
Palavras-Chave: |
Espécie exótica; Espécie florestal; Melhoramento genético; Seleção genômica. |
Thesaurus NAL: |
Eucalyptus. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/128039/1/2015-PauloE-IUFRO-GenomicSelection.pdf
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Marc: |
LEADER 00884nam a2200241 a 4500 001 2027043 005 2023-03-17 008 2015 bl uuuu u01u1 u #d 100 1 $aMÜLLER, B. S. F. 245 $aGenomic selection for growth traits in Eucalyptus benthamii and E. pellita populations using a genome-wide Eucalyptus 60K SNPs chip.$h[electronic resource] 260 $aIn: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2015, Florence. Forests: the importance to the planet and society. [S.l.]: IBBR: ICCOM$c2015 650 $aEucalyptus 653 $aEspécie exótica 653 $aEspécie florestal 653 $aMelhoramento genético 653 $aSeleção genômica 700 1 $aNEVES, L. G. 700 1 $aRESENDE JÚNIOR, M. F. R. 700 1 $aMUÑOZ, P. R. 700 1 $aKIRST, M. 700 1 $aSANTOS, P. E. T. dos 700 1 $aPALUDZYSZYN FILHO, E. 700 1 $aGRATTAPAGLIA, D.
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