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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
07/02/2020 |
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Data da última atualização: |
20/04/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
COSTA-NETO, G. M. F.; MORAIS JUNIOR, O. P.; HEINEMANN, A. B.; CASTRO, A. P. de; DUARTE, J. B. |
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Afiliação: |
GERMANO MARTINS FERREIRA COSTA-NETO, ESALQ; ODILON P. MORAIS JUNIOR, UFG; ALEXANDRE BRYAN HEINEMANN, CNPAF; ADRIANO PEREIRA DE CASTRO, CNPAF; JOÃO BATISTA DUARTE, UFG. |
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Título: |
A novel GIS-based tool to reveal spatial trends in reaction norm: upland rice case study. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Euphytica, v. 216, n. 37, p. 1-16, 2020. |
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DOI: |
10.1007/s10681-020-2573-4 |
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Idioma: |
Inglês |
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Conteúdo: |
The upland rice crop system located within Brazilian savannas and Amazon Rainforest is the largest rainfed rice growing area in Latin America. To develop and release higher yield and adapted cultivars for this large region, the upland rice breeders need to conduct multiple-location trials aiming to model the genotype 9 location (G x L) and evaluate the germplasm yield adaptability. Here we hypothesize that regional patterns of G x L across this extensive region can be modeled by integrating factorial regression models with a geographic information system (GIS). Two sets of advanced yield trials from different germplasm pool were used in this study. From GIS tools, we collect and process geographic covariates and produce thematic maps of yield adaptability. One advantage of the methodology is that adaptability can be dissected into genotypicsensibility coefficients related to the reaction norm for the geographic gradient. Then, breeders can discriminate different types of adaptability over a region, such as responsiveness for elevation, longitudinal or latitudinal adaptation, identifying possible ideotypes to solve current adaptation gaps for target regions. We observed that about of 53-59% of the G x L effects are due to predictable geographic-related factors. However, the upland rice germplasm is better adapted to higher elevations (> 700 m), which may indicate limitations in cultivar development because these regions do not represent the current upland rice growing region. We suggest to exploit geographicrelated factors by increasing breeding efforts for northern and western Brazil environments located at lower elevations (< 300 m) and Equador's near latitudes (2º S-2º N). MenosThe upland rice crop system located within Brazilian savannas and Amazon Rainforest is the largest rainfed rice growing area in Latin America. To develop and release higher yield and adapted cultivars for this large region, the upland rice breeders need to conduct multiple-location trials aiming to model the genotype 9 location (G x L) and evaluate the germplasm yield adaptability. Here we hypothesize that regional patterns of G x L across this extensive region can be modeled by integrating factorial regression models with a geographic information system (GIS). Two sets of advanced yield trials from different germplasm pool were used in this study. From GIS tools, we collect and process geographic covariates and produce thematic maps of yield adaptability. One advantage of the methodology is that adaptability can be dissected into genotypicsensibility coefficients related to the reaction norm for the geographic gradient. Then, breeders can discriminate different types of adaptability over a region, such as responsiveness for elevation, longitudinal or latitudinal adaptation, identifying possible ideotypes to solve current adaptation gaps for target regions. We observed that about of 53-59% of the G x L effects are due to predictable geographic-related factors. However, the upland rice germplasm is better adapted to higher elevations (> 700 m), which may indicate limitations in cultivar development because these regions do not represent the current upland rice growing region.... Mostrar Tudo |
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Palavras-Chave: |
Breeding for adaptation; Cultivar targeting; Envirotyping; Multi-environmental trials. |
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Thesagro: |
Arroz; Oryza Sativa. |
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Thesaurus Nal: |
Rice. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02491naa a2200265 a 4500
001 2120030
005 2020-04-20
008 2020 bl uuuu u00u1 u #d
024 7 $a10.1007/s10681-020-2573-4$2DOI
100 1 $aCOSTA-NETO, G. M. F.
245 $aA novel GIS-based tool to reveal spatial trends in reaction norm$bupland rice case study.$h[electronic resource]
260 $c2020
520 $aThe upland rice crop system located within Brazilian savannas and Amazon Rainforest is the largest rainfed rice growing area in Latin America. To develop and release higher yield and adapted cultivars for this large region, the upland rice breeders need to conduct multiple-location trials aiming to model the genotype 9 location (G x L) and evaluate the germplasm yield adaptability. Here we hypothesize that regional patterns of G x L across this extensive region can be modeled by integrating factorial regression models with a geographic information system (GIS). Two sets of advanced yield trials from different germplasm pool were used in this study. From GIS tools, we collect and process geographic covariates and produce thematic maps of yield adaptability. One advantage of the methodology is that adaptability can be dissected into genotypicsensibility coefficients related to the reaction norm for the geographic gradient. Then, breeders can discriminate different types of adaptability over a region, such as responsiveness for elevation, longitudinal or latitudinal adaptation, identifying possible ideotypes to solve current adaptation gaps for target regions. We observed that about of 53-59% of the G x L effects are due to predictable geographic-related factors. However, the upland rice germplasm is better adapted to higher elevations (> 700 m), which may indicate limitations in cultivar development because these regions do not represent the current upland rice growing region. We suggest to exploit geographicrelated factors by increasing breeding efforts for northern and western Brazil environments located at lower elevations (< 300 m) and Equador's near latitudes (2º S-2º N).
650 $aRice
650 $aArroz
650 $aOryza Sativa
653 $aBreeding for adaptation
653 $aCultivar targeting
653 $aEnvirotyping
653 $aMulti-environmental trials
700 1 $aMORAIS JUNIOR, O. P.
700 1 $aHEINEMANN, A. B.
700 1 $aCASTRO, A. P. de
700 1 $aDUARTE, J. B.
773 $tEuphytica$gv. 216, n. 37, p. 1-16, 2020.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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| Registros recuperados : 16 | |
| 3. |  | COSTA NETO, G. M. F.; CASTRO, A. P. de; HEINEMANN, A. B.; DUARTE, J. B. Adaptação genotípica regionalizada por regressão fatorial e covariáveis geográficas. In: SIMPÓSIO INTERNACIONAL DE GENÉTICA E MELHORAMENTO, 7., 2016, Viçosa, MG. Desafios biométricos no melhoramento genético: anais. Viçosa, MG: UFV, 2016. p. 27.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 7. | | ANTOLIN, L. A. S.; COSTA NETO, G. M. F.; BORGES, M. G.; HEINEMANN, A. B. Irrigation efficiency simulation for common bean during dry season, in the municipality of Goiânia, Goiás. In: INOVAGRI INTERNATIONAL MEETING, 3., 2015, Fortaleza. Anais... Fortaleza: INI, 2015.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 8. | | COSTA NETO, G. M. F.; CASTRO, A. P. de; HEINEMANN, A. B.; DUARTE, J. B. Integrando modelos mistos, variáveis ambientais e regressão PLS no estudo dos efeitos G+GE em ensaios de VCU em arroz de terras altas. In: SEMINÁRIO JOVENS TALENTOS, 11., 2017, Santo Antônio de Goiás. Coletânea dos resumos apresentados. Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2017. p. 29. (Embrapa Arroz e Feijão. Documentos, 316).| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 13. | | COSTA NETO, G. M. F.; DUARTE, J. B.; HEINEMANN, A. B.; CASTRO, A. P. de; ANTOLIN, L. A. S. Simulação de interação "genótipo x ambiente" para arroz de terras altas em cenários de aumento da temperatura do ar. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 8., 2015, Goiânia. O melhoramento de plantas, o futuro da agricultura e a soberania nacional: anais. Goiânia: UFG: SBMP, 2015.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 15. | | CROSSA, J.; MONTESINOS-LÓPEZ, O. A.; PÉREZ-RODRÍGUEZ, P.; COSTA-NETO, G.; FRITSCHE-NETO, R.; ORTIZ, R.; MARTINI, J. W. R.; LILLEMO, M.; MONTESINOS-LÓPEZ, A.; JARQUIN, D.; BRESEGHELLO, F.; CUEVAS, J.; RINCENT, R. Genome and environment based prediction models and methods of complex traits incorporating genotype × environment interaction. In: AHMADI, N.; BARTHOLOME, J. (ed.). Genomic prediction of complex traits: methods and protocols. New York: Humana Press, 2022. p. 245-283. (Methods in Molecular Biology).| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 16. | | 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. GIS-FA: an approach to integrating thematic maps, factor-analytic, and envirotyping for cultivar targeting. Theoretical and Applied Genetics, v. 137, 80, Mar. 2024.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| Registros recuperados : 16 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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