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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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Circulação/Nível: |
A - 2 |
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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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Embrapa Arroz e Feijão (CNPAF) |
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