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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
08/08/2011 |
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Data da última atualização: |
08/08/2011 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
HEINEMANN, A. B.; SENTELHAS, P. C. |
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Afiliação: |
ALEXANDRE BRYAN HEINEMANN, CNPAF; PAULO CESAR SENTELHAS, ESALQ. |
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Título: |
Environmental group identification for upland rice production in central Brazil. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
Scientia Agricola, Piracicaba, v. 68, n. 5, p. 540-547, set./out. 2011. |
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Idioma: |
Inglês |
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Conteúdo: |
Upland rice (Oryza sativa L.) production is basically concentrated in four central Brazilian States, Mato Grosso, Goiás, Rondônia and Tocantins. To reduce the genotype and environment (G × E) interactions, the classification of environment groups was proposed. The goal of this study explores possibilities to adjust the upland rice regional breeding systems to optimally fit to the range of environments they are targeting, based on a historical yield data set of the Brazilian Geographic and Statistics Institute (IBGE, www.ibge.gov.br/home/) from 54 microregions. The specific objectives of this study were: (i) to identify and classify environmental groups in the Brazilian upland rice production area; (ii) to validate these environmental groups using yield data set from the upland rice multi-trial experiments (MTEs); (iii) and to identify the most representative site for each environmental group. For this the historical upland rice yield data from 54 microregions were detrented from the effects of technological advances and adjusted to the reference year, 2006. The adjusted yield data were used to build a matrix, which was submitted to a cluster analysis allowing the identification of three different environmental groups. These groups were classified as: highly favorable environment (HFE); favorable environment (FE); and less favorable environment (LFE). The HFE is less affected by inter-annual rainfall variability than the other two groups. The upland rice breeding programs must take into account the differences among the environmental groups to conduct their trials and suggest genotypes for the upland production area. MenosUpland rice (Oryza sativa L.) production is basically concentrated in four central Brazilian States, Mato Grosso, Goiás, Rondônia and Tocantins. To reduce the genotype and environment (G × E) interactions, the classification of environment groups was proposed. The goal of this study explores possibilities to adjust the upland rice regional breeding systems to optimally fit to the range of environments they are targeting, based on a historical yield data set of the Brazilian Geographic and Statistics Institute (IBGE, www.ibge.gov.br/home/) from 54 microregions. The specific objectives of this study were: (i) to identify and classify environmental groups in the Brazilian upland rice production area; (ii) to validate these environmental groups using yield data set from the upland rice multi-trial experiments (MTEs); (iii) and to identify the most representative site for each environmental group. For this the historical upland rice yield data from 54 microregions were detrented from the effects of technological advances and adjusted to the reference year, 2006. The adjusted yield data were used to build a matrix, which was submitted to a cluster analysis allowing the identification of three different environmental groups. These groups were classified as: highly favorable environment (HFE); favorable environment (FE); and less favorable environment (LFE). The HFE is less affected by inter-annual rainfall variability than the other two groups. The upland rice breeding programs mus... Mostrar Tudo |
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Palavras-Chave: |
Breading program; Environment classification. |
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Thesagro: |
Análise estatística; Arroz; Oryza sativa. |
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Thesaurus Nal: |
Cluster analysis; Yields. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/39399/1/Scientiia.pdf
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Marc: |
LEADER 02301naa a2200217 a 4500
001 1897493
005 2011-08-08
008 2011 bl uuuu u00u1 u #d
100 1 $aHEINEMANN, A. B.
245 $aEnvironmental group identification for upland rice production in central Brazil.$h[electronic resource]
260 $c2011
520 $aUpland rice (Oryza sativa L.) production is basically concentrated in four central Brazilian States, Mato Grosso, Goiás, Rondônia and Tocantins. To reduce the genotype and environment (G × E) interactions, the classification of environment groups was proposed. The goal of this study explores possibilities to adjust the upland rice regional breeding systems to optimally fit to the range of environments they are targeting, based on a historical yield data set of the Brazilian Geographic and Statistics Institute (IBGE, www.ibge.gov.br/home/) from 54 microregions. The specific objectives of this study were: (i) to identify and classify environmental groups in the Brazilian upland rice production area; (ii) to validate these environmental groups using yield data set from the upland rice multi-trial experiments (MTEs); (iii) and to identify the most representative site for each environmental group. For this the historical upland rice yield data from 54 microregions were detrented from the effects of technological advances and adjusted to the reference year, 2006. The adjusted yield data were used to build a matrix, which was submitted to a cluster analysis allowing the identification of three different environmental groups. These groups were classified as: highly favorable environment (HFE); favorable environment (FE); and less favorable environment (LFE). The HFE is less affected by inter-annual rainfall variability than the other two groups. The upland rice breeding programs must take into account the differences among the environmental groups to conduct their trials and suggest genotypes for the upland production area.
650 $aCluster analysis
650 $aYields
650 $aAnálise estatística
650 $aArroz
650 $aOryza sativa
653 $aBreading program
653 $aEnvironment classification
700 1 $aSENTELHAS, P. C.
773 $tScientia Agricola, Piracicaba$gv. 68, n. 5, p. 540-547, set./out. 2011.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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Biblioteca |
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Origem |
Tipo/Formato |
Classificação |
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Registro |
Volume |
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URL |
Voltar
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
25/02/2013 |
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Data da última atualização: |
10/11/2022 |
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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: |
STARK, S. C.; LEITOLD, V.; WU, J. L.; HUNTER, M. O.; CASTILHO, C. V. de; COSTA, F. R. C.; MCMAHON, S. M.; PARKER, G. G.; SHIMABUKURO, M. T.; LEFSKY, M. A.; KELLER, M.; ALVES, L. F.; SCHIETTI, J.; SHIMABUKURO, Y. E.; BRANDÃO, D. O.; WOODCOCK, T. K.; HIGUCHI, N.; CAMARGO, P. B. de; OLIVEIRA, R. C. de; SALESKA, S. R. |
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Afiliação: |
Scott C. Stark; Veronika Leitold; Jin L. Wu; Maria O. Hunter; Carolina V. de Castilho; Flávia R. C. Costa; Sean M. McMahon; Geoffrey G. Parker; Mônica Takako Shimabukuro; Michael A. Lefsky; Michael Keller; Luciana F. Alves; Juliana Schietti; Yosio Edemir Shimabukuro; Diego O. Brandão; Tara K. Woodcock; Niro Higuchi; Plinio B. de Camargo; RAIMUNDO COSME DE OLIVEIRA JUNIOR, CPATU; Scott R. Saleska. |
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Título: |
Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Ecology Letters, v. 15, n. 12, p. 1406-1414, dez. 2012. |
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DOI: |
10.1111/j.1461-0248.2012.01864.x |
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Idioma: |
Inglês |
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Conteúdo: |
Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) ? remotely estimated from LiDAR ? control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth across tree size classes in forest near Manaus, Brazil. The same statistical model, with no parameterisation change but driven by different observed canopy structure, predicted the higher productivity of a site 500 km east. Gap fraction and a metric of vegetation vertical extent and evenness also predicted biomass gains and losses for one-hectare plots. Despite significant site differences in canopy structure and carbon dynamics, the relation between biomass growth and light fell on a unifying curve. This supported our hypothesis, suggesting that knowledge of canopy structure can explain variation in biomass growth over tropical landscapes and improve understanding of ecosystem function. |
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Palavras-Chave: |
Biomass growth; Carbon balance; Gap fraction; Leaf area profiles; Remote sensing of canopy structure. |
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Thesaurus NAL: |
lidar. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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Marc: |
LEADER 02301naa a2200433 a 4500
001 1950777
005 2022-11-10
008 2012 bl uuuu u00u1 u #d
024 7 $a10.1111/j.1461-0248.2012.01864.x$2DOI
100 1 $aSTARK, S. C.
245 $aAmazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment.$h[electronic resource]
260 $c2012
520 $aTropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) ? remotely estimated from LiDAR ? control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth across tree size classes in forest near Manaus, Brazil. The same statistical model, with no parameterisation change but driven by different observed canopy structure, predicted the higher productivity of a site 500 km east. Gap fraction and a metric of vegetation vertical extent and evenness also predicted biomass gains and losses for one-hectare plots. Despite significant site differences in canopy structure and carbon dynamics, the relation between biomass growth and light fell on a unifying curve. This supported our hypothesis, suggesting that knowledge of canopy structure can explain variation in biomass growth over tropical landscapes and improve understanding of ecosystem function.
650 $alidar
653 $aBiomass growth
653 $aCarbon balance
653 $aGap fraction
653 $aLeaf area profiles
653 $aRemote sensing of canopy structure
700 1 $aLEITOLD, V.
700 1 $aWU, J. L.
700 1 $aHUNTER, M. O.
700 1 $aCASTILHO, C. V. de
700 1 $aCOSTA, F. R. C.
700 1 $aMCMAHON, S. M.
700 1 $aPARKER, G. G.
700 1 $aSHIMABUKURO, M. T.
700 1 $aLEFSKY, M. A.
700 1 $aKELLER, M.
700 1 $aALVES, L. F.
700 1 $aSCHIETTI, J.
700 1 $aSHIMABUKURO, Y. E.
700 1 $aBRANDÃO, D. O.
700 1 $aWOODCOCK, T. K.
700 1 $aHIGUCHI, N.
700 1 $aCAMARGO, P. B. de
700 1 $aOLIVEIRA, R. C. de
700 1 $aSALESKA, S. R.
773 $tEcology Letters$gv. 15, n. 12, p. 1406-1414, dez. 2012.
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Embrapa Amazônia Oriental (CPATU) |
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