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 | Acesso ao texto completo restrito à biblioteca da Embrapa Clima Temperado. Para informações adicionais entre em contato com cpact.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Clima Temperado; Embrapa Meio Ambiente. |
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Data corrente: |
02/12/2011 |
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Data da última atualização: |
28/10/2014 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CUADRA, S. V.; COSTA, M. H.; KUCHARIK, C. J.; ROCHA, H. R. da; TATSCH, J. D.; INMAN-BAMBER, G.; ROCHA, R. P. da; LEITE, C. C.; CABRAL, O. M. R. |
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Afiliação: |
SANTIAGO VIANNA CUADRA, CPACT; M. H. COSTA; C. J. KUCHARIK; H. R. DA ROCHA; J. D. TATSCH; G . INMAN-BAMBER; R. P. DA ROCHA; C. C . L E I T E; OSVALDO MACHADO RODRIGUES CABRAL, CNPMA. |
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Título: |
A biophysical model of Sugarcane growth. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Global Change Biology. Bioenergy, v. 4, n. 1, p. 36-48, 2012. |
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Idioma: |
Inglês |
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Conteúdo: |
Scientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in cropbased biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/ overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and kE, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and ?12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sa?o Paulo, Brazil, over a period of 16 years, with a yield relative bias of 0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields. |
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Palavras-Chave: |
Biophysical; Cana-de-açúcar; Ciclos biogeoquímicos; Land surface model; Sugarcane model. |
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Thesagro: |
Biocombustível; Impacto ambiental. |
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Thesaurus Nal: |
Biofuels; Climate change; Sugarcane. |
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Categoria do assunto: |
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P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02371naa a2200337 a 4500
001 1940240
005 2014-10-28
008 2012 bl uuuu u00u1 u #d
100 1 $aCUADRA, S. V.
245 $aA biophysical model of Sugarcane growth.$h[electronic resource]
260 $c2012
520 $aScientists predict that global agricultural lands will expand over the next few decades due to increasing demands for food production and an exponential increase in cropbased biofuel production. These changes in land use will greatly impact biogeochemical and biogeophysical cycles across the globe. It is therefore important to develop models that can accurately simulate the interactions between the atmosphere and important crops. In this study, we develop and validate a new process-based sugarcane model (included as a module within the Agro-IBIS dynamic agro-ecosystem model) which can be applied at multiple spatial scales. At site level, the model systematically under/ overestimated the daily sensible/latent heat flux (by -10.5% and 14.8%, H and kE, respectively) when compared against the micrometeorological observations from southeast Brazil. The model underestimated ET (relative bias between -10.1% and ?12.5%) when compared against an agro-meteorological field experiment from northeast Australia. At the regional level, the model accurately simulated average yield for the four largest mesoregions (clusters of municipalities) in the state of Sa?o Paulo, Brazil, over a period of 16 years, with a yield relative bias of 0.68% to 1.08%. Finally, the simulated annual average sugarcane yield over 31 years for the state of Louisiana (US) had a low relative bias (-2.67%), but exhibited a lower interannual variability than the observed yields.
650 $aBiofuels
650 $aClimate change
650 $aSugarcane
650 $aBiocombustível
650 $aImpacto ambiental
653 $aBiophysical
653 $aCana-de-açúcar
653 $aCiclos biogeoquímicos
653 $aLand surface model
653 $aSugarcane model
700 1 $aCOSTA, M. H.
700 1 $aKUCHARIK, C. J.
700 1 $aROCHA, H. R. da
700 1 $aTATSCH, J. D.
700 1 $aINMAN-BAMBER, G.
700 1 $aROCHA, R. P. da
700 1 $aLEITE, C. C.
700 1 $aCABRAL, O. M. R.
773 $tGlobal Change Biology. Bioenergy$gv. 4, n. 1, p. 36-48, 2012.
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Registro original: |
Embrapa Clima Temperado (CPACT) |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Café. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Café; Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
10/01/2023 |
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Data da última atualização: |
11/07/2023 |
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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: |
ESTOPA, R. A.; PALUDETO, J. G. Z.; MÜLLER, B. S. F.; OLIVEIRA, R. A. de; AZEVEDO, C. F.; RESENDE, M. D. V. de; TAMBARUSSI, E. V.; GRATTAPAGLIA, D. |
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Afiliação: |
REGIANE ABJAUD ESTOPA, FORESTRY R&D - KLABIN S.A; JOÃO GABRIEL ZANON PALUDETO, FORESTRY R&D - KLABIN S.A; BÁRBARA SALOMÃO FARIA MÜLLER, UNIVERSITY OF FLORIDA; RICARDO AUGUSTO DE OLIVEIRA, UNIVERSIDADE FEDERAL DE VIÇOSA; CAMILA FERREIRA AZEVEDO, UNIVERSIDADE FEDERAL DE VIÇOSA; MARCOS DEON VILELA DE RESENDE, CNPCa; EVANDRO VAGNER TAMBARUSSI, UNIVERSIDADE ESTADUAL DO CENTRO-OESTE; DARIO GRATTAPAGLIA, Cenargen. |
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Título: |
Genomic prediction of growth and wood quality traits in Eucalyptus benthamii using different genomic models and variable SNP genotyping density. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
New Forests, 54, 2023. |
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DOI: |
https://doi.org/10.1007/s11056-022-09924-y |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic selection (GS) is poised to revolutionize eucalypt tree improvement by shortening breeding cycles and increasing selection intensities. This could be particularly valuable for alternative, non-mainstream Eucalyptus species that are still in the initial stages of breeding. Eucalyptus benthamii is important for its adaptation to frost-prone subtropical regions. In this work, we compared seven genomic prediction models, six Bayesian and one frequentist GBLUP (Genomic Best Linear Unbiased Prediction) with the conventional pedigree-based ABLUP approach. Models were evaluated for their ability to estimate heritabilities and predict wood quality traits (wood density, extractives, lignin, and carbohydrates content) and volume growth in 77 open-pollinated families of Eucalyptus benthamii. We also evaluated predictive abilities and heritabilities using variable numbers of SNP in the models. Heritabilities ranged from 0.09 (extractives content) using Bayesian Lasso (BL) to 0.55 (wood density) using ABLUP. Predictive abilities (PA) ranged from 0.12 (for volume using ABLUP) to 0.44 (for wood density using three Bayesian models). All seven genomic models performed similarly well and better than the pedigree model for all traits, except extractives content. Subsets of 5000?7000 SNPs yielded heritabilities and PAs nearly as large as using all 15,293 SNPs. However, a low-density SNP panel might not be economically and technically advantageous compared to the current high-density multi-species Eucalyptus EUCHIP60k. Our results support a positive outlook to implement GS to accelerate Eucalyptus benthamii breeding for adaptation to frost-prone regions. MenosGenomic selection (GS) is poised to revolutionize eucalypt tree improvement by shortening breeding cycles and increasing selection intensities. This could be particularly valuable for alternative, non-mainstream Eucalyptus species that are still in the initial stages of breeding. Eucalyptus benthamii is important for its adaptation to frost-prone subtropical regions. In this work, we compared seven genomic prediction models, six Bayesian and one frequentist GBLUP (Genomic Best Linear Unbiased Prediction) with the conventional pedigree-based ABLUP approach. Models were evaluated for their ability to estimate heritabilities and predict wood quality traits (wood density, extractives, lignin, and carbohydrates content) and volume growth in 77 open-pollinated families of Eucalyptus benthamii. We also evaluated predictive abilities and heritabilities using variable numbers of SNP in the models. Heritabilities ranged from 0.09 (extractives content) using Bayesian Lasso (BL) to 0.55 (wood density) using ABLUP. Predictive abilities (PA) ranged from 0.12 (for volume using ABLUP) to 0.44 (for wood density using three Bayesian models). All seven genomic models performed similarly well and better than the pedigree model for all traits, except extractives content. Subsets of 5000?7000 SNPs yielded heritabilities and PAs nearly as large as using all 15,293 SNPs. However, a low-density SNP panel might not be economically and technically advantageous compared to the current high-density mult... Mostrar Tudo |
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Thesaurus NAL: |
Eucalyptus benthamii; Genomics; Genotyping; Wood quality. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02502naa a2200265 a 4500
001 2150837
005 2023-07-11
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s11056-022-09924-y$2DOI
100 1 $aESTOPA, R. A.
245 $aGenomic prediction of growth and wood quality traits in Eucalyptus benthamii using different genomic models and variable SNP genotyping density.$h[electronic resource]
260 $c2023
520 $aGenomic selection (GS) is poised to revolutionize eucalypt tree improvement by shortening breeding cycles and increasing selection intensities. This could be particularly valuable for alternative, non-mainstream Eucalyptus species that are still in the initial stages of breeding. Eucalyptus benthamii is important for its adaptation to frost-prone subtropical regions. In this work, we compared seven genomic prediction models, six Bayesian and one frequentist GBLUP (Genomic Best Linear Unbiased Prediction) with the conventional pedigree-based ABLUP approach. Models were evaluated for their ability to estimate heritabilities and predict wood quality traits (wood density, extractives, lignin, and carbohydrates content) and volume growth in 77 open-pollinated families of Eucalyptus benthamii. We also evaluated predictive abilities and heritabilities using variable numbers of SNP in the models. Heritabilities ranged from 0.09 (extractives content) using Bayesian Lasso (BL) to 0.55 (wood density) using ABLUP. Predictive abilities (PA) ranged from 0.12 (for volume using ABLUP) to 0.44 (for wood density using three Bayesian models). All seven genomic models performed similarly well and better than the pedigree model for all traits, except extractives content. Subsets of 5000?7000 SNPs yielded heritabilities and PAs nearly as large as using all 15,293 SNPs. However, a low-density SNP panel might not be economically and technically advantageous compared to the current high-density multi-species Eucalyptus EUCHIP60k. Our results support a positive outlook to implement GS to accelerate Eucalyptus benthamii breeding for adaptation to frost-prone regions.
650 $aEucalyptus benthamii
650 $aGenomics
650 $aGenotyping
650 $aWood quality
700 1 $aPALUDETO, J. G. Z.
700 1 $aMÜLLER, B. S. F.
700 1 $aOLIVEIRA, R. A. de
700 1 $aAZEVEDO, C. F.
700 1 $aRESENDE, M. D. V. de
700 1 $aTAMBARUSSI, E. V.
700 1 $aGRATTAPAGLIA, D.
773 $tNew Forests, 54, 2023.
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Embrapa Café (CNPCa) |
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