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 | Acesso ao texto completo restrito à biblioteca da Embrapa Florestas. Para informações adicionais entre em contato com cnpf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
26/11/2018 |
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Data da última atualização: |
27/11/2018 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ALVES, R. S.; ROCHA, J. R. do A. de C.; TEODORO, P. E.; RESENDE, M. D. V. de; HENRIQUES, E. P.; SILVA, L. A.; CARNEIRO, P. C. S.; BHERING, L. L. |
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Afiliação: |
Rodrigo Silva Alves, UFV; João Romero do Amaral Santos de Carvalho Rocha, UFV; Paulo Eduardo Teodoro, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; Eduardo Pinheiro Henriques, Silviculture Genes; Lidiane Aparecida Silva, UFV; Pedro Crescêncio Souza Carneiro, UFV; Leonardo Lopes Bhering, UFV. |
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Título: |
Multiple-trait BLUP: a suitable strategy for genetic selection of Eucalyptus. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Tree Genetics & Genomes, v. 14, n. 5, article 77, Oct. 2018. 8 p. |
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DOI: |
10.1007/s11295-018-1292-7 |
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Idioma: |
Inglês |
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Conteúdo: |
Usually, genetic selection is carried out based on several traits, which can be genetically correlated. In this case, selection bias may occur if these traits are analyzed individually. Thus, the present work aimed to evaluate the applicability and efficiency of multiple-trait best linear unbiased prediction (BLUP) in the genetic selection of Eucalyptus. The data used in this work refer to the evaluation of a partial diallel of Eucalyptus spp. in relation to height, diameter at breast height (DBH), and volume. Variance components and genetic and non-genetic parameters were estimated via residual maximum likelihood (REML). Multiple-trait BLUP led to estimates of mean additive genetic variance higher than the estimates obtained via single-trait BLUP and, consequently, led to higher estimates of narrow-sense individual interpopulational heritabilities and mean accuracies. Partial genetic correlations obtained via multiple-trait BLUP allowed a real understanding of the association between traits, differently from those obtained via single-trait BLUP. Multiple-trait BLUP led to higher gains predicted with the selection for height, DBH, and volume and can be efficiently applied in the genetic selection of Eucalyptus. |
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Palavras-Chave: |
BLUP; Diallel; Mixed model methodology. |
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Thesagro: |
Eucalipto; Melhoramento Genético Vegetal; Seleção Genética. |
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Thesaurus Nal: |
Eucalyptus; Genetic correlation; Tree breeding. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
LEADER 02189naa a2200325 a 4500
001 2100094
005 2018-11-27
008 2018 bl uuuu u00u1 u #d
024 7 $a10.1007/s11295-018-1292-7$2DOI
100 1 $aALVES, R. S.
245 $aMultiple-trait BLUP$ba suitable strategy for genetic selection of Eucalyptus.$h[electronic resource]
260 $c2018
520 $aUsually, genetic selection is carried out based on several traits, which can be genetically correlated. In this case, selection bias may occur if these traits are analyzed individually. Thus, the present work aimed to evaluate the applicability and efficiency of multiple-trait best linear unbiased prediction (BLUP) in the genetic selection of Eucalyptus. The data used in this work refer to the evaluation of a partial diallel of Eucalyptus spp. in relation to height, diameter at breast height (DBH), and volume. Variance components and genetic and non-genetic parameters were estimated via residual maximum likelihood (REML). Multiple-trait BLUP led to estimates of mean additive genetic variance higher than the estimates obtained via single-trait BLUP and, consequently, led to higher estimates of narrow-sense individual interpopulational heritabilities and mean accuracies. Partial genetic correlations obtained via multiple-trait BLUP allowed a real understanding of the association between traits, differently from those obtained via single-trait BLUP. Multiple-trait BLUP led to higher gains predicted with the selection for height, DBH, and volume and can be efficiently applied in the genetic selection of Eucalyptus.
650 $aEucalyptus
650 $aGenetic correlation
650 $aTree breeding
650 $aEucalipto
650 $aMelhoramento Genético Vegetal
650 $aSeleção Genética
653 $aBLUP
653 $aDiallel
653 $aMixed model methodology
700 1 $aROCHA, J. R. do A. de C.
700 1 $aTEODORO, P. E.
700 1 $aRESENDE, M. D. V. de
700 1 $aHENRIQUES, E. P.
700 1 $aSILVA, L. A.
700 1 $aCARNEIRO, P. C. S.
700 1 $aBHERING, L. L.
773 $tTree Genetics & Genomes$gv. 14, n. 5, article 77, Oct. 2018. 8 p.
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Registro original: |
Embrapa Florestas (CNPF) |
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Biblioteca |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
14/09/2021 |
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Data da última atualização: |
14/09/2021 |
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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: |
MARÇAL, M. F. M.; SOUZA, Z. M. de; TAVARES, R. L. M.; FARHATE, C. V. V.; OLIVEIRA, S. R. de M.; GALINDO, F. S. |
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Afiliação: |
MARIA FERNANDA MAGIONI MARÇAL, FEAGRI/UNICAMP; ZIGOMAR MENEZES DE SOUZA, FEAGRI/UNICAMP; ROSE LUIZA MORAES TAVARES, UNIVERSITY OF RIO VERDE; CAMILA VIANA VIEIRA FARHATE, FEAGRI/UNICAMP, UNESP; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; FERNANDO SHINTATE GALINDO, FEAGRI/UNICAMP, UNESP. |
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Título: |
Predictive models to estimate carbon stocks in agroforestry systems. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Forests, v. 12, n. 9, p. 1-15, Sept. 2021. |
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DOI: |
https://doi.org/10.3390/f12091240 |
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Idioma: |
Inglês |
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Notas: |
Article 1240. Na publicação: Stanley Robson Medeiros Oliveira. |
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Conteúdo: |
Abstract: This study aims to assess the carbon stock in a pasture area and fragment of forest in natural regeneration, given the importance of agroforestry systems in mitigating gas emissions which contribute to the greenhouse effect, as well as promoting the maintenance of agricultural productivity. Our other goal was to predict the carbon stock, according to different land use systems, from physical and chemical soil variables using the Random Forest algorithm. We carried out our study at an Entisols Quartzipsamments area with a completely randomized experimental design: four treatments and six replites. The treatments consisted of the following: (i) an agroforestry system developed for livestock, (ii) an agroforestry system developed for fruit culture, (iii) a conventional pasture, and (iv) a forest fragment. Deformed and undeformed soil samples were collected in order to analyze their physical and chemical properties across two consecutive agricultural years. The response variable, carbon stock, was subjected to a boxplot analysis and all the databases were used for a predictive modeling which in turn used the Random Forest algorithm. Results led to the conclusion that the agroforestry systems developed both for fruit culture and livestock, are more efficient at stocking carbon in the soil than the pasture area and forest fragment undergoing natural regeneration. Nitrogen stock and land use systems are the most important variables to estimate carbon stock from the physical and chemical variables of soil using the Random Forest algorithm. The predictive models generated from the physical and chemical variables of soil, as well as the Random Forest algorithm, presented a high potential for predicting soil carbon stock and are sensitive to different land use systems. MenosAbstract: This study aims to assess the carbon stock in a pasture area and fragment of forest in natural regeneration, given the importance of agroforestry systems in mitigating gas emissions which contribute to the greenhouse effect, as well as promoting the maintenance of agricultural productivity. Our other goal was to predict the carbon stock, according to different land use systems, from physical and chemical soil variables using the Random Forest algorithm. We carried out our study at an Entisols Quartzipsamments area with a completely randomized experimental design: four treatments and six replites. The treatments consisted of the following: (i) an agroforestry system developed for livestock, (ii) an agroforestry system developed for fruit culture, (iii) a conventional pasture, and (iv) a forest fragment. Deformed and undeformed soil samples were collected in order to analyze their physical and chemical properties across two consecutive agricultural years. The response variable, carbon stock, was subjected to a boxplot analysis and all the databases were used for a predictive modeling which in turn used the Random Forest algorithm. Results led to the conclusion that the agroforestry systems developed both for fruit culture and livestock, are more efficient at stocking carbon in the soil than the pasture area and forest fragment undergoing natural regeneration. Nitrogen stock and land use systems are the most important variables to estimate carbon stock from the physic... Mostrar Tudo |
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Palavras-Chave: |
Agroforestry systems; Data mining technique; Floresta aleatória; Land use systems; Mineração de dados; Modelo preditivo; Predictive models; Random forest; Sequestro de carbono; Sistemas agroflorestais; Sistemas de uso da terra. |
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Thesagro: |
Matéria Orgânica; Uso da Terra. |
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Thesaurus NAL: |
Agroforestry; Carbon sequestration; Land use; Organic matter. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/225942/1/AP-Predictive-models-Forests-2021.pdf
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Marc: |
LEADER 03046naa a2200409 a 4500
001 2134318
005 2021-09-14
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/f12091240$2DOI
100 1 $aMARÇAL, M. F. M.
245 $aPredictive models to estimate carbon stocks in agroforestry systems.$h[electronic resource]
260 $c2021
500 $aArticle 1240. Na publicação: Stanley Robson Medeiros Oliveira.
520 $aAbstract: This study aims to assess the carbon stock in a pasture area and fragment of forest in natural regeneration, given the importance of agroforestry systems in mitigating gas emissions which contribute to the greenhouse effect, as well as promoting the maintenance of agricultural productivity. Our other goal was to predict the carbon stock, according to different land use systems, from physical and chemical soil variables using the Random Forest algorithm. We carried out our study at an Entisols Quartzipsamments area with a completely randomized experimental design: four treatments and six replites. The treatments consisted of the following: (i) an agroforestry system developed for livestock, (ii) an agroforestry system developed for fruit culture, (iii) a conventional pasture, and (iv) a forest fragment. Deformed and undeformed soil samples were collected in order to analyze their physical and chemical properties across two consecutive agricultural years. The response variable, carbon stock, was subjected to a boxplot analysis and all the databases were used for a predictive modeling which in turn used the Random Forest algorithm. Results led to the conclusion that the agroforestry systems developed both for fruit culture and livestock, are more efficient at stocking carbon in the soil than the pasture area and forest fragment undergoing natural regeneration. Nitrogen stock and land use systems are the most important variables to estimate carbon stock from the physical and chemical variables of soil using the Random Forest algorithm. The predictive models generated from the physical and chemical variables of soil, as well as the Random Forest algorithm, presented a high potential for predicting soil carbon stock and are sensitive to different land use systems.
650 $aAgroforestry
650 $aCarbon sequestration
650 $aLand use
650 $aOrganic matter
650 $aMatéria Orgânica
650 $aUso da Terra
653 $aAgroforestry systems
653 $aData mining technique
653 $aFloresta aleatória
653 $aLand use systems
653 $aMineração de dados
653 $aModelo preditivo
653 $aPredictive models
653 $aRandom forest
653 $aSequestro de carbono
653 $aSistemas agroflorestais
653 $aSistemas de uso da terra
700 1 $aSOUZA, Z. M. de
700 1 $aTAVARES, R. L. M.
700 1 $aFARHATE, C. V. V.
700 1 $aOLIVEIRA, S. R. de M.
700 1 $aGALINDO, F. S.
773 $tForests$gv. 12, n. 9, p. 1-15, Sept. 2021.
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Embrapa Agricultura Digital (CNPTIA) |
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