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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agroenergia. Para informações adicionais entre em contato com cnpae.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Agroenergia; Embrapa Café. |
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Data corrente: |
08/12/2023 |
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Data da última atualização: |
08/12/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
EVANGELISTA, J. S. P. C.; PEIXOTO, M. A.; COELHO, I. F.; FERREIRA, F. M.; MARÇAL, T. de S.; ALVES, R. S.; CHAVES, S. F. da S.; RODRIGUES, E. V.; LAVIOLA, B. G.; RESENDE, M. D. V. de; DIAS, K. O. das G.; BHERING, L. L. |
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Afiliação: |
JENIFFER SANTANA PINTO COELHO EVANGELISTA, UNIVERSIDADE FEDERAL DE VIÇOSA; MARCO ANTÔNIO PEIXOTO, UNIVERSIDADE FEDERAL DE VIÇOSA; IGOR FERREIRA COELHO, UNIVERSIDADE FEDERAL DE VIÇOSA; FILIPE MANOEL FERREIRA, UNIVERSIDADE FEDERAL DE VIÇOSA; TIAGO DE SOUZA MARÇAL, UNIVERSIDADE FEDERAL DE LAVRAS; RODRIGO SILVA ALVES, INSTITUTO NACIONAL DE CIÊNCIA E TECNOLOGIA DO CAFÉ; SAULO FABRICIO DA SILVA CHAVES, UNIVERSIDADE FEDERAL DE VIÇOSA; ERINA VITÓRIO RODRIGUES, UNIVERSIDADE DE BRASÍLIA; BRUNO GALVEAS LAVIOLA, CNPAE; MARCOS DEON VILELA DE RESENDE, CNPCa; KAIO OLIMPIO DAS GRAÇAS DIAS, UNIVERSIDADE FEDERAL DE VIÇOSA; LEONARDO LOPES BHERING, UNIVERSIDADE FEDERAL DE VIÇOSA. |
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Título: |
Modeling covariance structures and optimizing jatropha curcas breeding. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Tree Genetics & Genomes, v. 19, 21, 2023. |
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Páginas: |
11 p. |
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DOI: |
https://doi.org/10.1007/s11295-023-01596-9 |
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Idioma: |
Inglês |
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Conteúdo: |
Jatropha curcas has become a prominent source of biofuel, especially because of the high oil content in its fruit. The aim of this study was to test different statistic models and compare the best-fitted model with the compound symmetry model and study the grain yield persistence of J. curcas progenies. A total of 730 individuals from 73 half-sib families were evaluated for the fruit yield trait over six crop years. Repeated measures models with different covariance structures for the genetic and non-genetic effects were tested. Results show an increase up to in accuracy upon modeling the genetic and non-genetic effects when compared to the compound symmetry model. The selection gain obtained via the best-fit model for 10, 15, 20, and 25 selected best progenies was around 3 to 2% higher than gain obtained via the standard statistical model used by breeders (compound symmetry model). The harvests evaluated exhibited accuracies of high magnitude. The ten progenies that stood out with the best genetic performance are also those with the greatest persistence and greatest accumulated yield. Combining modeling of covariance structures for grain yield and selecting for persistence of production can sustain a successful long-term J. curcas breeding program. |
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Thesaurus Nal: |
Biofuels; Genetic covariance; Jatropha; Plant breeding. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02200naa a2200325 a 4500
001 2159353
005 2023-12-08
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s11295-023-01596-9$2DOI
100 1 $aEVANGELISTA, J. S. P. C.
245 $aModeling covariance structures and optimizing jatropha curcas breeding.$h[electronic resource]
260 $c2023
300 $a11 p.
520 $aJatropha curcas has become a prominent source of biofuel, especially because of the high oil content in its fruit. The aim of this study was to test different statistic models and compare the best-fitted model with the compound symmetry model and study the grain yield persistence of J. curcas progenies. A total of 730 individuals from 73 half-sib families were evaluated for the fruit yield trait over six crop years. Repeated measures models with different covariance structures for the genetic and non-genetic effects were tested. Results show an increase up to in accuracy upon modeling the genetic and non-genetic effects when compared to the compound symmetry model. The selection gain obtained via the best-fit model for 10, 15, 20, and 25 selected best progenies was around 3 to 2% higher than gain obtained via the standard statistical model used by breeders (compound symmetry model). The harvests evaluated exhibited accuracies of high magnitude. The ten progenies that stood out with the best genetic performance are also those with the greatest persistence and greatest accumulated yield. Combining modeling of covariance structures for grain yield and selecting for persistence of production can sustain a successful long-term J. curcas breeding program.
650 $aBiofuels
650 $aGenetic covariance
650 $aJatropha
650 $aPlant breeding
700 1 $aPEIXOTO, M. A.
700 1 $aCOELHO, I. F.
700 1 $aFERREIRA, F. M.
700 1 $aMARÇAL, T. de S.
700 1 $aALVES, R. S.
700 1 $aCHAVES, S. F. da S.
700 1 $aRODRIGUES, E. V.
700 1 $aLAVIOLA, B. G.
700 1 $aRESENDE, M. D. V. de
700 1 $aDIAS, K. O. das G.
700 1 $aBHERING, L. L.
773 $tTree Genetics & Genomes$gv. 19, 21, 2023.
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Embrapa Agroenergia (CNPAE) |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
25/04/2011 |
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Data da última atualização: |
08/07/2011 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
VIEIRA, S. R.; CARVALHO, J. R. P. de; PAZ GONZÁLEZ, A. |
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Afiliação: |
SIDNEY ROSA VIEIRA, IAC; JOSE RUY PORTO DE CARVALHO, CNPTIA; ANTONIO PAZ GONZÁLEZ, Universidade da Coruña, Espanha. |
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Título: |
Jack knifing for semivariogram validation. |
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Ano de publicação: |
2010 |
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Fonte/Imprenta: |
Bragantia, Campinas, v. 69, p. 97-105, 2010 |
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Idioma: |
Inglês |
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Notas: |
Suplemento. |
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Conteúdo: |
The semivariogram function fitting is the most important aspect of geostatistics and because of this the model chosen must be validated. Jack knifing may be one the most efficient ways for this validation purpose. The objective of this study was to show the use of the jack knifing technique to validate geostatistical hypothesis and semivariogram models. For that purpose, topographical heights data obtained from six distinct field scales and sampling densities were analyzed. Because the topographical data showed very strong trend for all fields as it was verified by the absence of a sill in the experimental semivariograms, the trend was removed with a trend surface fitted by minimum square deviation. Semivariogram models were fitted with different techniques and the results of the jack knifing with them were compared. The jack knifing parameters analyzed were the intercept, slope and correlation coefficient between measured and estimated values, and the mean and variance of the errors calculated by the difference between measured and estimated values, divided by the square root of the estimation variances. The ideal numbers of neighbors used in each estimation was also studied using the jack knifing procedure. The jack knifing results were useful in the judgment of the adequate models fitted independent of the scale and sampling densities. It was concluded that the manual fitted semivariogram models produced better jack knifing parameters because the user has the freedom to choose a better fit in distinct regions of the semivariogram. MenosThe semivariogram function fitting is the most important aspect of geostatistics and because of this the model chosen must be validated. Jack knifing may be one the most efficient ways for this validation purpose. The objective of this study was to show the use of the jack knifing technique to validate geostatistical hypothesis and semivariogram models. For that purpose, topographical heights data obtained from six distinct field scales and sampling densities were analyzed. Because the topographical data showed very strong trend for all fields as it was verified by the absence of a sill in the experimental semivariograms, the trend was removed with a trend surface fitted by minimum square deviation. Semivariogram models were fitted with different techniques and the results of the jack knifing with them were compared. The jack knifing parameters analyzed were the intercept, slope and correlation coefficient between measured and estimated values, and the mean and variance of the errors calculated by the difference between measured and estimated values, divided by the square root of the estimation variances. The ideal numbers of neighbors used in each estimation was also studied using the jack knifing procedure. The jack knifing results were useful in the judgment of the adequate models fitted independent of the scale and sampling densities. It was concluded that the manual fitted semivariogram models produced better jack knifing parameters because the user has the freedom to c... Mostrar Tudo |
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Palavras-Chave: |
Erro reduzido; Estacionaridade; Semivariograms; Stationarity. |
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Thesagro: |
Topografia. |
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Thesaurus NAL: |
Topography. |
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Categoria do assunto: |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/33101/1/Jack2.pdf
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Marc: |
LEADER 02167naa a2200229 a 4500
001 1886773
005 2011-07-08
008 2010 bl uuuu u00u1 u #d
100 1 $aVIEIRA, S. R.
245 $aJack knifing for semivariogram validation.$h[electronic resource]
260 $c2010
500 $aSuplemento.
520 $aThe semivariogram function fitting is the most important aspect of geostatistics and because of this the model chosen must be validated. Jack knifing may be one the most efficient ways for this validation purpose. The objective of this study was to show the use of the jack knifing technique to validate geostatistical hypothesis and semivariogram models. For that purpose, topographical heights data obtained from six distinct field scales and sampling densities were analyzed. Because the topographical data showed very strong trend for all fields as it was verified by the absence of a sill in the experimental semivariograms, the trend was removed with a trend surface fitted by minimum square deviation. Semivariogram models were fitted with different techniques and the results of the jack knifing with them were compared. The jack knifing parameters analyzed were the intercept, slope and correlation coefficient between measured and estimated values, and the mean and variance of the errors calculated by the difference between measured and estimated values, divided by the square root of the estimation variances. The ideal numbers of neighbors used in each estimation was also studied using the jack knifing procedure. The jack knifing results were useful in the judgment of the adequate models fitted independent of the scale and sampling densities. It was concluded that the manual fitted semivariogram models produced better jack knifing parameters because the user has the freedom to choose a better fit in distinct regions of the semivariogram.
650 $aTopography
650 $aTopografia
653 $aErro reduzido
653 $aEstacionaridade
653 $aSemivariograms
653 $aStationarity
700 1 $aCARVALHO, J. R. P. de
700 1 $aPAZ GONZÁLEZ, A.
773 $tBragantia, Campinas$gv. 69, p. 97-105, 2010
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Embrapa Agricultura Digital (CNPTIA) |
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