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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
21/02/2014 |
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Actualizado : |
09/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
AGUILAR, I.; TSURUTA, S.; MISZTAL, I. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay; S. TSURUTA, Animal and Dairy Science Department, University of Georgia, Athens, United State; I. MISZTAL, Animal and Dairy Science Department, University of Georgia, Athens, United States. |
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Título : |
Computing options for multiple-trait test-day random regression models while accounting for heat tolerance. |
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Fecha de publicación : |
2010 |
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Fuente / Imprenta : |
Journal of Animal Breeding and Genetics, 2010, v.127, no.3, p.235-241. |
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ISSN : |
0931-2668 |
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DOI : |
10.1111/j.1439-0388.2009.00842.x |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 24 December 2008 / Accepted: 08 September 2009. |
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Contenido : |
ABSTRACT.
Data included 90 242 799 test day records from first, second and third parities of 5 402 484 Holstein cows and 9 326 754 animals in the pedigree. Additionally, daily temperature humidity indexes (THI) from 202 weather stations were available. The fixed effects included herd test day, age at calving, milking frequency and days in milk classes (DIM). Random effects were additive genetic, permanent environment and herd-year and were fit as random regressions. Covariates included linear splines with four knots at 5, 50, 200 and 305 DIM and a function of THI. Mixed model equations were solved using an iteration on data program with a preconditioned conjugate gradient algorithm. Preconditioners used were diagonal (D), block diagonal due to traits (BT) and block diagonal due to traits and correlated effects (BTCORR). One run included BT with a 'diagonalized' model in which the random effects were reparameterized for diagonal (co)variance matrices among traits (BTDIAG). Memory requirements were 8.7 Gb for D, 10.4 Gb for BT and BTDIAG, and 24.3 Gb for BTCORR. Computing times (rounds) were 14 days (952) for D, 10.7 days (706) for BT, 7.7 days (494) for BTDIAG and 4.6 days (289) for BTCORR. The convergence pattern was strongly influenced by the choice of fixed effects. When sufficient memory is available, the option BTCORR is the fastest and simplest to implement; the next efficient method, BTDIAG, requires additional steps for diagonalization and back-diagonalization.
© 2009 Blackwell Verlag GmbH. MenosABSTRACT.
Data included 90 242 799 test day records from first, second and third parities of 5 402 484 Holstein cows and 9 326 754 animals in the pedigree. Additionally, daily temperature humidity indexes (THI) from 202 weather stations were available. The fixed effects included herd test day, age at calving, milking frequency and days in milk classes (DIM). Random effects were additive genetic, permanent environment and herd-year and were fit as random regressions. Covariates included linear splines with four knots at 5, 50, 200 and 305 DIM and a function of THI. Mixed model equations were solved using an iteration on data program with a preconditioned conjugate gradient algorithm. Preconditioners used were diagonal (D), block diagonal due to traits (BT) and block diagonal due to traits and correlated effects (BTCORR). One run included BT with a 'diagonalized' model in which the random effects were reparameterized for diagonal (co)variance matrices among traits (BTDIAG). Memory requirements were 8.7 Gb for D, 10.4 Gb for BT and BTDIAG, and 24.3 Gb for BTCORR. Computing times (rounds) were 14 days (952) for D, 10.7 days (706) for BT, 7.7 days (494) for BTDIAG and 4.6 days (289) for BTCORR. The convergence pattern was strongly influenced by the choice of fixed effects. When sufficient memory is available, the option BTCORR is the fastest and simplest to implement; the next efficient method, BTDIAG, requires additional steps for diagonalization and back-diagonalization.
© 2... Presentar Todo |
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Thesagro : |
GANADERÍA; GANADO DE LECHE. |
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Asunto categoría : |
L01 Ganadería |
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Marc : |
LEADER 02234naa a2200205 a 4500
001 1012846
005 2019-10-09
008 2010 bl uuuu u00u1 u #d
022 $a0931-2668
024 7 $a10.1111/j.1439-0388.2009.00842.x$2DOI
100 1 $aAGUILAR, I.
245 $aComputing options for multiple-trait test-day random regression models while accounting for heat tolerance.$h[electronic resource]
260 $c2010
500 $aArticle history: Received: 24 December 2008 / Accepted: 08 September 2009.
520 $aABSTRACT. Data included 90 242 799 test day records from first, second and third parities of 5 402 484 Holstein cows and 9 326 754 animals in the pedigree. Additionally, daily temperature humidity indexes (THI) from 202 weather stations were available. The fixed effects included herd test day, age at calving, milking frequency and days in milk classes (DIM). Random effects were additive genetic, permanent environment and herd-year and were fit as random regressions. Covariates included linear splines with four knots at 5, 50, 200 and 305 DIM and a function of THI. Mixed model equations were solved using an iteration on data program with a preconditioned conjugate gradient algorithm. Preconditioners used were diagonal (D), block diagonal due to traits (BT) and block diagonal due to traits and correlated effects (BTCORR). One run included BT with a 'diagonalized' model in which the random effects were reparameterized for diagonal (co)variance matrices among traits (BTDIAG). Memory requirements were 8.7 Gb for D, 10.4 Gb for BT and BTDIAG, and 24.3 Gb for BTCORR. Computing times (rounds) were 14 days (952) for D, 10.7 days (706) for BT, 7.7 days (494) for BTDIAG and 4.6 days (289) for BTCORR. The convergence pattern was strongly influenced by the choice of fixed effects. When sufficient memory is available, the option BTCORR is the fastest and simplest to implement; the next efficient method, BTDIAG, requires additional steps for diagonalization and back-diagonalization. © 2009 Blackwell Verlag GmbH.
650 $aGANADERÍA
650 $aGANADO DE LECHE
700 1 $aTSURUTA, S.
700 1 $aMISZTAL, I.
773 $tJournal of Animal Breeding and Genetics, 2010$gv.127, no.3, p.235-241.
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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
01/11/2021 |
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Actualizado : |
01/11/2021 |
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Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
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Autor : |
FERREIRA, V.; GONZÁLEZ-ARCOS, M.; PIANZZOLA, M.J.; COLL, N.S.; SIRI, M.I.; VALLS, M. |
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Afiliación : |
VIRGINIA FERREIRA, Área Microbiología, Departamento de Biociencias (DEPBIO), Facultad de Química, Universidad de la República, Montevideo, Uruguay; MATIAS GONZÁLEZ-ARCOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARÍA JULIA PIANZZOLA, Área Microbiología, Departamento de Biociencias (DEPBIO), Facultad de Química, Universidad de la República, Montevideo, Uruguay; NÚRIA S. COLL, Centre for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB), Bellaterra, Catalonia, Spain; MARÍA INÉS SIRI, Área Microbiología, Departamento de Biociencias (DEPBIO), Facultad de Química, Universidad de la República, Montevideo, Uruguay; MARC VALLS, Centre for Research in Agricultural Genomics (CSIC-IRTA-UAB-UB), Bellaterra, Catalonia, Spain; Department of Genetics, University of Barcelona, Bellaterra, Catalonia, Spain. |
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Título : |
Molecular detection of Ralstonia solanacearum to facilitate breeding for resistance to bacterial wilt in potato. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
In: Dobnik D., Gruden K., Ram?ak ?., Coll A. (eds). Solanum tuberosum. Methods in Molecular Biology, 2021, vol 2354. Humana, New York, NY. doi: https://doi.org/10.1007/978-1-0716-1609-3_18 |
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Serie : |
eBook Packages Springer Protocols, (Methods in Molecular Biology, volume 2354). |
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ISBN : |
978-1-0716-1608-6 (print) / 978-1-0716-1609-3 (e-book) |
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ISSN : |
1064-3745 (print) / 1940-6029 (electronic) |
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DOI : |
10.1007/978-1-0716-1609-3_18 |
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Idioma : |
Inglés |
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Notas : |
Article history: First Online 27 August 2021. |
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Contenido : |
ABSTRACT. - Potato bacterial wilt is caused by the devastating bacterial pathogen Ralstonia solanacearum. Quantitative resistance to this disease has been and is currently introgressed from a number of wild relatives into cultivated varieties through laborious breeding programs. Here, we present two methods that we have developed to facilitate the screening for resistance to bacterial wilt in potato. The first one uses R. solanacearum reporter strains constitutively expressing the luxCDABE operon or the green fluorescent protein (gfp) to follow pathogen colonization in potato germplasm. Luminescent strains are used for nondestructive live imaging, while fluorescent ones enable precise pathogen visualization inside the plant tissues through confocal microscopy. The second method is a BIO-multiplex-PCR assay that is useful for sensitive and specific detection of viable R. solanacearum (IIB-1) cells in latently infected potato plants. This BIO-multiplex-PCR assay can specifically detect IIB-1 sequevar strains as well as strains belonging to all four R. solanacearum phylotypes and is sensitive enough to detect without DNA extraction ten bacterial cells per mL in complex samples. The described methods allow the detection of latent infections in roots and stems of asymptomatic plants and were shown to be efficient tools to assist potato breeding programs. © 2021, Springer Science+Business Media, LLC, part of Springer Nature. |
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Palabras claves : |
Bacterial wilt; Disease resistance; Plant breeding; Potato brown rot; Ralstonia solanacearum; Solanum tuberosum. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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Marc : |
LEADER 02607naa a2200301 a 4500
001 1062509
005 2021-11-01
008 2021 bl uuuu u00u1 u #d
022 $a1064-3745 (print) / 1940-6029 (electronic)
024 7 $a10.1007/978-1-0716-1609-3_18$2DOI
100 1 $aFERREIRA, V.
245 $aMolecular detection of Ralstonia solanacearum to facilitate breeding for resistance to bacterial wilt in potato.$h[electronic resource]
260 $c2021
490 $aeBook Packages Springer Protocols, (Methods in Molecular Biology, volume 2354).
500 $aArticle history: First Online 27 August 2021.
520 $aABSTRACT. - Potato bacterial wilt is caused by the devastating bacterial pathogen Ralstonia solanacearum. Quantitative resistance to this disease has been and is currently introgressed from a number of wild relatives into cultivated varieties through laborious breeding programs. Here, we present two methods that we have developed to facilitate the screening for resistance to bacterial wilt in potato. The first one uses R. solanacearum reporter strains constitutively expressing the luxCDABE operon or the green fluorescent protein (gfp) to follow pathogen colonization in potato germplasm. Luminescent strains are used for nondestructive live imaging, while fluorescent ones enable precise pathogen visualization inside the plant tissues through confocal microscopy. The second method is a BIO-multiplex-PCR assay that is useful for sensitive and specific detection of viable R. solanacearum (IIB-1) cells in latently infected potato plants. This BIO-multiplex-PCR assay can specifically detect IIB-1 sequevar strains as well as strains belonging to all four R. solanacearum phylotypes and is sensitive enough to detect without DNA extraction ten bacterial cells per mL in complex samples. The described methods allow the detection of latent infections in roots and stems of asymptomatic plants and were shown to be efficient tools to assist potato breeding programs. © 2021, Springer Science+Business Media, LLC, part of Springer Nature.
653 $aBacterial wilt
653 $aDisease resistance
653 $aPlant breeding
653 $aPotato brown rot
653 $aRalstonia solanacearum
653 $aSolanum tuberosum
700 1 $aGONZÁLEZ-ARCOS, M.
700 1 $aPIANZZOLA, M.J.
700 1 $aCOLL, N.S.
700 1 $aSIRI, M.I.
700 1 $aVALLS, M.
773 $tIn: Dobnik D., Gruden K., Ram?ak ?., Coll A. (eds). Solanum tuberosum. Methods in Molecular Biology, 2021, vol 2354. Humana, New York, NY. doi: https://doi.org/10.1007/978-1-0716-1609-3_18
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