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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha : |
03/01/2019 |
Actualizado : |
07/06/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
LEWIS ,C.M.; PERSOONS, A.; BEBBER, D.P.; KIGATHI, R.N.; MAINTZ, J.; FINDLAY, K.; BUENO-SANCHO, V.; CORREDOR-MORENO, P.; HARRINGTON, S.A.; KANGARA, N.; BERLIN, A.; GARCIA, R.; GERMAN, S.; HANZALOVÁ, A.; HODSON, D.P.; HOVMØLLER, M.S.; HUERTA-ESPINO, J.; IMTIAZ, M.; MIRZA, J.I.; JUSTESEN, A.F.; NIKS, R.E.; OMRANI, A.; PATPOUR, M.; PRETORIUS ,Z.A.; ROOHPARVAR, R.; SELA, H.; SINGH, R.P.; STEFFENSON ,B.; VISSER, B.; FENWICK, P.M.; THOMAS, J.; WULFF, B.B.H.; SAUNDERS, D.G.O. |
Afiliación : |
John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; University of Exeter, Exeter, EX4 4QD UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; ohn Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala, 750 07 Sweden; RICHARD ANSELMO GARCIA USUCA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SILVIA ELISA GERMAN FAEDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Crop Research Institute, Ruzyn?, 161 06 Praha 6 Czech Republic.; International Maize and Wheat Improvement Center (CIMMYT), 5689 Addis Ababa, Ethiopia.; Aarhus University, Flakkebjerg, 4200 Denmark.; Campo Experimental Valle de México INIFAP, Texcoco, C. P. 56237 Mexico.; CIMMYT-Pakistan, Islamabad, 44000 Pakistan.; Crop Disease Research Program, National Agriculture Research Center, Islamabad, 44000 Pakistan.; Aarhus University, Flakkebjerg, 4200 Denmark.; Wageningen University, Wageningen, 6700 The Netherlands; Faculty of Agriculture, Department of Plant Breeding and Biotechnology, University of Tabriz, Tabriz, 5166616471 Iran.; Aarhus University, Flakkebjerg, 4200 Denmark.; University of the Free State, Bloemfontein, 9301 South Africa.; Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), 4119 Karaj, Iran.; Tel Aviv University, Tel Aviv, 69978 Israel.; CIMMYT, Apdo. Postal 6-641, D. F. México, 06600 Mexico.; University of Minnesota, St. Paul, 55455 MN USA.; University of the Free State, Bloemfontein, 9301 South Africa.; Limagrain UK Ltd, Woolpit, IP30 9UP UK.; National Institute of Agricultural Botany, Cambridge, CB3 0LE UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK.; John Innes Centre, Norwich Research Park, Norwich, NR4 7UH UK. |
Título : |
Potential for re-emergence of wheat stem rust in the United Kingdom. |
Fecha de publicación : |
2018 |
Fuente / Imprenta : |
Veterinary Pathology [Vet Pathol], 2018 Sep 24, p. 300985818798117.OPEN ACCESS. |
DOI : |
10.1038/s42003-018-0013-y |
Idioma : |
Inglés |
Notas : |
Article history: Date Created: 20181002 //Latest Revision: 20181003. |
Contenido : |
Wheat stem rust, a devastating disease of wheat and barley caused by the fungal pathogen
Puccinia graminis f. sp. tritici, was largely eradicated in Western Europe during the mid-to-late
twentieth century. However, isolated outbreaks have occurred in recent years. Here we
investigate whether a lack of resistance in modern European varieties, increased presence of its
alternate host barberry and changes in climatic conditions could be facilitating its resurgence.
We report the first wheat stem rust occurrence in the United Kingdom in nearly 60 years,
with only 20% of UK wheat varieties resistant to this strain. Climate changes over the past 25
years also suggest increasingly conducive conditions for infection. Furthermore, we document
the first occurrence in decades of P. graminis on barberry in the UK . Our data illustrate that
wheat stem rust does occur in the UK and, when climatic conditions are conducive, could
severely harm wheat and barley production. |
Thesagro : |
TRIGO. |
Asunto categoría : |
-- |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12241/1/Commun-Biol.-2018.pdf
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Marc : |
LEADER 02459naa a2200541 a 4500 001 1059410 005 2019-06-07 008 2018 bl uuuu u00u1 u #d 024 7 $a10.1038/s42003-018-0013-y$2DOI 100 1 $aLEWIS ,C.M. 245 $aPotential for re-emergence of wheat stem rust in the United Kingdom.$h[electronic resource] 260 $c2018 500 $aArticle history: Date Created: 20181002 //Latest Revision: 20181003. 520 $aWheat stem rust, a devastating disease of wheat and barley caused by the fungal pathogen Puccinia graminis f. sp. tritici, was largely eradicated in Western Europe during the mid-to-late twentieth century. However, isolated outbreaks have occurred in recent years. Here we investigate whether a lack of resistance in modern European varieties, increased presence of its alternate host barberry and changes in climatic conditions could be facilitating its resurgence. We report the first wheat stem rust occurrence in the United Kingdom in nearly 60 years, with only 20% of UK wheat varieties resistant to this strain. Climate changes over the past 25 years also suggest increasingly conducive conditions for infection. Furthermore, we document the first occurrence in decades of P. graminis on barberry in the UK . Our data illustrate that wheat stem rust does occur in the UK and, when climatic conditions are conducive, could severely harm wheat and barley production. 650 $aTRIGO 700 1 $aPERSOONS, A. 700 1 $aBEBBER, D.P. 700 1 $aKIGATHI, R.N. 700 1 $aMAINTZ, J. 700 1 $aFINDLAY, K. 700 1 $aBUENO-SANCHO, V. 700 1 $aCORREDOR-MORENO, P. 700 1 $aHARRINGTON, S.A. 700 1 $aKANGARA, N. 700 1 $aBERLIN, A. 700 1 $aGARCIA, R. 700 1 $aGERMAN, S. 700 1 $aHANZALOVÁ, A. 700 1 $aHODSON, D.P. 700 1 $aHOVMØLLER, M.S. 700 1 $aHUERTA-ESPINO, J. 700 1 $aIMTIAZ, M. 700 1 $aMIRZA, J.I. 700 1 $aJUSTESEN, A.F. 700 1 $aNIKS, R.E. 700 1 $aOMRANI, A. 700 1 $aPATPOUR, M. 700 1 $aPRETORIUS ,Z.A. 700 1 $aROOHPARVAR, R. 700 1 $aSELA, H. 700 1 $aSINGH, R.P. 700 1 $aSTEFFENSON ,B. 700 1 $aVISSER, B. 700 1 $aFENWICK, P.M. 700 1 $aTHOMAS, J. 700 1 $aWULFF, B.B.H. 700 1 $aSAUNDERS, D.G.O. 773 $tVeterinary Pathology [Vet Pathol], 2018 Sep 24, p. 300985818798117.OPEN ACCESS.
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INIA La Estanzuela (LE) |
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| Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
09/11/2017 |
Actualizado : |
25/11/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
MASUDA, Y; MISZTAL, I.; LEGARRA, A.; TSURUTA, S.; LOURENCO, D.A.L.; FRAGOMENI, B.O.; AGUILAR, I. |
Afiliación : |
Y. MASUDA, Department of Animal and Dairy Science, University of Georgia; I. MISZTAL, Department of Animal and Dairy Science, University of Georgia; A. LEGARRA, INRA (Institut National de la Recherche Agronomique); S. TSURUTA, Department of Animal and Dairy Science, University of Georgia; D.A.L. LOURENCO, Department of Animal and Dairy Science, University of Georgia; B.O. FRAGOMENI, Department of Animal and Dairy Science, University of Georgia; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient. |
Fecha de publicación : |
2017 |
Fuente / Imprenta : |
Journal of Animal Science, 2017, v. 95(1): 49-52. |
DOI : |
10.2527/jas.2016.0699 |
Idioma : |
Inglés |
Notas : |
Article history: Received: July 05, 2016; Accepted: Aug 16, 2016; Published: February 2, 2017.
This research was partially funded by the United States Department of Agriculture?s National Institute of Food and Agriculture (Agriculture and Food Research Initiative competitive grant 2015-67015-22936). |
Contenido : |
ABSTRACT.
This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (q). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix (A−1) including genotyped animals and their ancestors. The elements of A−1 were rapidly calculated with the Henderson?s rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix?vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of A22 with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations.
Copyright © 2016. American Society of Animal Science. MenosABSTRACT.
This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (q). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix (A−1) including genotyped animals and their ancestors. The elements of A−1 were rapidly calculated with the Henderson?s rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix?vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of A22 with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When t... Presentar Todo |
Palabras claves : |
COMPUTATION; GENOMIC SELECTION; INVERSION; NUMERATOR RELATIONSHIP MATRIX; PRECONDITIONED CONJUGATE GRADIENT; SPARSE MATRIX. |
Asunto categoría : |
-- |
Marc : |
LEADER 02919naa a2200289 a 4500 001 1057743 005 2019-11-25 008 2017 bl uuuu u00u1 u #d 024 7 $a10.2527/jas.2016.0699$2DOI 100 1 $aMASUDA, Y 245 $aTechnical note$bAvoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient.$h[electronic resource] 260 $c2017 500 $aArticle history: Received: July 05, 2016; Accepted: Aug 16, 2016; Published: February 2, 2017. This research was partially funded by the United States Department of Agriculture?s National Institute of Food and Agriculture (Agriculture and Food Research Initiative competitive grant 2015-67015-22936). 520 $aABSTRACT. This paper evaluates an efficient implementation to multiply the inverse of a numerator relationship matrix for genotyped animals () by a vector (q). The computation is required for solving mixed model equations in single-step genomic BLUP (ssGBLUP) with the preconditioned conjugate gradient (PCG). The inverse can be decomposed into sparse matrices that are blocks of the sparse inverse of a numerator relationship matrix (A−1) including genotyped animals and their ancestors. The elements of A−1 were rapidly calculated with the Henderson?s rule and stored as sparse matrices in memory. Implementation of was by a series of sparse matrix?vector multiplications. Diagonal elements of , which were required as preconditioners in PCG, were approximated with a Monte Carlo method using 1,000 samples. The efficient implementation of was compared with explicit inversion of A22 with 3 data sets including about 15,000, 81,000, and 570,000 genotyped animals selected from populations with 213,000, 8.2 million, and 10.7 million pedigree animals, respectively. The explicit inversion required 1.8 GB, 49 GB, and 2,415 GB (estimated) of memory, respectively, and 42 s, 56 min, and 13.5 d (estimated), respectively, for the computations. The efficient implementation required <1 MB, 2.9 GB, and 2.3 GB of memory, respectively, and <1 sec, 3 min, and 5 min, respectively, for setting up. Only <1 sec was required for the multiplication in each PCG iteration for any data sets. When the equations in ssGBLUP are solved with the PCG algorithm, is no longer a limiting factor in the computations. Copyright © 2016. American Society of Animal Science. 653 $aCOMPUTATION 653 $aGENOMIC SELECTION 653 $aINVERSION 653 $aNUMERATOR RELATIONSHIP MATRIX 653 $aPRECONDITIONED CONJUGATE GRADIENT 653 $aSPARSE MATRIX 700 1 $aMISZTAL, I. 700 1 $aLEGARRA, A. 700 1 $aTSURUTA, S. 700 1 $aLOURENCO, D.A.L. 700 1 $aFRAGOMENI, B.O. 700 1 $aAGUILAR, I. 773 $tJournal of Animal Science, 2017$gv. 95(1): 49-52.
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