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Registro completo
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Biblioteca (s) : |
INIA Tacuarembó; INIA Treinta y Tres. |
Fecha : |
24/10/2019 |
Actualizado : |
20/01/2020 |
Tipo de producción científica : |
Documentos |
Autor : |
BALMELLI, G.; RESQUÍN, F.; SIMETO, S.; GONZÁLEZ, M.; SCOZ, R.; BRITO, G.; ROSSI, C.; MARANGES, F. |
Afiliación : |
GUSTAVO DANIEL BALMELLI HERNANDEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE FERNANDO RESQUIN PEREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SOFIA SIMETO FERRARI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MILENA GONZÁLEZ CHAVEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ROBERTO JAVIER SCOZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUSTAVO WALTER BRITO DIAZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS ALBERTO ROSSI RODRIGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARÍA FLORENCIA MARANGES BORDABEHERE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Montes con INIA Sombra: protección del ganado y diversificación productiva. |
Fecha de publicación : |
2019 |
Fuente / Imprenta : |
En: DÍA DE CAMPO, 2019, UNIDAD EXPERIMENTAL PALO A PIQUE (UEPP), TREINTA Y TRES, UY. |
Páginas : |
p. 15. |
Idioma : |
Español |
Contenido : |
Los montes de protección para el ganado mejoran el bienestar de los animales y disminuyen el impacto negativo de eventos climáticos extremos. Los árboles reducen el estrés térmico en verano y actúan como abrigo, principalmente paran ovinos en invierno-primavera, reduciendo el riesgo de mortalidad por temporales durante la parición y post-esquila. Se estima que en el país existen más
de 40.000 hectáreas de pequeños montes en establecimientos agropecuarios, denominados “cortinas”, granjas o islas, plantados con el doble objetivo de brindar sombra y abrigo al ganado y obtener madera con varios fines. La mayor parte de estos montes fueron plantados con eucaliptos colorados (nombre común de algunas especies de Eucalyptus dado por la coloración rojiza de su madera), principalmente con Eucalyptus camaldulensis y Eucalyptus tereticornis |
Thesagro : |
BIENESTAR ANIMAL; EUCALIPTUS; SOMBRA. |
Asunto categoría : |
A50 Investigación agraria |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/13575/1/DC-UEPP-octubre-2019-p.15-17.pdf
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Marc : |
LEADER 01548nam a2200241 a 4500 001 1060649 005 2020-01-20 008 2019 bl uuuu u0uu1 u #d 100 1 $aBALMELLI, G. 245 $aMontes con INIA Sombra$bprotección del ganado y diversificación productiva.$h[electronic resource] 260 $aEn: DÍA DE CAMPO, 2019, UNIDAD EXPERIMENTAL PALO A PIQUE (UEPP), TREINTA Y TRES, UY.$c2019 300 $ap. 15. 520 $aLos montes de protección para el ganado mejoran el bienestar de los animales y disminuyen el impacto negativo de eventos climáticos extremos. Los árboles reducen el estrés térmico en verano y actúan como abrigo, principalmente paran ovinos en invierno-primavera, reduciendo el riesgo de mortalidad por temporales durante la parición y post-esquila. Se estima que en el país existen más de 40.000 hectáreas de pequeños montes en establecimientos agropecuarios, denominados “cortinas”, granjas o islas, plantados con el doble objetivo de brindar sombra y abrigo al ganado y obtener madera con varios fines. La mayor parte de estos montes fueron plantados con eucaliptos colorados (nombre común de algunas especies de Eucalyptus dado por la coloración rojiza de su madera), principalmente con Eucalyptus camaldulensis y Eucalyptus tereticornis 650 $aBIENESTAR ANIMAL 650 $aEUCALIPTUS 650 $aSOMBRA 700 1 $aRESQUÍN, F. 700 1 $aSIMETO, S. 700 1 $aGONZÁLEZ, M. 700 1 $aSCOZ, R. 700 1 $aBRITO, G. 700 1 $aROSSI, C. 700 1 $aMARANGES, F.
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INIA Tacuarembó (TBO) |
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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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