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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó. |
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Fecha : |
21/02/2014 |
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Actualizado : |
05/11/2020 |
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Autor : |
Correa, A. ; Monteiro, C. ; Aramendi, A. |
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Título : |
Evaluación de la micoflora en semilla de soja |
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Fecha de publicación : |
1984 |
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Fuente / Imprenta : |
Montevideo: Facultad de Agronomía, 1984. |
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Páginas : |
p63 |
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Idioma : |
Español |
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Thesagro : |
FLORA MICROBIANA; HONGOS; PATOLOGIA DE LA SEMILLA; SOJA; TRATAMIENTO DE SEMILLAS. |
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Asunto categoría : |
--
A50 Investigación agraria |
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Marc : |
LEADER 00526naa a2200205 a 4500
001 1004973
005 2020-11-05
008 1984 bl uuuu u00u1 u #d
100 1 $aCORREA, A.
245 $aEvaluación de la micoflora en semilla de soja
260 $c1984
300 $ap63
650 $aFLORA MICROBIANA
650 $aHONGOS
650 $aPATOLOGIA DE LA SEMILLA
650 $aSOJA
650 $aTRATAMIENTO DE SEMILLAS
700 1 $aMONTEIRO, C.
700 1 $aARAMENDI, A.
773 $tMontevideo: Facultad de Agronomía, 1984.
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Registro original : |
INIA Las Brujas (LB) |
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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
12/11/2015 |
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Actualizado : |
02/12/2015 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
FRAGOMENI, B.O.; LOURENCO, D.A.L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; MISZTAL, I. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Use of genomic recursions and algorithm for proven and young animals for single-step genomic BLUP analyses - a simulation study. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Journal of Animal Breeding and Genetics, 2015, v.132, no.5, p. 340-345. |
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ISSN : |
0931-2668 |
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DOI : |
10.1111/jbg.12161 |
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Idioma : |
Inglés |
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Contenido : |
ABSTRACT.
The purpose of this study was to examine accuracy of genomic selection via single-step genomic BLUP (ssGBLUP) when the direct inverse of the genomic relationship matrix (G) is replaced by an approximation of G1 based on recursions for young genotyped animals conditioned on a subset of proven animals, termed algorithm for proven and young animals
(APY). With the efficient implementation, this algorithm has a cubic cost with proven animals and linear with young animals. Ten duplicate data sets mimicking a dairy cattle population were simulated. In a first scenario, genomic information for 20k genotyped bulls, divided in 7k proven and 13k young bulls, was generated for each replicate. In a second scenario, 5k genotyped cows with phenotypes were included in the analysis as young animals. Accuracies (average for the 10 replicates) in regular EBV were 0.72 and 0.34 for proven and young animals, respectively.
When genomic information was included, they increased to 0.75 and 0.50. No differences between genomic EBV (GEBV) obtained with the regular G1 and the approximated G1 via the recursive method were observed. In the second scenario, accuracies in GEBV (0.76, 0.51 and 0.59 for proven bulls, young males and young females, respectively)
were also higher than those in EBV (0.72, 0.35 and 0.49). Again, no differences between GEBV with regular G1 and with recursions were observed. With the recursive algorithm, the number of iterations to achieve convergence was reduced from 227 to 206 in the first scenario and from 232 to 209 in the second scenario. Cows can be treated as young animals in APY without reducing the accuracy. The proposed algorithm can be implemented to reduce computing costs and to overcome current limitations on the number of genotyped animals in the ssGBLUP method.
© 2015 Blackwell Verlag GmbH MenosABSTRACT.
The purpose of this study was to examine accuracy of genomic selection via single-step genomic BLUP (ssGBLUP) when the direct inverse of the genomic relationship matrix (G) is replaced by an approximation of G1 based on recursions for young genotyped animals conditioned on a subset of proven animals, termed algorithm for proven and young animals
(APY). With the efficient implementation, this algorithm has a cubic cost with proven animals and linear with young animals. Ten duplicate data sets mimicking a dairy cattle population were simulated. In a first scenario, genomic information for 20k genotyped bulls, divided in 7k proven and 13k young bulls, was generated for each replicate. In a second scenario, 5k genotyped cows with phenotypes were included in the analysis as young animals. Accuracies (average for the 10 replicates) in regular EBV were 0.72 and 0.34 for proven and young animals, respectively.
When genomic information was included, they increased to 0.75 and 0.50. No differences between genomic EBV (GEBV) obtained with the regular G1 and the approximated G1 via the recursive method were observed. In the second scenario, accuracies in GEBV (0.76, 0.51 and 0.59 for proven bulls, young males and young females, respectively)
were also higher than those in EBV (0.72, 0.35 and 0.49). Again, no differences between GEBV with regular G1 and with recursions were observed. With the recursive algorithm, the number of iterations to achieve convergence was reduced from... Presentar Todo |
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Palabras claves : |
GENETIC EVALUATION; GENOMIC SELECTION; SINGLE-STEP METHOD. |
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Thesagro : |
MEJORAMIENTO GENETICO ANIMAL. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 02627naa a2200253 a 4500
001 1053862
005 2015-12-02
008 2015 bl uuuu u00u1 u #d
022 $a0931-2668
024 7 $a10.1111/jbg.12161$2DOI
100 1 $aFRAGOMENI, B.O.
245 $aUse of genomic recursions and algorithm for proven and young animals for single-step genomic BLUP analyses - a simulation study.
260 $c2015
520 $aABSTRACT. The purpose of this study was to examine accuracy of genomic selection via single-step genomic BLUP (ssGBLUP) when the direct inverse of the genomic relationship matrix (G) is replaced by an approximation of G1 based on recursions for young genotyped animals conditioned on a subset of proven animals, termed algorithm for proven and young animals (APY). With the efficient implementation, this algorithm has a cubic cost with proven animals and linear with young animals. Ten duplicate data sets mimicking a dairy cattle population were simulated. In a first scenario, genomic information for 20k genotyped bulls, divided in 7k proven and 13k young bulls, was generated for each replicate. In a second scenario, 5k genotyped cows with phenotypes were included in the analysis as young animals. Accuracies (average for the 10 replicates) in regular EBV were 0.72 and 0.34 for proven and young animals, respectively. When genomic information was included, they increased to 0.75 and 0.50. No differences between genomic EBV (GEBV) obtained with the regular G1 and the approximated G1 via the recursive method were observed. In the second scenario, accuracies in GEBV (0.76, 0.51 and 0.59 for proven bulls, young males and young females, respectively) were also higher than those in EBV (0.72, 0.35 and 0.49). Again, no differences between GEBV with regular G1 and with recursions were observed. With the recursive algorithm, the number of iterations to achieve convergence was reduced from 227 to 206 in the first scenario and from 232 to 209 in the second scenario. Cows can be treated as young animals in APY without reducing the accuracy. The proposed algorithm can be implemented to reduce computing costs and to overcome current limitations on the number of genotyped animals in the ssGBLUP method. © 2015 Blackwell Verlag GmbH
650 $aMEJORAMIENTO GENETICO ANIMAL
653 $aGENETIC EVALUATION
653 $aGENOMIC SELECTION
653 $aSINGLE-STEP METHOD
700 1 $aLOURENCO, D.A.L.
700 1 $aTSURUTA, S.
700 1 $aMASUDA, Y.
700 1 $aAGUILAR, I.
700 1 $aMISZTAL, I.
773 $tJournal of Animal Breeding and Genetics, 2015$gv.132, no.5, p. 340-345.
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