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Biblioteca (s) : |
INIA La Estanzuela. |
Fecha : |
04/05/2021 |
Actualizado : |
04/05/2021 |
Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
Autor : |
JARDON, M.; ALVAREZ PRADO, S.; SEVERINI, A.D.; FERNÁNDEZ LONG, M.E.; CRESPO, A.O.; CASTRO, M.; QUINCKE, M.; KAVANOVÁ, M.; SCHOLZ DRODOWSKI, R.; CHÁVEZ SANABRIA, P.; PEREZ-GIANMARCO, T.; ALFARO, C.; CASTILLO, D.; MATUS, I.; GÓMEZ, D; SERRAGO, R.; GÓNZALEZ, F.G.; MIRALLES, D.J. |
Afiliación : |
Universidad de Buenos Aires, Facultad de Agronomía, Argentina.; Universidad de Buenos Aires, Facultad de Agronomía, Argentina.; INTA Instituto Nacional de Tecnología Agropecuaria, Argentina.; Universidad de Buenos Aires, Facultad de Agronomía, Argentina.; Universidad de Buenos Aires, Facultad de Agronomía, Argentina.; MARINA CASTRO DERENYI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MONIKA KAVANOVÁ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IPTA Capitán Miranda, Paraguay.; IPTA Capitán Miranda, Paraguay.; CONICET.; INIA Rayentué, Chile.; INIA Quilamapu, Chile.; INIA Quilamapu, Chile.; INTA Instituto Nacional de Tecnología Agropecuaria, Argentina.; Universidad de Buenos Aires, Facultad de Agronomía, Argentina.; INTA Instituto Nacional de Tecnología Agropecuaria, Argentina.; INTA Instituto Nacional de Tecnología Agropecuaria, Argentina. |
Título : |
CRONOTRIGO 2.0: nueva versión del modelo de predicción fenológica para el cultivo de trigo. |
Fecha de publicación : |
2021 |
Fuente / Imprenta : |
In: Revista Técnica de la Asociación Argentina de Productores en Siembra Directa, Abril 2021, Rosario: AAPRESID. |
Páginas : |
p. 53-60. |
ISSN : |
1850-0633 |
Idioma : |
Español |
Notas : |
Se incorporaron cambios respecto a la versión original en cuanto al alcance y la precisión del modelo. |
Contenido : |
CRONOTRIGO© 2.0 se inició en el marco de un proyecto financiado por PROCISUR en el que están involucrados grupos de investigación de Argentina, Paraguay,Uruguay y Chile. El modelo CRONOTRIGO© 2.0 ya puede utilizarse en Argentina en el dominio http://cronotrigo.agro.uba.ar/ y para este año (2021) se expandirá al resto de los países involucrados en el proyecto PROCISUR (coordinado por la Dra. Fernanda G. González, EEA INTA Pergamino). |
Palabras claves : |
ESTADIOS FENOLÓGICOS; PREDICCIÓN; VARIEDADES. |
Thesagro : |
TRIGO. |
Asunto categoría : |
F01 Cultivo |
Marc : |
LEADER 01696nam a2200397 a 4500 001 1062006 005 2021-05-04 008 2021 bl uuuu u01u1 u #d 022 $a1850-0633 100 1 $aJARDON, M. 245 $aCRONOTRIGO 2.0$bnueva versión del modelo de predicción fenológica para el cultivo de trigo.$h[electronic resource] 260 $aIn: Revista Técnica de la Asociación Argentina de Productores en Siembra Directa, Abril 2021, Rosario: AAPRESID.$c2021 300 $ap. 53-60. 500 $aSe incorporaron cambios respecto a la versión original en cuanto al alcance y la precisión del modelo. 520 $aCRONOTRIGO© 2.0 se inició en el marco de un proyecto financiado por PROCISUR en el que están involucrados grupos de investigación de Argentina, Paraguay,Uruguay y Chile. El modelo CRONOTRIGO© 2.0 ya puede utilizarse en Argentina en el dominio http://cronotrigo.agro.uba.ar/ y para este año (2021) se expandirá al resto de los países involucrados en el proyecto PROCISUR (coordinado por la Dra. Fernanda G. González, EEA INTA Pergamino). 650 $aTRIGO 653 $aESTADIOS FENOLÓGICOS 653 $aPREDICCIÓN 653 $aVARIEDADES 700 1 $aALVAREZ PRADO, S. 700 1 $aSEVERINI, A.D. 700 1 $aFERNÁNDEZ LONG, M.E. 700 1 $aCRESPO, A.O. 700 1 $aCASTRO, M. 700 1 $aQUINCKE, M. 700 1 $aKAVANOVÁ, M. 700 1 $aSCHOLZ DRODOWSKI, R. 700 1 $aCHÁVEZ SANABRIA, P. 700 1 $aPEREZ-GIANMARCO, T. 700 1 $aALFARO, C. 700 1 $aCASTILLO, D. 700 1 $aMATUS, I. 700 1 $aGÓMEZ, D 700 1 $aSERRAGO, R. 700 1 $aGÓNZALEZ, F.G. 700 1 $aMIRALLES, D.J.
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INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
13/11/2015 |
Actualizado : |
15/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
FRAGOMENI, B.O.; LOURENCO, D.A.L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; LAWLOR, T.J.; MIZTAL, I. |
Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes. |
Fecha de publicación : |
2015 |
Fuente / Imprenta : |
Journal of Dairy Science, 2015, v.98, no.6, p.4090-4094. OPEN ACCESS. |
ISSN : |
0022-0302 |
DOI : |
10.3168/jds.2014-9125 |
Idioma : |
Inglés |
Notas : |
Article history: Received November 18, 2014 / Accepted March 13, 2015 / Published online: April 8, 2015. |
Contenido : |
ABSTRACT.
The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomic BLUP (ssGBLUP) when the inverse of the genomic relationship matrix (G) is derived by the "algorithm for proven and young animals" (APY). This algorithm implements genomic recursions on a subset of "proven" animals. Only a relationship matrix for animals treated as "proven" needs to be inverted, and the extra costs of adding animals treated as "young" are linear. Analyses involved 10,102,702 final scores on 6,930,618 Holstein cows. Final score, which is a composite of type traits, is popular trait in the United States and was easily available for this study. A total of 100,000 animals with genotypes were used in the analyses and included 23,000 sires (16,000 with >5 progeny), 27,000 cows, and 50,000 young animals. Genomic EBV (GEBV) were calculated with a regular inverse of G, and with the G inverse approximated by APY. Animals in the proven subset included only sires (23,000), sires + cows (50,000), only cows (27,000), or sires with >5 progeny (16,000). The correlations of GEBV with APY and regular GEBV for young genotyped animals were 0.994, 0.995, 0.992, and 0.992, respectively Later, animals in the proven subset were randomly sampled from all genotyped animals in sets of 2,000, 5,000, 10,000, 15,000, and 20,000; each sample was replicated 4 times. Respective correlations were 0.97 (5,000 sample), 0.98 (10,000 sample), and 0.99 (20,000 sample), with minimal difference between samples of the same size. Genomic EBV with APY were accurate when the number of animals used in the subset is between 10,000 and 20,000, with little difference between the ways of creating the subset. Due to the approximately linear cost of APY, ssGBLUP with APY could support any number of genotyped animals without affecting accuracy.
© 2015 American Dairy Science Association. MenosABSTRACT.
The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomic BLUP (ssGBLUP) when the inverse of the genomic relationship matrix (G) is derived by the "algorithm for proven and young animals" (APY). This algorithm implements genomic recursions on a subset of "proven" animals. Only a relationship matrix for animals treated as "proven" needs to be inverted, and the extra costs of adding animals treated as "young" are linear. Analyses involved 10,102,702 final scores on 6,930,618 Holstein cows. Final score, which is a composite of type traits, is popular trait in the United States and was easily available for this study. A total of 100,000 animals with genotypes were used in the analyses and included 23,000 sires (16,000 with >5 progeny), 27,000 cows, and 50,000 young animals. Genomic EBV (GEBV) were calculated with a regular inverse of G, and with the G inverse approximated by APY. Animals in the proven subset included only sires (23,000), sires + cows (50,000), only cows (27,000), or sires with >5 progeny (16,000). The correlations of GEBV with APY and regular GEBV for young genotyped animals were 0.994, 0.995, 0.992, and 0.992, respectively Later, animals in the proven subset were randomly sampled from all genotyped animals in sets of 2,000, 5,000, 10,000, 15,000, and 20,000; each sample was replicated 4 times. Respective correlations were 0.97 (5,000 sample), 0.98 (10,000 sample), and 0.99 (20,000 sample), with minimal differe... Presentar Todo |
Palabras claves : |
ANIMALIA; GENOMIC RECURSION; GENOMIC SELECTION; SINGLE-STEP GENOMIC BLUP. |
Thesagro : |
BLUP; MEJORAMIENTO GENETICO ANIMAL. |
Asunto categoría : |
L10 Genética y mejoramiento animal |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5183/1/Aguilar-I.-2015.-Jr.DairyScience-v.984-p.4090-4094.pdf
https://www.journalofdairyscience.org/article/S0022-0302(15)00238-6/pdf
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Marc : |
LEADER 02932naa a2200313 a 4500 001 1053873 005 2019-10-15 008 2015 bl uuuu u00u1 u #d 022 $a0022-0302 024 7 $a10.3168/jds.2014-9125$2DOI 100 1 $aFRAGOMENI, B.O. 245 $aHot topic$bUse of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes.$h[electronic resource] 260 $c2015 500 $aArticle history: Received November 18, 2014 / Accepted March 13, 2015 / Published online: April 8, 2015. 520 $aABSTRACT. The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomic BLUP (ssGBLUP) when the inverse of the genomic relationship matrix (G) is derived by the "algorithm for proven and young animals" (APY). This algorithm implements genomic recursions on a subset of "proven" animals. Only a relationship matrix for animals treated as "proven" needs to be inverted, and the extra costs of adding animals treated as "young" are linear. Analyses involved 10,102,702 final scores on 6,930,618 Holstein cows. Final score, which is a composite of type traits, is popular trait in the United States and was easily available for this study. A total of 100,000 animals with genotypes were used in the analyses and included 23,000 sires (16,000 with >5 progeny), 27,000 cows, and 50,000 young animals. Genomic EBV (GEBV) were calculated with a regular inverse of G, and with the G inverse approximated by APY. Animals in the proven subset included only sires (23,000), sires + cows (50,000), only cows (27,000), or sires with >5 progeny (16,000). The correlations of GEBV with APY and regular GEBV for young genotyped animals were 0.994, 0.995, 0.992, and 0.992, respectively Later, animals in the proven subset were randomly sampled from all genotyped animals in sets of 2,000, 5,000, 10,000, 15,000, and 20,000; each sample was replicated 4 times. Respective correlations were 0.97 (5,000 sample), 0.98 (10,000 sample), and 0.99 (20,000 sample), with minimal difference between samples of the same size. Genomic EBV with APY were accurate when the number of animals used in the subset is between 10,000 and 20,000, with little difference between the ways of creating the subset. Due to the approximately linear cost of APY, ssGBLUP with APY could support any number of genotyped animals without affecting accuracy. © 2015 American Dairy Science Association. 650 $aBLUP 650 $aMEJORAMIENTO GENETICO ANIMAL 653 $aANIMALIA 653 $aGENOMIC RECURSION 653 $aGENOMIC SELECTION 653 $aSINGLE-STEP GENOMIC BLUP 700 1 $aLOURENCO, D.A.L. 700 1 $aTSURUTA, S. 700 1 $aMASUDA, Y. 700 1 $aAGUILAR, I. 700 1 $aLEGARRA, A. 700 1 $aLAWLOR, T.J. 700 1 $aMIZTAL, I. 773 $tJournal of Dairy Science, 2015$gv.98, no.6, p.4090-4094. OPEN ACCESS.
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