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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha : |
21/02/2014 |
Actualizado : |
07/03/2019 |
Tipo de producción científica : |
Documentos |
Autor : |
BEMHAJA, M.; BERRETTA, E.J.; PÉREZ GOMAR, E. |
Afiliación : |
MARIA DE LURDES BEMHAJA SARAIVA FERREIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ELBIO JOAQUIN BERRETTA CARVALLO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ENRIQUE PEREZ GOMAR CAPURRO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Productividad de campo natural: pastoreo con terneros año 2009/2010. |
Fecha de publicación : |
2010 |
Fuente / Imprenta : |
In: INIA TACUAREMBÓ. UNIDAD EXPERIMENTAL GLENCOE. JORNADA, 25 MARZO, TACUAREMBÓ, 2010. Después de las lluvias: Desafíos de producción animal y forraje para los próximos meses. Tacuarembó (Uruguay): INIA, 2010. |
Páginas : |
p. 21-23 |
Serie : |
(INIA Serie Actividades de Difusión ; 601) |
Idioma : |
Español |
Contenido : |
La productividad de campo natural del Basalto implica una alta variabilidad entre años, entre estaciones y dentro de estaciones, basada por la composición de las comunidades herbáceas y su respuesta a la disponibilidad de agua en el suelo (Castro, 1980; Berretta, Bemhaja; 1998). La precipitación anual para el año 2008, fue de 872 mm y de 1431 mm para el año 2009 (de Barbieri, com pers), con 51% de precipitación en noviembre y diciembre en el último año. A continuación se presentan algunos de los registros del comportamiento de la pastura y en terneros para el periodo de abril 2009 (destete) a febrero 2010, en el ensayo de largo plazo de campo natural y CN Fertilizado en la Unidad Experimental Glencoe. Se mantuvo el esquema de Sanidad de la Unidad Experimental y se contó con asistencia de la Dra. A. Rodríguez por tema oftalmológico ocurrido en febrero. En setiembre 2009 (SAD, N. 589), se presentaron los datos de pasturas y terneros de abril a agosto 2009, que son completados en esta entrega. |
Palabras claves : |
ANIMAL PRODUCTION. |
Thesagro : |
PASTOREO; SUELO BASALTICO; TERNERO. |
Asunto categoría : |
L01 Ganadería |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/10343/1/SAD-601p21-23.pdf
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Marc : |
LEADER 01789naa a2200217 a 4500 001 1025836 005 2019-03-07 008 2010 bl uuuu u00u1 u #d 100 1 $aBEMHAJA, M. 245 $aProductividad de campo natural$bpastoreo con terneros año 2009/2010. 260 $c2010 300 $ap. 21-23 490 $a(INIA Serie Actividades de Difusión ; 601) 520 $aLa productividad de campo natural del Basalto implica una alta variabilidad entre años, entre estaciones y dentro de estaciones, basada por la composición de las comunidades herbáceas y su respuesta a la disponibilidad de agua en el suelo (Castro, 1980; Berretta, Bemhaja; 1998). La precipitación anual para el año 2008, fue de 872 mm y de 1431 mm para el año 2009 (de Barbieri, com pers), con 51% de precipitación en noviembre y diciembre en el último año. A continuación se presentan algunos de los registros del comportamiento de la pastura y en terneros para el periodo de abril 2009 (destete) a febrero 2010, en el ensayo de largo plazo de campo natural y CN Fertilizado en la Unidad Experimental Glencoe. Se mantuvo el esquema de Sanidad de la Unidad Experimental y se contó con asistencia de la Dra. A. Rodríguez por tema oftalmológico ocurrido en febrero. En setiembre 2009 (SAD, N. 589), se presentaron los datos de pasturas y terneros de abril a agosto 2009, que son completados en esta entrega. 650 $aPASTOREO 650 $aSUELO BASALTICO 650 $aTERNERO 653 $aANIMAL PRODUCTION 700 1 $aBERRETTA, E.J. 700 1 $aPÉREZ GOMAR, E. 773 $tIn: INIA TACUAREMBÓ. UNIDAD EXPERIMENTAL GLENCOE. JORNADA, 25 MARZO, TACUAREMBÓ, 2010. Después de las lluvias: Desafíos de producción animal y forraje para los próximos meses. Tacuarembó (Uruguay): INIA, 2010.
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Registro original : |
INIA Tacuarembó (TBO) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
11/12/2018 |
Actualizado : |
06/02/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
A - 1 |
Autor : |
MOTA, R. R.; LOPES, P. S.; TEMPELMAN, R. J.; SILVA, F. F.; AGUILAR, I.; GOMES, C. C. G.; CARDOSO, F. F. |
Afiliación : |
R. R. MOTA, Animal Science Department, Federal University of Viçosa, Brazil; P. S. LOPES, Animal Science Department, Federal University of Viçosa, Viçosa, Brazil; R. J. TEMPELMAN, Animal Science Department, Michigan State University, United States; F. F. SILVA, Animal Science Department, Federal University of Viçosa, Brazil; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; C. C. G. GOMES, Embrapa South Livestock, Brazil; F. F. CARDOSO, eAnimal Science Department, Federal University of Pelotas, Brazil. |
Título : |
Genome-enabled prediction for tick resistance in Hereford and Braford beef cattle via reaction norm models. |
Fecha de publicación : |
2016 |
Fuente / Imprenta : |
Journal of Animal Science, May 2016, Volume 94, Issue 5, Pages 1834 - 1843. |
ISSN : |
0021-8812 |
DOI : |
10.2527/jas.2015-0194 |
Idioma : |
Inglés |
Notas : |
Article history: Received December 11, 2015. // Accepted March 10, 2016. |
Contenido : |
ABSTRACT.
Very few studies have been conducted to infer genotype × environment interaction (G×E) based in genomic prediction models using SNP markers. Therefore, our main objective was to compare a conventional genomic-based single-step model (HBLUP) with its reaction norm model extension (genomic 1-step linear reaction norm model [HLRNM]) to provide EBV for tick resistance as well as to compare predictive performance of these models with counterpart models that ignore SNP marker information, that is, a linear animal model (ABLUP) and its reaction norm extension (1-step linear reaction norm model [ALRNM]). Phenotypes included 10,673 tick counts on 4,363 Hereford and Braford animals, of which 3,591 were genotyped. Using the deviance information criterion for model choice, ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic model extensions. The HLRNM estimated lower average and reaction norm genetic variability compared with the ALRNM, whereas ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic reaction norm model extensions. Heritability and repeatability estimates varied along the environmental gradient (EG) and the genetic correlations were remarkably low between high and low EG, indicating the presence of G×E for tick resistance in these populations. Based on 5-fold K-means partitioning, mean cross-validation estimates with their respective SE of predictive accuracy were 0.66 (SE 0.02), 0.67 (SE 0.02), 0.67 (SE 0.02), and 0.66 (SE 0.02) for ABLUP, HBLUP, HLRNM, and ALRNM, respectively. For 5-fold random partitioning, HLRNM (0.71 ± 0.01) was statistically different from ABLUP (0.67 ± 0.01). However, no statistical significance was reported when considering HBLUP (0.70 ± 0.01) and ALRNM (0.70 ± 0.01). Our results suggest that SNP marker information does not lead to higher prediction accuracies in reaction norm models. Furthermore, these accuracies decreased as the tick infestation level increased and as the relationship between animals in training and validation data sets decreased.
© 2016 American Society of Animal Science. All rights reserved. MenosABSTRACT.
Very few studies have been conducted to infer genotype × environment interaction (G×E) based in genomic prediction models using SNP markers. Therefore, our main objective was to compare a conventional genomic-based single-step model (HBLUP) with its reaction norm model extension (genomic 1-step linear reaction norm model [HLRNM]) to provide EBV for tick resistance as well as to compare predictive performance of these models with counterpart models that ignore SNP marker information, that is, a linear animal model (ABLUP) and its reaction norm extension (1-step linear reaction norm model [ALRNM]). Phenotypes included 10,673 tick counts on 4,363 Hereford and Braford animals, of which 3,591 were genotyped. Using the deviance information criterion for model choice, ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic model extensions. The HLRNM estimated lower average and reaction norm genetic variability compared with the ALRNM, whereas ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic reaction norm model extensions. Heritability and repeatability estimates varied along the environmental gradient (EG) and the genetic correlations were remarkably low between high and low EG, indicating the presence of G×E for tick resistance in these populations. Based on 5-fold K-means partitioning, mean cross-validation estimates with their respective SE of predictive accuracy were 0.66 (SE 0.02), 0.67 (SE 0.02)... Presentar Todo |
Palabras claves : |
ACCURACY; CROSS-VALIDATION; GENETIC CORRELATION; HERITABILITY. |
Asunto categoría : |
-- |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12162/1/mota2016.pdf
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Marc : |
LEADER 03053naa a2200277 a 4500 001 1059370 005 2019-02-06 008 2016 bl uuuu u00u1 u #d 022 $a0021-8812 024 7 $a10.2527/jas.2015-0194$2DOI 100 1 $aMOTA, R. R. 245 $aGenome-enabled prediction for tick resistance in Hereford and Braford beef cattle via reaction norm models.$h[electronic resource] 260 $c2016 500 $aArticle history: Received December 11, 2015. // Accepted March 10, 2016. 520 $aABSTRACT. Very few studies have been conducted to infer genotype × environment interaction (G×E) based in genomic prediction models using SNP markers. Therefore, our main objective was to compare a conventional genomic-based single-step model (HBLUP) with its reaction norm model extension (genomic 1-step linear reaction norm model [HLRNM]) to provide EBV for tick resistance as well as to compare predictive performance of these models with counterpart models that ignore SNP marker information, that is, a linear animal model (ABLUP) and its reaction norm extension (1-step linear reaction norm model [ALRNM]). Phenotypes included 10,673 tick counts on 4,363 Hereford and Braford animals, of which 3,591 were genotyped. Using the deviance information criterion for model choice, ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic model extensions. The HLRNM estimated lower average and reaction norm genetic variability compared with the ALRNM, whereas ABLUP and HBLUP seemed to be poorer fitting in comparison with their respective genomic reaction norm model extensions. Heritability and repeatability estimates varied along the environmental gradient (EG) and the genetic correlations were remarkably low between high and low EG, indicating the presence of G×E for tick resistance in these populations. Based on 5-fold K-means partitioning, mean cross-validation estimates with their respective SE of predictive accuracy were 0.66 (SE 0.02), 0.67 (SE 0.02), 0.67 (SE 0.02), and 0.66 (SE 0.02) for ABLUP, HBLUP, HLRNM, and ALRNM, respectively. For 5-fold random partitioning, HLRNM (0.71 ± 0.01) was statistically different from ABLUP (0.67 ± 0.01). However, no statistical significance was reported when considering HBLUP (0.70 ± 0.01) and ALRNM (0.70 ± 0.01). Our results suggest that SNP marker information does not lead to higher prediction accuracies in reaction norm models. Furthermore, these accuracies decreased as the tick infestation level increased and as the relationship between animals in training and validation data sets decreased. © 2016 American Society of Animal Science. All rights reserved. 653 $aACCURACY 653 $aCROSS-VALIDATION 653 $aGENETIC CORRELATION 653 $aHERITABILITY 700 1 $aLOPES, P. S. 700 1 $aTEMPELMAN, R. J. 700 1 $aSILVA, F. F. 700 1 $aAGUILAR, I. 700 1 $aGOMES, C. C. G. 700 1 $aCARDOSO, F. F. 773 $tJournal of Animal Science, May 2016, Volume 94, Issue 5, Pages 1834 - 1843.
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