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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
09/09/2014 |
Actualizado : |
23/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
LOURENCO, D.A.L.; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; EZRA, E.; RON, M.; SHIRAK, A.; WELLER, J.I. |
Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
Título : |
Methods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses. |
Fecha de publicación : |
2014 |
Fuente / Imprenta : |
Journal of Dairy Science, 2014, v.97, no.3, p.1742-1752. OPEN ACCESS. |
ISSN : |
0022-0302 |
DOI : |
10.3168/jds.2013-6916 |
Idioma : |
Inglés |
Notas : |
Article history: Received September 10, 2013. / Accepted December 6, 2013. |
Contenido : |
ABSTRACTS.
Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coefficients was observed from parities 1 through 3. Fat and protein yields had the lowest R2 for all the methods. On average, R2 was lowest for parent averages, followed by GBLUP, BayesC, ssGBLUP, and WssGBLUP. For some traits, R2 for direct genomic values from BayesC and GBLUP were lower than those for parent averages. Genomic estimated breeding values using ssGBLUP were the least biased, and this method appears to be a suitable tool for genomic evaluation of a small genotyped population, as it automatically accounts for parental index, allows for inclusion of female genomic information without preadjustments in evaluations, and uses the same model as in traditional evaluations. Weighted ssGBLUP has the potential for higher evaluation accuracy.
© 2014 American Dairy Science Association. MenosABSTRACTS.
Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coe... Presentar Todo |
Thesagro : |
MEJORAMIENTO GENÉTICO ANIMAL; MODELOS MATEMÁTICOS; SELECCIÓN DE GENOTIPOS; SELECCIÓN GENÓMICA. |
Asunto categoría : |
L10 Genética y mejoramiento animal |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/3043/1/Aguilar-I.-2014-Jr.Dairy-Sci.-v.973-p.1742-1752.pdf
https://www.journalofdairyscience.org/article/S0022-0302(14)00052-6/pdf
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Marc : |
LEADER 03270naa a2200289 a 4500 001 1050061 005 2019-10-23 008 2014 bl uuuu u00u1 u #d 022 $a0022-0302 024 7 $a10.3168/jds.2013-6916$2DOI 100 1 $aLOURENCO, D.A.L. 245 $aMethods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses.$h[electronic resource] 260 $c2014 500 $aArticle history: Received September 10, 2013. / Accepted December 6, 2013. 520 $aABSTRACTS. Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coefficients was observed from parities 1 through 3. Fat and protein yields had the lowest R2 for all the methods. On average, R2 was lowest for parent averages, followed by GBLUP, BayesC, ssGBLUP, and WssGBLUP. For some traits, R2 for direct genomic values from BayesC and GBLUP were lower than those for parent averages. Genomic estimated breeding values using ssGBLUP were the least biased, and this method appears to be a suitable tool for genomic evaluation of a small genotyped population, as it automatically accounts for parental index, allows for inclusion of female genomic information without preadjustments in evaluations, and uses the same model as in traditional evaluations. Weighted ssGBLUP has the potential for higher evaluation accuracy. © 2014 American Dairy Science Association. 650 $aMEJORAMIENTO GENÉTICO ANIMAL 650 $aMODELOS MATEMÁTICOS 650 $aSELECCIÓN DE GENOTIPOS 650 $aSELECCIÓN GENÓMICA 700 1 $aMISZTAL, I. 700 1 $aTSURUTA, S. 700 1 $aAGUILAR, I. 700 1 $aEZRA, E. 700 1 $aRON, M. 700 1 $aSHIRAK, A. 700 1 $aWELLER, J.I. 773 $tJournal of Dairy Science, 2014$gv.97, no.3, p.1742-1752. OPEN ACCESS.
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Registro original : |
INIA Las Brujas (LB) |
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Biblioteca (s) : |
INIA Tacuarembó. |
Fecha actual : |
21/02/2014 |
Actualizado : |
31/07/2018 |
Tipo de producción científica : |
Artículos en Revistas Agropecuarias |
Autor : |
GARCIA, A. |
Afiliación : |
ADRIANA GARCIA LAMOTHE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Fertilización del trigo. |
Fecha de publicación : |
2010 |
Fuente / Imprenta : |
El País Agropecuario, 2010, v. 16, no. 183, p. 36-37. |
Idioma : |
Español |
Contenido : |
Un buen programa de fertilización del cultivo de trigo es esencial para la sostenibilidad de los agro-ecosistemas. Contribuye a la expresión del potencial de los cultivares
y también a mantener la fertilidad del suelo. |
Thesagro : |
APLICACION DE ABONOS; TRIGO. |
Asunto categoría : |
F01 Cultivo |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/10921/1/183p36-37.pdf
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Marc : |
LEADER 00580naa a2200145 a 4500 001 1028613 005 2018-07-31 008 2010 bl uuuu u00u1 u #d 100 1 $aGARCIA, A. 245 $aFertilización del trigo. 260 $c2010 520 $aUn buen programa de fertilización del cultivo de trigo es esencial para la sostenibilidad de los agro-ecosistemas. Contribuye a la expresión del potencial de los cultivares y también a mantener la fertilidad del suelo. 650 $aAPLICACION DE ABONOS 650 $aTRIGO 773 $tEl País Agropecuario, 2010$gv. 16, no. 183, p. 36-37.
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INIA Tacuarembó (TBO) |
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