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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 : |
02/05/2023 |
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Actualizado : |
02/05/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
PRAVIA, M.I.; NAVAJAS, E.; AGUILAR, I.; RAVAGNOLO, O. |
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Afiliación : |
MARIA ISABEL PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ELLY ANA NAVAJAS VALENTINI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OLGA RAVAGNOLO GUMILA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Prediction ability of an alternative multi-trait genomic evaluation for residual feed intake. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Journal of Animal Breeding and Genetics, 2023. https://doi.org/10.1111/jbg.12775 [Article in Press] |
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ISSN : |
0931-2668 |
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DOI : |
10.1111/jbg.12775 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 23 February 2023; Revised 4 April 2023; Accepted 6 April 2023; First published 25 April 2023. -- Corresponding author: Pravia, M.I.; Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, Canelones, Uruguay; email:mpravia@inia.org.uy -- |
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Contenido : |
Selection for feed efficiency is the goal for many genetic breeding programs in beef cattle. Residual feed intake has been included in genetic evaluations to reduce feed intake without compromising performance traits as liveweight, body gain or carcass traits. However, measuring feed intake is expensive, and only a small percentage of selection candidates are phenotyped. Genomic selection has become a very important tool to achieve effective genetic progress in these traits. Another effective strategy has been the implementation of multi-trait prediction using easily recordable predictor traits on both reference animals and candidates without phenotypes, and this could be another inexpensive way to increase accuracy. The objective of this work was to analyse and compare the prediction ability of two alternative different approaches to predict GEBVs for RFI. The population of inference was Hereford bulls in Uruguay that were genotyped candidates for to selection. © 2023 John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd. |
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Palabras claves : |
Genomic prediction; Multi-trait; Validation strategies. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 02029naa a2200229 a 4500
001 1064066
005 2023-05-02
008 2023 bl uuuu u00u1 u #d
022 $a0931-2668
024 7 $a10.1111/jbg.12775$2DOI
100 1 $aPRAVIA, M.I.
245 $aPrediction ability of an alternative multi-trait genomic evaluation for residual feed intake.$h[electronic resource]
260 $c2023
500 $aArticle history: Received 23 February 2023; Revised 4 April 2023; Accepted 6 April 2023; First published 25 April 2023. -- Corresponding author: Pravia, M.I.; Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, Canelones, Uruguay; email:mpravia@inia.org.uy --
520 $aSelection for feed efficiency is the goal for many genetic breeding programs in beef cattle. Residual feed intake has been included in genetic evaluations to reduce feed intake without compromising performance traits as liveweight, body gain or carcass traits. However, measuring feed intake is expensive, and only a small percentage of selection candidates are phenotyped. Genomic selection has become a very important tool to achieve effective genetic progress in these traits. Another effective strategy has been the implementation of multi-trait prediction using easily recordable predictor traits on both reference animals and candidates without phenotypes, and this could be another inexpensive way to increase accuracy. The objective of this work was to analyse and compare the prediction ability of two alternative different approaches to predict GEBVs for RFI. The population of inference was Hereford bulls in Uruguay that were genotyped candidates for to selection. © 2023 John Wiley & Sons Ltd. Published by John Wiley & Sons Ltd.
653 $aGenomic prediction
653 $aMulti-trait
653 $aValidation strategies
700 1 $aNAVAJAS, E.
700 1 $aAGUILAR, I.
700 1 $aRAVAGNOLO, O.
773 $tJournal of Animal Breeding and Genetics, 2023. https://doi.org/10.1111/jbg.12775 [Article in Press]
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