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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 : |
30/11/2022 |
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Actualizado : |
21/03/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
BRUNES, L.C.; FARIA, C.U.D.; MAGNABOSCO, C.U.; LOBO, R.B.; PERIPOLLI, E.; AGUILAR, I.; BALDI, F. |
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Afiliación : |
LUDMILLA COSTA BRUNES, Animal Performance Center, Embrapa Cerrados, Planaltina, 73310-970, Brazil; CARINA UBIRAJARA DE FARIA, College of Veterinary Medicine, Federal University of Uberlandia, Uberlandia, 38410-337, Brazil; CLÁUDIO ULHOA MAGNABOSCO, Animal Performance Center, Embrapa Cerrados, Planaltina, 73310-970, Brazil; RAYSILDO BARBOSA LOBO, National Association of Breeders and Researchers, Ribeirao Preto, 14020-230, Brazil; ELISA PERIPOLLI, Departament of Animal Science, College of Agricultural and Veterinary Sciences, Sao Paulo State University (UNESP), Jaboticabal, 14884-900, Brazil; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BALDI, Departament of Animal Science, College of Agricultural and Veterinary Sciences, Sao Paulo State University (UNESP), Jaboticabal, 14884-900, Brazil. |
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Título : |
Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Journal of Applied Genetics, 2023, Volume 64, Issue 1, Pages 159 - 167. doi: https://doi.org/10.1007/s13353-022-00734-8 |
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ISSN : |
1234-1983 |
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DOI : |
10.1007/s13353-022-00734-8 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 25 February 2022; Revised 3 September 2022; Accepted 26 October 2022; Published online 15 November 2022; Published February 2023. -- Corresponding author: Brunes, L.C.; Animal Performance Center, Embrapa Cerrados, Planaltina, Brazil; email:ludmillabrunes@hotmail.com -- |
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Contenido : |
ABSTRACT.- This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFItest) and for the whole population (RFIpop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFIpop and RFItest with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFItest and RFIpop. The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFItest and RFIpop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFItest and RFIpop genomic breeding values (GEBV). The RFIpop ANOVA showed a higher significance level (p < 0.0001) than did the RFItest for the fixed effects. The RFIpop displayed higher additive genetic variance estimated than the RFItest, although the RFIpop and RFItest displayed similar heritabilities. Overall, the RFItest showed higher residual correlations with growth, reproductive, and carcass traits, while the RFIpop displayed higher genetic correlations with such traits. The GEBV for the RFItest was slightly biased than GEBV RFIpop. The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFIpop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI. © 2022, The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences. MenosABSTRACT.- This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFItest) and for the whole population (RFIpop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFIpop and RFItest with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFItest and RFIpop. The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFItest and RFIpop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFItest and RFIpop genomic breeding values (GEBV). The RFIpop ANOVA showed a higher significance level (p < 0.0001) than did the RFItest for the fixed effects. The RFIpop displayed higher additive genetic variance estimated than the RFItest, although the RFIpop and RFItest displayed similar heritabilities. Overall, the RFItest showed higher residual correlations with growth, reproductive, and carcass traits, while the RFIpop displayed higher genetic correlations with such traits. The GEBV for the RFItest was slightly biased than GEBV RFIpop. The approach t... Presentar Todo |
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Palabras claves : |
Accuracy; Beef cattle; Bos taurus indicus; Feed efficiency; Genomic selection; Residual feed intake equation. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 03223naa a2200301 a 4500
001 1063803
005 2023-03-21
008 2023 bl uuuu u00u1 u #d
022 $a1234-1983
024 7 $a10.1007/s13353-022-00734-8$2DOI
100 1 $aBRUNES, L.C.
245 $aGenomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle.$h[electronic resource]
260 $c2023
500 $aArticle history: Received 25 February 2022; Revised 3 September 2022; Accepted 26 October 2022; Published online 15 November 2022; Published February 2023. -- Corresponding author: Brunes, L.C.; Animal Performance Center, Embrapa Cerrados, Planaltina, Brazil; email:ludmillabrunes@hotmail.com --
520 $aABSTRACT.- This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFItest) and for the whole population (RFIpop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFIpop and RFItest with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFItest and RFIpop. The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFItest and RFIpop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFItest and RFIpop genomic breeding values (GEBV). The RFIpop ANOVA showed a higher significance level (p < 0.0001) than did the RFItest for the fixed effects. The RFIpop displayed higher additive genetic variance estimated than the RFItest, although the RFIpop and RFItest displayed similar heritabilities. Overall, the RFItest showed higher residual correlations with growth, reproductive, and carcass traits, while the RFIpop displayed higher genetic correlations with such traits. The GEBV for the RFItest was slightly biased than GEBV RFIpop. The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFIpop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI. © 2022, The Author(s), under exclusive licence to Institute of Plant Genetics Polish Academy of Sciences.
653 $aAccuracy
653 $aBeef cattle
653 $aBos taurus indicus
653 $aFeed efficiency
653 $aGenomic selection
653 $aResidual feed intake equation
700 1 $aFARIA, C.U.D.
700 1 $aMAGNABOSCO, C.U.
700 1 $aLOBO, R.B.
700 1 $aPERIPOLLI, E.
700 1 $aAGUILAR, I.
700 1 $aBALDI, F.
773 $tJournal of Applied Genetics, 2023, Volume 64, Issue 1, Pages 159 - 167. doi: https://doi.org/10.1007/s13353-022-00734-8
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INIA Las Brujas (LB) |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
16/09/2019 |
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Actualizado : |
18/09/2019 |
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Tipo de producción científica : |
Abstracts/Resúmenes |
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Autor : |
BERBERIAN, N.; BONNECARRERE, V.; BLANCO, P.H.; PÉREZ DE VIDA, F.; ROSAS, J.E.; MARTÍNEZ, S.; GUTIÉRREZ, L. |
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Afiliación : |
NATALIA BERBERIAN, Dpto. de Biometría, Estadìstica y Computación, Facultad de Agronomía, UDELAR.; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PEDRO HORACIO BLANCO BARRAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BLAS PEREZ DE VIDA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN EDUARDO ROSAS CAISSIOLS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SEBASTIÁN MARTÍNEZ KOPP, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCÍA GUTIÉRREZ, Dpto. de Biometría, Estadística y Computación, Facultad de Agronomía, UDELAR. |
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Título : |
Model comparison and experimental design simulation including natural field variability in rice crop (Oryza sativa L.). |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
In: UNIVERSIDAD DE LA REPÚBLICA (UDELAR). FACULTAD DE AGRONOMÍA. Resúmenes. Jornadas de Investigación, 8-9 nov., 2018, Montevideo, Uruguay. Montevideo; FAGRO, 2019. |
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Páginas : |
p. 14 |
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Idioma : |
Inglés |
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Notas : |
Trabajo originalmente presentado en: Berberian, N.; Bonecarrere, V.; Blaco, P.; Pérez de Vida, F.; Rosas, J.; Martínez, S.; Gutíerrez, L. 2018. International Biometric Conference, 29. Model comparison and experimental design simulation including natural field variability in rice crop (Oriza Satia L.) Barcelona, España (Trabajo completo). |
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Palabras claves : |
ARROZ; GEOESTADÍSTICA; GEOESTATISTICS; MIXED MODELS; MODELOS DE SIMULACION; POSTBLOCKING. |
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Asunto categoría : |
F01 Cultivo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/13260/1/14.pdf
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Marc : |
LEADER 01244nam a2200265 a 4500
001 1060161
005 2019-09-18
008 2019 bl uuuu u01u1 u #d
100 1 $aBERBERIAN, N.
245 $aModel comparison and experimental design simulation including natural field variability in rice crop (Oryza sativa L.).$h[electronic resource]
260 $aIn: UNIVERSIDAD DE LA REPÚBLICA (UDELAR). FACULTAD DE AGRONOMÍA. Resúmenes. Jornadas de Investigación, 8-9 nov., 2018, Montevideo, Uruguay. Montevideo; FAGRO$c2019
300 $ap. 14
500 $aTrabajo originalmente presentado en: Berberian, N.; Bonecarrere, V.; Blaco, P.; Pérez de Vida, F.; Rosas, J.; Martínez, S.; Gutíerrez, L. 2018. International Biometric Conference, 29. Model comparison and experimental design simulation including natural field variability in rice crop (Oriza Satia L.) Barcelona, España (Trabajo completo).
653 $aARROZ
653 $aGEOESTADÍSTICA
653 $aGEOESTATISTICS
653 $aMIXED MODELS
653 $aMODELOS DE SIMULACION
653 $aPOSTBLOCKING
700 1 $aBONNECARRERE, V.
700 1 $aBLANCO, P.H.
700 1 $aPÉREZ DE VIDA, F.
700 1 $aROSAS, J.E.
700 1 $aMARTÍNEZ, S.
700 1 $aGUTIÉRREZ, L.
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