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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
21/02/2014 |
Actualizado : |
04/07/2017 |
Tipo de producción científica : |
Artículos en Revistas Agropecuarias |
Autor : |
FORMOSO, F. |
Afiliación : |
FRANCISCO ANTONIO FORMOSO CAVALLERI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Mezclas forrajeras raigrás más leguminosas: ventajas y limitantes. |
Fecha de publicación : |
2012 |
Fuente / Imprenta : |
Revista INIA Uruguay, 2012, no. 28, p. 34-40 |
Serie : |
(Revista INIA; 28) |
ISSN : |
1510-9011 |
Idioma : |
Español |
Thesagro : |
DENSIDAD DE SIEMBRA; MEZCLAS FORRAJERAS; PASTOREO; PASTURAS; PRODUCCION DE FORRAJES. |
Asunto categoría : |
L01 Ganadería |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/7004/1/revista-INIA-28-p.34-40.pdf
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Marc : |
LEADER 00538naa a2200193 a 4500 001 1007452 005 2017-07-04 008 2012 bl uuuu u00u1 u #d 022 $a1510-9011 100 1 $aFORMOSO, F. 245 $aMezclas forrajeras raigrás más leguminosas$bventajas y limitantes. 260 $c2012 490 $a(Revista INIA; 28) 650 $aDENSIDAD DE SIEMBRA 650 $aMEZCLAS FORRAJERAS 650 $aPASTOREO 650 $aPASTURAS 650 $aPRODUCCION DE FORRAJES 773 $tRevista INIA Uruguay, 2012, no. 28, p. 34-40
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INIA Las Brujas (LB) |
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| Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
18/08/2022 |
Actualizado : |
20/07/2023 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
PRAVIA, M.I.; NAVAJAS, E.; AGUILAR, I.; RAVAGNOLO, O. |
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. |
Título : |
Evaluation of feed efficiency traits in different Hereford populations and their effect on variance component estimation. |
Fecha de publicación : |
2022 |
Fuente / Imprenta : |
Animal Production Science, 2022, Volume 62, Issue 17, pages 1652-1660. doi: https://doi.org/10.1071/AN21420 |
ISSN : |
1836-0939 |
DOI : |
10.1071/AN21420 |
Idioma : |
Inglés |
Notas : |
Article history: Submitted 24 August 2021; Accepted 10 June 2022; Published online 1 August 2022. -- Handling Editor: Sue Hatcher. --
Corresponding author: Pravia, M.I.; Instituto Nacional de Investigación Agropecuaria (INIA), Estación Experimental Las Brujas, Ruta 48 Km. 10, Canelones, Uruguay; email:mpravia@inia.org.uy -- FUNDING: Financial support was provided by the National Agency for Research and Innovation (grant RTS-1-2012-1-3489). -- |
Contenido : |
ABSTRACT.- Context: Residual feed intake is a relevant trait for beef cattle, given the positive impact on reducing feeding costs and greenhouse gas emissions. The lack of large databases is a restriction when estimating accurate genetic parameters for dry matter intake (DMI) and residual feed intake (RFI), and combining different data sets could be an alternative to increase the amount of data and achieve better estimations. Aim: The main objective was to compare Uruguayan data (URY; 780 bulls) and Canadian data (CAN; 1597 bulls), and to assess the adequacy of pooling both data sets (ALL) for the estimation of genetic parameters for DMI and RFI. Methods: Feed intake and growth traits phenotypes in both data sets were measured following the same protocols established by the Beef Improvement Federation. Pedigree connections among data sets existed, but were weak. Performance data were analysed for each data set, and individual partial regression coefficients for each energy sink on DMI were obtained and compared. Univariate and multivariate variance components were estimated by the restricted maximum likelihood (REML) for DMI, RFI and their energy sinks traits (average daily gain, metabolic mid weight and back fat thickness). Key results: There were some differences in phenotypic performance among data (P < 0.01); however, no differences (P > 0.1) were observed for phenotypic values of RFI between sets. Heritability estimates for DMI were 0.42 (URY), 0.41 (CAN) and 0.45 for ALL data, whereas heritability estimates for RFI were 0.34 (URY), 0.20 (CAN) and 0.25 for ALL data. The results obtained indicate selection on reducing RFI could lead to a decrease in DMI, without compromising other performance traits, as genetic correlations between RFI, growth and liveweight were low or close to 0 (-0.12-0.07). Conclusions: As genetic parameters were similar between national data sets (URY, CAN), pooling data (ALL) provided more accurate parameter estimations, as they presented smaller standard deviations, especially in multivariate analysis. Implications: Parameters estimated here may be used in international or national genetic evaluation programs. © 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing. MenosABSTRACT.- Context: Residual feed intake is a relevant trait for beef cattle, given the positive impact on reducing feeding costs and greenhouse gas emissions. The lack of large databases is a restriction when estimating accurate genetic parameters for dry matter intake (DMI) and residual feed intake (RFI), and combining different data sets could be an alternative to increase the amount of data and achieve better estimations. Aim: The main objective was to compare Uruguayan data (URY; 780 bulls) and Canadian data (CAN; 1597 bulls), and to assess the adequacy of pooling both data sets (ALL) for the estimation of genetic parameters for DMI and RFI. Methods: Feed intake and growth traits phenotypes in both data sets were measured following the same protocols established by the Beef Improvement Federation. Pedigree connections among data sets existed, but were weak. Performance data were analysed for each data set, and individual partial regression coefficients for each energy sink on DMI were obtained and compared. Univariate and multivariate variance components were estimated by the restricted maximum likelihood (REML) for DMI, RFI and their energy sinks traits (average daily gain, metabolic mid weight and back fat thickness). Key results: There were some differences in phenotypic performance among data (P < 0.01); however, no differences (P > 0.1) were observed for phenotypic values of RFI between sets. Heritability estimates for DMI were 0.42 (URY), 0.41 (CAN) and 0.45 for A... Presentar Todo |
Palabras claves : |
Across country evaluation; Beef cattle; Feed intake; Genetic correlations; Heritability; Multiple trait model; Residual feed intake; Variance component estimation. |
Asunto categoría : |
L10 Genética y mejoramiento animal |
Marc : |
LEADER 03625naa a2200289 a 4500 001 1063535 005 2023-07-20 008 2022 bl uuuu u00u1 u #d 022 $a1836-0939 024 7 $a10.1071/AN21420$2DOI 100 1 $aPRAVIA, M.I. 245 $aEvaluation of feed efficiency traits in different Hereford populations and their effect on variance component estimation.$h[electronic resource] 260 $c2022 500 $aArticle history: Submitted 24 August 2021; Accepted 10 June 2022; Published online 1 August 2022. -- Handling Editor: Sue Hatcher. -- Corresponding author: Pravia, M.I.; Instituto Nacional de Investigación Agropecuaria (INIA), Estación Experimental Las Brujas, Ruta 48 Km. 10, Canelones, Uruguay; email:mpravia@inia.org.uy -- FUNDING: Financial support was provided by the National Agency for Research and Innovation (grant RTS-1-2012-1-3489). -- 520 $aABSTRACT.- Context: Residual feed intake is a relevant trait for beef cattle, given the positive impact on reducing feeding costs and greenhouse gas emissions. The lack of large databases is a restriction when estimating accurate genetic parameters for dry matter intake (DMI) and residual feed intake (RFI), and combining different data sets could be an alternative to increase the amount of data and achieve better estimations. Aim: The main objective was to compare Uruguayan data (URY; 780 bulls) and Canadian data (CAN; 1597 bulls), and to assess the adequacy of pooling both data sets (ALL) for the estimation of genetic parameters for DMI and RFI. Methods: Feed intake and growth traits phenotypes in both data sets were measured following the same protocols established by the Beef Improvement Federation. Pedigree connections among data sets existed, but were weak. Performance data were analysed for each data set, and individual partial regression coefficients for each energy sink on DMI were obtained and compared. Univariate and multivariate variance components were estimated by the restricted maximum likelihood (REML) for DMI, RFI and their energy sinks traits (average daily gain, metabolic mid weight and back fat thickness). Key results: There were some differences in phenotypic performance among data (P < 0.01); however, no differences (P > 0.1) were observed for phenotypic values of RFI between sets. Heritability estimates for DMI were 0.42 (URY), 0.41 (CAN) and 0.45 for ALL data, whereas heritability estimates for RFI were 0.34 (URY), 0.20 (CAN) and 0.25 for ALL data. The results obtained indicate selection on reducing RFI could lead to a decrease in DMI, without compromising other performance traits, as genetic correlations between RFI, growth and liveweight were low or close to 0 (-0.12-0.07). Conclusions: As genetic parameters were similar between national data sets (URY, CAN), pooling data (ALL) provided more accurate parameter estimations, as they presented smaller standard deviations, especially in multivariate analysis. Implications: Parameters estimated here may be used in international or national genetic evaluation programs. © 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing. 653 $aAcross country evaluation 653 $aBeef cattle 653 $aFeed intake 653 $aGenetic correlations 653 $aHeritability 653 $aMultiple trait model 653 $aResidual feed intake 653 $aVariance component estimation 700 1 $aNAVAJAS, E. 700 1 $aAGUILAR, I. 700 1 $aRAVAGNOLO, O. 773 $tAnimal Production Science, 2022, Volume 62, Issue 17, pages 1652-1660. doi: https://doi.org/10.1071/AN21420
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