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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Tacuarembó; INIA Treinta y Tres. |
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Fecha : |
21/02/2014 |
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Actualizado : |
27/02/2018 |
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Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
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Autor : |
BAEZA, S.; PARUELO, J.M.; LEZAMA, F. |
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Afiliación : |
S. BAEZA; J.M. PARUELO; FEDERICO LEZAMA. |
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Título : |
Caracterización funcional en pastizales y sus aplicaciones en Uruguay |
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Fecha de publicación : |
2011 |
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Fuente / Imprenta : |
In: ALTESOR, A.; AYALA, W.; PARUELO, J.M. (Eds.). Bases ecológicas y tecnológicas para el manejo de pastizales. Montevideo (UY): INIA, 2011. |
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Páginas : |
p. 165-182 |
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Serie : |
(Serie FPTA-INIA; 26) |
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ISBN : |
978-9974-38-308-1 |
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ISSN : |
1688-924X |
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Idioma : |
Español |
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Contenido : |
El funcionamiento de la vegetación (ej. intercambio de materia y energía) complementa y mejora las descripciones estructurales de los ecosistemas. Varios de los procesos del funcionamiento de los ecosistemas pueden ser analizados mediante el uso de imágenes de satélite. En este capítulo analizamos el funcionamiento de los pastizales uruguayos utilizando el análisis de series temporales de imágenes de satélite a partir de dos ejemplos. En primer lugar, describimos el funcionamiento de los pastizales naturales de las diferentes unidades geomorfológicas del Uruguay a diferentes escalas espaciales y mostramos cómo esta información puede utilizarse para la definición y monitoreo
de áreas protegidas. En segundo lugar, describimos en forma detallada el funcionamiento de pastizales naturales de una de las áreas de pastizales naturales más extensa del Uruguay (Basalto superficial) y mostramos cómo se puede utilizar esta información para el manejo de sistemas productivos. |
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Thesagro : |
COMPOSICION BOTANICA; ECOSISTEMAS; FACTORES AMBIENTALES; INTERCAMBIO DE ENERGIA; PASTIZAL NATURAL; PASTIZALES; PRODUCTIVIDAD; URUGUAY; VEGETACION. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/8814/1/Fpta-26-p.163-182.pdf
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Marc : |
LEADER 01890naa a2200301 a 4500
001 1009036
005 2018-02-27
008 2011 bl uuuu u00u1 u #d
020 $a978-9974-38-308-1
022 $a1688-924X
100 1 $aBAEZA, S.
245 $aCaracterización funcional en pastizales y sus aplicaciones en Uruguay
260 $c2011
300 $ap. 165-182
490 $a(Serie FPTA-INIA; 26)
520 $aEl funcionamiento de la vegetación (ej. intercambio de materia y energía) complementa y mejora las descripciones estructurales de los ecosistemas. Varios de los procesos del funcionamiento de los ecosistemas pueden ser analizados mediante el uso de imágenes de satélite. En este capítulo analizamos el funcionamiento de los pastizales uruguayos utilizando el análisis de series temporales de imágenes de satélite a partir de dos ejemplos. En primer lugar, describimos el funcionamiento de los pastizales naturales de las diferentes unidades geomorfológicas del Uruguay a diferentes escalas espaciales y mostramos cómo esta información puede utilizarse para la definición y monitoreo de áreas protegidas. En segundo lugar, describimos en forma detallada el funcionamiento de pastizales naturales de una de las áreas de pastizales naturales más extensa del Uruguay (Basalto superficial) y mostramos cómo se puede utilizar esta información para el manejo de sistemas productivos.
650 $aCOMPOSICION BOTANICA
650 $aECOSISTEMAS
650 $aFACTORES AMBIENTALES
650 $aINTERCAMBIO DE ENERGIA
650 $aPASTIZAL NATURAL
650 $aPASTIZALES
650 $aPRODUCTIVIDAD
650 $aURUGUAY
650 $aVEGETACION
700 1 $aPARUELO, J.M.
700 1 $aLEZAMA, F.
773 $tIn: ALTESOR, A.; AYALA, W.; PARUELO, J.M. (Eds.). Bases ecológicas y tecnológicas para el manejo de pastizales. Montevideo (UY): INIA, 2011.
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Registro original : |
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. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
18/08/2022 |
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Actualizado : |
20/07/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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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 : |
Evaluation of feed efficiency traits in different Hereford populations and their effect on variance component estimation. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Animal Production Science, 2022, Volume 62, Issue 17, pages 1652-1660. doi: https://doi.org/10.1071/AN21420 |
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ISSN : |
1836-0939 |
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DOI : |
10.1071/AN21420 |
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Idioma : |
Inglés |
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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). -- |
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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 |
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Palabras claves : |
Across country evaluation; Beef cattle; Feed intake; Genetic correlations; Heritability; Multiple trait model; Residual feed intake; Variance component estimation. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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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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