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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
09/03/2022 |
Actualizado : |
02/12/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
SILVEIRA, F. A.; DE BARBIERI, I.; COBUCI, J. A.; MARQUES, C. B.; FERREIRA, G. F. DE; CIAPPESONI, G. |
Afiliación : |
FERNANDO AMARILHO-SILVEIRA, Universidade Federal do Rio Grande do Sul, Avenida Bento Gonçalves 7712, RS 91509-900, Brazil; LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JAIME ARAUJO COBUCI, Universidade Federal do Rio Grande do Sul, Avenida Bento Gonçalves 7712, RS 91509-900, Brazil; CAMILA BALCONI MARQUES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GRACIALDA FERREIRA DE FERREIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS GABRIEL CIAPPESONI SCARONE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Residual feed intake for Australian Merino sheep estimated in less than 42 days of trial. |
Fecha de publicación : |
2022 |
Fuente / Imprenta : |
Livestock Science, 2022, Volume 258, Article 104889. OPEN ACCESS. doi: https://doi.org/10.1016/j.livsci.2022.104889 |
ISSN : |
1871-1413 |
DOI : |
10.1016/j.livsci.2022.104889 |
Idioma : |
Inglés |
Notas : |
Article history: Received 16 August 2021, Revised 18 February 2022, Accepted 28 February 2022, Available online 3 March 2022, Version of Record 8 March 2022. --
Corresponding author: Fernando Amarilho-Silveira, mailto: fernando@proagovina.com.br -- This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Thank the Instituto Nacional de Investigación Agropecuaria (INIA - UY) for the conduction of the field work in the data collection, which received funding from the European Union’s Horizon 2020 research and innovation program under the Grant Agreement n°772787 (Smarter) and from the Instituto Nacional de Investigación (INIA_CL_38: Rumiar). -- LICENSE: This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). |
Contenido : |
ABSTRACT.- The evaluation of sheep feed intake (FI) in feed efficiency tests is expensive. Decreasing the test period could be a resource-saving tool by reducing the cost of evaluating each animal and allowing to test a greater number of animals per year. For this reason, the objective of this research was to explore residual feed intake (RFI) models and to decreasing the test duration. Data was collected from 286 Australian Merino sheep of three performed trials, the test period consisted of 56 days (14 days of feed and facilities adaptation and 42 days of FI and average daily gain (ADG) evaluation). Two models were used to calculate RFI, Model 1 (based on Koch et al. (1963) linear model) and Model 2 (repeated measures, weekly model). Model 1 included ADG and FI estimates in a linear regression. The second model included weekly average FI as repeated measure and the weekly ADG. The increase in body weight during the test period was not perfectly linear, presenting a marked variance increase in two of the three tests while FI presented a tendency to increase throughout of the evaluation period, however presenting a high variance per day. In the 42-days tests, Pearson and Spearman correlations between models for ADG were of 0.89 and 0.87, respectively. The best correlations were detected for FI between 42 and 35-days models, presenting Pearson and Spearman correlations of 0.95 and 0.94 in the linear model, and 0.96 and 0.95 in the weekly model. When considering RFI, the correlations between linear and weekly 42-days models were from 0.93 to 0.92, respectively. The 35-days RFI length models (linear and weekly) presented a Pearson and Spearman correlations greater than 0.98 with the 42-days models. Therefore, the RFI models 35-days of duration allowed to decrease seven days of the FI test while maintaining accuracy and explaining 75.3% of the FI in the linear model, and 63.6% of the weekly model. Reducing seven days of testing would provide a greater data collection into a year of phenotypic evaluation. © 2022 The Authors. Published by Elsevier B.V. MenosABSTRACT.- The evaluation of sheep feed intake (FI) in feed efficiency tests is expensive. Decreasing the test period could be a resource-saving tool by reducing the cost of evaluating each animal and allowing to test a greater number of animals per year. For this reason, the objective of this research was to explore residual feed intake (RFI) models and to decreasing the test duration. Data was collected from 286 Australian Merino sheep of three performed trials, the test period consisted of 56 days (14 days of feed and facilities adaptation and 42 days of FI and average daily gain (ADG) evaluation). Two models were used to calculate RFI, Model 1 (based on Koch et al. (1963) linear model) and Model 2 (repeated measures, weekly model). Model 1 included ADG and FI estimates in a linear regression. The second model included weekly average FI as repeated measure and the weekly ADG. The increase in body weight during the test period was not perfectly linear, presenting a marked variance increase in two of the three tests while FI presented a tendency to increase throughout of the evaluation period, however presenting a high variance per day. In the 42-days tests, Pearson and Spearman correlations between models for ADG were of 0.89 and 0.87, respectively. The best correlations were detected for FI between 42 and 35-days models, presenting Pearson and Spearman correlations of 0.95 and 0.94 in the linear model, and 0.96 and 0.95 in the weekly model. When considering RFI, the corre... Presentar Todo |
Palabras claves : |
Average daily gain; Feed efficiency; Genetic model; Repeated measures. |
Asunto categoría : |
L10 Genética y mejoramiento animal |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16902/1/1-s2.0-S1871141322000695.pdf
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Marc : |
LEADER 03781naa a2200265 a 4500 001 1062809 005 2022-12-02 008 2022 bl uuuu u00u1 u #d 022 $a1871-1413 024 7 $a10.1016/j.livsci.2022.104889$2DOI 100 1 $aSILVEIRA, F. A. 245 $aResidual feed intake for Australian Merino sheep estimated in less than 42 days of trial.$h[electronic resource] 260 $c2022 500 $aArticle history: Received 16 August 2021, Revised 18 February 2022, Accepted 28 February 2022, Available online 3 March 2022, Version of Record 8 March 2022. -- Corresponding author: Fernando Amarilho-Silveira, mailto: fernando@proagovina.com.br -- This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. Thank the Instituto Nacional de Investigación Agropecuaria (INIA - UY) for the conduction of the field work in the data collection, which received funding from the European Union’s Horizon 2020 research and innovation program under the Grant Agreement n°772787 (Smarter) and from the Instituto Nacional de Investigación (INIA_CL_38: Rumiar). -- LICENSE: This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). 520 $aABSTRACT.- The evaluation of sheep feed intake (FI) in feed efficiency tests is expensive. Decreasing the test period could be a resource-saving tool by reducing the cost of evaluating each animal and allowing to test a greater number of animals per year. For this reason, the objective of this research was to explore residual feed intake (RFI) models and to decreasing the test duration. Data was collected from 286 Australian Merino sheep of three performed trials, the test period consisted of 56 days (14 days of feed and facilities adaptation and 42 days of FI and average daily gain (ADG) evaluation). Two models were used to calculate RFI, Model 1 (based on Koch et al. (1963) linear model) and Model 2 (repeated measures, weekly model). Model 1 included ADG and FI estimates in a linear regression. The second model included weekly average FI as repeated measure and the weekly ADG. The increase in body weight during the test period was not perfectly linear, presenting a marked variance increase in two of the three tests while FI presented a tendency to increase throughout of the evaluation period, however presenting a high variance per day. In the 42-days tests, Pearson and Spearman correlations between models for ADG were of 0.89 and 0.87, respectively. The best correlations were detected for FI between 42 and 35-days models, presenting Pearson and Spearman correlations of 0.95 and 0.94 in the linear model, and 0.96 and 0.95 in the weekly model. When considering RFI, the correlations between linear and weekly 42-days models were from 0.93 to 0.92, respectively. The 35-days RFI length models (linear and weekly) presented a Pearson and Spearman correlations greater than 0.98 with the 42-days models. Therefore, the RFI models 35-days of duration allowed to decrease seven days of the FI test while maintaining accuracy and explaining 75.3% of the FI in the linear model, and 63.6% of the weekly model. Reducing seven days of testing would provide a greater data collection into a year of phenotypic evaluation. © 2022 The Authors. Published by Elsevier B.V. 653 $aAverage daily gain 653 $aFeed efficiency 653 $aGenetic model 653 $aRepeated measures 700 1 $aDE BARBIERI, I. 700 1 $aCOBUCI, J. A. 700 1 $aMARQUES, C. B. 700 1 $aFERREIRA, G. F. DE 700 1 $aCIAPPESONI, G. 773 $tLivestock Science, 2022, Volume 258, Article 104889. OPEN ACCESS. doi: https://doi.org/10.1016/j.livsci.2022.104889
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INIA Las Brujas (LB) |
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
20/06/2015 |
Actualizado : |
20/06/2015 |
Tipo de producción científica : |
Informes Agroclimáticos |
Autor : |
GIMENEZ, A.; CASTAÑO, J.; FUREST, J.; CAL, A.; TISCORNIA, G.; SCHIAVI, C. |
Afiliación : |
AGUSTIN EDUARDO GIMENEZ FUREST, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE PEDRO CASTAÑO SANCHEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSE MARIA FUREST CROCCO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ADRIAN TABARE CAL ALVAREZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUADALUPE TISCORNIA TOSAR, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS IGNACIO SCHIAVI RAMPELBERG, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Informe Agroclimático 2013 - Situación a Noviembre. |
Fecha de publicación : |
2013 |
Fuente / Imprenta : |
Montevideo (Uruguay): INIA, 2013. |
Páginas : |
4 p. |
Idioma : |
Español |
Palabras claves : |
AGROCLIMA; AGROCLIMATOLOGÍA; BOLETIN AGROCLIMÁTICO; CARACTERIZACIÓN AGROCLIMÁTICA; DIRECCION VIENTO; ESTACIONES AGROMETEOROLOGICAS; ESTACIONES AUTOMATICAS; ESTACIONES INIA; ESTADO DEL TIEMPO; ESTRÉS HÍDRICO; GRAFICAS AGROCLIMATICOS; GRAS; HELIOFANOGRAFO; INFORMACION SATELITAL; INUNDACIONES; LLUVIAS DIARIAS; MAXIMA; MEDIA; MINIMA; PANEL SOLAR; PERSPECTIVAS CLIMATICAS; PLUVIOMETRO; PRECIPITACION NACIONAL; PREVENCION HELADAS; PRONOSTICO; SENSOR; SIMETRICO; TANQUE A; TERMOCUPLAS; TERMOHIDROGRAFO; VARIABLES AGROCLIMATICAS; VELETA. |
Thesagro : |
AGROCLIMATOLOGIA; CAMBIO CLIMATICO; CLIMA; CLIMATOLOGIA; ESTACIONES METEOROLOGICAS; ESTRES HIDRICO; EVAPORACION; EVAPOTRANSPIRACION; HUMEDAD; HUMEDAD RELATIVA; LLUVIA; METEOROLOGIA; PERSPECTIVAS; PLUVIOMETROS; PRONOSTICO DEL TIEMPO; SENSORES; SISTEMAS; SISTEMAS DE INFORMACION; SUELO; TEMPERATURA; TERMOMETROS. |
Asunto categoría : |
P40 Meteorología y climatología |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/4729/1/Inf.Agr.-noviembre-2013.pdf
http://www.inia.uy/Publicaciones/Paginas/Informe-agroclimatico-2013-Situacion-Noviembre.aspx
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Marc : |
LEADER 02095nam a2200805 a 4500 001 1052885 005 2015-06-20 008 2013 bl uuuu u0uu1 u #d 100 1 $aGIMENEZ, A. 245 $aInforme Agroclimático 2013 - Situación a Noviembre.$h[electronic resource] 260 $aMontevideo (Uruguay): INIA$c2013 300 $a4 p. 650 $aAGROCLIMATOLOGIA 650 $aCAMBIO CLIMATICO 650 $aCLIMA 650 $aCLIMATOLOGIA 650 $aESTACIONES METEOROLOGICAS 650 $aESTRES HIDRICO 650 $aEVAPORACION 650 $aEVAPOTRANSPIRACION 650 $aHUMEDAD 650 $aHUMEDAD RELATIVA 650 $aLLUVIA 650 $aMETEOROLOGIA 650 $aPERSPECTIVAS 650 $aPLUVIOMETROS 650 $aPRONOSTICO DEL TIEMPO 650 $aSENSORES 650 $aSISTEMAS 650 $aSISTEMAS DE INFORMACION 650 $aSUELO 650 $aTEMPERATURA 650 $aTERMOMETROS 653 $aAGROCLIMA 653 $aAGROCLIMATOLOGÍA 653 $aBOLETIN AGROCLIMÁTICO 653 $aCARACTERIZACIÓN AGROCLIMÁTICA 653 $aDIRECCION VIENTO 653 $aESTACIONES AGROMETEOROLOGICAS 653 $aESTACIONES AUTOMATICAS 653 $aESTACIONES INIA 653 $aESTADO DEL TIEMPO 653 $aESTRÉS HÍDRICO 653 $aGRAFICAS AGROCLIMATICOS 653 $aGRAS 653 $aHELIOFANOGRAFO 653 $aINFORMACION SATELITAL 653 $aINUNDACIONES 653 $aLLUVIAS DIARIAS 653 $aMAXIMA 653 $aMEDIA 653 $aMINIMA 653 $aPANEL SOLAR 653 $aPERSPECTIVAS CLIMATICAS 653 $aPLUVIOMETRO 653 $aPRECIPITACION NACIONAL 653 $aPREVENCION HELADAS 653 $aPRONOSTICO 653 $aSENSOR 653 $aSIMETRICO 653 $aTANQUE A 653 $aTERMOCUPLAS 653 $aTERMOHIDROGRAFO 653 $aVARIABLES AGROCLIMATICAS 653 $aVELETA 700 1 $aCASTAÑO, J. 700 1 $aFUREST, J. 700 1 $aCAL, A. 700 1 $aTISCORNIA, G. 700 1 $aSCHIAVI, C.
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