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| 1. |  | STEWART, S.; RODRIGUEZ, M.; CORALLO, B.; DEL PALACIO, A.; CEA, J.; SIMOENS, M.; SANCHEZ, A.; PAN, D. Explorando prácticas de manejo que tiendan a minimizar la contaminación de micotoxinas producidas por Fusarium spp. en sorgo y maíz. In: Sociedad Uruguaya de Fitopatología Jornada Uruguaya de Fitopatología, 6., Jornada Uruguaya de Protección Vegetal, 4., 21-22 octubre, 2021, Montevideo, Uruguay. Libro de resúmenes. Montevideo (UY): Sociedad Uruguay de Fitopatología (SUFIT), 2021. p. 52. Financiamiento: Proyecto INNOVAGRO ANII FSA-I-2017-1-139531.| Biblioteca(s): INIA La Estanzuela. |
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| 2. | | CORALLO, A.B.; DEL PALACIO, A.; OLIVER, M.; TISCORNIA, S.; SIMOENS, M.; CEA, J.; DE AURRECOECHEA, I.; MARTÍNEZ, I.; SÁNCHEZ, A.; STEWART, S.; PAN, D. Fusarium species and mycotoxins associated with sorghum grains in Uruguay. Toxins. 2023, Volume 15, Issue 8, article 484. https://doi.org/10.3390/toxins15080484 ----OPEN ACCESS. Article history: Received 28 June 2023; Revised 23 July 2023; Accepted 25 July 2023; Published 31 July 2023. -- This article belongs to the Section Mycotoxins (https://www.mdpi.com/journal/toxins/sections/mycotoxins ). -- LICENSE:...| Biblioteca(s): INIA Las Brujas. |
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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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