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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
17/10/2018 |
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Actualizado : |
11/03/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
ZARZA, R.; REBUFFO, M.; LA MANNA, A.; BALZARINI, M. |
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Afiliación : |
RODRIGO TABARE ZARZA FUENTES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MONICA IRENE REBUFFO GFELLER, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALEJANDRO FRANCISCO LA MANNA ALONSO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MÓNICA BALZARINI, Universidad Nacional de Córdoba, Facultad de Ciencias Agropecuarias, Córdoba, Argentina. |
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Título : |
Plant density in red clover (Trifolium pratense L.) pastures as an early predictor of forage production. |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
European Journal of Agronomy, November 2018, v. 101, p. 193-199. Doi: https://doi.org/10.1016/j.eja.2018.10.004 |
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DOI : |
10.1016/j.eja.2018.10.004 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 6 March 2018// Received in revised form 3 October 2018// Accepted 8 October 2018. |
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Contenido : |
ABSTRACT.-
Red clover (Trifolium pratense L.) is an alternative of great potential productivity for dairy systems, particularly in heavily compacted soils. Plant density (PD) during pasture establishment can be related to forage production and used as an early indicator of pasture quality. However, biomass predictive models for red clover are not readily available. To predict red clover biomass a few weeks after sowing would help farmers to adopt suitable management practices. The aim of this paper has therefore been to model the relationship between red clover biomass and PD at different time points during pasture establishment to identify the best monitoring moment for
estimating future herbage productivity. A multi-environment trial, including several seeding rates simulating different levels of establishment within each of the nine environments, was conducted in Uruguay. Seedlings were counted 3, 7 and 12 weeks after sowing (WS). Biomass of first-cut (C1) harvest was linearly related to PD at
7 WS, whereas a second-order polynomial on PD at 7 WS was a significant predictor of accumulated biomass one (Y1) and two (Y2) years after sowing. PD at 3 WS was a strong predictor of biomass only in high-yielding environments. In such environments, more than 64 plants m?2 at 3 WS suggest a high probability of achieving
annual yields above 10,000 kg DM ha-1. Therefore, early PD determination (3 or 7 WS) is a good indicator of annual productivity in pure red clover pastures. |
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Palabras claves : |
DENSIDAD DE PLANTAS; FORAGE BIOMASS; GRASSLAND; PASTURE ESTABLISHMENT; PASTURES; PLANT DENSITY; PREDICTIVE MODEL; PRODUCCIÓN FORRAJERA. |
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Thesagro : |
FORRAJES; LEGUMINOSAS; PASTURAS; TREBOL ROJO; TRIFOLIUM PRATENSE. |
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Asunto categoría : |
F01 Cultivo |
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Marc : |
LEADER 02604naa a2200337 a 4500
001 1059208
005 2021-03-11
008 2018 bl uuuu u00u1 u #d
024 7 $a10.1016/j.eja.2018.10.004$2DOI
100 1 $aZARZA, R.
245 $aPlant density in red clover (Trifolium pratense L.) pastures as an early predictor of forage production.$h[electronic resource]
260 $c2018
500 $aArticle history: Received 6 March 2018// Received in revised form 3 October 2018// Accepted 8 October 2018.
520 $aABSTRACT.- Red clover (Trifolium pratense L.) is an alternative of great potential productivity for dairy systems, particularly in heavily compacted soils. Plant density (PD) during pasture establishment can be related to forage production and used as an early indicator of pasture quality. However, biomass predictive models for red clover are not readily available. To predict red clover biomass a few weeks after sowing would help farmers to adopt suitable management practices. The aim of this paper has therefore been to model the relationship between red clover biomass and PD at different time points during pasture establishment to identify the best monitoring moment for estimating future herbage productivity. A multi-environment trial, including several seeding rates simulating different levels of establishment within each of the nine environments, was conducted in Uruguay. Seedlings were counted 3, 7 and 12 weeks after sowing (WS). Biomass of first-cut (C1) harvest was linearly related to PD at 7 WS, whereas a second-order polynomial on PD at 7 WS was a significant predictor of accumulated biomass one (Y1) and two (Y2) years after sowing. PD at 3 WS was a strong predictor of biomass only in high-yielding environments. In such environments, more than 64 plants m?2 at 3 WS suggest a high probability of achieving annual yields above 10,000 kg DM ha-1. Therefore, early PD determination (3 or 7 WS) is a good indicator of annual productivity in pure red clover pastures.
650 $aFORRAJES
650 $aLEGUMINOSAS
650 $aPASTURAS
650 $aTREBOL ROJO
650 $aTRIFOLIUM PRATENSE
653 $aDENSIDAD DE PLANTAS
653 $aFORAGE BIOMASS
653 $aGRASSLAND
653 $aPASTURE ESTABLISHMENT
653 $aPASTURES
653 $aPLANT DENSITY
653 $aPREDICTIVE MODEL
653 $aPRODUCCIÓN FORRAJERA
700 1 $aREBUFFO, M.
700 1 $aLA MANNA, A.
700 1 $aBALZARINI, M.
773 $tEuropean Journal of Agronomy, November 2018$gv. 101, p. 193-199. Doi: https://doi.org/10.1016/j.eja.2018.10.004
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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
27/07/2022 |
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Actualizado : |
27/02/2023 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
NAVAJAS, E.; RAVAGNOLO, O.; DE BARBIERI, I.; PRAVIA, M.I.; AGUILAR, I.; LEMA, O.M.; VERA, B.; PERAZA, P.; MARQUES, C. B.; VELAZCO, J.I.; CIAPPESONI, G. |
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Afiliación : |
ELLY ANA NAVAJAS VALENTINI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OLGA RAVAGNOLO GUMILA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA ISABEL PRAVIA NIN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OSCAR MARIO LEMA QUEIJO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; BRENDA VERA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PABLO PERAZA DOS SANTOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CAMILA BALCONI MARQUES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JOSÉ IGNACIO VELAZCO DE LOS REYES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS GABRIEL CIAPPESONI SCARONE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Genetic selection of feed efficiency and methane emissions in sheep and cattle in Uruguay: progress and limitations. [29] |
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Complemento del título : |
Part 5 - Novel traits: environment and greenhouse gas- |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
In: Proceedings of the World Congress on Genetics Applied to Livestock Production (WCGALP), 12., Rotterdam, the Netherlands, 3-8 July 2022. doi: https://doi.org/10.3920/978-90-8686-940-4_29 |
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Páginas : |
164-167. |
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DOI : |
10.3920/978-90-8686-940-4_29 |
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Idioma : |
Inglés |
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Notas : |
Article history: Published online: February 9, 2023. -- Corresponding author: E.A. Navajas, email: enavajas@inia.org.uy -- Acknowledgements: The authors acknowledge the funding organizations INIA, Agencia Nacional de Investigación e Innovación (RTS_1_2012_1_3489), the European Union?s Horizon 2020 research and innovation program under grant agreement No 772787 (SMARTER) and the SusAn, ICT-AGRI 2 and FACCE ERA-GAS funding bodies (GrassToGas project). |
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Contenido : |
ABSTRACT.- Residual feed intake (RFI) and methane (CH4) emissions are potential new selection objectives in beef and sheep breeding programmes to assist reaching greenhouse gas mitigation targets and to support economic, social, and environmental sustainability. Phenotyping platforms in both species are in place in Uruguay, linked with the genetically evaluated populations of main breeds (Hereford, Merino, Corriedale, Dohne and Texel), being the basis of the reference populations for genomic selection. Current progress and main findings are described here. New selection indexes and selection criteria, as residual CH4, are needed given the potential unfavourable associations between CH4 and performance. Larger reference populations imply higher genomic prediction accuracies, accurate estimations of genetic correlations among feed intake, RFI, CH4 and performance and a comprehensive understanding of these associations. On-going rumen metagenomics and metatrascriptomics will also provide information about its value as predictor of genetic merit of these traits. |
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Palabras claves : |
Beef breeding programmes; Greenhouse gas (GHG) mitigation; Methane (CH4) emissions; Sheep breeding programmes. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16995/1/978-90-8686-940-4-29.pdf
https://www.wageningenacademic.com/doi/epdf/10.3920/978-90-8686-940-4_29
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Marc : |
LEADER 02623nam a2200313 a 4500
001 1063460
005 2023-02-27
008 2022 bl uuuu u01u1 u #d
024 7 $a10.3920/978-90-8686-940-4_29$2DOI
100 1 $aNAVAJAS, E.
245 $aGenetic selection of feed efficiency and methane emissions in sheep and cattle in Uruguay$bprogress and limitations. [29]$h[electronic resource]
260 $aIn: Proceedings of the World Congress on Genetics Applied to Livestock Production (WCGALP), 12., Rotterdam, the Netherlands, 3-8 July 2022. doi: https://doi.org/10.3920/978-90-8686-940-4_29$c8686
300 $a164-167.
500 $aArticle history: Published online: February 9, 2023. -- Corresponding author: E.A. Navajas, email: enavajas@inia.org.uy -- Acknowledgements: The authors acknowledge the funding organizations INIA, Agencia Nacional de Investigación e Innovación (RTS_1_2012_1_3489), the European Union?s Horizon 2020 research and innovation program under grant agreement No 772787 (SMARTER) and the SusAn, ICT-AGRI 2 and FACCE ERA-GAS funding bodies (GrassToGas project).
520 $aABSTRACT.- Residual feed intake (RFI) and methane (CH4) emissions are potential new selection objectives in beef and sheep breeding programmes to assist reaching greenhouse gas mitigation targets and to support economic, social, and environmental sustainability. Phenotyping platforms in both species are in place in Uruguay, linked with the genetically evaluated populations of main breeds (Hereford, Merino, Corriedale, Dohne and Texel), being the basis of the reference populations for genomic selection. Current progress and main findings are described here. New selection indexes and selection criteria, as residual CH4, are needed given the potential unfavourable associations between CH4 and performance. Larger reference populations imply higher genomic prediction accuracies, accurate estimations of genetic correlations among feed intake, RFI, CH4 and performance and a comprehensive understanding of these associations. On-going rumen metagenomics and metatrascriptomics will also provide information about its value as predictor of genetic merit of these traits.
653 $aBeef breeding programmes
653 $aGreenhouse gas (GHG) mitigation
653 $aMethane (CH4) emissions
653 $aSheep breeding programmes
700 1 $aRAVAGNOLO, O.
700 1 $aDE BARBIERI, I.
700 1 $aPRAVIA, M.I.
700 1 $aAGUILAR, I.
700 1 $aLEMA, O.M.
700 1 $aVERA, B.
700 1 $aPERAZA, P.
700 1 $aMARQUES, C. B.
700 1 $aVELAZCO, J.I.
700 1 $aCIAPPESONI, G.
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