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.
Proceedings of 12th World Congress on Genetics Applied to Livestock Production (WCGALP)
Technical and species orientated innovations in animal breeding, and contribution of genetics to solving societal challenges
EditorsR.F. Veerkamp and Y. de Haas
Published: 2022 Pages: 3364
eISBN: 978-90-8686-940-4
Book Type: Conference Proceedings
29. Genetic selection of feed efficiency and methane emissions in sheep and cattle in Uruguay: progress and limitations
E.A. Navajas Related information
1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
*Corresponding author: enavajas@inia. org. uy
, O. Ravagnolo Related information*Corresponding author: enavajas@inia.
1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, I. De Barbieri Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, M.I. Pravia Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, I. Aguilar Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, M.O. Lema Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, B. Vera Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, P. Peraza Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, C.B Marques Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, J.I. Velazco Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
, G. Ciappesoni Related information1Instituto Nacional de Investigación Agropecuaria, INIA Las Brujas, 90100, Rincón del Colorado, Canelones, Uruguay.
Pages: 164 - 167
Published Online: February 09, 2023
Abstract: