Estimation of Variance Components for Methane Emission in Dairy Cattle

Recently several studies had been conducted to estimate the production of methane (CH4) and other greenhouse gases. Several authors have proposed mitigation strategies to reduce CH4 emissions. Some of them are: to reduce the number of ruminant animals, to increase the number of non-ruminant animals, genetic selection for low emission, modulation of methanogenic rumen microorganisms, dietary manipulation and nutritional development of breeds with lower rate of CH4 emissions. The available information on genetic parameters of CH4 emissions in dairy cattle is limited. The aim of this study was to estimate variance components for production and emission of methane in dairy cattle. Data from 313 dairy cows in four production systems in Mexico were used. CH4 measurement was carried out for 20 days at the time of milking as described by Garnsworthy et al (2012). DNA samples were obtained from hair follicle to obtain SNP genotypes. After quality control and identification of markers on both platforms the number of markers available was 20,776 SNP. The estimation of variance components was performed by mixed models and an animal model with the genomic relationships matrix. Analyses were implemented in the ASREMlL-R 3.0 (Gilmour et al. 2009). The heritability estimated for CH4 emission was 0.30 ± 0.21. Similar results had been reports previously (Haas et al., 2011 and Pickering et al2015). The information suggests that it is possible to propose the implementation of breeding programs as a strategy for climate change mitigation.