Dairy farming's environmental impact, notably nitrogen and methane emissions, prompts concern. If selecting cows for lower nitrogen and methane emissions becomes possible, sustainability could improve further (Van Breukelen et al., 2023; Chen, 2023). The presented project aims to estimate nitrogen use efficiency (NUE, milk N yield/N intake) and methane (CH4) production and intensity from milk samples, estimate heritability of these traits, and identify traits for co-selection by estimating genetic correlations of NUE and CH4. In an ongoing experiment (01/22 to 12/25), approximately 2,500 Swiss Holstein dairy cows in mid-lactation (90 and 250 days) are sampled on more than 40 private and cantonal farms. Gold-standard measurements of NUE and CH4 require expensive equipment that is usually only available on experimental farms, making it difficult to obtain the sample size of several thousand phenotyped animals required for genetic analyses. We will therefore rely on estimation via infrared spectroscopy (Grelet et al., 2019). In a subset of cows, feed intake and CH4 are recorded using feed-weigh throughs and the GreenFeed system, respectively. These data serve as reference for calibration equations for mid- and near- infrared spectroscopy (MIRS and NIRS). From all cows, milk, faeces, and feed samples are collected during three consecutive days. This will allow to estimate NUE and CH4 for each cow from milk and faecal samples. A univariate animal model will be used to estimate the heritability of NUE and CH4. To investigate if selection on these traits simultaneously will result in the desired genetic gain in both traits, and to estimate the correlations of NUE or CH4 with other traits, we will apply multivariate animal models. The data set for the quantitative genetics analysis is currently being compiled for the 600 cows that have been sampled so far. Overall, this comprehensive analysis is expected to aid in estimating genetic parameter of NUE and CH4, which can contribute to selection of more sustainable dairy cows.
