• From 24 to 28 February, CIHEAM Zaragoza hosted the course “Cattle breeding for low methane emissions: From farm measurement to genetic progress” as part of the Re-Livestock project and within the framework of the Mediterranean Network on Greenhouse Gases in Agriculture.
• The training activity was jointly organised by CIHEAM Zaragoza, the Basque Institute for Agricultural Research and Development (NEIKER), and the Global Research Alliance on Agricultural Greenhouse Gases (GRA); in collaboration with Wageningen University and Research (WUR) and the National Institute for Agricultural and Food Research and Technology of the Spanish National Research Council (INIA-CSIC).

From farm measurement to genetic improvement

The course attracted 43 participants from 21 countries across Europe, Africa, America, and Oceania. Attendees included researchers, academics, and representatives from breeders’ associations and genetic companies working in cattle breeding to reduce methane emissions. Delivered by 15 prominent lecturers from international universities, research centres, and companies, the course fostered an exchange of experiences and perspectives among participants and lecturers. The programme combined lectures with practical work, technical visits, and case studies.

David Yáñez (CSIC-EEZ) introduced the Re-Livestock project, while Birgit Gredler-Grandl (Wageningen University and Research) provided an overview of the course structure and activities. The opening lecture, given by Hayden Montgomery (Global Methane Hub) and Roel Veerkamp (Wageningen University and Research), addressed the current emissions associated with livestock production and ongoing mitigation efforts. Aser Garcia and Idoia Goiri (NEIKER) followed with a lecture on the characteristics, advantages, and disadvantages of various methane recording techniques.

Lisanne Koning and Coralia Manzanilla-Pech (Wageningen University and Research), alongside Oscar González-Recio and Ester Terán (CSIC-INIA), presented techniques for processing and analysing GreenFeed and Sniffer data. In a hands-on session, they demonstrated how raw methane data can be transformed into traits for use in genetic modelling. Another practical session focused on estimating genetic parameters for different methane traits, with guidance from Birgit Gredler-Grandl and Coralia Manzanilla-Pech. Later, Amélie Vanlierde (Walloon Agricultural Research Centre) introduced mid-infrared spectroscopy, while Oscar González-Recio and Suzanne Rowe (AgResearch) shared insights into how to use the rumen microbiome as a proxy method for methane measurement.

Discussions on integrating methane traits into national breeding programmes featured case studies from several countries. Oscar González-Recio presented Spain’s approach, Lorna McNaughton (LIC) shared insights from New Zealand, Jennie Pryce (La Trobe University) covered Australia’s initiatives, Christopher Orrett (CRV) discussed developments in the Netherlands, and Filippo Miglior (University of Guelph) provided an overview of Canada’s efforts.

The course concluded with a field trip to observe methane measurement devices in operation. At the Fraisoro Eskola dairy farm, Aser Garcia, Idoia Goiri, and NEIKER technicians demonstrated GreenFeed, sniffer systems, and laser methane detectors, while respiration chambers were showcased at the NEIKER experimental farm.

Lessons learned

Like all economic activities, livestock production is a source of greenhouse gases (GHG) that contribute to global warming. Of the GHGs produced by livestock production, methane from enteric fermentation in ruminants is the most important, accounting for about 30% of total global methane emissions.

Currently several techniques are being developed to decrease methane emission in livestock production, including additives, vaccines, modification of rumen microbiome and genetic selection.

Genetic selection is one of the most promising tools to decrease methane emissions in ruminants to be applied in the short term. Genetic improvement to reduce methane emissions is based on identifying and breeding cattle with low methane emissions and developing genetic models for national breeding programmes. This strategy is relatively easy to integrate into routine farm management, is cost effective and provides long-term results. Existing genetic modelling techniques could be easily applied in breeding programmes to reduce methane emissions; however, this type of breeding programme is difficult to implement.

The first issue on using genetic selection as a tool to reduce methane in ruminants is associated with difficulties to identify low-emitting cows. Phenotyping cows for emissions requires measuring methane from a large number of individuals on different farms using expensive and complex equipment which also raises questions about the reliability and comparability of different methods to record methane emissions. The most common equipment used to record methane emissions are Sniffer and GreenFeed, both based on estimating the quantity of methane from cattle breath. Different countries rely on different methods to measure methane, for instance, Spain and Denmark use Sniffer for cow phenotyping. Norway and New Zealand use GreenFeed; and the Netherlands combine Sniffer and Greenfeeds to phenotype cattle. Other countries such as France, Belgium, Canada and Ireland rely on mid-infrared spectroscopy (MIR) to estimate methane emissions. MIR is based on estimating content of fatty acids in milk, a proxy indicator for methane emissions. All these methods present a series of advantages and disadvantages, and there is not enough scientific evidence to determine whether they are reliable or comparable.

A second issue to implement breeding programmes as tool to reduce methane emission is related with the standardisation, curation and construction of large databases containing information of phenotyped animals. Large datasets are required to obtain reliable breeding values for methane traits. In this regard, a first limitation on constructing large datasets is that measurement is time consuming. In many cases measurement devices require adaptation periods for cows to learn to use them. Correct phenotyping also requires several measures for each animal, meaning that recording devices must remain on one farm for several weeks or months.  A second limitation lies in the need to standardise registration methods and deal with legal issues related with data acquisition and ownership. Several projects are currently combining efforts to create a large dataset of ruminants phenotyped for methane. One of the largest databases contains >28,000 phenotyped Holstein cattle, the aim being to have information for >110,000 cattle and sheep.

The final issue concerning implementation of breeding programmes is related to the lack of policy and incentive for farmers to adopt breeding programmes to decrease methane emissions. Currently there is no legislation to regulate and promote strategies to decrease emissions in livestock production. In most cases, incentives for farmers come from private initiatives, for instance, in the Netherlands some dairy companies pay an extra fee for farmers for reduction of emissions. In other countries there is ongoing discussion on including incentives for farmers based on carbon markers.

Despite these challenges, genetic selection remains a viable and effective strategy for reducing methane emissions from ruminants. By improving methane measurement techniques, standardising data collection and overcoming logistical barriers, genetic selection can make a significant contribution to climate change mitigation while ensuring the sustainability of livestock production systems.

About Re-Livestock

Re-Livestock “Facilitating Innovations for Resilient Livestock Farming Systems” is a Horizon Europe project (GA No.101059609) aiming to evaluate and mobilise the adoption of innovative practices applied cross-scale (animal, herd, farm, sector and region) to reduce GHG emissions from livestock farming systems and increase their capacity to deal with potential climate change impacts. To reach our aim, Re-Livestock has brought together scientific expertise in Europe and Australia and across disciplines, including co-innovation, animal feeding, breeding, welfare, farm management, environmental and socioeconomic assessment and policy analysis, to develop novel and scientifically supported integrated approaches specific for different dairy, beef and pig systems and geographic regions in the context of climate change. Strong collaboration with industry stakeholders to identify the innovations and to co-design the validation will ensure relevance and maximise the adoption of best practices. National groups of farmers (case studies) and ‘stakeholder forums’ together with a ‘European multi-actor platform’ will allow for an engaged co-design of transition pathways whilst ‘learning from innovation networks’ to test and share the latest innovative solutions. A ‘community of practice’ will extend the multi-actor approach to a broad range of stakeholders.