TY - ABST

T1 - Breeding for feed efficient and low methane-emitting dairy cows is feasible

AU - Manzanilla Pech, Coralia Ines V

AU - Stephansen, Rasmus Bak

AU - Lassen, Jan

PY - 2022/9

Y1 - 2022/9

N2 - Methane (CH4) is the second largest GHG, with a short half-life but more heat-trapping power than CO2. In Europe, the dairy cattle sector contribute with 37.5% of the total GHG emissions from livestock. Thus, the EU Commission has the aim of reducing GHG emissions to at least 55% by 2030 and reach neutrality by 2050. Using genetics to select for low methane emitting cows is a sustainable and permanent approach. In the last decade, several countries have included a feed efficiency index (including residual feed intake; RFI) in their breeding goal. Several studies have showed that RFI is favorably correlated with CH4 emissions. Consequently selecting for RFI could help reducing CH4 emissions. Could RFI alone or in combination with methane records help to reduce methane emissions in dairy cattle without compromising yield? Hence, the aim of this study was to 1) evaluate the expected correlated response of CH4 and milk production, when selecting for feed efficiency with or without including methane; 2) quantify the economic impact of reducing CH4 emissions in the Danish Holstein population; 3) compare our results with a previous study with a collation of 4 countries and 3 different CH4 measuring methods. Measurements of CH4 on 650 Holstein cows recorded between 2013 and 2020 at the Danish Cattle Research Center were available. Records on dry matter intake (DMI), body weight (BW), and energy corrected milk (ECM) were also available, and they were used to calculate RFI. Methane emissions and RFI were strongly correlated. Selecting for feed efficiency had a positive impact on reducing CH4 emissions; though, adding a negative economic value for methane would accelerate the reduction of emissions, although with a small impact in the genetic gain for milk production. These results confirmed earlier results with an international dataset with CH4 measurements from different methods.

AB - Methane (CH4) is the second largest GHG, with a short half-life but more heat-trapping power than CO2. In Europe, the dairy cattle sector contribute with 37.5% of the total GHG emissions from livestock. Thus, the EU Commission has the aim of reducing GHG emissions to at least 55% by 2030 and reach neutrality by 2050. Using genetics to select for low methane emitting cows is a sustainable and permanent approach. In the last decade, several countries have included a feed efficiency index (including residual feed intake; RFI) in their breeding goal. Several studies have showed that RFI is favorably correlated with CH4 emissions. Consequently selecting for RFI could help reducing CH4 emissions. Could RFI alone or in combination with methane records help to reduce methane emissions in dairy cattle without compromising yield? Hence, the aim of this study was to 1) evaluate the expected correlated response of CH4 and milk production, when selecting for feed efficiency with or without including methane; 2) quantify the economic impact of reducing CH4 emissions in the Danish Holstein population; 3) compare our results with a previous study with a collation of 4 countries and 3 different CH4 measuring methods. Measurements of CH4 on 650 Holstein cows recorded between 2013 and 2020 at the Danish Cattle Research Center were available. Records on dry matter intake (DMI), body weight (BW), and energy corrected milk (ECM) were also available, and they were used to calculate RFI. Methane emissions and RFI were strongly correlated. Selecting for feed efficiency had a positive impact on reducing CH4 emissions; though, adding a negative economic value for methane would accelerate the reduction of emissions, although with a small impact in the genetic gain for milk production. These results confirmed earlier results with an international dataset with CH4 measurements from different methods.

M3 - Conference abstract for conference

T2 - 73 Annual Meeting of the European Federation of Animal Science

Y2 - 5 September 2022 through 9 September 2022

ER -