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Good opportunities for international collaboration to combine methane data
Combining methane data from multiple countries is essential to make progress in all countries. That is the conclusion Yvette de Haas, researcher at Wageningen UR Livestock Research made after investigating the opportunities to collate data on methane (CH4) from multiple sources during a 9-week sabbatical in Melbourne, Australia. Her study included data recorded in 5 countries, and she showed that the correlations were all positive. This strengthens the hypothesis that international collaboration is essential to make progress in each country.
Since the 2015 Paris Climate Conference it is even more clear that greenhouse gas (GHG) emissions of livestock has to reduce in order to fulfil the target set at that conference. One of the GHG is enteric methane of ruminants. Genetic can be a useful tool to lower the emissions, however, it requires data on many individual animals.
Climate change is a growing international concern and it is well established that the release of GHG is a major contributing factor. Within Breed4Food we work also on the reduction of enteric CH4 of dairy cattle, by exploring the possibilities to breed for lower-emitting cows. Measuring CH4 emissions from cows is challenging and expensive, thus individual experiments typically record only a limited number of records for this trait, generally too few to enable accurate estimates of genetic parameters, and genomic predictions. One solution to this would be to combine information from multiple experiments that have been collected in different countries.
An attempt for that was initiated by Yvette de Haas. The work was based on data from NL, DK, AUS, UK and IRL. In total, 12,820 weekly CH4 emission records from 2,857 cows were available. Although different equipment was used across countries to measure methane emissions, we aimed to define similar methane output phenotypes in each country. The analysed methane traits, that are available in each country, are (1) methane production in g/d, and (2) methane intensity in g/d per kg fat protein corrected milk (FPCM). Genetic variation has been shown for these traits, and correlations between countries show that it is possible to merge data from different experiments. This opens up possibilities to collaborate and extend the database. The approach is novel and no other attempt has been performed before to make genetic analysis of methane traits across countries. The analysis can be repeated in future studies when more data hopefully will be available.