RUMENPREDICT

Predicting appropriate GHG mitigation strategies based on modelling variables that contribute to ruminant environmental impact.


Ruminant production is responsible for ~ 9% of anthropogenic CO2 emission and 37% of CH4 emissions. Release of methane results in 6-12% less energy being available to the animal. Ruminants also contribute towards NO2 within the environment, a persistent gas in the atmosphere which has 296 times more warming potential than CO2. RumenPredict brings together members of the international Rumen Microbial Genomics network (led by IBERS, AU), of which the Hungate 1000 (focussed on sequencing 1000 rumen microbes) and the Rumen Census (focussed on evaluating effects of diet, host genetics and geographical location on the rumen microbiome) are projects within.

RumenPredict brings together key members of the RMG network to generate the necessary data to link rumen microbiome information to host genetics and phenotype and develop feed based mitigation strategies. This will enhance innovative capacity and allow integration of new knowledge with that previously generated to devise geographic and animal-specific solutions to reduce the environmental impact of livestock ruminants. The project members have access to recent data/tools resulting from an array of projects, and RumenPredict will build upon and enhance the integration of knowledge generated from these projects whilst providing innovation through further testing and validation of key hypotheses resulting from the previously obtained data. RumenPredict will provide a platform for predicting how host genetics, feed additives or microbiome may affect emission phenotypes and develop genetic/diet/prediction technologies further for implementation to improve nitrogen use efficiency whilst decreasing environmental impact of ruminants.


Coordinator

Queen's University, Northern Ireland

Dr. Sharon Huws
Email: s.huws[at]qub.ac.uk

Project partners

Natural Resources Institute Finland, Finland

Agresearch, New Zealand

Swedish University of Agricultural Sciences, Sweden

Teagasc, Ireland

Irish Breeding Federation, Ireland

University College Dublin, Ireland

Wageningen University, The Netherlands

Institut National de Recherche en Agronomie (INRA), France


Total requested funding

1.592.000 €


Project duration

36 months