Abstract
The rapid evolution of humanity has led to a drastic increase in Green House Gas (GHG) levels in the atmosphere. This has caused an unprecedented rise in the Earth’s surface temperature, resulting in Global Warming and Climate Instability. 30% of the current rise in global temperature is due to Methane (CH4). However, approximately 60% of global CH4 emissions are man-made. Agriculture is the primary source of anthropogenic CH4 emissions, from which 40% originates, primarily generated by Livestock. Cattle are the most prolific contributor of CH4 amongst all Livestock, responsible for 77% of emissions. Despite the current situation, the human population continues to grow, and is expected to reach 9.7 billion by 2050, placing even further pressure on Agricultural production systems. Therefore, Cattle CH4 emissions must be harnessed, so that the expected population growth can be catered for, without further damaging the Earth’s already strained climate. Selective Breeding of low CH4 emitting dairy cattle (DC) is a cutting- edge approach in the mitigation of Agricultural CH4 emissions. Several studies have shown that CH4 emissions in DC have a genetic component which is heritable. Therefore, Selective Breeding of low CH4 emitting DC has a permanent, compounding effect over time, as future generations inherit the low CH4 emission characteristics of their more efficient ancestors. Machine Learning (ML) models are a groundbreaking option for the identification of low CH4 emitting DC. Their incredible ability to facilitate cross talk between a diverse range of features, makes them ideal for modelling the intricate relationships between the biological, environmental, and genetic factors behind CH4 production. Therefore, my PhD project aims to develop a ubiquitous ML framework which can incorporate complex biological, environmental and genetic factors for the accurate prediction of DC CH4 emissions so that low CH4 emitting DC can be identified for Selective Breeding.
Original language | English |
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Publication status | Unpublished - May 2023 |
Event | Festival of PhD Research - Ulster University, Belfast, Northern Ireland Duration: 10 May 2023 → 11 May 2023 |
Conference
Conference | Festival of PhD Research |
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Country/Territory | Northern Ireland |
City | Belfast |
Period | 10/05/23 → 11/05/23 |
Keywords
- Dairy Cattle
- Methane
- Machine Learning
- Selective Breeding