AI Tools Help UK Farmers Cut Livestock Emissions and Boost Sustainability

AI-driven platform empowers UK farmers with real-time insights to cut methane emissions, improve land use efficiency, and contribute to the nation’s net zero goal.

Research: AI for sustainable land management and greenhouse gas emission forecasting: advancing climate action. Image Credit: Barillo_Images / Shutterstock

Loughborough University computer scientists have developed AI tools that offer insights into how greenhouse gas emissions associated with UK livestock farming and land use can be reduced.

The tools—hosted on an online digital platform and created as part of research funded by UK Research and Innovation (UKRI) and the Engineering and Physical Sciences Research Council (EPSRC)—aim to provide farmers, farming organizations, and government bodies with valuable data on how changes in livestock practices and land use can help the UK achieve its 2050 net zero goal.

Developed by a team led by Professor Baihua Li and Professor Qinggang Meng, the platform's key features include machine learning models designed to estimate methane emissions from livestock farming, predict milk productivity and ammonia emissions from dairy farms, and analyze how land use and environmental factors influence methane emissions across the UK.

"Our mission is to bridge the gap between innovation and practicality, offering a platform that supports data-driven decisions to combat climate change, advance sustainable farming, and achieve global net-zero emissions goals," said Professor Li.

"By harnessing AI, our platform can offer data-driven insights that can help forecast future emissions based on a diverse range of data, giving stakeholders actionable intelligence to make cost-effective proactive decisions."

Why tackling livestock emissions and promoting sustainable land use will help achieve net zero

Achieving net zero by 2050 requires balancing greenhouse gas emissions with their removal and storage in 'carbon sinks' – natural systems like forests, oceans, plants, and soil that absorb more carbon than they release.

Livestock farming plays a dual role. It contributes to greenhouse gas emissions—particularly methane and nitrous oxide, two potent heat-trapping gases—while also affecting the land's ability to function as a carbon sink through grazing, feed production, and pasture management.

Reducing farming's environmental impact is challenging. Emissions, interacting factors, such as animal breed, feed, pasture, climate shape emissions, carbon storage, and farm productivity. These factors vary across farms, making a one-size-fits-all approach ineffective.

Beyond livestock farming, land use significantly influences emissions. Different types of land—such as agricultural, woodland, or urban areas—interact with environmental factors to determine how much methane is released or absorbed. Understanding these complex interactions is essential for identifying the best strategies to minimize emissions.

The Loughborough University AI models provide a solution. Trained on diverse livestock and environmental datasets, they analyze how various factors interact to impact emissions, providing farm-level and nationwide insights that can help shape strategies to support the UK's net zero goal.

An in-depth look at the tools

The AI tools developed for livestock farms allow farmers to input details about their specific animals and practices to estimate their current annual greenhouse gas emissions. Farmers can easily explore potential changes to their practices by selecting options from drop-down menus or entering variable values. These adjustments provide immediate insights into their potential impact on emissions and farm productivity.

One tool is designed specifically for dairy farmers, helping them estimate how their current practices affect individual cow milk yield and ammonia levels in waste. Monitoring ammonia is crucial, as it interacts with soil microbes to produce nitrous oxide and may also indicate dietary imbalances. This development was made possible through the support of the National Bovine Data Centre and the Cattle Information Service.

Another tool, developed for beef farmers, predicts methane emissions for individual cows based on farm-specific data. It also helps farmers understand emissions in context by offering relatable comparisons-such as the number of trees needed to offset a cow's annual emissions, the equivalent emissions from flights between London and New York, or the months of energy use in an average UK household.

The team has also developed a livestock emissions calculator based on Intergovernmental Panel on Climate Change (IPCC) guidelines, the global standard for climate reporting. Suitable for farmers worldwide, it simplifies complex government formulas and presents them in a user-friendly format, helping farmers compare their emissions to official baselines.

Digital twin

Beyond farm-level tools, the research team has harnessed artificial intelligence to develop a user-friendly, web-based platform – referred to as a 'digital twin' – to provide detailed insights into how different types of land use affect methane emissions across the UK.

The digital twin features heat maps of ruminant livestock distribution, land cover types (such as agriculture, urban areas, and woodland), and methane emission concentrations across the UK. It integrates real-time satellite methane observations from Sentinel-5P TROPOMI, AI models, datasets, and various intuitive visualization tools.

Users can adjust parameters such as location, land cover percentages, seasons, and years to track historical changes and model future emission scenarios based on climate and land use projections.

The Loughborough team has analyzed the UK's methane emissions using the digital twin with early findings – intended for future publication in a peer-reviewed journal– indicating that methane emissions have been increasing year after year. Agriculture arable land and improved grassland used for livestock farming have also been identified by the researchers as key contributors closely linked to methane hotspots.

It is hoped the tool will be used by policymakers, government bodies, and farming organizations to deepen understanding of how environmental factors influence emissions and enable data-backed decisions to be made to reduce emissions.

Call for collaboration

Before the digital platform hosting the tools can be deployed to users, the Loughborough researchers need to further refine and test their AI models, which requires additional data.

The team is calling for the following collaborators:

• Individual farmers that can share data on their specific practices, for example, livestock details and feeding strategies
• Farming cooperatives and organizations that have data from multiple farms
• Governmental and regulatory bodies that manage compliance data and can provide historical and geographical data
• Agricultural research institutions
• Retailers and supply chain stakeholders with data relevant to the agricultural industry.

Professor Meng said: "We hope key stakeholders recognize the value of this platform, support efforts to achieve net zero emissions, and contribute essential data to help bring the technology to life, ultimately transforming our practises and ensuring a sustainable future for all."