Digital twins in animal farming: Tackling climate change and enhancing sustainability

The agricultural sector is currently at the forefront of global sustainability efforts, particularly as the planet faces increasingly severe environmental challenges. With technological advancements rapidly transforming industries, agriculture is now experiencing a wave of innovation that offers potential solutions to some of its most pressing problems. Among these advancements is the digital twin—a virtual model that mirrors physical systems in real time, providing data-driven insights into various processes. In animal farming, digital twins offer transformative potential by improving operational efficiency, ensuring animal welfare, and most critically, reducing the sector’s environmental footprint.

Climate change poses a significant threat to global food security, and agriculture remains one of the largest contributors to greenhouse gas (GHG) emissions. The livestock industry, in particular, is under growing pressure to become more sustainable. In this context, digital twins present an innovative and scalable solution for reducing emissions, optimizing resource use, and contributing to global climate action. Here, we explore the role of digital twins in animal farming, their immediate relevance in tackling climate change, and how they offer a path toward more sustainable and resilient agricultural practices.

Why now? The urgency of climate action in agriculture

The global climate crisis is worsening at an alarming rate. As temperatures rise, sea levels increase, and extreme weather events become more frequent, the impacts on agricultural productivity are becoming clear. Agriculture, especially livestock farming, is a key contributor to global greenhouse gas emissions. The Food and Agriculture Organization (FAO) estimates that livestock farming is responsible for around 14.5% of global GHG emissions, primarily from methane produced through enteric fermentation in ruminants and nitrous oxide from manure management practices. These emissions are among the most potent and persistent contributors to global warming.

The Intergovernmental Panel on Climate Change (IPCC) has issued repeated warnings about the necessity for immediate action to avoid catastrophic climate outcomes. Without significant interventions, global warming could increase by 1.5°C as soon as 20305, leading to widespread consequences for ecosystems, weather patterns, and food production. Agriculture is not only impacted by climate change but also plays a crucial role in both mitigating and exacerbating it. As global populations increase—projected to reach nearly 10 billion by 2050—the demand for food is expected to grow by 70%, putting immense pressure6 on the environment.

The question facing the agriculture sector is no longer whether to adopt new technologies but why such solutions, particularly digital twins, must be integrated now. Every year of delay exacerbates the environmental impacts of agriculture, making it increasingly difficult to meet global food demand in a sustainable way. Immediate integration of digital twins can help farmers reduce emissions, optimize resource use, and adjust to the rapidly changing environmental conditions affecting agriculture worldwide.

What are digital twins?

Digital twins are data-driven, real-time models of physical or biological or an integrated physico-biological systems that allow for constant monitoring, simulation, and optimization. In the context of animal farming, these digital replicas gather data from sensors embedded in barns, on animals, and throughout the farming infrastructure. The collected data feeds into advanced algorithms that enable farmers to predict and simulate a wide range of scenarios, from health and behavior changes in livestock to shifts in environmental conditions. These real-time simulations offer a means to optimize various aspects of farm management, from feeding strategies to waste disposal, energy use, and animal welfare. The ability to mirror farm operations allows for adjustments to be made on the fly, reducing resource waste and minimizing the environmental impact of farming activities. In livestock farming, digital twins offer unparalleled potential to track emissions, monitor animal health, and provide more sustainable farming practices.

The role of digital twins in tackling climate change

Digital twins offer significant opportunities for emission reduction and sustainability in animal farming. Through the integration of sensors, AI, and machine learning, digital twins can continuously assess, adjust, and optimize farming operations. This adaptability provides key solutions for some of the most pressing environmental issues facing livestock farming today.

1. Optimizing feed efficiency and reducing methane emissions

Methane, produced during the digestive process of ruminants such as cattle, is one of the largest contributors to greenhouse gas emissions in livestock farming. Though methane remains in the atmosphere for a shorter period than carbon dioxide, it is far more potent at trapping heat, with an impact on the greenhouse effect up to 100 times greater than that of carbon dioxide. Methane emissions from enteric fermentation significantly contribute to the environmental footprint of livestock production.

Digital twins provide farmers with the ability to simulate and test different feeding strategies in real time. By modeling how various feed compositions affect methane production, farmers can make informed decisions that reduce methane output without compromising the health11 or productivity of their livestock12. Research has shown that the use of specific feed additives, such as seaweed, can reduce methane emissions13 by up to 80%. However, the implementation of these strategies requires careful monitoring to avoid adverse effects on animal health and productivity. Digital twins offer an effective solution by continuously monitoring the impact of these additives and making real-time adjustments as necessary.

This data-driven approach to feeding optimization not only reduces methane emissions but also enhances the overall efficiency of resource use. Farmers can achieve a delicate balance between environmental sustainability and productivity, ensuring that livestock remains healthy while minimizing their contribution to climate change.

2. Improving waste management systems

Manure management presents another significant challenge for livestock farmers, as it is a major source of both methane and nitrous oxide emissions. Improper storage and disposal of manure can lead to the release of these harmful gases, further exacerbating the environmental impact of farming practices. However, digital twins allow for the simulation and optimization of manure management systems, providing farmers with strategies to mitigate emissions while also making use of manure as a valuable resource.

By modeling various manure handling techniques, such as anaerobic digestion, digital twins can help farmers capture methane before it is released into the atmosphere. In anaerobic digestion, the methane produced from manure is converted into biogas, which can be used as a renewable energy source on the farm. This dual-purpose approach not only reduces emissions but also generates energy, making the farm more energy-efficient and sustainable. Through the use of digital twins, farmers can test the efficiency of different manure management strategies without risking real-world losses. These virtual models provide an evidence-based approach to reducing waste, capturing valuable resources, and minimizing emissions.

3. Monitoring animal welfare and reducing resource waste

There is an intrinsic connection between animal welfare and environmental sustainability14. Healthier animals are more productive, require fewer resources, and contribute less to the overall environmental impact of farming. Monitoring animal welfare, therefore, becomes an important component of reducing the carbon footprint of livestock farming.

Digital twins allow for continuous, real-time monitoring of animal health, behavior, and overall well-being. Sensors attached to animals can track vital signs such as heart rate, body temperature, and movement. This data provides farmers with early warnings of potential health issues, allowing for timely interventions before the problem escalates. By detecting illness or stress early, farmers can reduce the need for antibiotics and other interventions that have negative environmental impacts. Optimizing feed intake, water use, and energy consumption is another key area where digital twins make a difference. By monitoring these resources in real time, digital twins ensure that they are used as efficiently as possible, reducing waste and lowering the overall environmental footprint of the farm. 

4. Enhancing energy efficiency and reducing carbon footprint

The agricultural sector is energy-intensive, with substantial amounts of electricity and fuel required for the daily operation of barns, heating systems, ventilation, and lighting. Digital twins offer a way to optimize energy use by monitoring consumption in real time and making adjustments based on immediate needs. By analyzing the data collected from energy use sensors, digital twins can suggest real-time changes to reduce unnecessary consumption. For example, they can adjust heating and ventilation systems based on current weather conditions or animal needs. Additionally, digital twins can help integrate renewable energy sources such as solar panels or wind turbines into the farm's operations. By aligning energy use with sustainable sources, farmers can further reduce their carbon footprint while maintaining operational efficiency. The ability to predict and simulate energy use scenarios means that farmers can plan for seasonal variations in energy needs, ensuring that they remain sustainable throughout the year. In turn, this reduces the reliance on fossil fuels and lowers overall emissions.

Socio-economic and environmental impacts

The introduction of digital twins into animal farming is not only environmentally beneficial but also offers a range of socio-economic advantages. Environmentally, reducing GHG emissions and improving resource efficiency directly contribute to global efforts to combat climate change. The Paris Agreement, which seeks to limit global warming to well below 2°C, emphasizes the role of agriculture in achieving these goals.

Economically, digital twins have the potential to increase farm profitability by reducing waste, optimizing resource use, and lowering operational costs. For smaller farms that often struggle to invest in new technologies, digital twins provide an affordable and scalable solution that can improve efficiency without compromising their financial stability. As technology becomes more accessible, digital twins can help bridge the gap between large industrial farms and smaller operations, fostering more equitable and sustainable food production systems.

The technology also plays a crucial role in democratizing innovation within the agri-food ecosystem. Smaller farmers, who may lack access to advanced tools and insights, can now utilize digital twins to optimize their operations. This not only enhances sustainability at the individual farm level but also has broader implications for regional and national food systems. By making cutting-edge technology more accessible, digital twins can reduce disparities between different farming practices and regions.

Overcoming challenges to adoption

While the benefits of digital twins are evident, several barriers to their widespread adoption remain. The initial investment in sensors, infrastructure, and digital twin software can be prohibitive, particularly for smaller farms. Additionally, the technical expertise required to implement and maintain these systems is another significant hurdle, especially in rural areas where access to training and resources may be limited.

To overcome these challenges, governments and private organizations must work collaboratively to provide financial incentives and technical support. Public-private partnerships can help fund the infrastructure needed for digital twins, while subsidies and tax incentives can encourage farmers to adopt these systems. Additionally, training programs aimed at providing farmers with the necessary technical skills are essential to ensure that they can effectively manage and utilize digital twins. Ensuring access to high-speed internet in rural areas is also critical. As farms become increasingly data-driven, reliable internet connectivity is required for real-time monitoring and adjustments. Governments must invest in rural broadband (5G/6G) infrastructure to ensure that farmers can fully benefit from the advantages of digital twin technology

A path to climate-resilient farming

The future of agriculture is digital, and digital twins are leading the charge toward a more sustainable and climate-resilient industry. By providing real-time insights, optimizing resource use, and reducing emissions, digital twins enable farmers to make data-driven decisions that benefit both their operations and the environment. The time to act is now. Climate change presents an existential threat to global food security, and the agricultural sector must embrace innovative solutions to reduce its environmental impact.

The integration of Artificial Intelligence, machine learning, and digital twins represents a critical turning point for agriculture. By adopting these technologies, farmers can meet the growing global demand for food while reducing their contribution to climate change. Digital twins offer a unique and scalable solution to one of the most pressing challenges of our time, helping to create a future where productivity and sustainability go hand in hand. The potential for digital twins to transform animal farming is clear. With the right investments, training, and infrastructure, the farming industry can harness this technology to ensure a more sustainable, efficient, and climate-resilient future for generations to come.

Footnotes

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[3] Neethirajan, S., 2023. Innovative Strategies for Sustainable Dairy Farming in Canada amidst Climate Change. Sustainability, 16(1), p.265. https://doi.org/10.3390/su16010265

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[8] Ravishankara, A.R., Kuylenstierna, J.C., Michalopoulou, E., Höglund-Isaksson, L., Zhang, Y., Seltzer, K., Ru, M., Castelino, R., Faluvegi, G., Naik, V. and Horowitz, L., 2021. Global methane assessment: Benefits and costs of mitigating methane emissions (No. Job No: DTI/2352/PA). United Nations Environment Programme.

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[10] Bi, Hanqing and Neethirajan, Suresh, Utilizing Satellite Data and Machine Learning for Benchmarking Methane Emissions in the Canadian Dairy Industry (June 03, 2024). http://dx.doi.org/10.2139/ssrn.4939071

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[13] Abbott, D.W., Aasen, I.M., Beauchemin, K.A., Grondahl, F., Gruninger, R., Hayes, M., Huws, S., Kenny, D.A., Krizsan, S.J., Kirwan, S.F. and Lind, V., 2020. Seaweed and seaweed bioactives for mitigation of enteric methane: challenges and opportunities. Animals, 10(12), p.2432. https://doi.org/10.3390/ani10122432

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