INSIGHTS

Tackling Methane Emissions in Dairy Farming: A Collaborative Effort for Sustainable Agriculture

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Agriculture is a key driver of global food security, but it also significantly contributes to methane emissions, particularly from livestock. With the growing need to address climate change while enhancing agricultural productivity and reducing costs for farmers, a new initiative led by the University of California (UC Davis), college of Agricultural and Environmental Sciences, through its Department of Global Engagement, is making strides. This project, funded by the Global Methane Hub, is implemented over three years across 16 countries in Asia and Africa, including Thailand, Vietnam, Indonesia, and Ethiopia. It focuses on developing a Feed Ration Formulation (FRF) tool that balances cost, nutritional value, and availability of ingredients. This groundbreaking FRF tool integrates cutting-edge scientific models and data to optimize nutrient requirements for dairy cows. The tool is designed to reduce costs, improve milk yield, and cut methane emissions, ultimately contributing to more sustainable livestock farming.

At Digital Green, we are leading the effort to create a practical, user-friendly tool that connects researchers, extension workers, and farmers, allowing them to access optimized feed recommendations tailored to local conditions. This tool will empower farmers to make informed decisions about feed, reducing expenses while boosting productivity and aligning with global climate goals.

Field Piloting in Ethiopia

A significant milestone was reached in October 2024, when Digital Green, UC Davis, and Hawassa University conducted a field pilot of the Feed Ration Formulation tool in Ethiopia’s Kofele Woreda at Gurmicho and Wamagne Abosa Kebeles. Woreda and Kebele livestock experts participated in the pilot and provided very positive feedback on the tool’s usability and potential. These local experts highlighted the value of the tool in improving their extension services, noting its simplicity and its ability to provide feed recommendations that can enhance dairy productivity.

The primary purpose of the pilot was to conduct user research and gather a list of key improvements for the tool. These improvements will be added in the coming months as UC Davis finalizes the scientific model and other partners complete their respective feed libraries. Hawassa University and Haramaya University are specifically focused on building a comprehensive feed library with nutrient data for Ethiopia, which will be integral to the tool’s accuracy and utility in local contexts.

Expanding the Project’s Reach

In future phases, the project will expand beyond Ethiopia, with plans to roll out in India and other countries including Vietnam, Kenya, Uganda, Rwanda, and Bangladesh. This expansion will involve tailoring the tool to meet the specific needs of farmers in each country, with feed libraries and models adjusted to reflect local conditions and resources. The project will also work on integrating the tool into broader digital platforms to maximize its impact and accessibility.

Looking Ahead

As the project progresses into its next phase, the focus will be on enhancing the feed libraries, refining the tool’s features, and expanding its reach across multiple regions. In parallel, Digital Green is planning to integrate this tool with its Farmer.Chat platform, which would further enhance the tool’s accessibility to farmers. This initiative represents a significant step forward in sustainable agriculture by making cutting-edge science accessible to farmers, enabling them to reduce costs, improve productivity, and reduce their environmental impact.

This collaboration between Global Methane Hub, UC Davis, Digital Green, Hawassa University, and other partners marks a transformative effort toward a more sustainable and prosperous future for dairy farming.

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To learn more about Digital Green’s AI-powered platform and how it impacts small-scale farmers in India, Ethiopia, Kenya, Nigeria and Nepal, we encourage you to sign up for our newsletter.

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