AI-Driven Benchmarking Tool for Emission Reduction in Canadian Dairy Farms

Central to our project is the development of the Sustainable Dairy Farming Navigator (SDFN). This tool, leveraging artificial intelligence, is tailored to address the complexities of dairy farming. It functions by aggregating and analyzing data across various parameters including emissions, resource utilization, soil health, biodiversity, and animal welfare.

The primary objective is to equip dairy farmers with data-driven strategies to significantly reduce GHG emissions. This involves identifying key intervention points for emission reduction, thereby aligning farm practices with environmental targets.

The SDFN stands at the nexus of data analysis and farm management. It translates complex datasets into tangible, actionable advice for farmers, enabling alignment of day-to-day operations with long-term sustainability objectives.

Our approach includes establishing benchmarks for emissions and resource consumption, integrating these with other critical sustainability metrics. This endeavor necessitates collaborative efforts with dairy farmers, industry stakeholders, and processors, promoting an exchange of knowledge and a unified commitment to sustainable practices.


Lead Proponent: Suresh Raja Neethirajan

Institution: Dalhousie University

December 1, 2023 – March 31, 2025