New open-source tool streamlines GreenFeed livestock emissions data analysis

May 15, 2025 by Elsevier

Collected at: https://phys.org/news/2025-05-source-tool-greenfeed-livestock-emissions.html

The dairy and agriculture sectors’ pursuit of sustainability and efficiency has fueled a dramatic expansion in research aimed at understanding and reducing livestock greenhouse gas emissions. Central to this effort is the ability to accurately measure methane and carbon dioxide output from cattle on a large scale. GreenFeed is a popular tool helping researchers and producers measure emissions in real time.

A new open-source tool, greenfeedr—outlined in a new technical note in JDS Communications—is simplifying processing and data reporting from GreenFeed systems, making it easier to get flexible, useful, and impactful data and accelerate the work toward a sustainable future for dairy and livestock production.

GreenFeed systems are portable head chambers that measure individual animal gas production in real time, generating substantial amounts of data. Animals voluntarily use the machine, receiving pelleted feed throughout the day, meaning that the system gathers data 24 hours a day, often for weeks at a time. While all of these data are crucial for researchers and producers aiming to understand and mitigate livestock’s contribution to climate change, it comes with challenges. Managing and analyzing this high volume of data—especially across different research projects, dairy herds, and teams—are often time consuming and can lead to error and data inconsistencies.

Guillermo Martinez-Boggio, Ph.D., of the Department of Animal and Dairy Sciences, University of Wisconsin–Madison, and lead author of the article, said, “The sheer volume of data produced by GreenFeed systems can be really overwhelming. We set out to create an open-source tool that simplifies this process, making it more efficient and reproducible, and flexible to the variety of situations in which these systems are used.”

Motivated by the principle of “doing as little as possible by hand and as much as possible with functions,” Dr. Martinez-Boggio, of the Peñagaricano Lab, developed greenfeedr—a toolkit with functions for downloading, processing, and reporting GreenFeed data—all freely and publicly available as an R package, an open-source software and programming language. Interested users can access greenfeedr on the Comprehensive R Archive Network (CRAN) at cran.r-project.org/web/packages/greenfeedr and its source code on GitHub at github.com/GMBog/greenfeedr .

The R package has functions for downloading GreenFeed data (get_gfdata), for generating daily and final reports (report_gfdata), for processing daily and final records (process_gfdata), and extra functions that help to extract information regarding pellet intakes and daily visits (pellin and viseat).

After development, the team demonstrated the package’s capabilities using data from 32 lactating dairy cows. The article demonstrates how greenfeedr can generate comprehensive reports and efficiently process large datasets, allowing for a detailed analysis of methane and carbon dioxide emissions. The package also permits user-defined parameters to allow the best use of each research group’s datasets.

Dr. Martinez-Boggio explained, “We wanted the tool to be as versatile as possible, so it was designed to be used with all livestock species and housing systems, including freestall, tiestall, and pasture-based.

This important advancement allows teams to automate routine processes as they gather data with GreenFeed systems, simplifying formerly complex workflows, saving time, and creating insightful outputs that can inform study results and farm management decisions.

This tool is expected to benefit researchers and producers by enhancing the efficiency and accuracy of GreenFeed data analysis, ultimately contributing to a better understanding of livestock emissions and the development of mitigation strategies.

More information: Guillermo Martinez-Boggio et al, greenfeedr: An R package for processing and reporting GreenFeed data, JDS Communications (2024). DOI: 10.3168/jdsc.2024-0662