Benchmarking Management Practices on Canadian Feedlots
Project Title
A Benchmark Study of the Canadian Feedlot Industry and an Evaluation of Best Management Practices (BMPs) to Improve the Sustainability of Feedlots
Researchers
Gabriel Ribeiro (University of Saskatchewan) gabriel.ribeiro@usask.ca
Greg Penner (University of Saskatchewan), Tim McAllister (AAFC Lethbridge), Stephanie Terry (AAFC Lethbridge), Kim Ominski (University of Manitoba), Katie Wood (University of Guelph), Brenna Grant (Canfax Research Services), Megan Van Schaik (OMAFRA), Mary Lou Swift (University of Saskatchewan and Trouw Nutrition), and Jenilee Peters (University of Saskatchewan and Trouw Nutrition)
| Status | Project Code |
|---|---|
| In progress. Results expected in March, 2028 | FDE.20.21C |
Background
Greenhouse gas estimates for the beef industry are often developed using lifecycle analysis (LCA), but an LCA is only as valuable as the data that has been added to it. In Canada, there is a data gap surrounding management practices in the feedlot including growth promotants and feed additives currently used in feedlots to help to improve efficiencies and reduce greenhouse gas production.
Objectives
- Provide a snapshot of the current beef cattle production, nutritional, and management practices adopted by beef producers.
- Evaluate the impact of BMPs adopted by the feedlots on production performance.
- Evaluate the applicability of fecal NIRS analysis as a management tool to improve the precision of nutritional practices and feed efficiency of beef cattle, reducing the environment impact Canadian beef production.
- Evaluate the impact of different by-products fed to cattle on feed efficiency and fecal NIRS spectra.
What they will do
These researchers will survey Canadian beef cattle feedlots over 1000 head on general feedlot management, feed sources and milling systems, feed and bunk management, nutrient composition, feed additives, antimicrobials, growth enhancing technologies used, animal health problems, and main sources of information.
From those who respond 20 will be selected based on location and will have feed, feces, and manure sampled every 2 months for 2 years with animal performance collected on the pens sampled. Feed processing will be evaluated. All samples will be scanned for NIR and sent for wet chemistry analysis. Correlation between NIR and feed source and animal performance. Researchers will then use feed sample NIR to determine if they can predict urinary and fecal N losses.
Finally, 10 feedlots will be selected to participate in a pilot study where feed, fecal, and manure samples will be collected once a month. Half of the group will receive a monthly report, the other half will not. The researchers will assess if feedlots made the recommended changes and if there was value provided to those who received the report.
Implications
This study will develop benchmarks for practices used in the Canadian feedlot sector. It will also help to further evaluate the use of fecal NIR to use in both research and on farm.