PSVIII-19 Assessing methane and carbon dioxide production in beef cows across diverse foraging conditions
Bibliographic record
Abstract
Abstract Beef cattle grazing across more than 40M ha of Canada’s grasslands is economically significant yet contributes to methane (CH4) emissions. Accurately measuring CH4 emissions across diverse environments presents substantial challenges. Our study investigated CH4 and carbon dioxide (CO2) production in 3-yr-old pregnant crossbred beef cows (n = 30) across different phases of the beef production cycle, including in drylot and while grazing on native rangeland, in Western Canada’s Aspen Parkland region using the GreenFeed Emissions Monitoring System (GEM). During the January to March drylot phase, enteric CH4 and CO2 production of the cows were monitored for 63 d in consort with feed efficiency testing while consuming a mixed oat-barley silage diet. Following this, cows were categorized into three distinct groups based on the standard deviation (SD) of CH4 yield [gּ kg−1 dry matter intake (DMI)]: Low (< 0.5 SD; n = 11), Medium (± 0.5 SD; n = 10), and High (> 0.5 SD; n = 9). Post-calving, cows and calves transitioned to native pastures for CH4 and carbon dioxide (CO2) assessment across three distinct foraging conditions: high-quality, high-quantity forage in summer (SUM; 50 d); moderate-quality, high-quantity forage in September (SEP; 22 d); and finally, low-quality, low-quantity forage in October (OCT; 22 d). We hypothesize that ranking cows based on their CH4 yield (gּ kg−1 DMI) in drylot settings may have the potential to reflect their CH4 production (g/d) during grazing conditions, even without feed intake data. Data were analyzed using the PROC MIXED procedure of SAS to examine CH4 production among cows categorized by their assigned ranking. Spot CH4 and CO2 measurements totaled 1,242, 1,145, and 1,205 for the SUM, SEP, and OCT, production phases, respectively. Average daily visits to GEM units were 1.4 ± 0.1, 1.84 ± 0.1, and 1.96 ± 0.1 for the corresponding phases. While High CH4-ranked cows had methane production similar to Low CH4-ranked cows (234.8 ± 8.2 vs. 235.0 ± 6.0 g/d, respectively), the Medium group had significantly greater methane production (260.5 ± 6.2 g/d; P = 0.008) than the Low and High CH4 groups. Furthermore, significant interactions were observed between CH4 ranking groups and CH4 production during the grazing phase (P = 0.035). Cows in the Medium CH4 group emitted greater amounts of CH4 compared with the High group in SUM (288.2 ± 9.3 vs. 247.0 ± 14.1 g/d) and to the Low group in SEP and OCT (276.5 ± 6.6 vs. 238.1 ± 6.3, and 216.7 ± 7.2 vs. 191.8 ± 7.5 g/d, respectively). In conclusion, the drylot CH4 ranking may hold promise in predicting outcomes for both Low and Medium CH4-ranked groups during grazing phases. However, High CH4-ranked cows had decreased methane production, likely influenced by grazing-induced changes in feed intake and individual feeding behaviors, prompting further exploration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".