Predicted methane emissions and metabolizable energy intakes of steers grazing a grass/alfalfa pasture and finished in a feedlot or at pasture using the GrassGro decision support tool
Bibliographic record
Abstract
Dry matter intakes (DMI) and methane (CH4) emissions from steers grazing alfalfa/(Medicago sativa L)/meadow bromegrass (Bromus biebersteinii Roem & Schult.)/Russian wild ryegrass [Psathyrostachys juncea (Fisch.) Nevski] at 1.1 and 2.2 steers ha-1 in continuous and rotational grazing systems at Brandon, Manitoba, during the 1994 grazing season were predicted using the GrassGro decision support tool and compared with those reported from a field experiment. Observed DMI (13.82 ± 0.39 kg d-1) did not differ significantly (P = 0.052) from predicted DMI (12.10 ± 0.19 kg d-1). Mean predicted CH4 (278.5 ± 2.2 g d-1) was greater (P < 0.002) than field observations (195.8 ± 9.7 g d-1). This difference may reflect the difficulty of ensuring total collection of all CH4 emitted in a field experiment. GrassGro predicted that feeding a barley supplement to the steers while at pasture would cause a small though significant increase (P < 0.001) in mean daily emissions of CH4 (287.8 ± 1.9 g d-1) compared with unsupplemented steers (274.1 ± 2.9 g d-1). However, when CH4 emissions were compared as g kg-1 liveweight gain (LWG), they were less (P < 0.0001) for supplemented (133.2 ± 6.4 g kg-1 LWG) than unsupplemented steers (199.1 ± 5.9 g kg-1 LWG). In addition, supplementing barley at pasture would reduce (P < 0.0001) the total emissions of CH4 (38.7 ± 2.1 kg) compared with backgrounding at pasture and finishing in a feedlot (54.4 ± 1.1 kg). This would also reduce (P < 0.001) the metabolizable energy intake (MEI) required for liveweight gain (68.3 ± 1.94 vs. 87.2 ± 1.20 MJ MEI kg-1 liveweight gain). We conclude that finishing cattle at pasture will reduce the total emissions of CH4 and increase the efficiency of conversion of feed energy to liveweight gain when compared with backgrounding at pasture and finishing in a feedlot. Key words: Methane, steers, grass, alfalfa, pasture, barley, feedlot, metabolizable energy intake
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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".