Greenhouse gas emissions intensity of Ontario milk production in 2011 compared with 1991
Bibliographic record
Abstract
Jayasundara, S. and Wagner-Riddle, C. 2014. Greenhouse gas emissions intensity of Ontario milk production in 2011 compared with 1991. Can. J. Anim. Sci. 94: 155–173. For identifying opportunities for reducing greenhouse gas (GHG) emissions from milk production in Ontario, this study analyzed GHG intensity of milk [kg CO 2 equivalents kg −1 fat and protein corrected milk (FPCM)] in 2011 compared with 1991 considering cow and crop productivity improvements and management changes over this period. It also assessed within-province variability in GHG intensity of milk in 2011 using county-level data related to milk production. After allocating whole-farm GHG emissions between milk and meat using an allocation factor calculated according to the International Dairy Federation equation, GHG intensity of Ontario milk was 1.03 kgCO 2 eq kg −1 FPCM in 2011, 22% lower than that in 1991 (1.32 kg CO 2 eq kg −1 FPCM). Greenhouse gas sources directly associated with dairy cattle decreased less (21 and 14% for enteric fermentation and manure management, respectively) than sources associated with feed crop production (30 to 34% for emissions related to N inputs and farm-field work). Proportions of GHG contributed from different life cycle activities did not change, with enteric fermentation contributing 46%, feed crop production 34%, manure management 18% and milking and related activities 2%. Within province, GHG intensity varied from 0.89 to 1.36 kg CO 2 eq kg −1 FPCM, a variation inversely correlated with milk productivity per cow (kg FPCM sold cow −1 year −1 ). The existence of a wide variation is strong indication for potential further reductions in GHG intensity of Ontario milk through the identification of practices associated with high efficiency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".