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 CO2 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 kgCO2eq kg-1 FPCM in 2011, 22% lower than that in 1991 (1.32 kg CO2eq 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 CO2eq 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 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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".