Optimal Housing and Manure Management Strategies to Favor Productive and Environment-Friendly Dairy Farms in Québec, Canada: Part I. Representative Farm Simulations
Bibliographic record
Abstract
Abstract. Tie-stall housing (93%) and solid manure management (44%) are used on many dairy farms in the province of Québec, Canada. However, this could change in the near future because the rise in average herd size and the popularity of milking robots are such that the industry expects an increase in free-stall dairies managing manure with liquid systems. This shift could affect the carbon (C), nitrogen (N), and phosphorus (P) footprints of Québec’s dairy production. In this context, whole-farm modeling (N-CyCLES), considering all the production cycle, provides a tool for evaluating the economics and environmental impacts of standard housing and manure management systems (Part I) in combination with different mitigation approaches (Part II). Two representative dairy farms in southwestern Québec (SWQ; 45.3° N, 73.2° W) and eastern Québec (EQ; 48.45° N, 68.1° W) were simulated considering four scenarios involving combinations of tie-stall or free-stall housing and solid or liquid manure management. Maximum farm net income (FNI) was $0.33 and $0.18 kg-1 of fat- and protein-corrected milk (FPCM) for the SWQ and EQ farms, respectively, with N and P footprints of 12.22 to 16.99 g N kg-1 and 0.52 to 0.79 g P kg-1 of FPCM in SWQ, and 11.48 to 15.39 g N kg-1 and 1.41 to 1.88 g P kg-1 of FPCM in EQ. Greenhouse gas (GHG) emissions reached 1.78 to 1.87 kg CO2e kg-1 and 1.67 to 1.71 kg CO2e kg-1 of FPCM in SWQ and EQ, respectively. The SWQ farm was associated with greater production of cash crops but also greater imports of fertilizers and purchased feeds, which negatively affected the N footprint and GHG emissions. Housing and manure management types did not influence FNI. Free-stall dairies were associated with greater N surpluses. Nevertheless, they emitted slightly less GHG than tie-stall dairies. Dairy farms under liquid manure management imported less fertilizers and produced less GHG despite greater CH4 emissions. As a result, the current transition toward free-stall barns and liquid manure systems in Québec seems advantageous from an environmental standpoint without compromising economic profitability. Keywords: Climate change, Dairy cow, Farm net income, Free stall, Greenhouse gas emission, Manure handling, Mitigation, Nutrient footprint, Tie stall, Whole-farm model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".