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Record W2967326080 · doi:10.13031/trans.13271

Optimal Housing and Manure Management Strategies to Favor Productive and Environment-Friendly Dairy Farms in Québec, Canada: Part I. Representative Farm Simulations

2019· article· en· W2967326080 on OpenAlex
Édith Charbonneau, Simon Binggeli, Jean‐Michel Dion, D. Pellerin, Martin H. Chantigny, Stéphane Godbout, Sébastien Fournel

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTransactions of the ASABE · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsnot available
Fundersnot available
KeywordsManureMilkingGreenhouse gasManure managementEnvironmental scienceAgricultural scienceStall (fluid mechanics)Context (archaeology)Animal scienceAgricultural economicsEngineeringEnvironmental engineeringGeographyAgronomyEconomicsBiologyEcology

Abstract

fetched live from OpenAlex

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 CO 2 e kg -1 and 1.67 to 1.71 kg CO 2 e 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 CH 4 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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.209
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it