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Record W3166245838 · doi:10.3168/jds.2020-19893

Economic and environmental effects of revised metabolizable protein and amino acid recommendations on Canadian dairy farms

2021· article· en· W3166245838 on OpenAlexafffundabout
Simon Binggeli, H. Lapierre, Édith Charbonneau, D.R. Ouellet, D. Pellerin

Bibliographic record

VenueJournal of Dairy Science · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsAgriculture and Agri-Food CanadaUniversité Laval
FundersAgriculture and Agri-Food CanadaCanadian Dairy CommissionDairy Farmers of CanadaUniversité Laval
KeywordsHerdAgricultural scienceDairy farmingResearch councilAgricultureAnimal scienceMathematicsEnvironmental scienceBiologyMilk production

Abstract

fetched live from OpenAlex

The objective of this research was to evaluate the potential economic and environmental effects of the formulation model used to balance dairy rations for metabolizable protein (MP) or 3 essential AA (EAA: His, Lys, and Met) in 3 regions of Canada with different farming systems. The Maritimes, Central Canada, and the Prairies reference dairy farms averaged 63, 71, 144 mature cows per herd and 135, 95, 255 ha of land, respectively. Using N-CyCLES, a whole-farm linear program model, dairy rations were balanced for (1) MP, based on National Research Council (NRC) requirements (MP_2001); (2) MP plus Lys and Met, based on NRC (AA_2001); (3) MP (MP_Rev); or (4) for His, Lys, and Met (AA_Rev), both based on a revised factorial approach revisiting both supply and requirements of MP and EAA. Energy was balanced to meet requirements based on NRC (2001). Assuming the requirements were met within each approach, it was considered that milk yield and composition were not affected by the type of formulation. Given the assumptions of the study, when compared with MP_2001 formulation, balancing dairy rations using the AA_Rev approach reduced calculated farm N balance by 3.8%, on average from 12.71 to 12.24 g/kg of fat- and protein-corrected milk; it also enhanced farm net income by 4.5%, from 19.00 to 19.70 $CAN/100 kg of fat- and protein-corrected milk, by reducing inclusion of protein concentrate in dairy rations. Calculated animal N efficiency was on average 4.3% higher with AA_Rev than with MP_2001 for mid-lactation cows. This gain in N efficiency would result in a reduction in N 2 O emission by manure, contributing to a partial decrease of total greenhouse gas emission by 1.7%, through a reduction of N excreted in manure. With the AA_2001 formulation, farm N balance was 1% higher than with MP_2001 formulation while reducing farm net income by 6.4%, due to the need to purchase rumen-protected AA, with no effect on total greenhouse gas emission. Both MP formulations lead to fairly similar outputs. The AA_Rev formulation also indicated that His might be a co-limiting AA with Met in dairy rations balanced with ingredients usually included in Canadian dairy rations. Given the assumptions of the study, balancing dairy rations for 3 EAA (His, Lys, and Met) rather than MP, has some potential positive effects on Canadian dairy farms by increasing net incomes through a reduction of crude protein supply, leading to a decreased environmental effect.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.423

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2021
Admission routes3
Has abstractyes

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