Economic and environmental effects of revised metabolizable protein and amino acid recommendations on Canadian dairy farms
Bibliographic record
Abstract
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.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".