Effects of replacing soybean meal with canola meal for lactating dairy cows fed 3 different ratios of alfalfa to corn silage
Bibliographic record
Abstract
Previous research has demonstrated that feeding canola meal (CM) improves milk production and N utilization by lactating dairy cows when replacing solvent-extracted soybean meal (SBM). The objective of the present study was to evaluate whether CM would improve milk yield and components and N utilization, compared with SBM, at different ratios of alfalfa silage (AS) to corn silage (CS) fed to lactating dairy cows. Twenty-four multiparous Holstein cows averaging, at the beginning of the study (mean ± SD), 2.8 ± 0.9 parity, 684 ± 56 kg of BW, 102 ± 41 DIM, and 49 ± 4 kg milk/d, and 24 primiparous cows averaging (mean ± SD) 565 ± 46 kg of BW, 123 ± 30 DIM, and 40 ± 4 kg milk/d were blocked by parity and DIM. A cyclic changeover design with 4 replications of 2 blocks of treatments of 6 cows was used in an arrangement with 4 28-d periods. Dietary treatments were arranged in a 3 × 2 factorial design of 3 proportions of AS to CS as forage source (HAS = high AS, 50% AS to 10% CS; MAS = medium AS, 30% AS to 30% CS; LAS = low AS, 10% AS to 50% CS) and 2 protein supplements (CM vs. SBM). Diets were formulated to contain [dry matter (DM) basis]: 60% forage, 8 to 15% high-moisture corn, 2 to 5% soy hulls, 1.3% mineral-vitamin premix, 16% crude protein, and 31 to 33% NDF. Data from the last 2 weeks of each period were used to compute mean milk yield and composition, and efficiencies of feed conversion, for each cow in each period. Data for the other variables were collected during the last week of each period. All data were analyzed using the MIXED procedure of SAS (SAS Institute Inc., Cary, NC). Regardless of the forage source, replacing SBM with CM improved yields of milk, milk protein, and solids-not-fat. Moreover, milk urea nitrogen concentration and urinary excretion of total N (g/d) and urea N (% of total urinary N) decreased when CM replaced SBM. An interaction effect occurred between forage source and protein supplements for apparent total-tract digestibility, and, overall, this effect was due to small differences in ingredient and chemical compositions of the diets. In addition, these differences had a minor effect on cow performance. Yields of milk and milk components were greatest for cows fed 50% CS, intermediate for 30% CS, and lowest for 10% CS, indicating that, under the conditions of the present study, cows fed 50% CS in the diet (DM basis) had greater production compared with those fed 50% AS.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".