Evaluation of canola meal derived from <i>Brassica juncea</i> and <i>Brassica napus</i> on rumen fermentation and nutrient digestibility by feedlot heifers fed finishing diets
Bibliographic record
Abstract
Five yearling heifers (387 ± 6.5 kg) were utilized in a 5 × 5 Latin square to evaluate the substitution of canola meal (CM) derived from Brassica (B.) napus and B.juncea seed for barley grain on feed intake and nutrient utilization. The control diet (CONTROL) consisted of 88.3% barley grain, 4.4% barley silage, and 7.3% supplement [dry matter (DM) basis]. The four CM treatments included 10% and 20% B.napus or B.juncea meal, with CM replacing barley grain. Dry matter intake was not affected (P > 0.05) by treatment. Total duration and area under rumen pH 5.8, 5.5, and 5.2 increased (P < 0.05) with greater inclusion of CM, regardless of type. Cattle fed 20% CM had elevated rumen ammonia-N concentration and urinary N excretion. Cattle fed B. juncea meal exhibited greater (P < 0.05) apparent nutrient digestibility compared with those fed B. napus meal. In conclusion, meal derived from B. napus or B. juncea can be used to replace barley grain at levels up to 20% (DM) in finishing diets without compromising rumen fermentation or total tract nutrient digestibility. However, animal performance and possible economic benefits need to be balanced against the increasing N excretion resulting from over-feeding protein to cattle.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".