Effect of feeding strategically blended feed pellets on rumen fermentation and nutrient digestion
Bibliographic record
Abstract
Zenobi, M. G., Lardner, H. A., Jefferson, P. G. and McKinnon, J. J. 2015. Effect of feeding strategically blended feed pellets on rumen fermentation and nutrient digestion. Can. J. Anim. Sci. 95: 243–254. Five rumen-cannulated heifers (631±31 kg) were used in a 5×5 Latin square design to evaluate the effect of feeding blended by-product feed pellets (BP) on rumen fermentation and nutrient utilization. Four BP were formulated to be high in starch (HS) or fat (HF) and either low (LSP) or high (HSP) in soluble crude protein. The control diet consisted of 49.1% forage and 50.9% barley-based concentrate. Treatments were 50.3% forage and 49.7% BP (DM). Heifers fed HF BP had higher (P=0.05) mean pH values than those fed the control diet and tended (P=0.07) to have higher mean pH than those fed the HS BP. Feeding HF BP decreased (P<0.05) rumen propionate concentration without affecting acetate or total volatile fatty acid concentration. Rumen ammonia-nitrogen (N) levels and digestibility of crude protein was highest (P<0.05) for HS, intermediate for HF, and the lowest for the control. Feeding HF BP reduced (P<0.05) gross energy digestibility and digestible energy content relative to both the control and HS diets while both BP increased (P<0.01) their extract digestibility compared with the control. There was minimal effect of pellet soluble crude protein content. Total N excretion (% of N intake) was not affected (P>0.05) by treatment. These results indicate that BP had no adverse effects on rumen fermentation or apparent nutrient digestibility and did not result in issues with excess nutrient excretion. As such BP can be used as an alternative energy source in backgrounding diets to cereal grains and can help counteract volatility in feed grain prices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".