Effects of pellet size and inclusion of binding agents on ruminal fermentation and total-tract digestibility of beef heifers, and cow performance under winter grazing conditions
Bibliographic record
Abstract
The objective of this research was to evaluate the effect of pellet size and the inclusion of binders to increase pellet durability on ruminal fermentation and total-tract digestibility, and pellet utilization when grazing. In study 1, 8 ruminally cannulated heifers were used in a replicated 4 × 4 Latin square design. Heifers were fed a grass-hay-based diet supplemented with small (SP; 3.96-mm diameter) or large pellets (LP; 12-mm diameter) that either included (B+) or did not include binders (B−). In study 2, groups of 5 cows grazing straw–chaff in paddocks (n = 4) during winter were supplemented with SP, SP-B+, or LP-B+. In study 1, pellet size and binder inclusion did not affect (P > 0.10) forage intake, pellet intake, or ruminal pH (P > 0.10). Heifers fed LP-B+ had a greater proportion of acetate than heifers fed the SP-B+ (size × binder; P = 0.01), and heifers fed LP-B− had a greater proportion of propionate than did those fed LP-B+ (size × binder; P = 0.03). The molar proportion of butyrate was greater for heifers fed B+ compared with B− (binder, P = 0.05). Apparent total-tract digestibility was not affected (P > 0.10). In study 2, differences were not observed among treatments (P > 0.10). These data indicate that pellet size and binder inclusion do not affect forage or pellet intake, apparent total-tract digestibility, or cow performance. However, pellet size and binder inclusion may modulate ruminal fermentation.
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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 | 0.001 | 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".