PSXVII-37 Effect of canola oil supplementation to AAC Mountainview sainfoin, alone or in combination with grass mixtures, on in vitro DMD, methane production and ruminal fermentation.
Bibliographic record
Abstract
This study assessed supplementing AAC Mountainview sainfoin, with 2 sources of canola oil (CO; commodity and high oleic acid variety) at 3 inclusion rates (0, 3, 5% DM), on in-vitro fermentation, DMD and CH4 production. Sainfoin was seeded alone or in combination with hybrid bromegrass at 3 seeding ratios (100, 70:30 and 50:50). An alfalfa-meadow bromegrass (AG) mixture was included as a check. This experiment was analysed as a randomised complete block design including the fixed effects of forage and CO and the random effects of run, replication and interactions between mixture, replication and CO. Forage samples were incubated at 39°C in vials containing buffered medium and rumen fluid for 48- hrs. At pre-determined timepoints, gas pressure was recorded and gas samples for CH4 determination were collected. Pure sainfoin had lower (P>0.001) DMD and higher CH4 (55.4 ml/g DMD) than all other treatments. Highest (P>0.001) DMD was observed for AG, however CH4 did not differ between sainfoin-mixtures and AG (m=51.3 ml/g DMD). CO supplementation did not have an effect on forage digestibility nor did it effect CH4 production. Fermented fluid of pure sainfoin had the highest (P>0.001) molar proportions of acetate and butyrate to propionate (a+b:p) compared to all other treatments. The lowest (P>0.001) ratio of a+b:p was observed for AG. Regardless of source or inclusion rate, CO had no effect on the molar proportions of a+b:p. In conclusion, the AG treatment had higher digestibility and produced less CH4 compared to all other sainfoin treatments, which may indicate that CT in in sainfoin had no effect on CH4 production. Moreover, regardless of rate or source, CO supplementation had no effect on forage digestibility or CH4 production.
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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) | 0.001 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".