PSXVI-6 Ruminal dry Matter Disappearance, Methane Production and Fermentation Parameters as Affected by fat and Protein Concentration in by-Product Supplemented Grass hay-Based Diets
Bibliographic record
Abstract
Abstract This batch culture study evaluated the effects of crude protein (CP) and fat concentration on ruminal dry matter disappearance (DMD), methane (CH4) production, and ruminal fermentation in grass hay-based diets supplemented with by-product feeds. Eight treatments provided low or high CP (8 or 12% DM, respectively), with a range of fat concentrations (1.8 to 6.0% DM) and included the following: Control (grass hay only); corn distillers grains with solubles at 8.0% (CDDGS8) and 12% CP (CDDGS12); flax at 8% (FS8) and 12% CP (FS12); canola meal at 8% (Can8); sunflower screenings from Winkler (SFW8) or Deloraine (SFD8) at 8%. Data were analyzed as a randomized complete block design, with fixed effect of treatment and random effects of block and treatment × block. Comparisons were performed between a) Control and mean of by-product treatments b) low and high CP treatments c) CDDGS treatments, d) FS treatments and e) SF treatments. Comparisons between low and high fat treatments at both CP concentrations, as well as CDDGS and FS treatments differing in fat concentrations were also conducted. Overall, DMD did not differ between the Control and by-product treatments; however, comparisons indicated decreased (P < 0.001) DMD in treatments with 8% compared with 12% CP. The DMD was also greater (P≤0.009) with low fat compared with high fat, regardless of CP. Methane production did not differ between any of the low and high CP treatments but was greater (P≤0.003) in the low fat compared with high fat treatments, regardless of CP, as well as in FS vs CDDGS and SFD vs SFW. No effects of treatment on fermentation parameters were observed. In conclusion, greater CP increased DMD in vitro but did not affect CH4 or fermentation. Additionally, greater dietary fat can mitigate enteric CH4 production, but can negatively impact DMD in grass hay-based diets.
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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) | 0.001 | 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 | 0.000 | 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".