Triticale Dried Distillers' Grain Increases Alpha‐Linolenic Acid in Subcutaneous Fat of Beef Cattle Fed Oilseeds
Bibliographic record
Abstract
This study investigated the effect of triticale dried distillers' grain with solubles (DDGS), flax (FS) and sunflower (SS) seed on growth and the fatty acid profile of subcutaneous (SQ) fat in individually housed steers (n = 15 per diet) fed ad libitum (DM basis); (1) control (CON) 90% barley grain + 10% barley silage; or substitution of barley grain for: (2) 30% DDGS; (3) 10% FS; (4) 30% DDGS + 8.5% FS; (5) 10% SS and (6) 30% DDGS + 8.5% SS. Oilseeds in the combination diets were reduced to maintain diet lipid levels below 9% DM and to determine if favorable changes in the fatty acid profile could be maintained or enhanced at reduced levels of oilseed. Plasma and SQ fat biopsies were collected at 0, 6, and 12 weeks. Inclusion of DDGS decreased (P < 0.05) average daily gain, feed conversion and backfat thickness. Feeding FS increased (P < 0.05) plasma ALA compared to CON and SS and consistently increased (P < 0.01) ALA and non-conjugated and non-methylene interrupted dienes (NCD), whereas SS tended to decrease ALA in fat. Inclusion of DDGS with FS further increased (P < 0.02) ALA and decreased (P < 0.05) NCD and 18:1-t10 in fat. The fact that the levels of n-3 fatty acids in SQ fat from steers fed DDGS + FS were higher than those obtained with FS alone, has obvious benefits to the practical cost of favorably manipulating fatty acid profiles in beef.
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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".