Feeding wheat dried distillers grains with solubles improves beef trans and conjugated linoleic acid profiles1
Bibliographic record
Abstract
In western Canada, ethanol is produced mainly from wheat. As the demand for wheat increases, so do grain prices, which in turn creates incentives for feeding reduced-cost distillers coproducts to livestock. Substitution of wheat dried distillers grains plus solubles (DDGS) for barley grain may also create opportunities for enhancing beef fatty acid profiles because reducing starch concomitantly increases dietary fiber and oil and may shift PUFA biohydrogenation toward a healthier trans and CLA profile. To study this potential, heifers were fed diets containing 0, 20, 40, or 60% wheat DDGS (DM basis) substituted for rolled barley (n = 24; 133-d finishing period). Adding DDGS increased dietary oil (from 1.9 to 3.7%), but dietary fatty acid compositions remained consistent. Feeding increasing amounts of DDGS linearly decreased total diaphragm fatty acids on a milligram per gram basis (P = 0.031). For both brisket fat and diaphragm, feeding increasing amounts of DDGS caused linear increases in percentages of 18:2n-6 (P = 0.001) and total n-6 fatty acids (P = 0.001) but did not change the concentrations of individual or total n-3 fatty acids. Feeding increasing amounts of DDGS did not change the content of total trans MUFA in either brisket fat or diaphragm but led to linear decreases in 10t-18:1 (P = 0.033, brisket fat; P = 0.004, diaphragm) and increases in 11t-18:1 (P = 0.005, brisket fat; P = 0.003, diaphragm). Feeding increasing amounts of DDGS also caused a linear increase in 9c11t-18:2 (P = 0.044, brisket fat; P = 0.023, diaphragm) and total CLA (P = 0.086, brisket fat; P = 0.039, diaphragm). Overall, feeding DDGS enhanced the fatty acid composition of beef by decreasing 10t-18:1 while increasing the major CLA isomer (9c,11t-18:2) and its precursor 11t-18:1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".