Use of a post-production fractionation process improves the nutritional value of wheat distillers grains with solubles for young broiler chicks
Bibliographic record
Abstract
BACKGROUND: Post-production fractionation of wheat distillers grains with solubles (DDGS) increases their crude protein content and reduces their fiber content. This experiment was conducted to determine the effects of fractionation of wheat DDGS on apparent total tract digestibility (ATTD) and performance when fed to broiler chicks (0-21 d). METHODS: A total of 150, day-old, male broiler chicks (Ross-308 line; Lilydale Hatchery, Wynyard, Saskatchewan) weighing an average of 49.6 ± 0.8 g were assigned to one of five dietary treatments in a completely randomized design. The control diet was based on wheat and soybean meal and contained 20% regular wheat DDGS. The experimental diets contained 5, 10, 15 or 20% fractionated wheat DDGS added at the expense of regular wheat DDGS. RESULTS: The ATTD of dry matter and gross energy were linearly increased (P < 0.01) as the level of fractionated wheat DDGS in the diet increased. Nitrogen retention was unaffected by level of fractionated wheat DDGS (P > 0.05). Weight gain increased linearly (P = 0.05) as the level of fractionated wheat DDGS in the diet increased. Feed intake, feed conversion and mortality were unaffected by level of fractionated wheat DDGS in the diet (P > 0.05). CONCLUSIONS: Post-production fractionation of wheat DDGS improves their nutritional value by lowering their fiber content and increasing their content of crude protein and energy. These changes in chemical composition supported increased weight gain of broilers fed wheat DDGS.
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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".