Comparison of normal and low‐lignin hull/high‐oil groat oat as energy sources for broiler chicks
Bibliographic record
Abstract
Abstract BACKGROUND: Oats are not widely utilised in poultry rations. The principal reason for this is their high fibre content. Fibre is not very digestible by poultry and its presence impairs the digestibility of energy and other nutrients. A new low‐lignin hull/high‐oil groat (LLH/HOG) oat was developed recently and the present study was conducted to determine its nutritional value for poultry. RESULTS: In experiment 1, gain of broiler chicks fed the control was higher (P < 0.01) than that of birds fed normal oat. Gain and intake of birds fed LLH/HOG oat were superior (P < 0.01) to those of birds fed normal oat. Feed conversion (FC) was higher for birds fed the control than for birds fed normal oat (P < 0.01), while FC for birds fed the control and LLH/HOG oat did not differ (P > 0.05). FC was better for birds fed LLH/HOG than for birds fed normal oat (P < 0.01). In experiment 2, weight gain (P < 0.01), feed intake (P < 0.01) and FC (P = 0.07) declined as the level of LLH/HOG oat in the diet increased. CONCLUSION: Feeding LLH/HOG oat to broilers improved weight gain and FC compared with feeding normal oat. These results give a strong indication that LLH/HOG oat is superior to normal oat as an energy source for poultry. However, despite improvements in chemical composition, LLH/HOG oat is still inferior to wheat for use in broiler rations. Copyright © 2009 Society of Chemical Industry
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".