Nutritive value of an extruded blend of canola seed and pea (Enermax™) for poultry
Bibliographic record
Abstract
A study was conducted to evaluate the nutritive value of Enermax™, which is a blend (50:50 wt/wt) of extruded full- fat canola seed and pea. Four blended samples from each of four batches were collected prior to extrusion (raw) and four samples from the same batches were collected after extrusion to give eight test samples. The canola seed in two of four batches were of good quality and in the other two were 8% bin-heated. The precision-fed adult rooster assay was used to determine the true metabolisable energy (TMEn) and true amino acid digestibility (TAAD) contents of variously treated feed samples. Both intact and cecectomized roosters were used in the assays. The average TMEn (kcal kg-1 DM) of the extruded product was 4051 ± 93 (mean ± SD; n = 16) for intact birds and 4019 ± 110 (n = 16) for cecectomized birds whereas the TMEn of the raw product was 3754 ± 136 (n = 16 ) in cecectomized birds. The true digestibilities of all amino acids were similar for extruded and raw product of canola seed-pea blend containing either good quality or 8% bin-heated canola seed (P > 0.10). These data indicate a high available energy content of the extruded product with little difference in TMEn content when measured using either intact or cecectomized roosters. It was concluded that extrusion improved the bio-available energy content of the canola seed-pea product, but not true amino acid digestibility. Further, the current results indicate that substitution of bin-heated (8%) canola seed for good quality canola seed did not adversely affect TMEn or TAAD of the extruded product. Key words: Poultry, nutritive value, extruded canola seed-pea blend
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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 | 0.001 | 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".