The effects of toasting canola meal on body weight, feed conversion efficiency, and mortality in broiler chickens
Bibliographic record
Abstract
It is hypothesized that the moisture incorporated into canola meal (CM) during desolventization, as sparge steam, promotes toasting. Elimination of toasting of CM would result in higher digestible amino acid content, but it is not known if it is required to reduce anti-nutritional factors. Therefore, the objectives of this study were to determine if suspending the use of sparge steam would prevent toasting and to study the effects of toasting on broiler chicken performance. Conventional toasted CM (TCM) and a hexane laden, nontoasted CM (NTCM) were collected from a commercial crushing plant. NTCM was desolventized in a research desolventizer/toaster without the use of sparge steam, producing a yellow-colored meal. The meals were fed to broiler chickens from 0 to 39 d and replaced 0, 20, 40, 60, 80, and 100% of the soybean meal (SBM) in wheat-based diets. Elimination of toasting increased broiler weight from 0.606 and 2.148 to 0.618 and 2.181 kg at 19 and 39 d of age, respectively. The feed ratio (0 to 19 d) increased from 0.637 to 0.642, but toasting did not affect mortality. Total mortality and chronic heart failure between 19 and 39 d increased with level of CM addition from 5.2 to 13.9% and 1.9 to 9.6%, respectively. Chronic heart failure in males, but not females, was increased from 3.3 to 17.4% with increasing CM level. In conclusion, desolventization without sparge steam produced a nontoasted meal and improved broiler growth and feed efficiency in comparison to TCM. Therefore, NTCM could be fed to broiler chickens.
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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 | 0.001 |
| 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".