Enhancing the nutritive value of canola meal for broiler chickens through enzymatic modifications
Bibliographic record
Abstract
Enzymatic modification of canola meal (CM) is a potential method to enhance its nutritional value as it can depolymerize nonstarch polysaccharides (NSP) and mitigate its potential antinutritive properties. Based on the previous studies, pectinase A (PA), pectinase B (PB), xylanase B (XB), and invertase (Inv) were used for the enzymatic modifications. The highest NSP depolymerization ratio was obtained when 4 g/kg of each PA, PB, and XB, and 0.2 g/kg of Inv were used during 48 h incubation at 40 °C. In the current study, changes in pH, simple sugars, sucrose, oligosaccharides, and NSP contents during the enzymatic modification (CM+E) of CM were measured and compared to Control (CM) without enzymes addition or with the addition of bacteriostat sodium azide (CM+E+NaN3). The results showed that spontaneous fermentation occurred during incubation. After incubation, the pH of the slurry decreased, lactic acid was produced, phytate disappeared, and the concentration of simple sugars decreased substantially. The NSP of the slurry was progressively depolymerized by the enzyme blend. The chemical composition and nutritive value of enzymatically-modified CM (ECM) were evaluated. Ross 308 broilers were randomly assigned to 18 cages of six birds each for the standardized ileal amino acid digestibility (SIAAD) and nitrogen-corrected apparent metabolizable energy (AMEn) assay. A corn/soybean meal-based basal diet formulated to meet Ross 308 breeder recommendations and two test diets contained 70% of the basal diet and 30% of CM or ECM, respectively, were fed to Ross 308 from 13 to 17 d of age. No difference was observed between SIAAD of CM and ECM. The AMEn value of ECM was 2118.0 kcal/kg on a dry matter basis which was 30.9% greater (P < 0.05) than the CM.
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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 | 0.000 | 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) | 0.000 | 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 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".