Effect of Hydrothermal, Phytase, or Organic Acid Pretreatments of Canola Meal on Phytate Level of the Meal
Bibliographic record
Abstract
The objective of this study was to investigate the effect of pretreatment of canola meal with hydrothermal processing, phytase, and organic acid on phytate degradation. Six experiments were conducted processing canola meal in a hydrothermal reactor with different moisture conditions (15-350%), acid additions (hydrochloric acid, citric acid, malic acid, and lactic acid), pH (pH 4, 5, and 6), incubation times (30, 45, and 60 min), and phytase enzymes (‘Quantum Blue’ and ‘Finase’). The study revealed that although hydrothermal pretreatment of canola meal with phytase and higher moisture (200-350%) would allow 24.8-36% phytate breakdown, and a higher moisture addition (200%) combined with organic acid increased even further to 46.6%, lower moisture (50 and 100%) and organic acid was still effective in reducing phytate (by 7.9-19.4%). Optimal pH and incubation time in hydrothermal reactor for phytase efficacy were determined to be pH 4 and 5 and 30 to 60 min. Still, the results of the current study suggest that pretreatments should be further evaluated to optimize the efficacy of enzyme and organic acids as prebiotics to reduce anti-nutrients in canola meal, thus improving its utilization for livestock and reducing excretion to environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".