Release of Ferulic Acid from Oat Hulls by<i>Aspergillus</i>Ferulic Acid Esterase and<i>Trichoderma</i>Xylanase
Bibliographic record
Abstract
Oat hulls, an agricultural byproduct, contain a relatively high amount of ferulic acid (FA; 4-hydroxy-3-methoxycinnamic acid), which is believed to be inhibitory to oat hull biodegradability by rumen microorganisms. In this paper, Aspergillus ferulic acid esterase (FAE) was investigated for its ability to release FA from oat hulls. The objectives were to determine the effects of particle size of oat hulls (ground to pass through 1 mm and 250 microm screens and a 100 microm sieve) on release of FA by FAE both in the presence and in the absence of Trichoderma xylanase. The results show that the release of FA by FAE was dependent upon the particle size of oat hulls (< or = 250 microm). In the absence of Trichoderma xylanase, little FA was released by FAE. In the presence of Trichoderma xylanase, there was a significant release of FA by FAE, indicating a synergistic interaction between FAE and Trichoderma xylanase on release of FA from oat hulls. These results indicate that FAE is able to break the ester linkage between FA and the attached sugar, releasing FA from oat hulls. This may leave the remainder of the polysaccharides open for further hydrolytic attack by rumen microorganisms. It is likely that removing FA from oat hulls could improve rumen biodegradability, thus improving the nutritional value of oat hulls.
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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".