Porcine <scp><i>in vitro</i></scp> digestion and matrix structure of undigested residue of xylanase‐ and cellulase‐supplemented maize and wheat
Bibliographic record
Abstract
Abstract Background This study investigated the effects of supplementing maize and wheat with a combination of xylanase and cellulase on porcine in vitro digestibility, nonstarch polysaccharides (NSP) solubilization, and matrix structure. The latter was assessed using synchrotron‐based micro‐computed tomography (SR‐μCT) and Fourier transform mid‐infrared (FTMIR) spectroscopy after porcine in vitro degradation. Cereal grains were subjected to porcine in vitro digestion with or without enzyme supplementation (20 000 U kg−1 of each enzyme) in a 2 × 2 factorial design. Results In vitro dry matter digestibility (IVDDM) was lower for maize than for wheat (P < 0.05), and enzyme supplementation had no effect on IVDDM. Supplemental enzymes reduced arabinoxylan content in the undigested residue of wheat (53 vs 46 g kg−1, P < 0.05) but not maize (42 vs 44 g kg⁻¹; P > 0.05). Synchrotron‐based micro‐computed tomography imaging revealed aleurone cells with intact content in the undigested residue of both maize and wheat, regardless of enzyme supplementation. Some endosperm cells in undigested maize residue retained their content, whereas nearly all endosperm cells in undigested enzyme‐unsupplemented wheat residue were empty. No endosperm cells were detected in undigested enzyme‐supplemented wheat residue. Fourier transform mid‐infrared imaging indicated a higher presence of phenolic compounds in maize cell walls than in wheat. Conclusion Supplemental enzymes did not affect IVDDM for wheat, as they primarily degraded endosperm cell walls, the content of which was already released by pepsin and pancreatin digestion. Similarly, IVDDM for maize remained unaffected, which was probably due to the high phenolic content of its cell walls. © 2025 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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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 | 0.000 |
| 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".