Maize‐derived arabinoxylans modulate starch pasting, gel structure, and retrogradation
Bibliographic record
Abstract
Abstract BACKGROUND Starch–fiber interactions play a paramount role in determining the functional quality and stability of starch‐based food products. This study systematically examined how maize arabinoxylans (MAX) influences the hydration, pasting, textural, and microstructural properties of maize starch gels. RESULTS Maize starch composites containing 0, 1, 3, 6, and 9 g 100 g −1 (w/w) MAX were subjected to water‐ and oil‐binding assays, Rapid Visco Analyzer (RVA) profiling, texture profile analysis (TPA), and scanning electron microscopy with morphometric quantification. Inclusion of MAX produced a marked shift in polymer–fluid dynamics: water‐binding capacity decreased from 0.95 (control) to 0.74–0.77 g g −1 , while oil‐binding capacity increased from 0.61 to 0.73 g g −1 at 9 g 100 g −1 MAX. Correspondingly, RVA pasting profiles exhibited concentration‐dependent reductions in peak, breakdown, and final viscosities, indicative of restricted granule swelling, diminished amylose leaching, and attenuated retrogradation. TPA revealed that gels with composites containing ≥ 6 g 100 g −1 MAX were significantly firmer, gummier, chewier, and more resilient both immediately and after 48 h of cold storage, confirming enhanced network rigidity and resistance to structural rearrangement. Microstructural analysis demonstrated a progressive transition where low MAX levels (1–3 g 100 g −1 ) yielded open, porous matrices, whereas higher levels (6–9 g 100 g −1 ) produced dense, cohesive architecture with thicker cell walls. CONCLUSION Collectively, these findings reveal that MAX contributes to the development of starch gels with controlled viscosity, improved structural stability, and minimized retrogradation. This mechanistic understanding provides a framework for tailoring starch–fiber composites in complex food matrices requiring controlled thickening and improved stability. © 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".