Textural and Rheological Properties of Oat Beta-Glucan Gels with Varying Molecular Weight Composition
Bibliographic record
Abstract
The impact of oat β-glucan concentration and molecular weight (MW) on gel properties was investigated. Mixed MW gels/viscous solutions at 3, 4, and 5% β-glucan with high molecular weight (HMW):low molecular weight (LMW) ratios of 0:100, 25:75, 50:50, 75:25, and 100:0 were evaluated. The 100:0 and 50:50 gels had the lowest tan δ values. The 50:50 gels had the highest storage moduli ( G ′), whereas 100:0 solutions did not gel. Peak melting temperature ( T P ) was highest for 0:100 gels and decreased with the addition of HMW β-glucan. Hardness, at 40% compression, increased with concentration, and 25:75 and 50:50 gels were hardest at each concentration. Ordered microstructure, apparent in 0:100 gels, diminished with HMW β-glucan addition. Glucose addition resulted in lower tan δ values and firmer, harder gels compared to gels without glucose. Thus, the textural properties and melting profiles of β-glucan gels can be manipulated by adjusting the ratios of molecular weight fractions or addition of sugar for different applications.
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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 | 0.000 | 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) | 0.000 | 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".