Application of the Rapid Visco Analyzer (RVA) as an Effective Rheological Tool for Measurement of β‐Glucan Viscosity
Bibliographic record
Abstract
ABSTRACT The physiochemical characteristics of β‐glucan in oat and barley foods can affect human physiological response. A method for continuous measurement of β‐glucan viscosity with a Rapid Visco Analyzer (RVA) was developed to overcome the complexity of the common protocols based on in vitro digestion methods. The effects of several parameters on viscosity and solubility were considered. Oat cereal foods showed different RVA viscosity profiles depending on their physiochemical characteristics. Products high in starch exhibited a high initial viscosity that was reduced by α‐amylase action, whereas products with low amounts of starch exhibited a slow increase in viscosity. The viscosity of all samples reached a plateau in the viscosity curve after 1–2 hr, which is the key for obtaining reproducible results. Optimum digestion condition was achieved using sodium phosphate buffer (pH 6.9) and 1% β‐glucan dispersion at 37°C and 160 rpm. A particle size of <0.6 mm gave more consistent viscosities than did larger particles without affecting the solubility of β‐glucan. Pancreatin and α‐amylase concentrations affected the viscosity profile by influencing the digestion rate of protein and starch in the samples, but pepsin had limited influence at pH 6.9. Highly significant Pearson correlation between the in vitro digestibility protocol and RVA methods was achieved, indicting that the developed method could be used as an effective alternative for measurement of β‐glucan viscosity.
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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".