Rheological Behavior of WPI Dispersion as a Function of pH and Protein Concentration
Bibliographic record
Abstract
Physical and flow properties of proteins can provide information necessary for the optimal design of unit processes and quality control of the manufacturing process and final products. Therefore, the purpose of this investigation was to characterize the rheological behavior of a whey protein isolate (WPI) (BiPRO) dispersion as a function of pH and protein concentration. A rotational viscometer was used to determine the apparent viscosity, shear rate, and shear stress of WPI dispersions. Both the consistency index (k) and the flow behavior index (n) were sensitive to changes in pH and protein concentration. Mathematical relations obtained from experimental values of k and n allowed the determination of a model for apparent viscosity (eta) of WPI dispersions as a function of pH and protein concentration. At 5 and 10% BiPRO, whatever the pH, the rheological behavior appeared to be a newtonian fluid, while at 20% BiPRO, the rheological behavior appeared to be a nonnewtonian pseudoplastic fluid. Furthermore, at 20% Bipro, the apparent viscosity presented an increase in viscosity from 5.6 to 5.4, followed by a decrease from pH 5.4 to 5.0 at all shear rates. The highest viscosity was obtained at 20% pH 5.4, with an approximate value of 0.25 Pa.s, 10 times higher than the one obtained at 5 and 10% BiPRO.
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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 | 0.001 |
| 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 | 0.001 |
| 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".