Complexation of pea protein isolate and betanin in red beet extract (Beta vulgaris L.): Effect of pH and temperature on stability
Bibliographic record
Abstract
Betanin is a natural red pigment found in red beet with applications in the food industry. The aim of this study was to examine the interaction between betanin in red beet extract (RBE) and pea protein isolate (PPI) at different pH conditions to improve the stability of betanin. PPI solutions were combined with RBE (1:1 v/v ratio) to facilitate complex formation across a pH range of 3 to 7. Among different pH conditions tested, the solubility of betanin in RBE was enhanced by complex interactions with PPI at pH 3. Furthermore, at pH 3, the particle size of the PPI-RBE complex increased to 133.03 ± 15.13 nm, compared to the PPI-water control, which measured 104.45 ± 8.13 nm. Zeta (ξ)-potential analysis indicated that the interaction between PPI and RBE at pH 3 leads to charge neutralization, with the charges of PPI-Water control (+18.37 ± 2.6 mV) and RBE-Water control (-2.16 ± 0.56 mV) altering in the PPI-RBE complex to +8.05 ± 1.63 mV. Compared to RBE control, the PPI-RBE complexes at pH 3 demonstrated the highest stability at room temperature over 15 days, achieving a betanin retention of 55.53 %, whereas RBE-Water exhibited only 4.31 %. Additionally, the PPI-RBE complex displayed enhanced thermal stability at 80 °C for 60 min, with a betanin retention of 12.5 %, in contrast to the RBE-Water control, which retained 6.5 %. These findings provide rationale for the stability considerations based on pH and temperature, to enable the utilization of PPI-RBE complexes as ingredients in acidic foods.
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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".