Improving the texture and structure of high protein yogurt alternative using pea protein hydrolysate as a functional ingredient
Bibliographic record
Abstract
Non-dairy yogurt alternatives have become increasingly popular in the market but the impact of enzymatic hydrolysis on the textural and structural properties of pea protein based yogurt alternative (PBYA) with high protein content is not well understood. In this study, commercial pea protein isolate was hydrolyzed with trypsin using the pH-stat method to obtain a degree of hydrolysis of approximately 1%. The hydrolysis led to a significant degradation of the major pea proteins including convicilin (~95–97%), vicilin (~88–93%) and legumin α (~93–97%). The PBYA made from pea protein hydrolysate, namely, PPH-PBYA, was produced at both bench and pilot scale with a protein content at 10% (w/w) and was compared with the control PBYA made from pea protein isolate (PPI-PBYA). The PPH-PBYA contained a smaller gel particle size (~20–40 µm) than PPI-PBYA (~50–70 µm), and possessed softer and smoother texture. For instance, the PPH-PBYA manufactured at pilot scale, when compared with the PPI counterpart, had lower yield stress (~32 Pa vs. ~454 Pa), a lower flow consistency coefficient (~135 Pa.s n vs. ~1016 Pa.s n ), and lower firmness (~3 N vs. ~9 N). Moreover, the hydrolysis treatment did not negatively impact syneresis stability; the characterized syneresis rates for both PPI- and PPH-PBYA were <1%. Furthermore, PPH-PBYA exhibited lower frication coefficients at the elastohydrodynamic lubrication regime, suggesting a better lubrication behavior compared with PPI-PBYA. The improvement in the texture and structure was consistent with visual and microscopical observations, where the PPH-PBYA featured smoother surface characteristics and more homogenous microstructure. The impacts of enzymatic hydrolysis of pea protein on particle size, texture, and microstructure of the PBYA produced from pilot scale trials showed a similar trend to those produced from the bench scale, validating the feasibility for scale-up production. The study provides a feasible route to manufacture commercial PBYA products with high protein content and optimized textural properties using enzymatic treatment.
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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".