Ultrasound-assisted processing: Science, technology and challenges for the plant-based protein industry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present-day consumer is not only conscious of the relationship between food consumption and positive health, but also keen on environmental sustainability. Thus, the demand for plant-based proteins, which are associated with nutrition and environmental sustainability. However, the plant-based protein industry still demands urgent innovation due to the low yield and long extraction time linked with traditional extraction methods. Although ultrasound is an eco-innovative technique, there exist limited data regarding its impact with plant-based protein. In this paper, the scientific principles of ultrasonication with regards to its application in plant-based protein research were reviewed. After comparing the cavitational and shearing impacts of different ultrasonic parameters, the paper further reviewed its effects on extracted protein characteristics and techno-functional properties. Additionally, current technological challenges and future perspectives of ultrasonication for the plant-based protein industry were also discussed. In summary, this review does not only present the novelty and environmental sustainability of ultrasound as a plant-based protein assisted-extraction method, but also highlights on the correlation between protein source, structure and subsequent functional properties which are important crucial factors for maximum application of ultrasound in the growing plant-based protein market.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it