Pulse Globulins 11S and 7S: Origins, Purification Methods, and Techno-functional Properties
Bibliographic record
Abstract
A growing interest in pulse proteins in recent years results from their crucial role in the transition toward sustainable food systems. Consequently, current research is mainly focused on the production of protein ingredients and the evaluation of their nutritional and techno-functional properties for the development of animal product analogues. However, the individual impacts of the major proteins 11S legumin and 7S vicilin on pulse techno-functionalities remains unclear. Thus, this review aims to represent current knowledge on pulse 11S and 7S globulin origins, extraction, separation, and purification methods as well as their techno-functionalities. This paper also discusses the principal challenges related to pulse vicilin and legumin purification methods, such as efficiency and environmental concerns, as well as 11S/7S ratio variability. This review highlights the fact that 11S and 7S fractions serve different purposes in pulse functionality and that more efficient and eco-friendly purification techniques are required to properly assess their respective functional attributes. Such research would allow the determination of optimal 11S/7S ratios for the integration of pulse protein ingredients in various food formulations. Hence, food industries would be able to select species/varieties, agronomical methods, and processing methods to produce ingredients with suitable 11S/7S ratios, catering to consumers' ethical, environmental, and nutritional concerns.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".