Glycine Betaine-Mediated Protection of Peas (<i>Pisum sativum</i> L.) During Blanching and Frozen Storage
Bibliographic record
Abstract
We used glycine betaine (5–20% w/v) for blanching green peas (100°C, 60 s), and their subsequent freezing and storage (–20°C, 90 days). Blanching after the addition of glycine betaine at ≥10% (w/v) followed by a 90 day storage period which resulted in the most desirable outcome: higher vitamin C levels, a superior green color, enhanced organoleptic quality and texture, and improved retention of peroxidase and lipoxygenase activity relative to control peas (no glycine betaine added). Microscopic characterizations of control and treated peas revealed that glycine betaine acts as a cryoprotectant which maintains cellular integrity. Glycine betaine (10% w/v) could be used commercially for production of frozen peas with better quality attributes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".