Ice Recrystallization Inhibition in Ice Cream as Affected by Ice Structuring Proteins from Winter Wheat Grass
Bibliographic record
Abstract
Ice recrystallization in quiescently frozen sucrose solutions that contained some of the ingredients commonly found in ice cream and in ice cream manufactured under commercial conditions, with or without ice structuring proteins (ISP) from cold-acclimated winter wheat grass extract (AWWE), was assessed by bright field microscopy. In sucrose solutions, critical differences in moisture content, viscosity, ionic strength, and other properties derived from the presence of other ingredients (skim milk powder, corn syrup solids, locust bean gum) caused a reduction in ice crystal growth. Significant ISP activity in retarding ice crystal growth was observed in all solutions (44% for the most complex mix) containing 0.13% total protein from AWWE. In heat-shocked ice cream, ice recrystallization rates were significantly reduced 40 and 46% with the addition of 0.0025 and 0.0037% total protein from AWWE. The ISP activity in ice cream was not hindered by its inclusion in mix prior to pasteurization. A synergistic effect between ISP and stabilizer was observed, as ISP activity was reduced in the absence of stabilizer in ice cream formulations. A remarkably smoother texture for ice creams containing ISP after heat-shock storage was evident by sensory evaluation. The efficiency of ISP from AWWE in controlling ice crystal growth in ice cream has been demonstrated.
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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) | 0.000 | 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) | 0.001 | 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".