Novel insight into the cross-linking of typical wheat starch-based food components during freeze-drying: Starch, lipids, proteins and their ternary mixtures
Bibliographic record
Abstract
Starch-based foods have a large consumer base worldwide. It is known that the quality of freeze-dried starch-based products is subject to deterioration during the production process. The present study was unprecedented carried out to examine the effects of freeze-drying on the cross-linking between components of gelatinized starch-based system. The results showed that the retrogradation of starch in the process of dehydration, the weakening of the binding capacity between the substrate and water of the freeze-dried product and the weakening of the interaction strength between the components of the product were the key mechanisms leading to the quality deterioration of the wheat starch-based conditioned food during the freeze-drying. The addition of lipid and protein can inhibit starch retrogradation during freeze-drying, and the inhibition effect of oil is better. However, the intervention of oil and fat will cause dehydrated starch to re-adsorb the melted oil/water mixture during the freeze-drying process, resulting in the deterioration of product quality. The intervention of protein will improve the binding ability of freeze-dried wheat starch-based product matrix to water. In the ternary system, the intervention of protein will weaken the inhibition effect of lipid on retrogradation of starch in the freeze-drying process. In addition, the lower drying temperature will lead to the decrease of the interaction strength between the components of ternary mixed system. Avoiding the melting of frozen materials during drying is the key control point to improve the quality of freeze-dried wheat starch-based products.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".