Use of Iodine as a Tool to Understand Wheat Starch Pasting Properties
Bibliographic record
Abstract
Abstract The ability of iodine to bind amylose has been used to understand a variety of structural and functional aspects of starch in food systems. In this study, the changes in starch granule swelling, polymer leaching and their relationship to pasting properties was investigated by adding iodine to the starch slurry at either room temperature or 95°C. The objective of the study was to investigate the contribution of leached and solubilized starch polymers on the pasting behavior of wheat starch. The addition of very small amounts of iodine (0.1%, dry basis, db) at room temperature increased peak and final pasting viscosities as compared to when no iodine was added. Further increases in iodine concentration resulted in a decrease in peak and final pasting viscosities. The amount of iodine required to completely inhibit granule swelling was more than that required to minimize amylose leaching from the granule. Adding increasing amounts of iodine at 95°C to the starch slurry resulted in the gradual decrease in peak and final pasting viscosities. The contrasting effects of iodine on paste viscosity behavior when added at room temperature or at 95°C suggest that the contribution of extra‐granular amylose on the setback viscosity is minimal and a larger proportion of amylose is retained in the intragranular spaces.
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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 | 0.001 | 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 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".