Iodine‐binding in Granular Starch: Different Effects of Moisture Content for Corn and Potato Starch
Bibliographic record
Abstract
Abstract The ability of iodine to complex with glucan polymers has been mainly used to elucidate the structure of dispersed starch molecules. In a previous publication [D. Saibene, K. Seetharaman, Carbohydr. Polym., 2006, 64, 539‐547] we reported the ability of granular corn starches to bind iodine at moisture contents as low as 8%. We presumed that iodine binding in a native granule requires a certain minimal level of mobility of the linear molecules, and that the water content would plasticize the starch, thus increasing the ability to bind iodine by the formation of single helices. The objective of the present study was to investigate iodine complex formation with starch molecules in granular common corn starch (CCS) and potato starch (PS) as a function of water content. CCS and PS granules have approximately similar amylose content (21 and 17% amylose, respectively), but different crystalline structures (A‐ and B‐type, respectively). Variable water contents were achieved using salt solutions at water activities (aw) of 0.33, 0.75 or 0.97, and also using Drierite® (aw less than 0.15). The granular samples were then exposed to iodine vapor before determination of the K/S spectra (the ratio of the absorption and scattering coefficients), and X‐ray diffraction patterns. Based on the K/S spectra, at moisture contents in the range of 12‐20%, CCS binds iodine more effectively than PS. We suggest that the reason may be related to the greater amount of water associated with the crystalline regions of PS. Iodination more strongly diminished the crystallinity of PS granules than it did in CCS granules. This behavior is consistent with a greater involvement of amylose in the crystalline structures of PS than in CCS.
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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 | 0.001 |
| 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".