Impact of Micronization on Rapidly Digestible, Slowly Digestible, and Resistant Starch Concentrations in Normal, High-Amylose, and Waxy Barley
Bibliographic record
Abstract
This study determined the effect of micronization (high intensity infrared heating) on the concentrations of rapidly digestible starch (RDS), slowly digestible starch (SDS), and resistant starch (RS) in normal barley (NB), high-amylose barley (HAB), and waxy barley (WB). The gelatinized starch contents and the thermal properties of the micronized samples also were determined. Samples of each barley type were tempered to each of three moisture contents (approximately 17, 31, or 41%), and then each tempered sample was micronized to each of three surface temperatures (100, 120, or 140 degrees C). Micronized barley samples were substantially lower in RS and in SDS and, therefore, higher in RDS than corresponding unprocessed samples. In general, higher concentrations of RDS and of gelatinized starch were associated with higher initial moisture contents and higher surface temperatures. The lowest concentrations of RS were observed in micronized WB samples. Similar concentrations of RS were observed in corresponding NB and HAB samples. Micronization resulted in slight increases in the onset (To), peak (Tp), and completion (Tc) gelatinization temperatures and in substantial reductions in the gelatinization enthalpy (DeltaH), the latter reflecting the levels of gelatinized starch in micronized samples, particularly in samples micronized at higher moisture contents and to higher surface temperatures. Endothermic transitions were evident only in samples tempered to 17% moisture or 31% moisture (surface temperature of 100 degrees C only).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".