Isolation and Characterization of High‐Purity Starch Isolates from Regular, Waxy, and High‐Amylose Hulless Barley Grains
Bibliographic record
Abstract
ABSTRACT Recovering starch from barley is problematic typically due to interference from β‐glucan (the soluble fiber component), which becomes highly viscous in aqueous solution. Dry fractionation techniques tend to be inefficient and often result in low yields. Recently, a protocol was developed in our laboratory for recovering β‐glucan from barley in which sieving whole barley flour in a semiaqueous (50% ethanol) medium allowed separation of the starch and fiber fractions without activating the viscosity of the β‐glucan. In this report, we investigate an aqueous method which further purifies the crude starch component recovered from this process. Six hulless barley (HB) cultivars representing two each of waxy, regular, and high‐amylose cultivars were fractionated into primarily starch, fiber, and protein components. Starch isolates primarily had large granules with high purity (>98%) and yield range was 22–39% (flour dry weight basis). More importantly, the β‐glucan extraction efficiency was 77–90%, meaning that it was well separated from the starch component during processing. Physicochemical evaluation of the starch isolates, which were mainly composed of large granules, showed properties that are typical of the barley genotypes.
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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) | 0.000 | 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".