Simplified Dilute Acetic Acid Based Extraction Procedure for Fractionation and Analysis of Wheat Flour Protein by Size Exclusion HPLC and Flow Field‐Flow Fractionation
Bibliographic record
Abstract
ABSTRACT A simple, highly efficient and reproducible two‐step extraction procedure using dilute acetic acid without (AN) and then with sonication (AS) has been developed for the fractionation of wheat flour protein. Approximately 97% of total protein was extracted from a Canadian hard red spring wheat flour; an additional 1.2% protein could be recovered by further extraction with 1% DDT and 50% 1‐propanol (AR). Size‐exclusion HPLC (SE‐HPLC) and flow field‐flow fractionation (flow FFF) showed that the AN extract, which accounted for most of the total extractable protein (AN + AS + AR), consisted primarily of monomeric protein. The AS extract was composed primarily of polymeric proteins. Flow FFF showed that AN polymeric protein, including that eluting at the SE‐HPLC void volume, showed smaller Stokes diameters than AS polymeric protein. Flow FFF profiles of AS SE‐HPLC subfractions showed that the void volume subfraction contained monomeric and small polymeric protein in addition to large polymeric protein, indicating formation of larger complexes through interaction between some or all of the components. AN and AS extracts, as well as SE‐HPLC and flow FFF fractions thereof, showed a fairly wide range of values among 12 Canadian hard red and white spring wheat cultivars. The proportion of total protein in the AS extract and in the larger sized polymeric protein fractions from SE‐HPLC and flow FFF were highly positively correlated to farinograph mixing time.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.001 |
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".