Effect of Transglutaminase, Citrate Buffer, and Temperature on a Soft Wheat Flour Dough System
Bibliographic record
Abstract
ABSTRACT Transglutaminase (TGase) can improve the functional characteristics of proteins by introducing covalent bonds inter‐ or intrachains. Temperature and pH interfere with the protein structure and the catalytic activity of enzymes. Because these three factors can act synergistically, TGase, citrate buffer, and temperature were evaluated for their effects on the rheological and chemical changes in low‐protein wheat flour dough. Dough strength, measured by microextension test, significantly increased with increasing levels of TGase (8 U/g of protein), with changes in pH of the citrate buffer (pH 6.5), and by the effect of interaction between these factors. The same trend was observed in the size‐exclusion HPLC measurements, indicating that these two parameters have the effect of increasing gluten protein aggregation. Temperature had a significant effect on dough extension, measured by microextension test. The changes in secondary structure of gluten protein were investigated by FTIR second‐derivative spectra (amide I region, 1,600–1,700 cm −1 ) and showed an increase in β‐sheet structures initiated by TGase, citrate buffer pH, and their interaction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".