Quality of dried white salted noodles affected by microbial transglutaminase
Bibliographic record
Abstract
Abstract To examine the potential application of microbial transglutaminase (MTGase) in oriental noodle making, the effects of various MTGase addition levels on the rheological, textural and structural properties of noodles were investigated using good quality (‘Red Bicycle’) and poor quality (‘Sandow’) wheat flours. Addition of MTGase at 5–20 g kg−1 levels, but not at 1 g kg−1 level, to the two different wheat flours decreased rapid visco‐analyser (RVA) parameters of hot paste viscosity and final viscosity while increasing breakdown. For fresh white salted noodle dough sheets, the storage modulus (G′) and loss modulus (G″) increased significantly at 1 g kg−1 MTGase addition for both types of flour, but there was no clear trend with higher levels of MTGase. For dried white salted noodles, textural parameters (tensile force, hardness and gumminess) generally increased, cooking loss was little affected and the yield of the cooked noodle was significantly decreased by MTGase. Color was slightly adversely affected. Scanning electron microscopy (SEM) results indicated that physical properties of dry noodles were improved through the formation of cross‐links [ε‐(γ‐glutamyl)lysine] by MTGase. Copyright © 2005 Society of Chemical Industry
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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) | 0.001 | 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".