Effect of Glutamate Accumulation During Sourdough Fermentation with <i>Lactobacillus reuteri</i> on the Taste of Bread and Sodium‐Reduced Bread
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
NaCl is an important contributor to the taste and texture of bread; therefore, it is challenging to reduce NaCl in bread without compromising quality. This study investigated sensory properties of bread with sourdough fermented with Lactobacillus reuteri accumulating glutamate or γ‐aminobutyrate (GABA). Sourdough was fermented with the GABA‐producing L. reuteri 100‐23 and LTH5448 as well as the glutamate‐accumulating L. reuteri 100‐23Δ gadB and TMW1.106. A consumer panel detected significant differences in the taste of bread with 6% addition of sourdough fermented with glutamate‐ or GABA‐producing L. reuteri . Remarkably, this difference was also detected when GABA‐producing L. reuteri 100‐23 was compared with its glutamate‐producing isogenic mutant L. reuteri 100‐23Δ gadB. The intensity of the salty taste of sourdough bread produced with 1% (flour basis) salt was equivalent to the intensity of the salty taste of reference bread produced with 1.5% salt. A trained panel found that sourdough breads (1 or 2% NaCl flour base) had a higher sour and umami taste intensity when compared with reference bread with the same salt content. Bread produced with sourdough fermented with L. reuteri 100‐23Δ gadB consistently had a higher umami taste intensity when compared with other sourdough breads. Neither sourdough addition nor NaCl level influenced bread volume or texture. In conclusion, the use of sourdough fermented with glutamate‐accumulating lactobacilli allowed reduction of NaCl without adverse effects on the taste or other quality attributes of bread.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it