Effect of Mixed Cultures of Yeast and Lactobacilli on the Quality of Wheat Sourdough Bread
Bibliographic record
Abstract
In this study, mixed starter cultures of yeast and lactobacilli were used for type I sourdough bread making to evaluate their ability to improve bread quality and increase the amount of flavor volatiles. Kazachstania humilis, Saccharomyces cerevisiae, Wickerhamomyces anomalus, Lactobacillus sanfranciscensis DSM20451T and Lactobacillus sakei LS8 were used in different combinations to ferment wheat sourdough. S. cerevisiae produced the highest amount of CO2 among all strains and thus enhanced bread volume and crumb texture. S. cerevisiae also increased the free thiol level in bread dough, and this study confirms that thiol accumulation was not strongly related to the content of the glutenin macropolymer or bread volume. The role of thiol exchange reactions on bread quality differs between long fermentation sourdough and straight dough with baker’s yeast only. The influence of different starter cultures on wheat sourdough bread volatiles was established by using head space solid-phase microextraction and gas chromatography/mass spectrometry analysis (SPME-GC/MS). The sourdough breads fermented with a combination of lactobacilli and yeast had a more complex profile of volatiles, particularly with respect to esters.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".