A review of bread qualities and current strategies for bread bioprotection: Flavor, sensory, rheological, and textural attributes
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
The unequivocal economical and social values of bread as a staple food commodity lead to constant interests in optimizing its postproduction quality and extending its shelf life, which is related to the maintenance and enhancement of flavors and textural properties, and finally, to the delay of microbial spoilage. The latter has been the subject of a multitude of studies and reviews, in which the different approaches and views were discussed. However, variations in bread freshness, flavor, and textural quality are still of concerns for the bread making industry, in conjunction with the expectation from consumers for bread products with high-quality attributes and free of synthetic ingredients that satisfy their pleasure and their sustainable lifestyle. This review mainly focuses on the quality profiles of bread, including flavor, rheological, textural, and sensorial aspects; on the modalities to assess them; as well as on the conventional and emerging approaches developed so far over the past decades. The applications of lactic acid bacteria (LAB) and enzymes as bioprotective technologies are examined and discussed, along with active packaging and novel processing technologies for either the maintenance or improvement of bread qualities during storage.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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