Application of Fermentation as a Strategy for the Transformation and Valorization of Vegetable Matrices
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
This review paper addresses vegetable fermentation from a microbiological and technological point of view, with particular emphasis on the potential of lactic acid bacteria to carry out these transformations. This review paper also covers the spectrum of traditional and emerging fermented plant foods. Fermentation with lactic acid bacteria represents an accessible and appropriate strategy to increase the daily consumption of legumes and vegetables. Often, lactic fermentation is carried out spontaneously following protocols firmly rooted in the culture and traditions of different countries worldwide. Fermented plant products are microbiologically safe, nutritious, and have pleasant sensory characteristics, and some of them can be stored for long periods without refrigeration. Controlled fermentation with selected lactic acid bacteria is a promising alternative to guarantee high-quality products from a nutritional and organoleptic point of view and with benefits for the consumer’s health. Recent advances in genomics and molecular microbial ecology predict a bright future for its application in plant fermentation. However, it is necessary to promote molecular approaches to study the microbiota composition, select starters aimed at different legumes and vegetables, generate products with nutritional properties superior to those currently available, and incorporate non-traditional vegetables.
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