Production and Physicochemical Characterization of the Gel Obtained in the Fermentation Process of Blue Corn Flour (Zea mays L.) with Colletotrichum gloeosporioides
Bibliographic record
Abstract
Food gels are viscoelastic substances used in various gelled products manufactured around the world. Polysaccharides are the most common food gelling agents. The aim of this work was the production and characterization of a gel produced in a blue corn flour fermentation process, where different proportions were used of blue corn (Zea mays L.) flour and Czapek Dox culture medium (90 mL of culture medium with 10 g of blue corn flour, 80 mL of culture medium with 20 g of blue corn flour, and 70 mL of culture medium with 30 g of blue corn flour) and were fermented for three different durations (20, 25, and 30 days) with the Colletotrichum gloeosporioides fungus. A characterization of the gel was carried out studying the rheological properties, proximal analysis, toxicological analysis, microscopic structure, and molecular characterization, in addition to a solubility test with three different organic solvents (ethanol, hexane, and ethyl acetate, in addition to water). The results obtained showed in the rheological analysis that the gel could have resistance to high temperatures and a reversible behavior. The gel is soluble in polar solvents (ethanol and water). The main chemical components of the gel are carbohydrates, especially polysaccharides, and it was confirmed by FT-IR spectroscopy that the gel may be composed of pectin.
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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) | 0.000 | 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 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".