Phenolic Acids and Flavonoids in Nonfermented and Fermented Red Sorghum (Sorghum bicolor (L.) Moench)
Bibliographic record
Abstract
This study aimed to identify phenolic acids and flavonoids in the red sorghum variety PAN 3860 and to determine changes in their concentrations during fermentation with lactobacilli. Sorghum sourdoughs fermented with two binary strain combinations, Lactobacillus plantarum and Lactobacillus casei or Lactobacillus fermentum and Lactobacillus reuteri , were compared to chemically acidified controls. Four glycerol esters were tentatively identified, caffeoylglycerol, dicaffeoylglycerol, coumaroyl-caffeoylglycerol, and coumaroyl-feruloylglycerol, that have previously not been detected in sorghum. Chemical acidification resulted in hydrolysis of phenolic acid esters and flavonoid glucosides. During lactic fermentation, phenolic acids, phenolic acid esters, and flavonoid glucosides were metabolized. Analysis of ferulic acid, caffeic acid, and naringenin-glucoside contents in single-strain cultures of lactobacilli demonstrated that glucosidase, phenolic acid reductase, and phenolic acid decarboxylase activities contributed to polyphenol metabolism. This study demonstrates that microbial fermentation of sorghum affects the content of polyphenols and can influence the nutritional value and antimicrobial activity of sorghum.
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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 | 0.001 | 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) | 0.001 | 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".