Changes in isoflavone profile, antioxidant activity, and phenolic contents in Taiwanese and Canadian soybeans during tempeh processing
Bibliographic record
Abstract
Soybean seeds of eight different varieties were processed to tempeh. Factors affecting each step of tempeh making include isoflavone profile, FRAP (ferric ion reducing antioxidant power) and DPPH (1,1-diphenyl-2-picrylhydrazyl radical scavenging ability) assayed antioxidant activity, and TPC (total phenolic content) in the prolonged fermentation were investigated respectively. The total isoflavone contents in the dry seeds of the tested varieties ranged from 893.3 to 1386.0 μmol/100 g, and more than 99% was in the form of isoflavone glucosides. Tempeh fermentation increased the isoflavone aglycone contents by more than 20 times. Principle component analysis provided evidence of the significant correlation (p < 0.05) between isoflavone aglycone content and FRAP and DPPH assayed antioxidant activities. Molar concentration (μmol/100 g) was the preferred unit to precisely present the conversion from isoflavone glucosides to aglycones, and the total isoflavone content (μmol/100 g) was not decreased after 10 d of fermentation in most varieties. In the prolonged fermentation, daidzein kept increasing throughout but genistein decreased after day 2. For extracting a higher amount of daidzein, longer fermentation could be considered. Our results provide information of preferable fermentation periods and soybean varieties and show that tempeh may be a functional food with readily bioavailable form of isoflavones.
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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".