Ultrasound- and hemicellulase-assisted extraction increase β-glucosidase activity, the content of isoflavone aglycones and antioxidant potential of soymilk
Bibliographic record
Abstract
Soymilk is consumed as such or used in the preparation of tofu, fermented soymilk, and soy yogurt, among others. In this study, hemicellulase-assisted extraction (HAE) and ultrasound-assisted extraction (UAE) were used during soymilk manufacturing. The activity of endogenous β-glicosidases was increased 1.3 and 1.5-fold in soymilk produced upon HAE and UAE, respectively. Likewise, the concentration of isoflavones in the aglycone form increased 1.7 and 2.4 times in samples subjected to HAE and UAE, respectively. UAE, but not HAE, rendered an equimolar conversion from conjugated isoflavones to their respective aglycones. In addition, HAE and UAE showed higher antiradical activity towards ABTS radical cation and peroxyl radical, compared to those of the control. The aglycone isoflavones/conjugated isoflavones (aISO/cISO) ratio correlated with the antiradical activity, thus suggesting that the soybean industry may use this new quality index to indicate the antioxidant potential of products. Food formulations containing soymilk with high aISO/cISO ratio may translate to higher oxidative stability of the final product. Likewise, the higher absorption of aglycone isoflavones compared to that of their conjugated counterparts is well recognized. Therefore, high aISO/cISO ratio of soymilk and/or its products may provide a better antioxidant protection under physiological conditions.
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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) | 0.001 | 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) | 0.001 | 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".