Ultrasonic assisted phenolic elicitation and antioxidant potential of common bean (Phaseolus vulgaris) sprouts
Bibliographic record
Abstract
Limited literature is available concerning the phenolic biosynthesis and antioxidative potential of common bean sprouts induced by ultrasound elicitation. In this study, common bean seeds were treated with ultrasound at different power (0, 180 and 360 W) and time (0, 30, 45 and 60 min) levels, before they were subjected to sprouting (24, 48, 72 and 96 h). Stress markers (H2O2, catalase and guaiacol peroxidase), activities of defense phenolic triggering enzymes (phenylalanine ammonia-lyase and tyrosine ammonia-lyase), phenolic contents (total phenolic acids, total flavonoids and anthocyanins) and antioxidant capacities (DPPH, ABTS and Fe2+ scavenging) were monitored. Results showed that, ultrasound elicitation (especially 360 W, 60 min) significantly increased accumulation of stress markers at 96 h of sprouting, leading to elevated activities of defense phenolic triggering enzymes, and final accumulation of phenolics and antioxidant capacities at significant levels compared to control. Ultrasound treatment at 360 W and 60 min reduced sprouting time by 60 h, compared to control. Results from principal component analysis clearly differentiated latter stages of sprouting and high ultrasound levels from other sprouting conditions as distinct treatments for the production of phenolic-rich common bean sprouts. Overall, results from this study indicated that elicitation with ultrasound can be a green and novel approach for producing phenolic-enriched common bean sprouts as an organic nutraceutical vegetable.
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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) | 0.001 | 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".