Determination of Antioxidant Activity in Foods and Beverages by Reaction with 2,2′-Diphenyl-1-Picrylhydrazyl (DPPH): Collaborative Study First Action 2012.04
Bibliographic record
Abstract
A colorimetric method for the determination of total antioxidant activity in a variety of foods and beverages was validated in both a single-laboratory validation and a collaborative laboratory validation study. The procedure involved extraction of the antioxidants directly into a methanol-water solution containing a known amount of 2,2'-diphenyl-1-picrylhydrazyl (DPPH), thus promoting the rapid reaction of extracted materials with DPPH. The reaction was monitored by spectrophotometric measurement of the absorbance loss at 517 nm. Antioxidant activity was quantified relative to a dilution series of vitamin E analog standards (Trolox), which were analyzed in parallel simultaneously with the food and beverage samples. The antioxidant activities of the samples ranged from 131 to 131 000 micromole Trolox equivalents/100 g. Statistical analysis of the results showed that nine of the 11 matrixes gave acceptable HorRat values, indicating that the method performed well in these cases. The acceptable matrixes include pomegranate juice, blueberry juice, carrot juice, green tea, wine, rosemary spice, ready-to-eat cereal, and yogurt. Two samples failed the HorRat test: the first was an almond milk that had an antioxidant level below the practical LOQ for the method; the second was a sample of canola oil with added omega-3 fatty acid that was immiscible in the reaction medium.
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".