Quantification of Individual Phenolic Compounds’ Contribution to Antioxidant Capacity in Apple: A Novel Analytical Tool Based on Liquid Chromatography with Diode Array, Electrochemical, and Charged Aerosol Detection
Bibliographic record
Abstract
Phenolics, particularly from apples, hold great interest because of their antioxidant properties. In the present study, the total antioxidant capacity of different apple extracts obtained by pressurized hot water extraction (PHWE) was determined by cyclic voltammetry (CV), which was compared with the conventional antioxidant assays. To measure the antioxidant capacity of individual antioxidants present in apple extracts, a novel method was developed based on high-performance liquid chromatography (HPLC) with photodiode array (DAD), electrochemical (ECD), and charged aerosol (CAD) detection. HPLC-DAD-ECD-CAD enabled rapid, qualitative, and quantitative determination of antioxidants in the apple extracts. The main advantage of using CAD was that this detector enabled quantification of a large number of phenolics using only a few standards. The results showed that phenolic acids and flavonols were mainly responsible for the total antioxidant capacity of apple extracts. In addition, protocatechuic acid, chlorogenic acid, hyperoside, an unidentified phenolic acid, and a quercetin derivative presented the highest antioxidant capacities.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".