Polyphenolic Profiles in Eight Apple Cultivars Using High-Performance Liquid Chromatography (HPLC)
Bibliographic record
Abstract
Polyphenolic compounds of apple may play an important role in physiologic functions related to human health. Different polyphenolics may have varied biological activities including antioxidant activity. The objective of this study was to investigate the profiles of polyphenolic compounds in different apple varieties and different parts of an apple. The total and individual polyphenolics differed significantly among the eight apple cultivars grown in Ontario, and the peels had higher concentrations than the flesh. Among the tested cultivars, Red Delicious and Northern Spy had the highest concentrations and Empire the lowest. Five major polyphenolic groups with a total of 16 identified individual compounds were found, among which the dihydroxycinnamic acid esters, phloretin glycosides, and flavan-3-ols were found in both flesh and peel, whereas quercetin glycosides were almost exclusively found in the peel. Cyanidin 3-galactoside was unique to and found only in red apple peels. In both apple peel and flesh, the predominant group of polyphenolics was the procyanidins, followed by quercetin glycosides in the peel and hydroxycinnamic acid esters in the flesh. 3-Hydroxyphloretin 2'-xyloglucoside was newly identified in apple. The results obtained in this study will further the understanding of the polyphenolic composition of apples and their roles in health-promoting physiological functions.
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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 | 0.001 | 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".