Activity and concentration of polyphenolic antioxidants and agronomic characteristics of selected cultivars and advanced apple lines from Quebec and British Columbia, Canada
Bibliographic record
Abstract
Agronomic characteristics, total phenolic content (TPC) and total antioxidant (TA) activity were determined in the flesh and peel of eight selected apple genotypes from Canada, namely seven from Quebec (‘SJC658’, ‘SJC82341’, ‘A15R5A15A’, ‘A15R5A15B’, ‘Diva’, ‘Eden’, and ‘Reinette Russet’) and one from British Columbia (‘11W-19-18’) intended for fresh market and processing. The agronomic characteristics differed significantly among the selected cultivars (cv.), reflecting their intended use. TPC was measured by the Folin-Ciocalteu method, total antioxidant capacity (TAC) by the ferric reducing/antioxidant power (FRAP) and oxygen radical absorbance capacity (ORAC) assays. The phenolic content (PC) and antioxidant capacity (AC) were found to be higher in the peel for all cv. and breeding lines. ‘Eden’ had the lowest PC and AC while ‘Reinette Russet’ and ‘SJC658’ had the highest PC in both the flesh and the peel. A significant positive correlation was found between the TPC and the TAC measured by the two different methods. A significant correlation (r = 0.810) was also found between the FRAP and ORAC measurements, showing that these methods give consistent results. The significant variation observed in the agronomic and antioxidant parameters confirms the potential of some of the unnamed lines for processing, use in a breeding program, or both.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".